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151. Virtual Ontogeny of Cortical Growth Preceding Mental Illness

Author: Patel, Y, Shin, J, Abe, C, Agartz, I, Alloza, C, Alnaes, D, Ambrogi, S, Antonucci, LA, Arango, C, Arolt, V, Auzias, G, Ayesa-Arriola, R, Banaj, N, Banaschewski, T, Bandeira, C, Basgoze, Z, Cupertino, RB, Bau, CHD, Bauer, J, Baumeister, S, Bernardoni, F, Bertolino, A, del Mar Bonnin, C, Brandeis, D, Brem, S, Bruggemann, J, Bulow, R, Bustillo, JR, Calderoni, S, Calvo, R, Canales-Rodriguez, EJ, Cannon, DM, Carmona, S, Carr, VJ, Catts, SV, Chenji, S, Chew, QH, Coghill, D, Connolly, CG, Conzelmann, A, Craven, AR, Crespo-Facorro, B, Cullen, K, Dahl, A, Dannlowski, U, Davey, CG, Deruelle, C, Diaz-Caneja, CM, Dohm, K, Ehrlich, S, Epstein, J, Erwin-Grabner, T, Eyler, LT, Fedor, J, Fitzgerald, J, Foran, W, Ford, JM, Fortea, L, Fuentes-Claramonte, P, Fullerton, J, Furlong, L, Gallagher, L, Gao, B, Gao, S, Goikolea, JM, Gotlib, I, Goya-Maldonado, R, Grabe, HJ, Green, M, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Haavik, J, Hahn, T, Harrison, BJ, Heindel, W, Henskens, F, Heslenfeld, DJ, Hilland, E, Hoekstra, PJ, Hohmann, S, Holz, N, Howells, FM, Ipser, JC, Jahanshad, N, Jakobi, B, Jansen, A, Janssen, J, Jonassen, R, Kaiser, A, Kaleda, V, Karantonis, J, King, JA, Kircher, T, Kochunov, P, Koopowitz, S-M, Landen, M, Landro, NI, Lawrie, S, Lebedeva, I, Luna, B, Lundervold, AJ, MacMaster, FP, Maglanoc, LA, Mathalon, DH, McDonald, C, McIntosh, A, Meinert, S, Michie, PT, Mitchell, P, Moreno-Alcazar, A, Mowry, B, Muratori, F, Nabulsi, L, Nenadic, I, Tuura, RO, Oosterlaan, J, Overs, B, Pantelis, C, Parellada, M, Pariente, JC, Pauli, P, Pergola, G, Piarulli, FM, Picon, F, Piras, F, Pomarol-Clotet, E, Pretus, C, Quide, Y, Radua, J, Ramos-Quiroga, JA, Rasser, PE, Reif, A, Retico, A, Roberts, G, Rossell, S, Rovaris, DL, Rubia, K, Sacchet, M, Salavert, J, Salvador, R, Sarro, S, Sawa, A, Schall, U, Scott, R, Selvaggi, P, Silk, T, Sim, K, Skoch, A, Spalletta, G, Spaniel, F, Stein, DJ, Steinstrater, O, Stolicyn, A, Takayanagi, Y, Tamm, L, Tavares, M, Teumer, A, Thiel, K, Thomopoulos, SI, Tomecek, D, Tomyshev, AS, Tordesillas-Gutierrez, D, Tosetti, M, Uhlmann, A, Van Rheenen, T, Vazquez-Bourgon, J, Vernooij, MW, Vieta, E, Vilarroya, O, Weickert, C, Weickert, T, Westlye, LT, Whalley, H, Willinger, D, Winter, A, Wittfeld, K, Yang, TT, Yoncheva, Y, Zijlmans, JL, Hoogman, M, Franke, B, van Rooij, D, Buitelaar, J, Ching, CRK, Andreassen, OA, Pozzi, E, Veltman, D, Schmaal, L, van Erp, TGM, Turner, J, Castellanos, FX, Pausova, Z, Thompson, P, Paus, T, Patel, Y, Shin, J, Abe, C, Agartz, I, Alloza, C, Alnaes, D, Ambrogi, S, Antonucci, LA, Arango, C, Arolt, V, Auzias, G, Ayesa-Arriola, R, Banaj, N, Banaschewski, T, Bandeira, C, Basgoze, Z, Cupertino, RB, Bau, CHD, Bauer, J, Baumeister, S, Bernardoni, F, Bertolino, A, del Mar Bonnin, C, Brandeis, D, Brem, S, Bruggemann, J, Bulow, R, Bustillo, JR, Calderoni, S, Calvo, R, Canales-Rodriguez, EJ, Cannon, DM, Carmona, S, Carr, VJ, Catts, SV, Chenji, S, Chew, QH, Coghill, D, Connolly, CG, Conzelmann, A, Craven, AR, Crespo-Facorro, B, Cullen, K, Dahl, A, Dannlowski, U, Davey, CG, Deruelle, C, Diaz-Caneja, CM, Dohm, K, Ehrlich, S, Epstein, J, Erwin-Grabner, T, Eyler, LT, Fedor, J, Fitzgerald, J, Foran, W, Ford, JM, Fortea, L, Fuentes-Claramonte, P, Fullerton, J, Furlong, L, Gallagher, L, Gao, B, Gao, S, Goikolea, JM, Gotlib, I, Goya-Maldonado, R, Grabe, HJ, Green, M, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Haavik, J, Hahn, T, Harrison, BJ, Heindel, W, Henskens, F, Heslenfeld, DJ, Hilland, E, Hoekstra, PJ, Hohmann, S, Holz, N, Howells, FM, Ipser, JC, Jahanshad, N, Jakobi, B, Jansen, A, Janssen, J, Jonassen, R, Kaiser, A, Kaleda, V, Karantonis, J, King, JA, Kircher, T, Kochunov, P, Koopowitz, S-M, Landen, M, Landro, NI, Lawrie, S, Lebedeva, I, Luna, B, Lundervold, AJ, MacMaster, FP, Maglanoc, LA, Mathalon, DH, McDonald, C, McIntosh, A, Meinert, S, Michie, PT, Mitchell, P, Moreno-Alcazar, A, Mowry, B, Muratori, F, Nabulsi, L, Nenadic, I, Tuura, RO, Oosterlaan, J, Overs, B, Pantelis, C, Parellada, M, Pariente, JC, Pauli, P, Pergola, G, Piarulli, FM, Picon, F, Piras, F, Pomarol-Clotet, E, Pretus, C, Quide, Y, Radua, J, Ramos-Quiroga, JA, Rasser, PE, Reif, A, Retico, A, Roberts, G, Rossell, S, Rovaris, DL, Rubia, K, Sacchet, M, Salavert, J, Salvador, R, Sarro, S, Sawa, A, Schall, U, Scott, R, Selvaggi, P, Silk, T, Sim, K, Skoch, A, Spalletta, G, Spaniel, F, Stein, DJ, Steinstrater, O, Stolicyn, A, Takayanagi, Y, Tamm, L, Tavares, M, Teumer, A, Thiel, K, Thomopoulos, SI, Tomecek, D, Tomyshev, AS, Tordesillas-Gutierrez, D, Tosetti, M, Uhlmann, A, Van Rheenen, T, Vazquez-Bourgon, J, Vernooij, MW, Vieta, E, Vilarroya, O, Weickert, C, Weickert, T, Westlye, LT, Whalley, H, Willinger, D, Winter, A, Wittfeld, K, Yang, TT, Yoncheva, Y, Zijlmans, JL, Hoogman, M, Franke, B, van Rooij, D, Buitelaar, J, Ching, CRK, Andreassen, OA, Pozzi, E, Veltman, D, Schmaal, L, van Erp, TGM, Turner, J, Castellanos, FX, Pausova, Z, Thompson, P, and Paus, T
Abstract: BACKGROUND: Morphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life. METHODS: Interregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed. RESULTS: Across the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth. CONCLUSIONS: Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from t
Published: 2022

152. Virtual ontogeny of cortical growth preceding mental illness

Author: German Research Foundation, University of Münster, National Health and Medical Research Council (Australia), University of Cape Town, National Research Foundation (South Africa), Swinburne University of Technology, Jack Brockhoff Foundation, University of Melbourne, Barbara Dicker Brain Sciences Foundation, Rebecca L. Cooper Medical Research Foundation, Society for Mental Health Research (Australia), Swedish Research Council, Swedish Foundation for Strategic Research, Swedish Brain Foundation, Health Research Board (Ireland), Russian Foundation for Basic Research, University of Zurich, Pratt Foundation, Ramsay Health Care, Viertel Charitable Foundation, Schizophrenia Research Institute (Australia), European Commission, Australian Research Council, Instituto de Salud Carlos III, National Institute for Health and Care Research (US), National Institute for Health Research (UK), Ministry of Health of the Czech Republic, Bill & Melinda Gates Foundation, South African Medical Research Council, Carnegie Corporation of New York, Wellcome Trust, Medical Research Council (UK), Medical Research Scotland, Netherlands Organization for Scientific Research, Ambrogi, Sonia [0000-0002-2897-358X], Banaschewski, Tobias [0000-0003-4595-1144], Bandeira, Cibele Edom [0000-0003-0681-1309], Cupertino, Renata [0000-0002-3452-0632], Calderoni, Sara [0000-0002-6250-5739], Cannon, Dara [0000-0001-7378-3411], Carr, Vaughan [0000-0002-8907-5804], Chew, Qian Hui [0000-0003-0969-7994], Coghill, David [0000-0003-3017-9737], Cullen, Kathryn [0000-0001-9631-3770], Dahl, Andreas [0000-0002-8097-2082], Epstein, Jeffery [0000-0003-3464-5256], Foran, William [0000-0001-7491-9798], Fortea, Lydia [0000-0001-6778-2316], Fuentes-Claramonte, Paola [0000-0002-1428-7976], Fullerton, Janice M. [0000-0003-4014-4490], Furlong, Lisa [0000-0001-6196-4565], Gallagher, Louise [0000-0001-9462-2836], Gao, Si [0000-0002-4473-1142], Gotlib, Ian [0000-0002-3622-3199], Haavik, Jan [0000-0001-7865-2808], Henskens, Frans [0000-0003-2358-5630], Hilland, Eva [0000-0002-7102-8372], Hoekstra, Pieter J [0000-0001-7260-4119], Howells, Fleur M [0000-0001-9759-2556], Ipser, Jonathan [0000-0003-1272-0032], Jørgensen, Jes Kristian [0000-0001-9133-1670], Karantonis, James A. [0000-0003-2281-0912], Lawrie, Stephen [0000-0002-2444-5675], Patel, Yash, Shin, Jean, Abé, Christoph, Agartz, Ingrid, Alloza, Clara, Alnæs, Dag, Ambrogi, Sonia, Antonucci, Linda A., Arango, Celso, Arolt, Volker, Auzias, Guillaume, Gruber, Oliver, Haavik, Jan, McDonald, Colm, Hahn, Tim, Harrison, Ben J., Heindel, Walter, Henskens, Frans, Heslenfeld, Dirk J., Hilland, Eva, King, Joseph A., Vernooij, Meike W., Hoekstra, Pieter J., Hohmann, Sarah, Holz, Nathalie, Howells, Fleur M., McIntosh, Andrew, Ipser, Jonathan C., Meinert, Susanne, Hoogman, Martine, Kircher, Tilo, Kochunov, Peter, Vieta, Eduard, Koopowitz, Sheri-Michelle, Landén, Mikael, Landrø, Nils Inge, Lawrie, Stephen, Michie, Patricia T., Ayesa Arriola, Rosa, Mitchell, Philip, Moreno-Alcázar, Ana, Franke, Barbara, Mowry, Bryan, Bau, Claiton H. D., Muratori, Filippo, Nabulsi, Leila, Nenadić, Igor, O'Gorman Tuura, Ruth, Oosterlaan, Jaap, Overs, Bronwyn, Pantelis, Christos, Banaj, Nerisa, Parellada, Mara, van Rooij, Daan, Vilarroya, Oscar, Pariente, Jose C., Pauli, Paul, Pergola, Giulio, Piarulli, Francesco Maria, Picon, Felipe, Piras, Fabrizio, Pomarol-Clotet, Edith, Pretus, Clara, Quidé, Yann, Banaschewski, Tobias, Weickert, Cynthia, Buitelaar, Jan, Radua, Joaquim, Ramos-Quiroga, J. Antoni, Rasser, Paul E., Reif, Andreas, Retico, Alessandra, Roberts, Gloria, Rossell, Susan, Rovaris, Diego Luiz, Rubia, Katya, Weickert, Thomas, Sacchet, Matthew, Ching, Christopher R. K., Bandeira, Cibele, Salavert, Josep, Salvador, Raymond, Sarró, Salvador, Sawa, Akira, Schall, Ulrich, Scott, Rodney, Selvaggi, Pierluigi, Westlye, Lars T., Silk, Tim, Sim, Kang, Andreassen, Ole A., Skoch, Antonin, Başgöze, Zeynep, Spalletta, Gianfranco, Spaniel, Filip, Stein, Dan J., Steinsträter, Olaf, Stolicyn, Aleks, Whalley, Heather, Takayanagi, Yoichiro, Tamm, Leanne, Tavares, Maria, Pozzi, Elena, Teumer, Alexander, Thiel, Katharina, Cupertino, Renata Basso, Thomopoulos, Sophia I., Tomecek, David, Tomyshev, Alexander S., Willinger, David, Tordesillas-Gutiérrez, Diana, Tosetti, Michela, Uhlmann, Anne, Van Rheenen, Tamsyn, Veltman, Dick, Vázquez-Bourgon, Javier, Schmaal, Lianne, Jahanshad, Neda, Winter, Alexandra, Wittfeld, Katharina, Yang, Tony T., Yoncheva, Yuliya, Bauer, Jochen, Zijlmans, Jendé L., Baumeister, Sarah, Lebedeva, Irina, van Erp, Theo G. M., Turner, Jessica, Jakobi, Babette, Castellanos, F. Xavier, Pausova, Zdenka, Thompson, Paul, Paus, Tomas, Bernardoni, Fabio, Bertolino, Alessandro, Bonnin, Caterina Del Mar, Brandeis, Daniel, Luna, Beatriz, Brem, Silvia, Jansen, Andreas, Bruggemann, Jason, Bülow, Robin, Bustillo, Juan R., Calderoni, Sara, Calvo, Rosa, Canales-Rodríguez, Erick J., Cannon, Dara M., Carmona, Susanna, Carr, Vaughan J., Lundervold, Astri J., Janssen, Joost, Catts, Stanley V., Chenji, Sneha, Chew, Qian Hui, Coghill, David, Connolly, Colm G., Conzelmann, Annette, Craven, Alexander R., Crespo-Facorro, Benedicto, Cullen, Kathryn, Dahl, Andreas, Jonassen, Rune, MacMaster, Frank P., Dannlowski, Udo, Davey, Christopher G., Deruelle, Christine, Díaz-Caneja, Covadonga M., Dohm, Katharina, Ehrlich, Stefan, Epstein, Jeffery, Erwin-Grabner, Tracy, Eyler, Lisa T., Kaiser, Anna, Fedor, Jennifer, Maglanoc, Luigi A., Fitzgerald, Jacqueline, Foran, William, Ford, Judith M., Fortea, Lydia, Fuentes-Claramonte, Paola, Fullerton, Janice, Furlong, Lisa, Gallagher, Louise, Kaleda, Vasiliy, Gao, Bingchen, Gao, Si, Mathalon, Daniel H., Goikolea, Jose M., Gotlib, Ian, Goya-Maldonado, Roberto, Grabe, Hans J., Green, Melissa, Grevet, Eugenio H., Groenewold, Nynke A., Karantonis, James, Grotegerd, Dominik., German Research Foundation, University of Münster, National Health and Medical Research Council (Australia), University of Cape Town, National Research Foundation (South Africa), Swinburne University of Technology, Jack Brockhoff Foundation, University of Melbourne, Barbara Dicker Brain Sciences Foundation, Rebecca L. Cooper Medical Research Foundation, Society for Mental Health Research (Australia), Swedish Research Council, Swedish Foundation for Strategic Research, Swedish Brain Foundation, Health Research Board (Ireland), Russian Foundation for Basic Research, University of Zurich, Pratt Foundation, Ramsay Health Care, Viertel Charitable Foundation, Schizophrenia Research Institute (Australia), European Commission, Australian Research Council, Instituto de Salud Carlos III, National Institute for Health and Care Research (US), National Institute for Health Research (UK), Ministry of Health of the Czech Republic, Bill & Melinda Gates Foundation, South African Medical Research Council, Carnegie Corporation of New York, Wellcome Trust, Medical Research Council (UK), Medical Research Scotland, Netherlands Organization for Scientific Research, Ambrogi, Sonia [0000-0002-2897-358X], Banaschewski, Tobias [0000-0003-4595-1144], Bandeira, Cibele Edom [0000-0003-0681-1309], Cupertino, Renata [0000-0002-3452-0632], Calderoni, Sara [0000-0002-6250-5739], Cannon, Dara [0000-0001-7378-3411], Carr, Vaughan [0000-0002-8907-5804], Chew, Qian Hui [0000-0003-0969-7994], Coghill, David [0000-0003-3017-9737], Cullen, Kathryn [0000-0001-9631-3770], Dahl, Andreas [0000-0002-8097-2082], Epstein, Jeffery [0000-0003-3464-5256], Foran, William [0000-0001-7491-9798], Fortea, Lydia [0000-0001-6778-2316], Fuentes-Claramonte, Paola [0000-0002-1428-7976], Fullerton, Janice M. [0000-0003-4014-4490], Furlong, Lisa [0000-0001-6196-4565], Gallagher, Louise [0000-0001-9462-2836], Gao, Si [0000-0002-4473-1142], Gotlib, Ian [0000-0002-3622-3199], Haavik, Jan [0000-0001-7865-2808], Henskens, Frans [0000-0003-2358-5630], Hilland, Eva [0000-0002-7102-8372], Hoekstra, Pieter J [0000-0001-7260-4119], Howells, Fleur M [0000-0001-9759-2556], Ipser, Jonathan [0000-0003-1272-0032], Jørgensen, Jes Kristian [0000-0001-9133-1670], Karantonis, James A. [0000-0003-2281-0912], Lawrie, Stephen [0000-0002-2444-5675], Patel, Yash, Shin, Jean, Abé, Christoph, Agartz, Ingrid, Alloza, Clara, Alnæs, Dag, Ambrogi, Sonia, Antonucci, Linda A., Arango, Celso, Arolt, Volker, Auzias, Guillaume, Gruber, Oliver, Haavik, Jan, McDonald, Colm, Hahn, Tim, Harrison, Ben J., Heindel, Walter, Henskens, Frans, Heslenfeld, Dirk J., Hilland, Eva, King, Joseph A., Vernooij, Meike W., Hoekstra, Pieter J., Hohmann, Sarah, Holz, Nathalie, Howells, Fleur M., McIntosh, Andrew, Ipser, Jonathan C., Meinert, Susanne, Hoogman, Martine, Kircher, Tilo, Kochunov, Peter, Vieta, Eduard, Koopowitz, Sheri-Michelle, Landén, Mikael, Landrø, Nils Inge, Lawrie, Stephen, Michie, Patricia T., Ayesa Arriola, Rosa, Mitchell, Philip, Moreno-Alcázar, Ana, Franke, Barbara, Mowry, Bryan, Bau, Claiton H. D., Muratori, Filippo, Nabulsi, Leila, Nenadić, Igor, O'Gorman Tuura, Ruth, Oosterlaan, Jaap, Overs, Bronwyn, Pantelis, Christos, Banaj, Nerisa, Parellada, Mara, van Rooij, Daan, Vilarroya, Oscar, Pariente, Jose C., Pauli, Paul, Pergola, Giulio, Piarulli, Francesco Maria, Picon, Felipe, Piras, Fabrizio, Pomarol-Clotet, Edith, Pretus, Clara, Quidé, Yann, Banaschewski, Tobias, Weickert, Cynthia, Buitelaar, Jan, Radua, Joaquim, Ramos-Quiroga, J. Antoni, Rasser, Paul E., Reif, Andreas, Retico, Alessandra, Roberts, Gloria, Rossell, Susan, Rovaris, Diego Luiz, Rubia, Katya, Weickert, Thomas, Sacchet, Matthew, Ching, Christopher R. K., Bandeira, Cibele, Salavert, Josep, Salvador, Raymond, Sarró, Salvador, Sawa, Akira, Schall, Ulrich, Scott, Rodney, Selvaggi, Pierluigi, Westlye, Lars T., Silk, Tim, Sim, Kang, Andreassen, Ole A., Skoch, Antonin, Başgöze, Zeynep, Spalletta, Gianfranco, Spaniel, Filip, Stein, Dan J., Steinsträter, Olaf, Stolicyn, Aleks, Whalley, Heather, Takayanagi, Yoichiro, Tamm, Leanne, Tavares, Maria, Pozzi, Elena, Teumer, Alexander, Thiel, Katharina, Cupertino, Renata Basso, Thomopoulos, Sophia I., Tomecek, David, Tomyshev, Alexander S., Willinger, David, Tordesillas-Gutiérrez, Diana, Tosetti, Michela, Uhlmann, Anne, Van Rheenen, Tamsyn, Veltman, Dick, Vázquez-Bourgon, Javier, Schmaal, Lianne, Jahanshad, Neda, Winter, Alexandra, Wittfeld, Katharina, Yang, Tony T., Yoncheva, Yuliya, Bauer, Jochen, Zijlmans, Jendé L., Baumeister, Sarah, Lebedeva, Irina, van Erp, Theo G. M., Turner, Jessica, Jakobi, Babette, Castellanos, F. Xavier, Pausova, Zdenka, Thompson, Paul, Paus, Tomas, Bernardoni, Fabio, Bertolino, Alessandro, Bonnin, Caterina Del Mar, Brandeis, Daniel, Luna, Beatriz, Brem, Silvia, Jansen, Andreas, Bruggemann, Jason, Bülow, Robin, Bustillo, Juan R., Calderoni, Sara, Calvo, Rosa, Canales-Rodríguez, Erick J., Cannon, Dara M., Carmona, Susanna, Carr, Vaughan J., Lundervold, Astri J., Janssen, Joost, Catts, Stanley V., Chenji, Sneha, Chew, Qian Hui, Coghill, David, Connolly, Colm G., Conzelmann, Annette, Craven, Alexander R., Crespo-Facorro, Benedicto, Cullen, Kathryn, Dahl, Andreas, Jonassen, Rune, MacMaster, Frank P., Dannlowski, Udo, Davey, Christopher G., Deruelle, Christine, Díaz-Caneja, Covadonga M., Dohm, Katharina, Ehrlich, Stefan, Epstein, Jeffery, Erwin-Grabner, Tracy, Eyler, Lisa T., Kaiser, Anna, Fedor, Jennifer, Maglanoc, Luigi A., Fitzgerald, Jacqueline, Foran, William, Ford, Judith M., Fortea, Lydia, Fuentes-Claramonte, Paola, Fullerton, Janice, Furlong, Lisa, Gallagher, Louise, Kaleda, Vasiliy, Gao, Bingchen, Gao, Si, Mathalon, Daniel H., Goikolea, Jose M., Gotlib, Ian, Goya-Maldonado, Roberto, Grabe, Hans J., Green, Melissa, Grevet, Eugenio H., Groenewold, Nynke A., Karantonis, James, and Grotegerd, Dominik.
Abstract: [Background]: Morphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life., [Methods]: Interregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed., [Results]: Across the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth., [Conclusions]: Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from typical brain development during pregnancy.
Published: 2022

153. Virtual Ontogeny of Cortical Growth Preceding Mental Illness

Author: Patel, Y., Shin, J., Abé, C., Agartz, I., Alloza, C., Alnæs, D., Ambrogi, S., Antonucci, L.A., Arango, C., Arolt, V., Auzias, G., Ayesa-Arriola, R., Banaj, N., Banaschewski, T., Bandeira, C., Başgöze, Z., Cupertino, R.B., Bau, C.H.D., Bauer, J., Baumeister, S., Bernardoni, F., Bertolino, A., Bonnin, C.D.M., Brandeis, D., Brem, S., Bruggemann, J., Bülow, R., Bustillo, J.R., Calderoni, S., Calvo, R., Canales-Rodríguez, E.J., Cannon, D.M., Carmona, S., Carr, V.J., Catts, S.V., Chenji, S., Chew, Q.H., Coghill, D., Connolly, C.G., Conzelmann, A., Craven, A.R., Crespo-Facorro, B., Cullen, K., Dahl, A., Dannlowski, U., Davey, C.G., Deruelle, C., Díaz-Caneja, C.M., Dohm, K., Ehrlich, S., Epstein, J., Erwin-Grabner, T., Eyler, L.T., Fedor, J., Fitzgerald, J., Foran, W., Ford, J.M., Fortea, L., Fuentes-Claramonte, P., Fullerton, J., Furlong, L., Gallagher, L., Gao, B., Gao, S., Goikolea, J.M., Gotlib, I., Goya-Maldonado, R., Grabe, H.J., Green, M., Grevet, E.H., Groenewold, N.A., Grotegerd, D., Gruber, O., Haavik, J., Hahn, T., Harrison, B.J., Heindel, W., Henskens, F., Heslenfeld, D.J., Hilland, E., Hoekstra, P.J., Hohmann, S., Holz, N., Howells, F.M., Ipser, J.C., Jahanshad, N., Jakobi, B., Jansen, A., Janssen, J., Jonassen, R., Kaiser, A., Kaleda, V., Karantonis, J., King, J.A., Kircher, T., Kochunov, P., Koopowitz, S.-M., Landén, M., Landrø, N.I., Lawrie, S., Lebedeva, I., Luna, B., Lundervold, A.J., MacMaster, F.P., Maglanoc, L.A., Mathalon, D.H., McDonald, C., McIntosh, A., Meinert, S., Michie, P.T., Mitchell, P., Moreno-Alcázar, A., Mowry, B., Muratori, F., Nabulsi, L., Nenadić, I., O'Gorman Tuura, R., Oosterlaan, J., Overs, B., Pantelis, C., Parellada, M., Pariente, J.C., Pauli, P., Pergola, G., Piarulli, F.M., Picon, F., Piras, F., Pomarol-Clotet, E., Pretus, C., Quidé, Y., Radua, J., Ramos-Quiroga, J.A., Rasser, P.E., Reif, A., Retico, A., Roberts, G., Rossell, S., Rovaris, D.L., Rubia, K., Sacchet, M., Salavert, J., Salvador, R., Sarró, S., Sawa, A., Schall, U., Scott, R., Selvaggi, P., Silk, T., Sim, K., Skoch, A., Spalletta, G., Spaniel, F., Stein, D.J., Steinsträter, O., Stolicyn, A., Takayanagi, Y., Tamm, L., Tavares, M., Teumer, A., Thiel, K., Thomopoulos, S.I., Tomecek, D., Tomyshev, A.S., Tordesillas-Gutiérrez, D., Tosetti, M., Uhlmann, A., Van Rheenen, T., Vazquez-Bourgón, J., Vernooij, M.W., Vieta, E., Vilarroya, O., Weickert, C., Weickert, T., Westlye, L.T., Whalley, H., Willinger, D., Winter, A., Wittfeld, K., Yang, T.T., Yoncheva, Y., Zijlmans, J.L., Hoogman, M., Franke, B., van Rooij, D., Buitelaar, J., Ching, C.R.K., Andreassen, O.A., Pozzi, E., Veltman, D., Schmaal, L., van Erp, T.G.M., Turner, J., Castellanos, F.X., Pausova, Z., Thompson, P., Paus, T., Patel, Y., Shin, J., Abé, C., Agartz, I., Alloza, C., Alnæs, D., Ambrogi, S., Antonucci, L.A., Arango, C., Arolt, V., Auzias, G., Ayesa-Arriola, R., Banaj, N., Banaschewski, T., Bandeira, C., Başgöze, Z., Cupertino, R.B., Bau, C.H.D., Bauer, J., Baumeister, S., Bernardoni, F., Bertolino, A., Bonnin, C.D.M., Brandeis, D., Brem, S., Bruggemann, J., Bülow, R., Bustillo, J.R., Calderoni, S., Calvo, R., Canales-Rodríguez, E.J., Cannon, D.M., Carmona, S., Carr, V.J., Catts, S.V., Chenji, S., Chew, Q.H., Coghill, D., Connolly, C.G., Conzelmann, A., Craven, A.R., Crespo-Facorro, B., Cullen, K., Dahl, A., Dannlowski, U., Davey, C.G., Deruelle, C., Díaz-Caneja, C.M., Dohm, K., Ehrlich, S., Epstein, J., Erwin-Grabner, T., Eyler, L.T., Fedor, J., Fitzgerald, J., Foran, W., Ford, J.M., Fortea, L., Fuentes-Claramonte, P., Fullerton, J., Furlong, L., Gallagher, L., Gao, B., Gao, S., Goikolea, J.M., Gotlib, I., Goya-Maldonado, R., Grabe, H.J., Green, M., Grevet, E.H., Groenewold, N.A., Grotegerd, D., Gruber, O., Haavik, J., Hahn, T., Harrison, B.J., Heindel, W., Henskens, F., Heslenfeld, D.J., Hilland, E., Hoekstra, P.J., Hohmann, S., Holz, N., Howells, F.M., Ipser, J.C., Jahanshad, N., Jakobi, B., Jansen, A., Janssen, J., Jonassen, R., Kaiser, A., Kaleda, V., Karantonis, J., King, J.A., Kircher, T., Kochunov, P., Koopowitz, S.-M., Landén, M., Landrø, N.I., Lawrie, S., Lebedeva, I., Luna, B., Lundervold, A.J., MacMaster, F.P., Maglanoc, L.A., Mathalon, D.H., McDonald, C., McIntosh, A., Meinert, S., Michie, P.T., Mitchell, P., Moreno-Alcázar, A., Mowry, B., Muratori, F., Nabulsi, L., Nenadić, I., O'Gorman Tuura, R., Oosterlaan, J., Overs, B., Pantelis, C., Parellada, M., Pariente, J.C., Pauli, P., Pergola, G., Piarulli, F.M., Picon, F., Piras, F., Pomarol-Clotet, E., Pretus, C., Quidé, Y., Radua, J., Ramos-Quiroga, J.A., Rasser, P.E., Reif, A., Retico, A., Roberts, G., Rossell, S., Rovaris, D.L., Rubia, K., Sacchet, M., Salavert, J., Salvador, R., Sarró, S., Sawa, A., Schall, U., Scott, R., Selvaggi, P., Silk, T., Sim, K., Skoch, A., Spalletta, G., Spaniel, F., Stein, D.J., Steinsträter, O., Stolicyn, A., Takayanagi, Y., Tamm, L., Tavares, M., Teumer, A., Thiel, K., Thomopoulos, S.I., Tomecek, D., Tomyshev, A.S., Tordesillas-Gutiérrez, D., Tosetti, M., Uhlmann, A., Van Rheenen, T., Vazquez-Bourgón, J., Vernooij, M.W., Vieta, E., Vilarroya, O., Weickert, C., Weickert, T., Westlye, L.T., Whalley, H., Willinger, D., Winter, A., Wittfeld, K., Yang, T.T., Yoncheva, Y., Zijlmans, J.L., Hoogman, M., Franke, B., van Rooij, D., Buitelaar, J., Ching, C.R.K., Andreassen, O.A., Pozzi, E., Veltman, D., Schmaal, L., van Erp, T.G.M., Turner, J., Castellanos, F.X., Pausova, Z., Thompson, P., and Paus, T.
Abstract: Background: Morphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life. Methods: Interregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed. Results: Across the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth. Conclusions: Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from t
Published: 2022
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154. Female children with autism spectrum disorder: An insight from mass-univariate and pattern classification analyses

Author: Calderoni, Sara, Retico, Alessandra, Biagi, Laura, Tancredi, Raffaella, Muratori, Filippo, and Tosetti, Michela
Published: 2012
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155. Subtly altered topological asymmetry of brain structural covariance networks in autism spectrum disorder across 43 datasets from the ENIGMA consortium

Author: Zhiqiang Sha, Daan van Rooij, Evdokia Anagnostou, Celso Arango, Guillaume Auzias, Marlene Behrmann, Boris Bernhardt, Sven Bolte, Geraldo F. Busatto, Sara Calderoni, Rosa Calvo, Eileen Daly, Christine Deruelle, Meiyu Duan, Fabio Luis Souza Duran, Sarah Durston, Christine Ecker, Stefan Ehrlich, Damien Fair, Jennifer Fedor, Jacqueline Fitzgerald, Dorothea L. Floris, Barbara Franke, Christine M. Freitag, Louise Gallagher, David C. Glahn, Shlomi Haar, Liesbeth Hoekstra, Neda Jahanshad, Maria Jalbrzikowski, Joost Janssen, Joseph A. King, Luisa Lazaro, Beatriz Luna, Jane McGrath, Sarah E. Medland, Filippo Muratori, Declan G. M. Murphy, Janina Neufeld, Kirsten O’Hearn, Bob Oranje, Mara Parellada, Jose C. Pariente, Merel C. Postema, Karl Lundin Remnelius, Alessandra Retico, Pedro Gomes Penteado Rosa, Katya Rubia, Devon Shook, Kristiina Tammimies, Margot J. Taylor, Michela Tosetti, Gregory L. Wallace, Fengfeng Zhou, Paul M. Thompson, Simon E. Fisher, Jan K. Buitelaar, Clyde Francks, Donders Center for Cognitive Neuroimaging, Donders Centre for Cognitive Neuroimaging, Radboud University [Nijmegen]-Radboud University [Nijmegen], Holland Bloorview Kids Rehabilitation Hospital [Toronto, ON, Canada], University of Toronto, Universidad Complutense de Madrid = Complutense University of Madrid [Madrid] (UCM), Institut de Neurosciences de la Timone (INT), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Karolinska Institutet [Stockholm], Stockholm Health Care Services (SLSO), Curtin University [Perth], Planning and Transport Research Centre (PATREC), Universidade de São Paulo = University of São Paulo (USP), University of Pisa - Università di Pisa, Department of Child and Adolescent Psychiatry and Psychology, Centro de Investigación Biomédica en Red de Salut Mental (CIBER-SAM Network), Hospital Clinic Barcelona, King‘s College London, University Medical Center [Utrecht], Goethe-Universität Frankfurt am Main, MetaGenoPolis (MGP (US 1367)), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Oregon Health and Science University [Portland] (OHSU), McConnell Brain Imaging Centre (MNI), Montreal Neurological Institute and Hospital, and McGill University = Université McGill [Montréal, Canada]-McGill University = Université McGill [Montréal, Canada]
Subjects: Neuroinformatics, Biochemistry & Molecular Biology, Autism Spectrum Disorder, [SDV]Life Sciences [q-bio], CHILDREN, ORGANIZATION, ACTIVATION, Cellular and Molecular Neuroscience, CONNECTIVITY, 130 000 Cognitive Neurology & Memory, CEREBRAL-CORTEX, Neural Pathways, Humans, HETEROGENEITY, Molecular Biology, 11 Medical and Health Sciences, Psychiatry, Cerebral Cortex, Brain Mapping, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], Science & Technology, LANGUAGE LATERALIZATION, Neurosciences, Brain, 06 Biological Sciences, Magnetic Resonance Imaging, 17 Psychology and Cognitive Sciences, Psychiatry and Mental health, INDIVIDUALS, MORPHOMETRY, Neurosciences & Neurology, Life Sciences & Biomedicine, CORTICAL THICKNESS
Abstract: Contains fulltext : 251394.pdf (Publisher’s version ) (Open Access) Small average differences in the left-right asymmetry of cerebral cortical thickness have been reported in individuals with autism spectrum disorder (ASD) compared to typically developing controls, affecting widespread cortical regions. The possible impacts of these regional alterations in terms of structural network effects have not previously been characterized. Inter-regional morphological covariance analysis can capture network connectivity between different cortical areas at the macroscale level. Here, we used cortical thickness data from 1455 individuals with ASD and 1560 controls, across 43 independent datasets of the ENIGMA consortium's ASD Working Group, to assess hemispheric asymmetries of intra-individual structural covariance networks, using graph theory-based topological metrics. Compared with typical features of small-world architecture in controls, the ASD sample showed significantly altered average asymmetry of networks involving the fusiform, rostral middle frontal, and medial orbitofrontal cortex, involving higher randomization of the corresponding right-hemispheric networks in ASD. A network involving the superior frontal cortex showed decreased right-hemisphere randomization. Based on comparisons with meta-analyzed functional neuroimaging data, the altered connectivity asymmetry particularly affected networks that subserve executive functions, language-related and sensorimotor processes. These findings provide a network-level characterization of altered left-right brain asymmetry in ASD, based on a large combined sample. Altered asymmetrical brain development in ASD may be partly propagated among spatially distant regions through structural connectivity.
Published: 2022

156. Computer-aided detection of pulmonary nodules in low-dose CT.

Author: Pasquale Delogu, Maria Evelina Fantacci, Ilaria Gori, A. Preite Martinez, and Alessandra Retico
Published: 2006

157. EXPLAINING THE BEHAVIOUR OF A CONVOLUTIONAL NEURAL NETWORK FOR BREAST DENSITY ASSESSMENT

Author: Camilla Scapicchio, Alessandra Retico, Francesca Lizzi, and Maria Evelina Fantacci
Subjects: Biophysics, General Physics and Astronomy, Radiology, Nuclear Medicine and imaging, General Medicine
Published: 2022

158. IMPROVING THE PERFORMANCE OF MACHINE LEARNING MODELS THROUGH A MULTI-SITE MRI DATA HARMONIZATION FRAMEWORK

Author: Sara Saponaro, Alessia Giuliano, Roberto Bellotti, Angela Lombardi, Sabina Tangaro, Piernicola Oliva, Sara Calderoni, and Alessandra Retico
Subjects: Biophysics, General Physics and Astronomy, Radiology, Nuclear Medicine and imaging, General Medicine
Published: 2022

159. DETECTION OF INTER-FRACTION MORPHOLOGICAL VARIATIONS IN 12C IONS TREATMENTS: RESULTS FROM A CLINICAL TRIAL AT CNAO FACILITY

Author: Micol De Simoni, Giuseppe Battistoni, Andrea Berti, Maria Giuseppina Bisogni, Pietro Carra, Piergiorgio Cerello, Mario Ciocca, Yun Dong, Veronica Ferrero, Elisa Fiorina, Marta Fischetti, Mr. Gabriele Giacchi, Aafke Christine Kraan, Michela Marafini, Ilaria Mattei, Enrico Mazzoni, Martina Moglioni, Matteo Morrocchi, Silvia Muraro, Ester Orlandi, Vincenzo Patera, Francesco Pennazio, Alessandra Retico, Alessio Sarti, Giancarlo Sportelli, Marco Toppi, Barbara Vischioni, Viviana Vitolo, Richard J. Wheadon, and Giacomo Traini
Subjects: Biophysics, General Physics and Astronomy, Radiology, Nuclear Medicine and imaging, General Medicine
Published: 2022

160. Voxelized breast phantoms for dosimetry in mammography

Author: Rocco Lamastra, Alessandra Retico, A. C. Traino, Antonio Sarno, Paolo Russo, Giovanni Mettivier, Maria Evelina Fantacci, Raffaele M. Tucciariello, D. Del Sarto, Patrizio Barca, Fantacci, M., Traino, A., Sarno, A., Russo, P., Retico, A., Mettivier, G., Lamastra, R., Sarto, D., Barca, P., and Tucciariello, R.
Subjects: medicine.medical_specialty, medicine.diagnostic_test, business.industry, Digital Mammography, GEANT4, Heterogeneous Breast Phantoms, Monte Carlo Simulations, Voxelized Phantoms, X-Ray Breast Dosimetry, medicine, Dosimetry, Mammography, Monte Carlo Simulations, Digital Mammography, X-Ray Breast Dosimetry, Voxelized Phantoms, Heterogeneous Breast Phantoms, GEANT4, Medical physics, business
Abstract: X-ray breast imaging techniques are an essential part of breast cancer screening programs and their improvements lead to gain in performance and accuracy. Radiation dose estimate and control play an important role in digital mammography and digital breast tomosynthesis investigations, since the risk of radioinduced cancer to the gland must be contained and dose delivered to the gland must be declared in the medical report. The actual dosimetric protocols suggest the assessment of radiation dose by means of Monte Carlo calculation on digital breast phantoms, providing the assumption of the homogeneous mixture of glandular and adipose tissues within the breast organ, leading to a drastic approximation. In line with the trend of other research groups, with the aim of improving the Monte Carlo model, in the current work a new heterogeneous digital breast model is proposed, involving a voxelized approach and disengaging from the concept of homogeneous phantom. The proposed model is based on new findings in the literature and after a validation process, the model is adopted to evaluate mean glandular dose discrepancies with the traditional model which is adopted in clinic for decades.
Published: 2021

161. Enhancing the impact of Artificial Intelligence in Medicine: A joint AIFM-INFN Italian initiative for a dedicated cloud-based computing infrastructure

Author: Cinzia Talamonti, Michele Avanzo, Michele Stasi, Annalisa Trianni, Mauro Iori, Alessandra Retico, Daniele Spiga, Francesca Botta, Davide Salomoni, Tommaso Boccali, Giacomo Cuttone, Daniele Bonacorsi, B Martelli, Retico, Alessandra, Avanzo, Michele, Boccali, Tommaso, Bonacorsi, Daniele, Botta, Francesca, Cuttone, Giacomo, Martelli, Barbara, Salomoni, Davide, Spiga, Daniele, Trianni, Annalisa, Stasi, Michele, Iori, Mauro, and Talamonti, Cinzia
Subjects: Artificial intelligenceDecision support systemsComputing infrastructureDistributed learning, Decision support system, business.industry, Artificial intelligence, Computing infrastructure, Decision support systems, Distributed learning, Humans, Italy, Nuclear Physics, Precision Medicine, Artificial Intelligence, Cloud Computing, Big data, Biophysics, General Physics and Astronomy, Cloud computing, General Medicine, Precision medicine, Field (computer science), Workflow, Medical imaging, Data Protection Act 1998, Radiology, Nuclear Medicine and imaging, business
Abstract: Artificial Intelligence (AI) techniques have been implemented in the field of Medical Imaging for more than forty years. Medical Physicists, Clinicians and Computer Scientists have been collaborating since the beginning to realize software solutions to enhance the informative content of medical images, including AI-based support systems for image interpretation. Despite the recent massive progress in this field due to the current emphasis on Radiomics, Machine Learning and Deep Learning, there are still some barriers to overcome before these tools are fully integrated into the clinical workflows to finally enable a precision medicine approach to patients’ care. Nowadays, as Medical Imaging has entered the Big Data era, innovative solutions to efficiently deal with huge amounts of data and to exploit large and distributed computing resources are urgently needed. In the framework of a collaboration agreement between the Italian Association of Medical Physicists (AIFM) and the National Institute for Nuclear Physics (INFN), we propose a model of an intensive computing infrastructure, especially suited for training AI models, equipped with secure storage systems, compliant with data protection regulation, which will accelerate the development and extensive validation of AI-based solutions in the Medical Imaging field of research. This solution can be developed and made operational by Physicists and Computer Scientists working on complementary fields of research in Physics, such as High Energy Physics and Medical Physics, who have all the necessary skills to tailor the AI-technology to the needs of the Medical Imaging community and to shorten the pathway towards the clinical applicability of AI-based decision support systems.
Published: 2021

162. Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders

Author: Committee, Writing, Disorder, Autism Spectrum, French, Leon, Grevet, Eugenio H, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Gruner, Patricia, Guerrero-Pedraza, Amalia, Gur, Raquel E, Gur, Ruben C, Haar, Shlomi, Haarman, Bartholomeus C M, Thomopoulos, Sophia I, Haavik, Jan, Hahn, Tim, Hajek, Tomas, Harrison, Benjamin J, Harrison, Neil A, Hartman, Catharina A, Whalley, Heather C, Heslenfeld, Dirk J, Hibar, Derrek P, Hilland, Eva, Pozzi, Elena, Hirano, Yoshiyuki, Ho, Tiffany C, Hoekstra, Pieter J, Hoekstra, Liesbeth, Hohmann, Sarah, Hong, L. E., Höschl, Cyril, Høvik, Marie F, Howells, Fleur M, Nenadic, Igor, Abe, Yoshinari, Jalbrzikowski, Maria, James, Anthony C, Janssen, Joost, Jaspers-Fayer, Fern, Xu, Jian, Jonassen, Rune, Karkashadze, Georgii, King, Joseph A, Kircher, Tilo, Kirschner, Matthias, Abé, Christoph, Koch, Kathrin, Kochunov, Peter, Kohls, Gregor, Konrad, Kerstin, Krämer, Bernd, Krug, Axel, Kuntsi, Jonna, Kwon, Jun Soo, Landén, Mikael, Landrø, Nils I, Anticevic, Alan, Lazaro, Luisa, Lebedeva, Irina S, Leehr, Elisabeth J, Lera-Miguel, Sara, Lesch, Klaus-Peter, Lochner, Christine, Louza, Mario R, Luna, Beatriz, Lundervold, Astri J, MacMaster, Frank P, Alda, Martin, Maglanoc, Luigi A, Malpas, Charles B, Portella, Maria J, Marsh, Rachel, Martyn, Fiona M, Mataix-Cols, David, Mathalon, Daniel H, McCarthy, Hazel, McDonald, Colm, McPhilemy, Genevieve, Aleman, Andre, Meinert, Susanne, Menchón, José M, Minuzzi, Luciano, Mitchell, Philip B, Moreno, Carmen, Morgado, Pedro, Muratori, Filippo, Murphy, Clodagh M, Murphy, Declan, Mwangi, Benson, Alloza, Clara, Nabulsi, Leila, Nakagawa, Akiko, Nakamae, Takashi, Namazova, Leyla, Narayanaswamy, Janardhanan, Jahanshad, Neda, Nguyen, Danai D, Nicolau, Rosa, O'Gorman Tuura, Ruth L, O'Hearn, Kirsten, Alonso-Lana, Silvia, Oosterlaan, Jaap, Opel, Nils, Ophoff, Roel A, Oranje, Bob, García de la Foz, Victor Ortiz, Overs, Bronwyn J, Paloyelis, Yannis, Pantelis, Christos, Parellada, Mara, Pauli, Paul, Disorder, Bipolar, Ameis, Stephanie H, Picó-Pérez, Maria, Picon, Felipe A, Piras, Fabrizio, Piras, Federica, Plessen, Kerstin J, Pomarol-Clotet, Edith, Preda, Adrian, Puig, Olga, Quidé, Yann, Radua, Joaquim, Anagnostou, Evdokia, Ramos-Quiroga, J Antoni, Rasser, Paul E, Rauer, Lisa, Reddy, Janardhan, Redlich, Ronny, Reif, Andreas, Reneman, Liesbeth, Repple, Jonathan, Retico, Alessandra, Richarte, Vanesa, McIntosh, Andrew A, Richter, Anja, Rosa, Pedro G P, Rubia, Katya K, Hashimoto, Ryota, Sacchet, Matthew D, Salvador, Raymond, Santonja, Javier, Sarink, Kelvin, Sarró, Salvador, Satterthwaite, Theodore D, Arango, Celso, Sawa, Akira, Schall, Ulrich, Schofield, Peter R, Schrantee, Anouk, Seitz, Jochen, Serpa, Mauricio H, Setién-Suero, Esther, Shaw, Philip, Shook, Devon, Silk, Tim J, Arnold, Paul D, Sim, Kang, Simon, Schmitt, Simpson, Helen Blair, Singh, Aditya, Skoch, Antonin, Skokauskas, Norbert, Soares, Jair C, Soreni, Noam, Soriano-Mas, Carles, Spalletta, Gianfranco, Asherson, Philip, Spaniel, Filip, Lawrie, Stephen M, Stern, Emily R, Stewart, S Evelyn, Takayanagi, Yoichiro, Temmingh, Henk S, Tolin, David F, Tomecek, David, Tordesillas-Gutiérrez, Diana, Tosetti, Michela, Assogna, Francesca, Uhlmann, Anne, van Amelsvoort, Therese, van der Wee, Nic J A, van der Werff, Steven J A, van Haren, Neeltje E M, van Wingen, Guido A, Vance, Alasdair, Vázquez-Bourgon, Javier, Vecchio, Daniela, Venkatasubramanian, Ganesan, Auzias, Guillaume, Vieta, Eduard, Vilarroya, Oscar, Vives-Gilabert, Yolanda, Voineskos, Aristotle N, Völzke, Henry, von Polier, Georg G, Walton, Esther, Weickert, Thomas W, Weickert, Cynthia Shannon, Weideman, Andrea S, Ayesa-Arriola, Rosa, Wittfeld, Katharina, Wolf, Daniel H, Wu, Mon-Ju, Yang, T. T., Yang, Sikun, Yoncheva, Yuliya, Yun, Je-Yeon, Cheng, Yuqi, Zanetti, Marcus V, Ziegler, Georg C, Bakker, Geor, Franke, Barbara, Hoogman, Martine, Buitelaar, Jan K, van Rooij, Daan, Andreassen, Ole A, Ching, Christopher R K, Veltman, Dick J, Schmaal, Lianne, Stein, Dan J, van den Heuvel, Odile A, Disorder, Major Depressive, Banaj, Nerisa, Turner, Jessica A, van Erp, Theo G M, Pausova, Zdenka, Thompson, Paul M, Paus, Tomáš, Attention-Deficit/Hyperactivity Disorder, Banaschewski, Tobias, Bandeira, Cibele E, Baranov, Alexandr, Bargalló, Núria, Bau, Claiton H D, Baumeister, Sarah, Baune, Bernhard T, Bellgrove, Mark A, Benedetti, Francesco, Disorder, Obsessive-Compulsive, Bertolino, Alessandro, Boedhoe, Premika S W, Boks, Marco, Bollettini, Irene, Del Mar Bonnin, Caterina, Borgers, Tiana, Borgwardt, Stefan, Brandeis, Daniel, Brennan, Brian P, Bruggemann, Jason M, Groups, Schizophrenia ENIGMA Working, Bülow, Robin, Busatto, Geraldo F, Calderoni, Sara, Calhoun, Vince D, Calvo, Rosa, Canales-Rodríguez, Erick J, Cannon, Dara M, Carr, Vaughan J, Cascella, Nicola, Cercignani, Mara, Patel, Yash, Chaim-Avancini, Tiffany M, Christakou, Anastasia, Coghill, David, Conzelmann, Annette, Crespo-Facorro, Benedicto, Cubillo, Ana I, Cullen, Kathryn R, Cupertino, Renata B, Daly, Eileen, Dannlowski, Udo, Parker, Nadine, Davey, Christopher G, Denys, Damiaan, Deruelle, Christine, Di Giorgio, Annabella, Dickie, Erin W, Dima, Danai, Dohm, Katharina, Ehrlich, Stefan, Ely, Benjamin A, Erwin-Grabner, Tracy, Shin, Jean, Ethofer, Thomas, Fair, Damien A, Fallgatter, Andreas, Faraone, Stephen V, Fatjó-Vilas, Mar, Fedor, Jennifer M, Fitzgerald, Kate D, Ford, Judith M, Frodl, Thomas, Fu, Cynthia H Y, Howard, Derek, Fullerton, Janice M, Gabel, Matt C, Glahn, David C, Roberts, Gloria, Gogberashvili, Tinatin, Goikolea, Jose M, Gotlib, Ian H, Goya-Maldonado, Roberto, Grabe, Hans, Green, Melissa J, Patel, Y., Parker, N., Shin, J., Howard, D., French, L., Thomopoulos, S. I., Pozzi, E., Abe, Y., Abe, C., Anticevic, A., Alda, M., Aleman, A., Alloza, C., Alonso-Lana, S., Ameis, S. H., Anagnostou, E., Mcintosh, A. A., Arango, C., Arnold, P. D., Asherson, P., Assogna, F., Auzias, G., Ayesa-Arriola, R., Bakker, G., Banaj, N., Banaschewski, T., Bandeira, C. E., Baranov, A., Bargallo, N., Bau, C. H. D., Baumeister, S., Baune, B. T., Bellgrove, M. A., Benedetti, F., Bertolino, A., Boedhoe, P. S. W., Boks, M., Bollettini, I., Del Mar Bonnin, C., Borgers, T., Borgwardt, S., Brandeis, D., Brennan, B. P., Bruggemann, J. M., Bulow, R., Busatto, G. F., Calderoni, S., Calhoun, V. D., Calvo, R., Canales-Rodriguez, E. J., Cannon, D. M., Carr, V. J., Cascella, N., Cercignani, M., Chaim-Avancini, T. M., Christakou, A., Coghill, D., Conzelmann, A., Crespo-Facorro, B., Cubillo, A. I., Cullen, K. R., Cupertino, R. B., Daly, E., Dannlowski, U., Davey, C. G., Denys, D., Deruelle, C., Di Giorgio, A., Dickie, E. W., Dima, D., Dohm, K., Ehrlich, S., Ely, B. A., Erwin-Grabner, T., Ethofer, T., Fair, D. A., Fallgatter, A. J., Faraone, S. V., Fatjo-Vilas, M., Fedor, J. M., Fitzgerald, K. D., Ford, J. M., Frodl, T., Fu, C. H. Y., Fullerton, J. M., Gabel, M. C., Glahn, D. C., Roberts, G., Gogberashvili, T., Goikolea, J. M., Gotlib, I. H., Goya-Maldonado, R., Grabe, H. J., Green, M. J., Grevet, E. H., Groenewold, N. A., Grotegerd, D., Gruber, O., Gruner, P., Guerrero-Pedraza, A., Gur, R. E., Gur, R. C., Haar, S., Haarman, B. C. M., Haavik, J., Hahn, T., Hajek, T., Harrison, B. J., Harrison, N. A., Hartman, C. A., Whalley, H. C., Heslenfeld, D. J., Hibar, D. P., Hilland, E., Hirano, Y., Ho, T. C., Hoekstra, P. J., Hoekstra, L., Hohmann, S., Hong, L. E., Hoschl, C., Hovik, M. F., Howells, F. M., Nenadic, I., Jalbrzikowski, M., James, A. C., Janssen, J., Jaspers-Fayer, F., Xu, J., Jonassen, R., Karkashadze, G., King, J. A., Kircher, T., Kirschner, M., Koch, K., Kochunov, P., Kohls, G., Konrad, K., Kramer, B., Krug, A., Kuntsi, J., Kwon, J. S., Landen, M., Landro, N. I., Lazaro, L., Lebedeva, I. S., Leehr, E. J., Lera-Miguel, S., Lesch, K. -P., Lochner, C., Louza, M. R., Luna, B., Lundervold, A. J., Macmaster, F. P., Maglanoc, L. A., Malpas, C. B., Portella, M. J., Marsh, R., Martyn, F. M., Mataix-Cols, D., Mathalon, D. H., Mccarthy, H., Mcdonald, C., Mcphilemy, G., Meinert, S., Menchon, J. M., Minuzzi, L., Mitchell, P. B., Moreno, C., Morgado, P., Muratori, F., Murphy, C. M., Murphy, D., Mwangi, B., Nabulsi, L., Nakagawa, A., Nakamae, T., Namazova, L., Narayanaswamy, J., Jahanshad, N., Nguyen, D. D., Nicolau, R., O'Gorman Tuura, R. L., O'Hearn, K., Oosterlaan, J., Opel, N., Ophoff, R. A., Oranje, B., Garcia De La Foz, V. O., Overs, B. J., Paloyelis, Y., Pantelis, C., Parellada, M., Pauli, P., Pico-Perez, M., Picon, F. A., Piras, F., Plessen, K. J., Pomarol-Clotet, E., Preda, A., Puig, O., Quide, Y., Radua, J., Ramos-Quiroga, J. A., Rasser, P. E., Rauer, L., Reddy, J., Redlich, R., Reif, A., Reneman, L., Repple, J., Retico, A., Richarte, V., Richter, A., Rosa, P. G. P., Rubia, K. K., Hashimoto, R., Sacchet, M. D., Salvador, R., Santonja, J., Sarink, K., Sarro, S., Satterthwaite, T. D., Sawa, A., Schall, U., Schofield, P. R., Schrantee, A., Seitz, J., Serpa, M. H., Setien-Suero, E., Shaw, P., Shook, D., Silk, T. J., Sim, K., Simon, S., Simpson, H. B., Singh, A., Skoch, A., Skokauskas, N., Soares, J. C., Soreni, N., Soriano-Mas, C., Spalletta, G., Spaniel, F., Lawrie, S. M., Stern, E. R., Stewart, S. E., Takayanagi, Y., Temmingh, H. S., Tolin, D. F., Tomecek, D., Tordesillas-Gutierrez, D., Tosetti, M., Uhlmann, A., Van Amelsvoort, T., Van Der Wee, N. J. A., Van Der Werff, S. J. A., Van Haren, N. E. M., Van Wingen, G. A., Vance, A., Vazquez-Bourgon, J., Vecchio, D., Venkatasubramanian, G., Vieta, E., Vilarroya, O., Vives-Gilabert, Y., Voineskos, A. N., Volzke, H., Von Polier, G. G., Walton, E., Weickert, T. W., Weickert, C. S., Weideman, A. S., Wittfeld, K., Wolf, D. H., Wu, M. -J., Yang, T. T., Yang, K., Yoncheva, Y., Yun, J. -Y., Cheng, Y., Zanetti, M. V., Ziegler, G. C., Franke, B., Hoogman, M., Buitelaar, J. K., Van Rooij, D., Andreassen, O. A., Ching, C. R. K., Veltman, D. J., Schmaal, L., Stein, D. J., Van Den Heuvel, O. A., Turner, J. A., Van Erp, T. G. M., Pausova, Z., Thompson, P. M., Paus, T., Institut de Neurosciences de la Timone (INT), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Pediatric surgery, Radiology and nuclear medicine, Anatomy and neurosciences, Psychiatry, Amsterdam Neuroscience - Brain Imaging, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Amsterdam Neuroscience - Neurodegeneration, Psychiatrie & Neuropsychologie, RS: MHeNs - R2 - Mental Health, MUMC+: MA Med Staf Spec Psychiatrie (9), Adult Psychiatry, ANS - Compulsivity, Impulsivity & Attention, General Paediatrics, ARD - Amsterdam Reproduction and Development, Radiology and Nuclear Medicine, APH - Personalized Medicine, ANS - Brain Imaging, ANS - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Mental Health, University of Zurich, Clinical Cognitive Neuropsychiatry Research Program (CCNP), Clinical Neuropsychology, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Child and Adolescent Psychiatry / Psychology, IBBA, and Cognitive Psychology
Subjects: Male, Obsessive-Compulsive Disorder, Bipolar Disorder, Autism Spectrum Disorder, Autism, [SDV]Life Sciences [q-bio], Gene Expression, cytology [Cerebral Cortex], Cohort Studies, Fetal Development, physiology [Gene Expression], 2738 Psychiatry and Mental Health, 0302 clinical medicine, diagnostic imaging [Cerebral Cortex], SCHIZOPHRENIA, BRAIN, Child, Obsessive-compulsive disorder (OCD), Original Investigation, Aged, 80 and over, Cerebral Cortex, 0303 health sciences, pathology [Depressive Disorder, Major], Principal Component Analysis, Adolescent psychiatry, 10058 Department of Child and Adolescent Psychiatry, Middle Aged, diagnostic imaging [Obsessive-Compulsive Disorder], REGIONS, Magnetic Resonance Imaging, 3. Good health, FALSE DISCOVERY RATE, Psychiatry and Mental health, Autism spectrum disorder, Schizophrenia, growth & development [Cerebral Cortex], Child, Preschool, Major depressive disorder, diagnostic imaging [Schizophrenia], Esquizofrènia, Female, Psiquiatria infantil, Psiquiatria de l'adolescència, diagnostic imaging [Autism Spectrum Disorder], Adult, medicine.medical_specialty, Adolescent, Human Development, 610 Medicine & health, diagnostic imaging [Bipolar Disorder], pathology [Autism Spectrum Disorder], diagnostic imaging [Depressive Disorder, Major], 03 medical and health sciences, Young Adult, All institutes and research themes of the Radboud University Medical Center, Neuroimaging, SDG 3 - Good Health and Well-being, CEREBRAL-CORTEX, Child psychiatry, medicine, Attention deficit hyperactivity disorder, Humans, Bipolar disorder, ddc:610, Psychiatry, pathology [Schizophrenia], 030304 developmental biology, Aged, Depressive Disorder, Major, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], business.industry, DENDRITE, Computational Biology, Correction, pathology [Attention Deficit Disorder with Hyperactivity], physiology [Fetal Development], medicine.disease, PATHOLOGY, pathology [Bipolar Disorder], pathology [Obsessive-Compulsive Disorder], 10036 Medical Clinic, Attention Deficit Disorder with Hyperactivity, 10054 Clinic for Psychiatry, Psychotherapy, and Psychosomatics, Case-Control Studies, DENSITY, ORIGINS, HIPPOCAMPUS, diagnostic imaging [Attention Deficit Disorder with Hyperactivity], pathology [Cerebral Cortex], Autisme, business, Neuroscience, 030217 neurology & neurosurgery, physiology [Human Development]
Abstract: [Importance] Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood., [Objective] To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia., [Design, Setting, and Participants] Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244., [Main Outcomes and Measures] Interregional profiles of group difference in cortical thickness between cases and controls., [Results] A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders., [Conclusions and Relevance] In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.
Published: 2021

163. Strategies to develop radiomics and machine learning models for lung cancer stage and histology prediction using small data samples

Author: L. Ubaldi, Giorgio Collura, Maria Evelina Fantacci, R.F. Borgese, Alessandra Retico, Antonella Tripoli, Francesco Laruina, Vito Valenti, B. Abbate, Giuseppe Ferrera, Maurizio Marrale, G. Iacoviello, Ubaldi L., Valenti V., Borgese R.F., Collura G., Fantacci M.E., Ferrera G., Iacoviello G., Abbate B.F., Laruina F., Tripoli A., Retico A., and Marrale M.
Subjects: Lung Neoplasms, Computer science, Biophysics, General Physics and Astronomy, Sample (statistics), Cross validation, Machine learning, computer.software_genre, Non-small cell lung cancer, Radiomics, Humans, Lung, Machine Learning, Neoplasm Staging, Carcinoma, Non-Small-Cell Lung, Cross-validation, Set (abstract data type), medicine, Radiology, Nuclear Medicine and imaging, Stage (cooking), Lung cancer, Non-Small-Cell Lung, Small data, business.industry, Carcinoma, General Medicine, medicine.disease, Random forest, Support vector machine, Artificial intelligence, business, computer
Abstract: Predictive models based on radiomics and machine-learning (ML) need large and annotated datasets for training, often difficult to collect. We designed an operative pipeline for model training to exploit data already available to the scientific community. The aim of this work was to explore the capability of radiomic features in predicting tumor histology and stage in patients with non-small cell lung cancer (NSCLC). We analyzed the radiotherapy planning thoracic CT scans of a proprietary sample of 47 subjects (L-RT) and integrated this dataset with a publicly available set of 130 patients from the MAASTRO NSCLC collection (Lung1). We implemented intra- and inter-sample cross-validation strategies (CV) for evaluating the ML predictive model performances with not so large datasets. We carried out two classification tasks: histology classification (3 classes) and overall stage classification (two classes: stage I and II). In the first task, the best performance was obtained by a Random Forest classifier, once the analysis has been restricted to stage I and II tumors of the Lung1 and L-RT merged dataset (AUC = 0.72 ± 0.11). For the overall stage classification, the best results were obtained when training on Lung1 and testing of L-RT dataset (AUC = 0.72 ± 0.04 for Random Forest and AUC = 0.84 ± 0.03 for linear-kernel Support Vector Machine). According to the classification task to be accomplished and to the heterogeneity of the available dataset(s), different CV strategies have to be explored and compared to make a robust assessment of the potential of a predictive model based on radiomics and ML.
Published: 2021

164. Node Centrality Measures Identify Relevant Structural MRI Features of Subjects with Autism

Author: Sara Calderoni, Giulia Menichetti, Daniel Remondini, Alessandra Retico, Marcello Zanghieri, Gastone Castellani, Zanghieri M., Menichetti G., Retico A., Calderoni S., Castellani G., and Remondini D.
Subjects: Network theory, Article, lcsh:RC321-571, 03 medical and health sciences, Functional brain, Class imbalance, 0302 clinical medicine, Autism disorder, Brain features, medicine, 0501 psychology and cognitive sciences, Brain feature, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, Group level, medicine.diagnostic_test, General Neuroscience, Node (networking), 05 social sciences, Magnetic resonance imaging, medicine.disease, Autism, Psychology, Centrality, Neuroscience, 030217 neurology & neurosurgery, 050104 developmental & child psychology
Abstract: Autism spectrum disorders (ASDs) are a heterogeneous group of neurodevelopmental conditions characterized by impairments in social interaction and communication and restricted patterns of behavior, interests, and activities. Although the etiopathogenesis of idiopathic ASD has not been fully elucidated, compelling evidence suggests an interaction between genetic liability and environmental factors in producing early alterations of structural and functional brain development that are detectable by magnetic resonance imaging (MRI) at the group level. This work shows the results of a network-based approach to characterize not only variations in the values of the extracted features but also in their mutual relationships that might reflect underlying brain structural differences between autistic subjects and healthy controls. We applied a network-based analysis on sMRI data from the Autism Brain Imaging Data Exchange I (ABIDE-I) database, containing 419 features extracted with FreeSurfer software. Two networks were generated: one from subjects with autistic disorder (AUT) (DSM-IV-TR), and one from typically developing controls (TD), adopting a subsampling strategy to overcome class imbalance (235 AUT, 418 TD). We compared the distribution of several node centrality measures and observed significant inter-class differences in averaged centralities. Moreover, a single-node analysis allowed us to identify the most relevant features that distinguished the groups.
Published: 2021
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165. Local MRI analysis approach in the diagnosis of early and prodromal Alzheimer's disease

Author: Chincarini, Andrea, Bosco, Paolo, Calvini, Piero, Gemme, Gianluca, Esposito, Mario, Olivieri, Chiara, Rei, Luca, Squarcia, Sandro, Rodriguez, Guido, Bellotti, Roberto, Cerello, Piergiorgio, De Mitri, Ivan, Retico, Alessandra, and Nobili, Flavio
Published: 2011
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166. Analysis of a Flexible Dual-Channel Octagonal Coil System for UHF MRI

Author: Curreli, Nicola, primary, Lodi, Matteo Bruno, additional, Melis, Andrea, additional, Puddu, Claudio, additional, Casu, Sergio, additional, Fanti, Alessandro, additional, Djuric, Nikola, additional, Retico, Alessandra, additional, and Mazzarella, Giuseppe, additional
Published: 2022
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167. Convolutional Neural Networks for Breast Density Classification: Performance and Explanation Insights

Author: Lizzi, Francesca, primary, Scapicchio, Camilla, additional, Laruina, Francesco, additional, Retico, Alessandra, additional, and Fantacci, Maria Evelina, additional
Published: 2021
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168. Localization of anatomical changes in patients during proton therapy with in‐beam PET monitoring: A voxel‐based morphometry approach exploiting Monte Carlo simulations

Author: Kraan, Aafke Christine, primary, Berti, Andrea, additional, Retico, Alessandra, additional, Baroni, Guido, additional, Battistoni, Giuseppe, additional, Belcari, Nicola, additional, Cerello, Piergiorgio, additional, Ciocca, Mario, additional, De Simoni, Micol, additional, Del Sarto, Damiano, additional, Donetti, Marco, additional, Dong, Yunsheng, additional, Embriaco, Alessia, additional, Ferrero, Veronica, additional, Fiorina, Elisa, additional, Fischetti, Marta, additional, Franciosini, Gaia, additional, Giraudo, Giuseppe, additional, Laruina, Francesco, additional, Maestri, Davide, additional, Magi, Marco, additional, Magro, Giuseppe, additional, Mancini Terracciano, Carlo, additional, Marafini, Michela, additional, Mattei, Ilaria, additional, Mazzoni, Enrico, additional, Mereu, Paolo, additional, Mirabelli, Riccardo, additional, Mirandola, Alfredo, additional, Morrocchi, Matteo, additional, Muraro, Silvia, additional, Patera, Alessandra, additional, Patera, Vincenzo, additional, Pennazio, Francesco, additional, Rivetti, Angelo, additional, Da Rocha Rolo, Manuel Dionisio, additional, Rosso, Valeria, additional, Sarti, Alessio, additional, Schiavi, Angelo, additional, Sciubba, Adalberto, additional, Solfaroli Camillocci, Elena, additional, Sportelli, Giancarlo, additional, Tampellini, Sara, additional, Toppi, Marco, additional, Traini, Giacomo, additional, Valle, Serena Marta, additional, Valvo, Francesca, additional, Vischioni, Barbara, additional, Vitolo, Viviana, additional, Wheadon, Richard, additional, and Bisogni, Maria Giuseppina, additional
Published: 2021
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169. In-vivo inter-fractional monitoring in particle therapy with the INSIDE in-beam PET

Author: Ferrero, V., primary, Battistoni, G., additional, Belcari, N., additional, Berti, A., additional, Bisogni, G., additional, Cerello, P., additional, Ciocca, M., additional, De Simoni, M., additional, Donetti, M., additional, Dong, Y., additional, Egidi, I., additional, Embriaco, A., additional, Fiorina, E., additional, Fischetti, M., additional, Franciosini, G., additional, Kraan, A., additional, Giraudo, G., additional, Laruina, F., additional, Luongo, C., additional, Magi, M., additional, Malekzadeh, E., additional, Mancini-Terracciano, C., additional, Marafini, M., additional, Mattei, I., additional, Mazzoni, E., additional, Mirabelli, R., additional, Morrocchi, M., additional, Muraro, S., additional, Patera, A., additional, Patera, V., additional, Pennazio, F., additional, Retico, A., additional, Rivetti, A., additional, Rolo, M.D., additional, Rosso, V., additional, Sarti, A., additional, Schiavi, A., additional, Sciubba, A., additional, Camillocci, E. Solfaroli, additional, Sportelli, G., additional, Tampellini, S., additional, Toppi, M., additional, Traini, G., additional, Trigilio, A., additional, Valle, S.M., additional, Valvo, F., additional, Vitolo, V., additional, and Wheadon, R., additional
Published: 2021
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170. Breast density characterization through convolutional neural networks and first order statistical features

Author: Lizzi, F., primary, Scapicchio, C., additional, Laruina, F., additional, Retico, A., additional, and Fantacci, M.E., additional
Published: 2021
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171. Machine learning models based on radiomic features extracted from lung cancer CT images

Author: Ubaldi, L., primary, Valenti, V., additional, Borgese, R.F., additional, Collura, G., additional, Fantacci, M.E., additional, Ferrera, G., additional, Iacoviello, G., additional, Abbate, B.F., additional, Laruina, F., additional, Tripoli, A., additional, Retico, A., additional, and Marrale, M., additional
Published: 2021
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172. Magnetic resonance thermometry implementation for safety assessment in ultra-high-field magnetic resonance imaging

Author: Biagi, L., primary, Gagliardi, V., additional, Aringhieri, G., additional, Marletta, M., additional, Tiberi, G., additional, Retico, A., additional, Campanella, F., additional, and Tosetti, M., additional
Published: 2021
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173. A Monte Carlo code for the creation of heterogeneous breast phantoms for mammography

Author: Tucciariello, R.M., primary, Aringhieri, G., additional, Barca, P., additional, Del Sarto, D., additional, Lamastra, R., additional, Retico, A., additional, Sarno, A., additional, Traino, A., additional, and Fantacci, M.E., additional
Published: 2021
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174. Radiomic and dosiomic profiling of paediatric medulloblastoma tumours treated with intensity modulated radiation therapy

Author: Talamonti, C., primary, Ubaldi, L., additional, Piffer, S., additional, Greto, D., additional, Laurina, F., additional, Ciccarone, A., additional, Fantacci, M.E., additional, Oliva, P., additional, Mortilla, M., additional, Pallotta, S., additional, and Retico, A., additional
Published: 2021
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175. Double-Tuned Birdcage Radio Frequency Coil for 7 T MRI: Optimization, Construction and Workbench Validation.

Author: Retico, Alessandra, Maggiorelli, Francesca, Giovannetti, Giulio, Boskamp, Eddy, Robb, Fraser, Fantasia, Marco, Galante, Angelo, Alecci, Marcello, Tiberi, Gianluigi, and Tosetti, Michela
Subjects: BIRDCAGES, MAXWELL equations, RADIO frequency, WORKBENCHES, MAGNETIC resonance imaging, IMPEDANCE matching
Abstract: The aim of the present study is the optimization, construction, and workbench validation of a double-tuned 1H- 23Na volume radio frequency (RF) coil suitable for human head imaging at 7 T, based on the birdcage geometry. The birdcage-like design which is considered is the four-ring model, in which two standard birdcage-like structures with the same diameters are nested along the longitudinal axis. Simulations based on Maxwell's equations are performed to evaluate the RF magnetic field homogeneity and the RF coil efficiency varying the coil geometrical parameters. The RF magnetic field homogeneity is evaluated both on the transverse (z = 0) and longitudinal (y = 0) planes without performing the impedance matching procedure, so that the RF coil symmetry is not perturbed by the matching network. The RF coil efficiency is instead dependent on the effective coil input RF power, and it is evaluated after matching the coil, so that the reflected power is minimized, assuming that the stimulation power is totally delivered to the RF coil. Considering the simulation results and the target application, the useful RF coil geometrical parameters are fixed. The four-ring model, which showed the best performances, has been built and tested on a workbench, using a cylindrical phantom filled with a 0.05 M saline solution as load. This provides the first example of a four-ring realization intended 1H- 23Na for human head imaging at 7 T. [ABSTRACT FROM AUTHOR]
Published: 2023
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176. Enhancing the impact of Artificial Intelligence in Medicine: A joint AIFM-INFN Italian initiative for a dedicated cloud-based computing infrastructure

Author: Retico, Alessandra, Avanzo, Michele, Boccali, Tommaso, Bonacorsi, Daniele, Botta, Francesca, Cuttone, Giacomo, Martelli, Barbara, Salomoni, Davide, Spiga, Daniele, Trianni, Annalisa, Stasi, Michele, Iori, Mauro, and Talamonti, Cinzia
Published: 2021
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177. M5L: A web-based Computer Aided Detection system for automated search of lung nodules in thoracic Computed Tomography scans

Author: Traverso, A, primary, Agnello, M, additional, Cerello, P, additional, Saletta, M, additional, Bagnasco, S, additional, Peroni, C, additional, Fiorina, E, additional, Fantacci, M, additional, Retico, A, additional, and Torres, E, additional
Published: 2015
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178. Subcortical brain volume, regional cortical thickness, and cortical surface area across disorders:Findings from the ENIGMA ADHD, ASD, and OCD working groups

Author: Pedro Moreira, Ruth O'Gorman Tuura, Mara Cercignani, Philip Aherson, Maria Jalbrzikowski, Kate D. Fitzgerald, Declan G. Murphy, Bernd Kardatzki, Christine Ecker, David F. Tolin, Fern Jaspers-Fayer, Pedro Morgado, Juan Carlos Soliva Vila, Kang Ik K. Cho, Kathrin Koch, Timothy J. Silk, Philip R. Szeszko, Thomas Frodl, Mara Parellada, Shlomi Haar, Eileen Daly, Bob Oranje, Anouk Schrantee, Leyla Namazova-Baranova, Joseph A. King, Beatriz Luna, Silvia Brem, Eric Earl, Alasdair Vance, Michela Tosetti, Christine Deruelle, Ramona Baur-Streubel, Jackie Fitzgerald, Kirsten O'Hearn, Michael C. Stevens, Yoshiyuki Hirano, J. Antoni Ramos-Quiroga, Erika L. Nurmi, Kaylita Chantiluke, Joseph O'Neill, Kerstin Kohls, Olga Puig, Devon Shook, Clodagh M. Murphy, Gustavo Sudre, Marlene Behrmann, Jaap Oosterlaan, Tinatin Gogberashvili, Lianne Schmaal, Carles Soriano-Mas, Liesbeth Hoekstra, Ignacio Martínez-Zalacaín, Noam Soreni, Marcel P. Zwiers, Paulo Mattos, Gregor Kohls, Andreas J. Fallgatter, Tiffany M. Chaim-Avancini, Alexander Baranov, S. Evelyn Stewart, Sara Dallaspezia, Gianfranco Spalletta, Jonna Kuntsi, Lizanne J. S. Schweren, Joel T. Nigg, Leanne Tamm, Premika S.W. Boedhoe, Adriana Di Martino, Jane McGrath, Marcelo C. Batistuzzo, Norbert Skokauskas, Filippo Muratori, John Piacentini, Jean-Paul Fouche, Sarah Baumeister, Alan Anticevic, Neil A. Harrison, Christine M. Freitag, Pedro G.P. Rosa, Stephen V. Faraone, Ana Cubillo, David Mataix-Cols, Yuki Sakai, Stefan Ehrlich, Eileen Oberwelland Weiss, Fabrizio Piras, Dirk J. Heslenfeld, Je-Yeon Yun, Paul Pauli, Catharina A. Hartman, Ganesan Venkatasubramanian, Janardhanan C. Narayanaswamy, Charles B Malpas, Jan C. Beucke, José M. Menchón, Egill A. Fridgeirsson, Margot J. Taylor, Mauricio Moller Martinho, H. Blair Simpson, Jan K. Buitelaar, Gerd Kvale, Ivanei E. Bramati, Aki Tsuchiyagaito, Susanne Walitza, Irene Bollettini, Jeffery N. Epstein, Anders M. Dale, Thomas Ethofer, Terry L. Jernigan, David Coghill, Rachel Marsh, Andreas Reif, Astri J. Lundervold, Pieter J. Hoekstra, Oana Georgiana Rus, Damiaan Denys, Gregory L. Wallace, Matt C. Gabel, Hazel McCarthy, Sarah Hohmann, Rosa Nicolau, Stephanie H. Ameis, Neda Jahanshad, Takashi Nakamae, Xin Feng, Emily R. Stern, Georg G. von Polier, Yanni Liu, Paulo Marques, Anushree Bose, Hao Hu, Sara Lera-Miguel, Deniz A. Gürsel, Jochen Seitz, Jos W. R. Twisk, Mario Rodrigues Louzã, Clare Kelly, Annette Conzelmann, Alysa E. Doyle, Odile A. van den Heuvel, Anthony A. James, Chris Perriello, Joost Janssen, Damien A. Fair, Norbert Kathmann, Francisco X. Castellanos, Paul D. Arnold, Oscar Vilarroya, Geraldo F. Busatto, Federica Piras, Pino Alonso, Akiko Nakagawa, Sarah Durston, Lena Schwarz, Mitul A. Mehta, Dan J. Stein, Celso Arango, Daan van Rooij, Ilan Dinstein, Anastasia Christakou, Klaus-Peter Lesch, Kerstin J. Plessen, Jennifer Fedor, Yolanda Vives-Gilabert, Ilaria Gori, Louise Gallagher, Brian P. Brennan, Yuqi Cheng, Barbara Franke, Sabin Khadka, Stephanie E. Novotny, Martine Hoogman, Georgii Karkashadze, Georg C. Ziegler, Yuliya N. Yoncheva, Rosa Calvo, Thomas Wolfers, Marcelo Q. Hoexter, Benjamin A. Ely, Masaru Kuno, Alessandra Retico, Yoshinari Abe, Geoffrey B. Hall, Tobias Banaschewski, Anatoly Anikin, Christine Lochner, Astrid Morer, Guido van Wingen, Jan Haavik, Joseph Biederman, Luisa Lázaro, Francesco Benedetti, Fengfeng Zhou, Guillaume Auzias, Daniel Brandeis, Dmitry Kapilushniy, Katya Rubia, Philip Shaw, Christian Kaufmann, Sara Calderoni, Marcus V. Zanetti, Anastasia Solovieva, Zhen Wang, Francesca Assogna, Jamie D. Feusner, Chaim Huyser, Fernanda Tovar-Moll, Theo G.M. van Erp, Y.C. Janardhan Reddy, Jun Soo Kwon, Yannis Paloyelis, Anna Calvo, Patricia Gruner, Kathrin C. Zierhut, Liesbeth Reneman, Tomohiro Nakao, Janita Bralten, Marie F. Høvik, Mark A. Bellgrove, Maarten Mennes, Paul M. Thompson, Institut de Neurosciences de la Timone (INT), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Epidemiology and Data Science, Pediatric surgery, Radiology and nuclear medicine, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Psychiatry, APH - Methodology, APH - Health Behaviors & Chronic Diseases, Boedhoe, Premika S W, van Rooij, Daan, Hoogman, Martine, Twisk, Jos W R, Schmaal, Lianne, Abe, Yoshinari, Alonso, Pino, Ameis, Stephanie H, Anikin, Anatoly, Anticevic, Alan, Arango, Celso, Arnold, Paul D, Asherson, Philip, Assogna, Francesca, Auzias, Guillaume, Banaschewski, Tobia, Baranov, Alexander, Batistuzzo, Marcelo C, Baumeister, Sarah, Baur-Streubel, Ramona, Behrmann, Marlene, Bellgrove, Mark A, Benedetti, Francesco, Beucke, Jan C, Biederman, Joseph, Bollettini, Irene, Bose, Anushree, Bralten, Janita, Bramati, Ivanei E, Brandeis, Daniel, Brem, Silvia, Brennan, Brian P, Busatto, Geraldo F, Calderoni, Sara, Calvo, Anna, Calvo, Rosa, Castellanos, Francisco X, Cercignani, Mara, Chaim-Avancini, Tiffany M, Chantiluke, Kaylita C, Cheng, Yuqi, Cho, Kang Ik K, Christakou, Anastasia, Coghill, David, Conzelmann, Annette, Cubillo, Ana I, Dale, Anders M, Dallaspezia, Sara, Daly, Eileen, Denys, Damiaan, Deruelle, Christine, Di Martino, Adriana, Dinstein, Ilan, Doyle, Alysa E, Durston, Sarah, Earl, Eric A, Ecker, Christine, Ehrlich, Stefan, Ely, Benjamin A, Epstein, Jeffrey N, Ethofer, Thoma, Fair, Damien A, Fallgatter, Andreas J, Faraone, Stephen V, Fedor, Jennifer, Feng, Xin, Feusner, Jamie D, Fitzgerald, Jackie, Fitzgerald, Kate D, Fouche, Jean-Paul, Freitag, Christine M, Fridgeirsson, Egill A, Frodl, Thoma, Gabel, Matt C, Gallagher, Louise, Gogberashvili, Tinatin, Gori, Ilaria, Gruner, Patricia, Gürsel, Deniz A, Haar, Shlomi, Haavik, Jan, Hall, Geoffrey B, Harrison, Neil A, Hartman, Catharina A, Heslenfeld, Dirk J, Hirano, Yoshiyuki, Hoekstra, Pieter J, Hoexter, Marcelo Q, Hohmann, Sarah, Høvik, Marie F, Hu, Hao, Huyser, Chaim, Jahanshad, Neda, Jalbrzikowski, Maria, James, Anthony, Janssen, Joost, Jaspers-Fayer, Fern, Jernigan, Terry L, Kapilushniy, Dmitry, Kardatzki, Bernd, Karkashadze, Georgii, Kathmann, Norbert, Kaufmann, Christian, Kelly, Clare, Khadka, Sabin, King, Joseph A, Koch, Kathrin, Kohls, Gregor, Konrad, Kerstin, Kuno, Masaru, Kuntsi, Jonna, Kvale, Gerd, Kwon, Jun Soo, Lázaro, Luisa, Lera-Miguel, Sara, Lesch, Klaus-Peter, Hoekstra, Liesbeth, Liu, Yanni, Lochner, Christine, Louza, Mario R, Luna, Beatriz, Lundervold, Astri J, Malpas, Charles B, Marques, Paulo, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Mataix-Cols, David, Mattos, Paulo, Mccarthy, Hazel, Mcgrath, Jane, Mehta, Mitul A, Menchón, José M, Mennes, Maarten, Martinho, Mauricio Moller, Moreira, Pedro S, Morer, Astrid, Morgado, Pedro, Muratori, Filippo, Murphy, Clodagh M, Murphy, Declan G M, Nakagawa, Akiko, Nakamae, Takashi, Nakao, Tomohiro, Namazova-Baranova, Leyla, Narayanaswamy, Janardhanan C, Nicolau, Rosa, Nigg, Joel T, Novotny, Stephanie E, Nurmi, Erika L, Weiss, Eileen Oberwelland, O'Gorman Tuura, Ruth L, O'Hearn, Kirsten, O'Neill, Joseph, Oosterlaan, Jaap, Oranje, Bob, Paloyelis, Yanni, Parellada, Mara, Pauli, Paul, Perriello, Chri, Piacentini, John, Piras, Fabrizio, Piras, Federica, Plessen, Kerstin J, Puig, Olga, Ramos-Quiroga, J Antoni, Reddy, Y C Janardhan, Reif, Andrea, Reneman, Liesbeth, Retico, Alessandra, Rosa, Pedro G P, Rubia, Katya, Rus, Oana Georgiana, Sakai, Yuki, Schrantee, Anouk, Schwarz, Lena, Schweren, Lizanne J S, Seitz, Jochen, Shaw, Philip, Shook, Devon, Silk, Tim J, Simpson, H Blair, Skokauskas, Norbert, Soliva Vila, Juan Carlo, Solovieva, Anastasia, Soreni, Noam, Soriano-Mas, Carle, Spalletta, Gianfranco, Stern, Emily R, Stevens, Michael C, Stewart, S Evelyn, Sudre, Gustavo, Szeszko, Philip R, Tamm, Leanne, Taylor, Margot J, Tolin, David F, Tosetti, Michela, Tovar-Moll, Fernanda, Tsuchiyagaito, Aki, van Erp, Theo G M, van Wingen, Guido A, Vance, Alasdair, Venkatasubramanian, Ganesan, Vilarroya, Oscar, Vives-Gilabert, Yolanda, von Polier, Georg G, Walitza, Susanne, Wallace, Gregory L, Wang, Zhen, Wolfers, Thoma, Yoncheva, Yuliya N, Yun, Je-Yeon, Zanetti, Marcus V, Zhou, Fengfeng, Ziegler, Georg C, Zierhut, Kathrin C, Zwiers, Marcel P, Thompson, Paul M, Stein, Dan J, Buitelaar, Jan, Franke, Barbara, van den Heuvel, Odile A, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Clinical Cognitive Neuropsychiatry Research Program (CCNP), Adult Psychiatry, ANS - Compulsivity, Impulsivity & Attention, Graduate School, Child Psychiatry, General Paediatrics, ARD - Amsterdam Reproduction and Development, Radiology and Nuclear Medicine, APH - Personalized Medicine, and APH - Mental Health
Subjects: Male, Research Report, Obsessive-Compulsive Disorder, Frontal cortex, Systems Analysis, Attention Deficit Hyperactivity Disorder, Autism Spectrum Disorder, [SDV]Life Sciences [q-bio], Hippocampal formation, Audiology, 0302 clinical medicine, 130 000 Cognitive Neurology & Memory, Child, Obsessive-compulsive disorder (OCD), ComputingMilieux_MISCELLANEOUS, Intelligence quotient, Psychopathology, ATTENTION-DEFICIT/HYPERACTIVITY DISORDER, ABNORMALITIES, ENIGMA, Organ Size, 3. Good health, Psychiatry and Mental health, Autism spectrum disorder, Brain size, Cohort, Female, MRI, Adult, medicine.medical_specialty, CORTEX, Adolescent, DEFICIT HYPERACTIVITY DISORDER, Human Development, Neuroimaging, behavioral disciplines and activities, Article, 03 medical and health sciences, FIELD-STRENGTH, mental disorders, medicine, MEGA-ANALYSIS, Attention deficit hyperactivity disorder, Humans, Cortical surface, Structural MRI, Attention Deficit Disorder with Hyperactivity, Cerebrum, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], business.industry, medicine.disease, 030227 psychiatry, VOXEL, Autism, business, 030217 neurology & neurosurgery
Abstract: ObjectiveAttention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. We aimed to directly compare all three disorders. The ENIGMA consortium is ideally positioned to investigate structural brain alterations across these disorders.MethodsStructural T1-weighted whole-brain MRI of controls (n=5,827) and patients with ADHD (n=2,271), ASD (n=1,777), and OCD (n=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. We examined subcortical volume, cortical thickness and surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults using linear mixed-effects models adjusting for age, sex and site (and ICV for subcortical and surface area measures).ResultsWe found no shared alterations among all three disorders, while shared alterations between any two disorders did not survive multiple comparisons correction. Children with ADHD compared to those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller ICV than controls and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared to adult controls and other clinical groups. No OCD-specific alterations across different age-groups and surface area alterations among all disorders in childhood and adulthood were observed.ConclusionOur findings suggest robust but subtle alterations across different age-groups among ADHD, ASD, and OCD. ADHD-specific ICV and hippocampal alterations in children and adolescents, and ASD-specific cortical thickness alterations in the frontal cortex in adults support previous work emphasizing neurodevelopmental alterations in these disorders.
Published: 2020

179. Residual Convolutional Neural Networks for Breast Density Classiﬁcation

Author: Paolo Bosco, Giacomo Aringhieri, Davide Caramella, Stefano Atzori, Carolina Marini, A. C. Traino, Alessandra Retico, Francesca Lizzi, Maria Evelina Fantacci, Francesca Lizzi , Stefano Atzori , Giacomo Aringhieri , Paolo Bosco , Carolina Marini , Alessandra Retico , Antonio Traino , Davide Caramella and M. Fantacci, elisabetta De Maria, Ana Fred, Hugo Gamboa, Fantacci, M., Caramella, Davide, Traino, Antonio, Retico, Alessandra, Marini, Carolina, Bosco, Paolo, Aringhieri, Giacomo, Atzori, Stefano, and Lizzi, Francesca
Subjects: Residual Neural Networks, BI-RADS, Computer science, business.industry, Convolutional Neural Networks, Pattern recognition, Residual, Convolutional neural network, Breast Density, Artificial intelligence, Breast density, business
Published: 2019

180. PREDICTIVE MODELS BASED ON RADIOMICS AND MACHINE LEARNING FOR LUNG CANCER RADIOTHERAPY DATA ANALYSIS

Author: L Ubaldi, V Valenti, RF Borgese, G Collura, ME Fantacci, G Ferrera, G Iacoviello, F Laruina, A Tripoli, A Retico, M Marrale, L Ubaldi, V Valenti, RF Borgese, G Collura, ME Fantacci, G Ferrera, G Iacoviello, F Laruina, A Tripoli, A Retico, and M Marrale
Subjects: lung cancer, machine learning
Published: 2020

181. Comparing and combining algorithms for computer-aided detection of pulmonary nodules in computed tomography scans: The ANODE09 study

Author: van Ginneken, Bram, Armato, Samuel G., III, de Hoop, Bartjan, van Amelsvoort-van de Vorst, Saskia, Duindam, Thomas, Niemeijer, Meindert, Murphy, Keelin, Schilham, Arnold, Retico, Alessandra, Fantacci, Maria Evelina, Camarlinghi, Niccolò, Bagagli, Francesco, Gori, Ilaria, Hara, Takeshi, Fujita, Hiroshi, Gargano, Gianfranco, Bellotti, Roberto, Tangaro, Sabina, Bolaños, Lourdes, Carlo, Francesco De, Cerello, Piergiorgio, Cristian Cheran, Sorin, Lopez Torres, Ernesto, and Prokop, Mathias
Published: 2010
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182. Vascular Function Is Improved After an Environmental Enrichment Program

Author: Bruno, Rosa Maria, Stea, Francesco, Sicari, Rosa, Ghiadoni, Lorenzo, Taddei, Stefano, Ungar, Andrea, Bonuccelli, Ubaldo, Tognoni, Gloria, Cintoli, Simona, Del Turco, Serena, Sbrana, Silverio, Gargani, Luna, D'Angelo, Gennaro, Pratali, Lorenza, Berardi, Nicoletta, Maffei, Lamberto, Picano Eugenio, on behalf of Train the Brain Consortium. Full list of consortium members: Maffei L, Picano E, Andreassi MG, Angelucci A, Baldacci F, Baroncelli L, Begenisic T, Bellinvia PF, Berardi N, Biagi L, Bonaccorsi J, Bonanni E, Bonuccelli U, Borghini A, Braschi C, Broccardi M, Bruno RM, Caleo M, Carlesi C, Carnicelli L, Cartoni G, Cecchetti L, Cenni MC, Ceravolo R, Chico L, Cintoli S, Cioni G, Costa M, D’Angelo G, D’Ascanio P, De Nes M, Del Turco S, Di Coscio E, Di Galante M, di Lascio N, Faita F, Falorni I, Faraguna U, Fenu A, Fortunato L, Franco R, Gargani L, Gargiulo R, Ghiadoni L, Giorgi FS, Iannarella R, Iofrida C, Kusmic C, Limongi F, Maestri M, Maffei M, Maggi S, Mainardi M, Mammana L, Marabotti A, Mariotti V, Melissari E, Mercuri A, Molinaro S, Narducci R, Navarra T, Noale M, Pagni C, Palumbo S, Pasquariello R, Pellegrini S, Pietrini P, Pizzorusso T, Poli A, Pratali L, Retico A, Ricciardi E, Rota G, Sale A, Sbrana S, Scabia G, Scali M, Scelfo D, Sicari R, Siciliano G, Stea F, Taddei S, Tognoni G, Tonacci A, Tosetti M, Turchi S, Volpi L, Bruno, Rosa Maria, Stea, Francesco, Sicari, Rosa, Ghiadoni, Lorenzo, Taddei, Stefano, Ungar, Andrea, Bonuccelli, Ubaldo, Tognoni, Gloria, Cintoli, Simona, Del Turco, Serena, Sbrana, Silverio, Gargani, Luna, D'Angelo, Gennaro, Pratali, Lorenza, Berardi, Nicoletta, Maffei, Lamberto, Picano, Eugenio, on behalf of Train the Brain Consortium., Full list of consortium members: Maffei L, Picano, E, Andreassi, Mg, Angelucci, A, Baldacci, F, Baroncelli, L, Begenisic, T, Bellinvia, Pf, Berardi, N, Biagi, L, Bonaccorsi, J, Bonanni, E, Bonuccelli, U, Borghini, A, Braschi, C, Broccardi, M, Bruno, Rm, Caleo, M, Carlesi, C, Carnicelli, L, Cartoni, G, Cecchetti, L, Cenni, Mc, Ceravolo, R, Chico, L, Cintoli, S, Cioni, G, Costa, M, D’Angelo, G, D’Ascanio, P, De Nes, M, Del Turco, S, Di Coscio, E, Di Galante, M, di Lascio, N, Faita, F, Falorni, I, Faraguna, U, Fenu, A, Fortunato, L, Franco, R, Gargani, L, Gargiulo, R, Ghiadoni, L, Giorgi, F, Iannarella, R, Iofrida, C, Kusmic, C, Limongi, F, Maestri, M, Maffei, M, Maggi, S, Mainardi, M, Mammana, L, Marabotti, A, Mariotti, V, Melissari, E, Mercuri, A, Molinaro, S, Narducci, R, Navarra, T, Noale, M, Pagni, C, Palumbo, S, Pasquariello, R, Pellegrini, S, Pietrini, P, Pizzorusso, T, Poli, A, Pratali, L, Retico, A, Ricciardi, E, Rota, G, Sale, A, Sbrana, S, Scabia, G, Scali, M, Scelfo, D, Sicari, R, Siciliano, G, Stea, F, Taddei, S, Tognoni, G, Tonacci, A, Tosetti, M, Turchi, S, and Volpi, L
Subjects: Male, control groups, medicine.medical_specialty, Brachial Artery, Pulse Wave Analysis, 030204 cardiovascular system & hematology, 03 medical and health sciences, endothelial progenitor cell, 0302 clinical medicine, cognitive dysfunction, Internal medicine, medicine.artery, Internal Medicine, medicine, human, Brachial artery, Cognitive decline, humans, Pulse wave velocity, Aged, endothelial progenitor cells, Aged, 80 and over, Environmental enrichment, business.industry, control group, Area under the curve, Neuropsychology, Brain, vascular stiffness, Cognition, Middle Aged, medicine.disease, Exercise Therapy, Vasodilation, Cross-Sectional Studies, Cardiovascular Diseases, Cardiology, Female, Endothelium, Vascular, Alzheimer's disease, business, 030217 neurology & neurosurgery
Abstract: Environmental enrichment may slow cognitive decay possibly acting through an improvement in vascular function. Aim of the study was to assess the effects of a 7-month cognitive, social, and physical training program on cognitive and vascular function in patients with mild cognitive impairment. In a single-center, randomized, parallel-group study, 113 patients (age, 65–89 years) were randomized to multidomain training (n=55) or usual care (n=58). All participants underwent neuropsychological tests and vascular evaluation, including brachial artery flow-mediated dilation, carotid–femoral pulse wave velocity, carotid distensibility, and assessment of circulating hematopoietic CD34+ and endothelial progenitor cells. At study entry, an age-matched control group (n=45) was also studied. Compared with controls, patients had at study entry a reduced flow-mediated dilation (2.97±2.14% versus 3.73±2.06%; P =0.03) and hyperemic stimulus (shear rate area under the curve, 19.1±15.7 versus 25.7±15.1×10 −3 ; P =0.009); only the latter remained significant after adjustment for confounders ( P =0.03). Training improved Alzheimer disease assessment scale cognitive (training, 14.0±4.8 to 13.1±5.5; nontraining, 12.1±3.9 to 13.2±4.8; P for interaction visit×training=0.02), flow-mediated dilation (2.82±2.19% to 3.40±1.81%, 3.05±2.08% to 2.24±1.59%; P =0.006; P =0.023 after adjustment for diameter and shear rate area under the curve), and circulating hematopoietic CD34 + cells and prevented the decline in carotid distensibility (18.4±5.3 to 20.0±6.6, 23.9±11.0 to 19.5±7.1 Pa −1 ; P =0.005). The only clinical predictor of improvement of cognitive function after training was established hypertension. There was no correlation between changes in measures of cognitive and vascular function. In conclusion, a multidomain training program slows cognitive decline, especially in hypertensive individuals. This effect is accompanied by improved systemic endothelial function, mobilization of progenitor CD34 + cells, and preserved carotid distensibility. Clinical Trial Registration— URL: http://www.clinicaltrials.gov . Unique identifier: NCT01725178.
Published: 2018

183. Quantification of pulmonary involvement in COVID-19 pneumonia by means of a cascade of two U-nets: training and assessment on multiple datasets using different annotation criteria

Author: Lizzi, Francesca, primary, Agosti, Abramo, additional, Brero, Francesca, additional, Cabini, Raffaella Fiamma, additional, Fantacci, Maria Evelina, additional, Figini, Silvia, additional, Lascialfari, Alessandro, additional, Laruina, Francesco, additional, Oliva, Piernicola, additional, Piffer, Stefano, additional, Postuma, Ian, additional, Rinaldi, Lisa, additional, Talamonti, Cinzia, additional, and Retico, Alessandra, additional
Published: 2021
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184. Double-Tuned Surface 1H–23Na Radio Frequency Coils at 7 T: Comparison of Three Decoupling Methods

Author: M R Symms, Michela Tosetti, Alessandra Retico, Eddy B. Boskamp, Francesca Maggiorelli, Fraser Robb, and Gianluigi Tiberi
Subjects: Larmor precession, Physics, Acoustics, Resonance, Electrical element, 010402 general chemistry, 01 natural sciences, Signal, Atomic and Molecular Physics, and Optics, 030218 nuclear medicine & medical imaging, 0104 chemical sciences, 03 medical and health sciences, 0302 clinical medicine, Electromagnetic coil, Q factor, Radio frequency, Decoupling (electronics)
Abstract: Magnetic Resonance Imaging (MRI) and Spectroscopy (MRS) with nuclei other than protons (X-nuclei) often require the acquisition of proton signal for shimming and co-registration procedures. Double-Tuned Radio Frequency (DT-RF) coils improve these procedures, avoiding the need for movement and repositioning of the subject during the examination. The drawback of DT-RF coils is basically the coupling between the two resonant structures, which increases signal losses leading to a degradation of the final MR image. To improve MR signal quality acquired via DT-RF coils, a suitable decoupling strategy should be implemented. For this purpose, three DT-RF coil prototypes, which differed only in the decoupling method, were built and their performances were compared through workbench measurements. Each prototype consisted of two concentric loops. The inner and outer loops were tuned at sodium (≈ 79 MHz) and proton (≈ 300 MHz) Larmor frequency at 7 Tesla, respectively. Active and passive decoupling designs were compared measuring the Q factor and the S21 parameter for each prototype. Active decoupling was tested as an alternative to the standard passive decoupling with a trap circuit, in which a non-negligible amount of current flows at resonance, perturbing the magnetic field responsible for producing the MR image. Workbench measurements showed satisfactory Q factors and S21 for both active and passive decoupling cases. Thus, active decoupling could be a promising alternative to achieve better MR signal quality. Furthermore, for active decoupling, two circuit elements were examined: PIN diodes and micro-electromechanical system (MEMS) switches.
Published: 2019

185. A Monte Carlo code for the creation of heterogeneous breast phantoms for mammography

Author: R.M. Tucciariello, G. Aringhieri, P. Barca, D. Del Sarto, R. Lamastra, A. Retico, A. Sarno, A. Traino, and M.E. Fantacci
Subjects: Biophysics, General Physics and Astronomy, Radiology, Nuclear Medicine and imaging, General Medicine
Published: 2021

186. Gray Matter Alterations in Young Children with Autism Spectrum Disorders: Comparing Morphometry at the Voxel and Regional Level

Author: Gori, Ilaria, Giuliano, Alessia, Muratori, Filippo, Saviozzi, Irene, Oliva, Piernicola, Tancredi, Raffaella, Cosenza, Angela, Tosetti, Michela, Calderoni, Sara, and Retico, Alessandra
Published: 2015
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187. Quadrature birdcage coil with distributed capacitors for 7.0 T magnetic resonance data acquisition of small animals

Author: Stara, Riccardo, Tiberi, Gianluigi, Gabrieli, Matteo, Buonincontri, Guido, Fontana, Nunzia, Monorchio, Agostino, Costagli, Mauro, Symms, Mark Roger, Retico, Alessandra, and Tosetti, Michela
Published: 2015
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188. Three dimensional MRF obtains highly repeatable and reproducible multi-parametric estimations in the healthy human brain at 1.5T and 3T

Author: Buonincontri, Guido, Kurzawski, Jan W., Kaggie, Joshua D, Matys, Tomasz, Gallagher, Ferdia A, Cencini, Matteo, Donatelli, Graziella, Cecchi, Paolo, Cosottini, Mirco, Martini, Nicola, Frijia, Francesca, Montanaro, Domenico, Gómez, Pedro A., Schulte, Rolf F, Retico, Alessandra, and Tosetti, Michela
Published: 2021
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189. Predictive Models Based on Support Vector Machines: Whole-Brain versus Regional Analysis of Structural MRI in the Alzheimerʼs Disease

Author: Retico, Alessandra, Bosco, Paolo, Cerello, Piergiorgio, Fiorina, Elisa, Chincarini, Andrea, and Fantacci, Maria Evelina
Published: 2015
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190. Pleural nodule identification in low-dose and thin-slice lung computed tomography

Author: Retico, A., Fantacci, M.E., Gori, I., Kasae, P., Golosio, B., Piccioli, A., Cerello, P., De Nunzio, G., and Tangaro, S.
Published: 2009
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191. Subtly altered topological asymmetry of brain structural covariance networks in autism spectrum disorder across 43 datasets from the ENIGMA consortium

Author: Mara Parellada, Beatriz Luna, Dorothea L. Floris, Bob Oranje, Merel Postema, Michela Tosetti, Paul M. Thompson, Celso Arango, Maria Jalbrzikowski, Stefan Ehrlich, Eileen Daly, Damien A. Fair, Marlene Behrmann, Jose C. Pariente, Pedro G.P. Rosa, Meiyu Duan, Zhiqiang Sha, Katya Rubia, Fábio L.S. Duran, Joseph A. King, Jacqueline Fitzgerald, Christine Deruelle, Devon Shook, Daan van Rooij, Boris C. Bernhardt, Kirsten O'Hearn, Jan K. Buitelaar, Simon E. Fisher, Geraldo F. Busatto, Alessandra Retico, Margot J. Taylor, Rosa Calvo, Neda Jahanshad, Declan G. Murphy, David C. Glahn, Christine M. Freitag, Shlomi Haar, Karl Lundin Remnélius, Luisa Lázaro, Janina Neufeld, Clyde Francks, Sarah Durston, Fengfeng Zhou, Louise Gallagher, Barbara Franke, Christine Ecker, Evdokia Anagnostou, Filippo Muratori, Sarah E. Medland, Guillaume Auzias, Liesbeth Hoekstra, Sara Calderoni, Kristiina Tammimies, Ciara Molloy, Sven Bölte, Joost Janssen, Jennifer Fedor, Jane McGrath, and Gregory L. Wallace
Subjects: Working memory, media_common.quotation_subject, Biology, Topology, Executive functions, medicine.disease, Asymmetry, Functional brain, Structural covariance, Autism spectrum disorder, Functional neuroimaging, medicine, Orbitofrontal cortex, media_common
Abstract: Small average differences in the left-right asymmetry of cerebral cortical thickness have been reported in individuals with autism spectrum disorder (ASD) compared to typically developing controls. Although these alterations affect multiple and widespread cortical regional asymmetries, the extent to which specific structural networks might be affected remains unknown. Inter-regional morphological covariance analysis can capture network connectivity relations between different cortical areas at the macroscale level. Here, we used cortical thickness data from 1,455 individuals with ASD and 1,560 controls, across 43 independent datasets of the ENIGMA consortium’s ASD Working Group, to assess hemispheric asymmetries of intra-individual structural covariance networks, using graph theory-based topological metrics. Compared with typical features of small-world architecture in controls, the ASD sample showed significantly altered asymmetry of hemispheric networks involving the fusiform, rostral middle frontal, and medial orbitofrontal cortex, driven by shifts toward higher randomization of the corresponding right-hemispheric networks in ASD. A network involving the superior frontal cortex showed decreased right-hemisphere randomization. Based on comparisons with meta-analyzed functional neuroimaging data, the altered connectivity asymmetry particularly affected networks that subserve working memory, executive functions, language, reading, and sensorimotor processes. Taken together, these findings provide new insights into how altered brain left-right asymmetry in ASD affects specific structural and functional brain networks. Altered asymmetrical brain development in ASD may be partly propagated among spatially distant regions through structural connectivity.
Published: 2021

192. PO-1799 Radiomic and dosiomic profiling of paediatric Medulloblastoma tumours treated with IMRT

Author: Talamonti, Cinzia, primary, Piffer, Stefano, additional, Ubaldi, Leonardo, additional, Greto, Daniela, additional, Laurina, Francesco, additional, Ciccarone, Antonio, additional, Oliva, Piernicola, additional, Evelina Fantacci, Maria, additional, Mortilla, Marzia, additional, Pallotta, Stefania, additional, and Retico, Alessandra, additional
Published: 2021
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193. Making Data Big for a Deep-learning Analysis: Aggregation of Public COVID-19 Datasets of Lung Computed Tomography Scans

Author: Maria Evelina Fantacci, Ian Postuma, Stefano Piffer, Alessandra Retico, Francesca Lizzi, Francesca Brero, Lisa Rinaldi, and Raffaella Fiamma Cabini
Subjects: Image segmentation, Ground truth, Lesion segmentation, medicine.diagnostic_test, Coronavirus disease 2019 (COVID-19), business.industry, Computer science, Deep learning, COVID-19, Pattern recognition, Computed tomography, U-net, Data aggregation, Identification (information), Automatic image annotation, Lung CT, medicine, Segmentation, Artificial intelligence, business
Abstract: Lung Computed Tomography (CT) is an imaging technique useful to assess the severity of COVID-19 infection in symptomatic patients and to monitor its evolution over time. Lung CT can be analysed with the support of deep learning methods for both aforementioned tasks. We have developed a U-net based algorithm to segment the COVID-19 lesions. Unfortunately, public datasets populated with a huge amount of labelled CT scans of patients affected by COVID-19 are not available. In this work, we first review all the currently available public datasets of COVID-19 CT scans, presenting an extensive description of their characteristics. Then, we describe the design of the U-net we developed for the automated identification of COVID-19 lung lesions. Finally, we discuss the results obtained by using the different publicly available datasets. In particular, we trained the U-net on the dataset made available within the COVID-19 Lung CT Lesion Segmentation Challenge 2020, and we tested it on data from the MosMed and the COVID-19-CT-Seg datasets to explore the transferability of the model and to assess whether the image annotation process affects the detection performances. We evaluated the performance of the system in lesion segmentation in terms of the Dice index, which measures the overlap between the ground truth and the predicted masks. The proposed U-net segmentation model reaches a Dice index equal to 0.67, 0.42 and 0.58 on the independent validation sets of the COVID-19 Lung CT Lesion Segmentation Challenge 2020, on the MosMed and on the COVID-19-CT-Seg datasets, respectively. This work focusing on lesion segmentation constitutes a preliminary work for a more accurate analysis of COVID-19 lesions, based for example on the extraction and analysis of radiomic features. Copyright © 2021 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved
Published: 2021

194. Localization of anatomical changes in patients during proton therapy with in-beam PET monitoring: a voxel-based morphometry approach exploiting Monte Carlo simulations

Author: M. Toppi, Marco Donetti, Andrea Berti, Adalberto Sciubba, Vincenzo Patera, Francesco Laruina, Gaia Franciosini, M.D. Rolo, Damiano Del Sarto, Elisa Fiorina, Davide Maestri, Alessandra Patera, Sara Tampellini, M. Marafini, A.C. Kraan, M. Fischetti, Micol De Simoni, Francesco Pennazio, Alessio Sarti, Veronica Ferrero, Francesca Valvo, Alfredo Mirandola, Viviana Vitolo, Ilaria Mattei, Matteo Morrocchi, Giancarlo Sportelli, Guido Baroni, Angelo Rivetti, Piergiorgio Cerello, Paolo Mereu, Angelo Schiavi, Richard Wheadon, Alessandra Retico, Barbara Vischioni, Enrico Mazzoni, Carlo Mancini Terracciano, Elena Solfaroli Camillocci, Giacomo Traini, Giuseppe Magro, Y. Dong, Valeria Rosso, S. M. Valle, Giuseppe Battistoni, Giuseppe Giraudo, Nicola Belcari, A. Embriaco, Marco Magi, R. Mirabelli, Silvia Muraro, Maria Giuseppina Bisogni, and Mario Ciocca
Subjects: Computer science, Monte Carlo method, computer.software_genre, In-beam PET monitoring, proton therapy, voxel-based morphometry, Neuroimaging, Voxel, medicine, Humans, In patient, Tomography, Proton therapy, Statistical hypothesis testing, in-beam PET monitoring, Monte Carlo Method, Positron-Emission Tomography, Tomography, X-Ray Computed, Proton Therapy, medicine.diagnostic_test, business.industry, Pattern recognition, General Medicine, Voxel-based morphometry, X-Ray Computed, Positron emission tomography, Artificial intelligence, business, computer
Abstract: PURPOSE In-beam Positron Emission Tomography (PET) is one of the modalities that can be used for in-vivo non-invasive treatment monitoring in proton therapy. Although PET monitoring has been frequently applied for this purpose, there is still no straightforward method to translate the information obtained from the PET images into easy to interpret information for clinical personnel. The purpose of this work is to propose a statistical method for analyzing in-beam PET monitoring images that can be used to locate, quantify and visualize regions with possible morphological changes occurring over the course of treatment. MATERIALS AND METHODS We selected a patient treated for Squamous Cell Carcinoma (SCC) with proton therapy, to perform multiple Monte Carlo (MC) simulations of the expected PET signal at the start of treatment, and to study how the PET signal may change along the treatment course due to morphological changes. We performed voxel-wise two-tailed statistical tests of the simulated PET images, resembling the Voxel-Based Morphometry (VBM) method commonly used in neuroimaging data analysis, to locate regions with significant morphological changes and to quantify the change. RESULTS The VBM resembling method has been successfully applied to the simulated in-beam PET images, despite the fact that such images suffer from image artifacts and limited statistics. Three dimensional probability maps were obtained, that allowed to identify inter-fractional morphological changes and to visualize them superimposed on the Computed Tomography (CT) scan. In particular, the characteristic color patterns resulting from the two-tailed statistical tests lend themselves to trigger alarms in case of morphological changes along the course of treatment. CONCLUSIONS The statistical method presented in this work is a promising method to apply to PET monitoring data to reveal inter-fractional morphological changes in patients, occurring over the course of treatment. Based on simulated in-beam PET treatment monitoring images, we showed that with our method it was possible to correctly identify the regions that changed. Moreover we could quantify the changes, and visualize them superimposed on the CT scan. The proposed method can possibly help clinical personnel in the replanning procedure in adaptive proton therapy treatments. This article is protected by copyright. All rights reserved.
Published: 2021

195. Three dimensional MRF obtains highly repeatable and reproducible multi-parametric estimations in the healthy human brain at 1.5T and 3T

Author: Ferdia A. Gallagher, Graziella Donatelli, Domenico Montanaro, Tomasz Matys, Mirco Cosottini, Joshua D Kaggie, Rolf F. Schulte, Michela Tosetti, Francesca Frijia, Paolo Cecchi, Matteo Cencini, Guido Buonincontri, Nicola Martini, Jan W. Kurzawski, Pedro A. Gómez, Alessandra Retico, Kaggie, Joshua [0000-0001-6706-3442], Matys, Tomasz [0000-0003-2285-5715], Gallagher, Ferdia [0000-0003-4784-5230], and Apollo - University of Cambridge Repository
Subjects: Adult, Male, Relaxometry, Cognitive Neuroscience, computer.software_genre, 050105 experimental psychology, lcsh:RC321-571, Quantitation, 03 medical and health sciences, 0302 clinical medicine, Imaging, Three-Dimensional, Voxel, medicine, Image Processing, Computer-Assisted, Humans, 0501 psychology and cognitive sciences, Multiparametric Magnetic Resonance Imaging, Projection (set theory), lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, Mathematics, General linear model, MR fingerprinting, Reproducibility, medicine.diagnostic_test, 05 social sciences, Three dimensional, Reproducibility of Results, Brain, Magnetic resonance imaging, Reconstruction algorithm, Repeatability, Magnetic Resonance Imaging, 3D, MRI, Healthy Volunteers, ddc, Neurology, Female, computer, 030217 neurology & neurosurgery, Biomedical engineering
Abstract: Magnetic resonance fingerprinting (MRF) is highly promising as a quantitative MRI technique due to its accuracy, robustness, and efficiency. Previous studies have found high repeatability and reproducibility of 2D MRF acquisitions in the brain. Here, we have extended our investigations to 3D MRF acquisitions covering the whole brain using spiral projection k-space trajectories. Our travelling head study acquired test/retest data from the brains of 12 healthy volunteers and 8 MRI systems (3 systems at 3 T and 5 at 1.5 T, all from a single vendor), using a study design not requiring all subjects to be scanned at all sites. The pulse sequence and reconstruction algorithm were the same for all acquisitions. After registration of the MRF-derived PD T1 and T2 maps to an anatomical atlas, coefficients of variation (CVs) were computed to assess test/retest repeatability and inter-site reproducibility in each voxel, while a General Linear Model (GLM) was used to determine the voxel-wise variability between all confounders, which included test/retest, subject, field strength and site. Our analysis demonstrated a high repeatability (CVs 0.7–1.3% for T1, 2.0–7.8% for T2, 1.4–2.5% for normalized PD) and reproducibility (CVs of 2.0–5.8% for T1, 7.4–10.2% for T2, 5.2–9.2% for normalized PD) in gray and white matter. Both repeatability and reproducibility improved when compared to similar experiments using 2D acquisitions. Three-dimensional MRF obtains highly repeatable and reproducible estimations of T1 and T2, supporting the translation of MRF-based fast quantitative imaging into clinical applications.
Published: 2021

196. Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders

Author: Patel, Y, Parker, N, Shin, J, Howard, D, French, L, Thomopoulos, SI, Pozzi, E, Abe, Y, Abe, C, Anticevic, A, Alda, M, Aleman, A, Alloza, C, Alonso-Lana, S, Ameis, SH, Anagnostou, E, McIntosh, AA, Arango, C, Arnold, PD, Asherson, P, Assogna, F, Auzias, G, Ayesa-Arriola, R, Bakker, G, Banaj, N, Banaschewski, T, Bandeira, CE, Baranov, A, Bargallo, N, Bau, CHD, Baumeister, S, Baune, BT, Bellgrove, MA, Benedetti, F, Bertolino, A, Boedhoe, PSW, Boks, M, Bollettini, I, del Mar Bonnin, C, Borgers, T, Borgwardt, S, Brandeis, D, Brennan, BP, Bruggemann, JM, Bulow, R, Busatto, GF, Calderoni, S, Calhoun, VD, Calvo, R, Canales-Rodriguez, EJ, Cannon, DM, Carr, VJ, Cascella, N, Cercignani, M, Chaim-Avancini, TM, Christakou, A, Coghill, D, Conzelmann, A, Crespo-Facorro, B, Cubillo, AI, Cullen, KR, Cupertino, RB, Daly, E, Dannlowski, U, Davey, CG, Denys, D, Deruelle, C, Di Giorgio, A, Dickie, EW, Dima, D, Dohm, K, Ehrlich, S, Ely, BA, Erwin-Grabner, T, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Fatjo-Vilas, M, Fedor, JM, Fitzgerald, KD, Ford, JM, Frodl, T, Fu, CHY, Fullerton, JM, Gabel, MC, Glahn, DC, Roberts, G, Gogberashvili, T, Goikolea, JM, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Green, MJ, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Guerrero-Pedraza, A, Gur, RE, Gur, RC, Haar, S, Haarman, BCM, Haavik, J, Hahn, T, Hajek, T, Harrison, BJ, Harrison, NA, Hartman, CA, Whalley, HC, Heslenfeld, DJ, Hibar, DP, Hilland, E, Hirano, Y, Ho, TC, Hoekstra, PJ, Hoekstra, L, Hohmann, S, Hong, LE, Hoschl, C, Hovik, MF, Howells, FM, Nenadic, I, Jalbrzikowski, M, James, AC, Janssen, J, Jaspers-Fayer, F, Xu, J, Jonassen, R, Karkashadze, G, King, JA, Kircher, T, Kirschner, M, Koch, K, Kochunov, P, Kohls, G, Konrad, K, Kramer, B, Krug, A, Kuntsi, J, Kwon, JS, Landen, M, Landro, NI, Lazaro, L, Lebedeva, IS, Leehr, EJ, Lera-Miguel, S, Lesch, K-P, Lochner, C, Louza, MR, Luna, B, Lundervold, AJ, MacMaster, FP, Maglanoc, LA, Malpas, CB, Portella, MJ, Marsh, R, Martyn, FM, Mataix-Cols, D, Mathalon, DH, McCarthy, H, McDonald, C, McPhilemy, G, Meinert, S, Menchon, JM, Minuzzi, L, Mitchell, PB, Moreno, C, Morgado, P, Muratori, F, Murphy, CM, Murphy, D, Mwangi, B, Nabulsi, L, Nakagawa, A, Nakamae, T, Namazova, L, Narayanaswamy, J, Jahanshad, N, Nguyen, DD, Nicolau, R, O'Gorman Tuura, RL, O'Hearn, K, Oosterlaan, J, Opel, N, Ophoff, RA, Oranje, B, Garcia de la Foz, VO, Overs, BJ, Paloyelis, Y, Pantelis, C, Parellada, M, Pauli, P, Pico-Perez, M, Picon, FA, Piras, F, Plessen, KJ, Pomarol-Clotet, E, Preda, A, Puig, O, Quide, Y, Radua, J, Ramos-Quiroga, JA, Rasser, PE, Rauer, L, Reddy, J, Redlich, R, Reif, A, Reneman, L, Repple, J, Retico, A, Richarte, V, Richter, A, Rosa, PGP, Rubia, KK, Hashimoto, R, Sacchet, MD, Salvador, R, Santonja, J, Sarink, K, Sarro, S, Satterthwaite, TD, Sawa, A, Schall, U, Schofield, PR, Schrantee, A, Seitz, J, Serpa, MH, Setien-Suero, E, Shaw, P, Shook, D, Silk, TJ, Sim, K, Simon, S, Simpson, HB, Singh, A, Skoch, A, Skokauskas, N, Soares, JC, Soreni, N, Soriano-Mas, C, Spalletta, G, Spaniel, F, Lawrie, SM, Stern, ER, Stewart, SE, Takayanagi, Y, Temmingh, HS, Tolin, DF, Tomecek, D, Tordesillas-Gutierrez, D, Tosetti, M, Uhlmann, A, van Amelsvoort, T, van der Wee, NJA, van der Werff, SJA, van Haren, NEM, van Wingen, GA, Vance, A, Vazquez-Bourgon, J, Vecchio, D, Venkatasubramanian, G, Vieta, E, Vilarroya, O, Vives-Gilabert, Y, Voineskos, AN, Volzke, H, von Polier, GG, Walton, E, Weickert, TW, Weickert, CS, Weideman, AS, Wittfeld, K, Wolf, DH, Wu, M-J, Yang, TT, Yang, K, Yoncheva, Y, Yun, J-Y, Cheng, Y, Zanetti, MV, Ziegler, GC, Franke, B, Hoogman, M, Buitelaar, JK, van Rooij, D, Andreassen, OA, Ching, CRK, Veltman, DJ, Schmaal, L, Stein, DJ, van den Heuvel, OA, Turner, JA, van Erp, TGM, Pausova, Z, Thompson, PM, Paus, T, Patel, Y, Parker, N, Shin, J, Howard, D, French, L, Thomopoulos, SI, Pozzi, E, Abe, Y, Abe, C, Anticevic, A, Alda, M, Aleman, A, Alloza, C, Alonso-Lana, S, Ameis, SH, Anagnostou, E, McIntosh, AA, Arango, C, Arnold, PD, Asherson, P, Assogna, F, Auzias, G, Ayesa-Arriola, R, Bakker, G, Banaj, N, Banaschewski, T, Bandeira, CE, Baranov, A, Bargallo, N, Bau, CHD, Baumeister, S, Baune, BT, Bellgrove, MA, Benedetti, F, Bertolino, A, Boedhoe, PSW, Boks, M, Bollettini, I, del Mar Bonnin, C, Borgers, T, Borgwardt, S, Brandeis, D, Brennan, BP, Bruggemann, JM, Bulow, R, Busatto, GF, Calderoni, S, Calhoun, VD, Calvo, R, Canales-Rodriguez, EJ, Cannon, DM, Carr, VJ, Cascella, N, Cercignani, M, Chaim-Avancini, TM, Christakou, A, Coghill, D, Conzelmann, A, Crespo-Facorro, B, Cubillo, AI, Cullen, KR, Cupertino, RB, Daly, E, Dannlowski, U, Davey, CG, Denys, D, Deruelle, C, Di Giorgio, A, Dickie, EW, Dima, D, Dohm, K, Ehrlich, S, Ely, BA, Erwin-Grabner, T, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Fatjo-Vilas, M, Fedor, JM, Fitzgerald, KD, Ford, JM, Frodl, T, Fu, CHY, Fullerton, JM, Gabel, MC, Glahn, DC, Roberts, G, Gogberashvili, T, Goikolea, JM, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Green, MJ, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Guerrero-Pedraza, A, Gur, RE, Gur, RC, Haar, S, Haarman, BCM, Haavik, J, Hahn, T, Hajek, T, Harrison, BJ, Harrison, NA, Hartman, CA, Whalley, HC, Heslenfeld, DJ, Hibar, DP, Hilland, E, Hirano, Y, Ho, TC, Hoekstra, PJ, Hoekstra, L, Hohmann, S, Hong, LE, Hoschl, C, Hovik, MF, Howells, FM, Nenadic, I, Jalbrzikowski, M, James, AC, Janssen, J, Jaspers-Fayer, F, Xu, J, Jonassen, R, Karkashadze, G, King, JA, Kircher, T, Kirschner, M, Koch, K, Kochunov, P, Kohls, G, Konrad, K, Kramer, B, Krug, A, Kuntsi, J, Kwon, JS, Landen, M, Landro, NI, Lazaro, L, Lebedeva, IS, Leehr, EJ, Lera-Miguel, S, Lesch, K-P, Lochner, C, Louza, MR, Luna, B, Lundervold, AJ, MacMaster, FP, Maglanoc, LA, Malpas, CB, Portella, MJ, Marsh, R, Martyn, FM, Mataix-Cols, D, Mathalon, DH, McCarthy, H, McDonald, C, McPhilemy, G, Meinert, S, Menchon, JM, Minuzzi, L, Mitchell, PB, Moreno, C, Morgado, P, Muratori, F, Murphy, CM, Murphy, D, Mwangi, B, Nabulsi, L, Nakagawa, A, Nakamae, T, Namazova, L, Narayanaswamy, J, Jahanshad, N, Nguyen, DD, Nicolau, R, O'Gorman Tuura, RL, O'Hearn, K, Oosterlaan, J, Opel, N, Ophoff, RA, Oranje, B, Garcia de la Foz, VO, Overs, BJ, Paloyelis, Y, Pantelis, C, Parellada, M, Pauli, P, Pico-Perez, M, Picon, FA, Piras, F, Plessen, KJ, Pomarol-Clotet, E, Preda, A, Puig, O, Quide, Y, Radua, J, Ramos-Quiroga, JA, Rasser, PE, Rauer, L, Reddy, J, Redlich, R, Reif, A, Reneman, L, Repple, J, Retico, A, Richarte, V, Richter, A, Rosa, PGP, Rubia, KK, Hashimoto, R, Sacchet, MD, Salvador, R, Santonja, J, Sarink, K, Sarro, S, Satterthwaite, TD, Sawa, A, Schall, U, Schofield, PR, Schrantee, A, Seitz, J, Serpa, MH, Setien-Suero, E, Shaw, P, Shook, D, Silk, TJ, Sim, K, Simon, S, Simpson, HB, Singh, A, Skoch, A, Skokauskas, N, Soares, JC, Soreni, N, Soriano-Mas, C, Spalletta, G, Spaniel, F, Lawrie, SM, Stern, ER, Stewart, SE, Takayanagi, Y, Temmingh, HS, Tolin, DF, Tomecek, D, Tordesillas-Gutierrez, D, Tosetti, M, Uhlmann, A, van Amelsvoort, T, van der Wee, NJA, van der Werff, SJA, van Haren, NEM, van Wingen, GA, Vance, A, Vazquez-Bourgon, J, Vecchio, D, Venkatasubramanian, G, Vieta, E, Vilarroya, O, Vives-Gilabert, Y, Voineskos, AN, Volzke, H, von Polier, GG, Walton, E, Weickert, TW, Weickert, CS, Weideman, AS, Wittfeld, K, Wolf, DH, Wu, M-J, Yang, TT, Yang, K, Yoncheva, Y, Yun, J-Y, Cheng, Y, Zanetti, MV, Ziegler, GC, Franke, B, Hoogman, M, Buitelaar, JK, van Rooij, D, Andreassen, OA, Ching, CRK, Veltman, DJ, Schmaal, L, Stein, DJ, van den Heuvel, OA, Turner, JA, van Erp, TGM, Pausova, Z, Thompson, PM, and Paus, T
Abstract: IMPORTANCE: Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood. OBJECTIVE: To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia. DESIGN, SETTING, AND PARTICIPANTS: Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244. MAIN OUTCOMES AND MEASURES: Interregional profiles of group difference in cortical thickness between cases and controls. RESULTS: A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene
Published: 2021

197. Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders

Author: Patel, Y., Parker, N., Shin, J., Howard, D., French, L., Thomopoulos, S.I., Pozzi, E., Abe, Y., Abé, C., Anticevic, A., Alda, M., Aleman, A., Alloza, C., Alonso-Lana, S., Ameis, S.H., Anagnostou, E., McIntosh, A.A., Arango, C., Arnold, P.D., Asherson, P., Assogna, F., Auzias, G., Ayesa-Arriola, R., Bakker, G., Banaj, N., Banaschewski, T., Bandeira, C.E., Baranov, A., Bargalló, N., Bau, C.H.D., Baumeister, S., Baune, B.T., Bellgrove, M.A., Benedetti, F., Bertolino, A., Boedhoe, P.S.W., Boks, M., Bollettini, I., Del Mar Bonnin, C., Borgers, T., Borgwardt, S., Brandeis, D., Brennan, B.P., Bruggemann, J.M., Bülow, R., Busatto, G.F., Calderoni, S., Calhoun, V.D., Calvo, R., Canales-Rodríguez, E.J., Cannon, D.M., Carr, V.J., Cascella, N., Cercignani, M., Chaim-Avancini, T.M., Christakou, A., Coghill, D., Conzelmann, A., Crespo-Facorro, B., Cubillo, A.I., Cullen, K.R., Cupertino, R.B., Daly, E., Dannlowski, U., Davey, C.G., Denys, D., Deruelle, C., Di Giorgio, A., Dickie, E.W., Dima, D., Dohm, K., Ehrlich, S., Ely, B.A., Erwin-Grabner, T., Ethofer, T., Fair, D.A., Fallgatter, A.J., Faraone, S.V., Fatjó-Vilas, M., Fedor, J.M., Fitzgerald, K.D., Ford, J.M., Frodl, T., Fu, C.H.Y., Fullerton, J.M., Gabel, M.C., Glahn, D.C., Roberts, G., Gogberashvili, T., Goikolea, J.M., Gotlib, I.H., Goya-Maldonado, R., Grabe, H.J., Green, M.J., Grevet, E.H., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Guerrero-Pedraza, A., Gur, R.E., Gur, R.C., Haar, S., Haarman, B.C.M., Haavik, J., Hahn, T., Hajek, T., Harrison, B.J., Harrison, N.A., Hartman, C.A., Whalley, H.C., Heslenfeld, D.J., Hibar, D.P., Hilland, E., Hirano, Y., Ho, T.C., Hoekstra, P.J., Hoekstra, L., Hohmann, S., Hong, L.E., Höschl, C., Høvik, M.F., Howells, F.M., Nenadic, I., Jalbrzikowski, M., James, A.C., Janssen, J., Jaspers-Fayer, F., Xu, J., Jonassen, R., Karkashadze, G., King, J.A., Kircher, T., Kirschner, M., Koch, K., Kochunov, P., Kohls, G., Konrad, K., Krämer, B., Krug, A., Kuntsi, J., Kwon, J.S., Landén, M., Landrø, N.I., Lazaro, L., Lebedeva, I.S., Leehr, E.J., Lera-Miguel, S., Lesch, K.-P., Lochner, C., Louza, M.R., Luna, B., Lundervold, A.J., Macmaster, F.P., Maglanoc, L.A., Malpas, C.B., Portella, M.J., Marsh, R., Martyn, F.M., Mataix-Cols, D., Mathalon, D.H., McCarthy, H., McDonald, C., McPhilemy, G., Meinert, S., Menchón, J.M., Minuzzi, L., Mitchell, P.B., Moreno, C., Morgado, P., Muratori, F., Murphy, C.M., Murphy, D., Mwangi, B., Nabulsi, L., Nakagawa, A., Nakamae, T., Namazova, L., Narayanaswamy, J., Jahanshad, N., Nguyen, D.D., Nicolau, R., O'Gorman Tuura, R.L., O'Hearn, K., Oosterlaan, J., Opel, N., Ophoff, R.A., Oranje, B., García De La Foz, V.O., Overs, B.J., Paloyelis, Y., Pantelis, C., Parellada, M., Pauli, P., Picó-Pérez, M., Picon, F.A., Piras, F., Plessen, K.J., Pomarol-Clotet, E., Preda, A., Puig, O., Quidé, Y., Radua, J., Ramos-Quiroga, J.A., Rasser, P.E., Rauer, L., Reddy, J., Redlich, R., Reif, A., Reneman, L., Repple, J., Retico, A., Richarte, V., Richter, A., Rosa, P.G.P., Rubia, K.K., Hashimoto, R., Sacchet, M.D., Salvador, R., Santonja, J., Sarink, K., Sarró, S., Satterthwaite, T.D., Sawa, A., Schall, U., Schofield, P.R., Schrantee, A., Seitz, J., Serpa, M.H., Setién-Suero, E., Shaw, P., Shook, D., Silk, T.J., Sim, K., Simon, S., Simpson, H.B., Singh, A., Skoch, A., Skokauskas, N., Soares, J.C., Soreni, N., Soriano-Mas, C., Spalletta, G., Spaniel, F., Lawrie, S.M., Stern, E.R., Stewart, S.E., Takayanagi, Y., Temmingh, H.S., Tolin, D.F., Tomecek, D., Tordesillas-Gutiérrez, D., Tosetti, M., Uhlmann, A., Van Amelsvoort, T., Van Der Wee, N.J.A., Van Der Werff, S.J.A., Van Haren, N.E.M., Van Wingen, G.A., Vance, A., Vázquez-Bourgon, J., Vecchio, D., Venkatasubramanian, G., Vieta, E., Vilarroya, O., Vives-Gilabert, Y., Voineskos, A.N., Völzke, H., Von Polier, G.G., Walton, E., Weickert, T.W., Weickert, C.S., Weideman, A.S., Wittfeld, K., Wolf, D.H., Wu, M.-J., Yang, T.T., Yang, K., Yoncheva, Y., Yun, J.-Y., Cheng, Y., Zanetti, M.V., Ziegler, G.C., Franke, B., Hoogman, M., Buitelaar, J.K., Van Rooij, D., Andreassen, O.A., Ching, C.R.K., Veltman, D.J., Schmaal, L., Stein, D.J., Van Den Heuvel, O.A., Turner, J.A., Van Erp, T.G.M., Pausova, Z., Thompson, P.M., Paus, T., Patel, Y., Parker, N., Shin, J., Howard, D., French, L., Thomopoulos, S.I., Pozzi, E., Abe, Y., Abé, C., Anticevic, A., Alda, M., Aleman, A., Alloza, C., Alonso-Lana, S., Ameis, S.H., Anagnostou, E., McIntosh, A.A., Arango, C., Arnold, P.D., Asherson, P., Assogna, F., Auzias, G., Ayesa-Arriola, R., Bakker, G., Banaj, N., Banaschewski, T., Bandeira, C.E., Baranov, A., Bargalló, N., Bau, C.H.D., Baumeister, S., Baune, B.T., Bellgrove, M.A., Benedetti, F., Bertolino, A., Boedhoe, P.S.W., Boks, M., Bollettini, I., Del Mar Bonnin, C., Borgers, T., Borgwardt, S., Brandeis, D., Brennan, B.P., Bruggemann, J.M., Bülow, R., Busatto, G.F., Calderoni, S., Calhoun, V.D., Calvo, R., Canales-Rodríguez, E.J., Cannon, D.M., Carr, V.J., Cascella, N., Cercignani, M., Chaim-Avancini, T.M., Christakou, A., Coghill, D., Conzelmann, A., Crespo-Facorro, B., Cubillo, A.I., Cullen, K.R., Cupertino, R.B., Daly, E., Dannlowski, U., Davey, C.G., Denys, D., Deruelle, C., Di Giorgio, A., Dickie, E.W., Dima, D., Dohm, K., Ehrlich, S., Ely, B.A., Erwin-Grabner, T., Ethofer, T., Fair, D.A., Fallgatter, A.J., Faraone, S.V., Fatjó-Vilas, M., Fedor, J.M., Fitzgerald, K.D., Ford, J.M., Frodl, T., Fu, C.H.Y., Fullerton, J.M., Gabel, M.C., Glahn, D.C., Roberts, G., Gogberashvili, T., Goikolea, J.M., Gotlib, I.H., Goya-Maldonado, R., Grabe, H.J., Green, M.J., Grevet, E.H., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Guerrero-Pedraza, A., Gur, R.E., Gur, R.C., Haar, S., Haarman, B.C.M., Haavik, J., Hahn, T., Hajek, T., Harrison, B.J., Harrison, N.A., Hartman, C.A., Whalley, H.C., Heslenfeld, D.J., Hibar, D.P., Hilland, E., Hirano, Y., Ho, T.C., Hoekstra, P.J., Hoekstra, L., Hohmann, S., Hong, L.E., Höschl, C., Høvik, M.F., Howells, F.M., Nenadic, I., Jalbrzikowski, M., James, A.C., Janssen, J., Jaspers-Fayer, F., Xu, J., Jonassen, R., Karkashadze, G., King, J.A., Kircher, T., Kirschner, M., Koch, K., Kochunov, P., Kohls, G., Konrad, K., Krämer, B., Krug, A., Kuntsi, J., Kwon, J.S., Landén, M., Landrø, N.I., Lazaro, L., Lebedeva, I.S., Leehr, E.J., Lera-Miguel, S., Lesch, K.-P., Lochner, C., Louza, M.R., Luna, B., Lundervold, A.J., Macmaster, F.P., Maglanoc, L.A., Malpas, C.B., Portella, M.J., Marsh, R., Martyn, F.M., Mataix-Cols, D., Mathalon, D.H., McCarthy, H., McDonald, C., McPhilemy, G., Meinert, S., Menchón, J.M., Minuzzi, L., Mitchell, P.B., Moreno, C., Morgado, P., Muratori, F., Murphy, C.M., Murphy, D., Mwangi, B., Nabulsi, L., Nakagawa, A., Nakamae, T., Namazova, L., Narayanaswamy, J., Jahanshad, N., Nguyen, D.D., Nicolau, R., O'Gorman Tuura, R.L., O'Hearn, K., Oosterlaan, J., Opel, N., Ophoff, R.A., Oranje, B., García De La Foz, V.O., Overs, B.J., Paloyelis, Y., Pantelis, C., Parellada, M., Pauli, P., Picó-Pérez, M., Picon, F.A., Piras, F., Plessen, K.J., Pomarol-Clotet, E., Preda, A., Puig, O., Quidé, Y., Radua, J., Ramos-Quiroga, J.A., Rasser, P.E., Rauer, L., Reddy, J., Redlich, R., Reif, A., Reneman, L., Repple, J., Retico, A., Richarte, V., Richter, A., Rosa, P.G.P., Rubia, K.K., Hashimoto, R., Sacchet, M.D., Salvador, R., Santonja, J., Sarink, K., Sarró, S., Satterthwaite, T.D., Sawa, A., Schall, U., Schofield, P.R., Schrantee, A., Seitz, J., Serpa, M.H., Setién-Suero, E., Shaw, P., Shook, D., Silk, T.J., Sim, K., Simon, S., Simpson, H.B., Singh, A., Skoch, A., Skokauskas, N., Soares, J.C., Soreni, N., Soriano-Mas, C., Spalletta, G., Spaniel, F., Lawrie, S.M., Stern, E.R., Stewart, S.E., Takayanagi, Y., Temmingh, H.S., Tolin, D.F., Tomecek, D., Tordesillas-Gutiérrez, D., Tosetti, M., Uhlmann, A., Van Amelsvoort, T., Van Der Wee, N.J.A., Van Der Werff, S.J.A., Van Haren, N.E.M., Van Wingen, G.A., Vance, A., Vázquez-Bourgon, J., Vecchio, D., Venkatasubramanian, G., Vieta, E., Vilarroya, O., Vives-Gilabert, Y., Voineskos, A.N., Völzke, H., Von Polier, G.G., Walton, E., Weickert, T.W., Weickert, C.S., Weideman, A.S., Wittfeld, K., Wolf, D.H., Wu, M.-J., Yang, T.T., Yang, K., Yoncheva, Y., Yun, J.-Y., Cheng, Y., Zanetti, M.V., Ziegler, G.C., Franke, B., Hoogman, M., Buitelaar, J.K., Van Rooij, D., Andreassen, O.A., Ching, C.R.K., Veltman, D.J., Schmaal, L., Stein, D.J., Van Den Heuvel, O.A., Turner, J.A., Van Erp, T.G.M., Pausova, Z., Thompson, P.M., and Paus, T.
Abstract: Importance Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood. Objective To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia. Design, Setting, and Participants Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244. Main Outcomes and Measures Interregional profiles of group difference in cortical thickness between cases and controls. Results A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (exce
Published: 2021
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198. Combination of computer-aided detection algorithms for automatic lung nodule identification

Author: Camarlinghi, Niccolò, Gori, Ilaria, Retico, Alessandra, Bellotti, Roberto, Bosco, Paolo, Cerello, Piergiorgio, Gargano, Gianfranco, Lopez Torres, Ernesto, Megna, Rosario, Peccarisi, Marco, and Fantacci, Maria Evelina
Published: 2012
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199. Lung nodule detection in low-dose and thin-slice computed tomography

Author: Retico, A., Delogu, P., Fantacci, M.E., Gori, I., and Preite Martinez, A.
Published: 2008
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200. PO-1799 Radiomic and dosiomic profiling of paediatric Medulloblastoma tumours treated with IMRT

Author: Leonardo Ubaldi, Piernicola Oliva, Stefania Pallotta, Francesco Laurina, Stefano Piffer, Cinzia Talamonti, Alessandra Retico, Antonio Ciccarone, Daniela Greto, Marzia Mortilla, and Maria Evelina Fantacci
Subjects: Medulloblastoma, Oncology, medicine.medical_specialty, business.industry, Internal medicine, medicine, Profiling (information science), Radiology, Nuclear Medicine and imaging, Hematology, medicine.disease, business
Published: 2021

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