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1. Genomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for variation across ancestries

Author

García-Marín, Luis M., Campos, Adrian I., Diaz-Torres, Santiago, Rabinowitz, Jill A., Ceja, Zuriel, Mitchell, Brittany L., Grasby, Katrina L., Thorp, Jackson G., Agartz, Ingrid, Alhusaini, Saud, Ames, David, Amouyel, Philippe, Andreassen, Ole A., Arfanakis, Konstantinos, Arias-Vasquez, Alejandro, Armstrong, Nicola J., Athanasiu, Lavinia, Bastin, Mark E., Beiser, Alexa S., Bennett, David A., Bis, Joshua C., Boks, Marco P. M., Boomsma, Dorret I., Brodaty, Henry, Brouwer, Rachel M., Buitelaar, Jan K., Burkhardt, Ralph, Cahn, Wiepke, Calhoun, Vince D., Carmichael, Owen T., Chakravarty, Mallar, Chen, Qiang, Ching, Christopher R. K., Cichon, Sven, Crespo-Facorro, Benedicto, Crivello, Fabrice, Dale, Anders M., Smith, George Davey, de Geus, Eco J. C., De Jager, Philip L., de Zubicaray, Greig I., Debette, Stéphanie, DeCarli, Charles, Depondt, Chantal, Desrivières, Sylvane, Djurovic, Srdjan, Ehrlich, Stefan, Erk, Susanne, Espeseth, Thomas, Fernández, Guillén, Filippi, Irina, Fisher, Simon E., Fleischman, Debra A., Fletcher, Evan, Fornage, Myriam, Forstner, Andreas J., Francks, Clyde, Franke, Barbara, Ge, Tian, Goldman, Aaron L., Grabe, Hans J., Green, Robert C., Grimm, Oliver, Groenewold, Nynke A., Gruber, Oliver, Gudnason, Vilmundur, Håberg, Asta K., Haukvik, Unn K., Heinz, Andreas, Hibar, Derrek P., Hilal, Saima, Himali, Jayandra J., Ho, Beng-Choon, Hoehn, David F., Hoekstra, Pieter J., Hofer, Edith, Hoffmann, Wolfgang, Holmes, Avram J., Homuth, Georg, Hosten, Norbert, Ikram, M. Kamran, Ipser, Jonathan C., Jack Jr, Clifford R., Jahanshad, Neda, Jönsson, Erik G., Kahn, Rene S., Kanai, Ryota, Klein, Marieke, Knol, Maria J., Launer, Lenore J., Lawrie, Stephen M., Hellard, Stephanie Le, Lee, Phil H., Lemaître, Hervé, Li, Shuo, Liewald, David C. M., Lin, Honghuang, Longstreth, Jr, W. T., Lopez, Oscar L., Luciano, Michelle, Maillard, Pauline, Marquand, Andre F., Martin, Nicholas G., Martinot, Jean-Luc, Mather, Karen A., Mattay, Venkata S., McMahon, Katie L., Mecocci, Patrizia, Melle, Ingrid, Meyer-Lindenberg, Andreas, Mirza-Schreiber, Nazanin, Milaneschi, Yuri, Mosley, Thomas H., Mühleisen, Thomas W., Müller-Myhsok, Bertram, Maniega, Susana Muñoz, Nauck, Matthias, Nho, Kwangsik, Niessen, Wiro J., Nöthen, Markus M., Nyquist, Paul A., Oosterlaan, Jaap, Pandolfo, Massimo, Paus, Tomas, Pausova, Zdenka, Penninx, Brenda W. J. H., Pike, G. Bruce, Psaty, Bruce M., Pütz, Benno, Reppermund, Simone, Rietschel, Marcella D., Risacher, Shannon L., Romanczuk-Seiferth, Nina, Romero-Garcia, Rafael, Roshchupkin, Gennady V., Rotter, Jerome I., Sachdev, Perminder S., Sämann, Philipp G., Saremi, Arvin, Sargurupremraj, Muralidharan, Saykin, Andrew J., Schmaal, Lianne, Schmidt, Helena, Schmidt, Reinhold, Schofield, Peter R., Scholz, Markus, Schumann, Gunter, Schwarz, Emanuel, Shen, Li, Shin, Jean, Sisodiya, Sanjay M., Smith, Albert V., Smoller, Jordan W., Soininen, Hilkka S., Steen, Vidar M., Stein, Dan J., Stein, Jason L., Thomopoulos, Sophia I., Toga, Arthur W., Tordesillas-Gutiérrez, Diana, Trollor, Julian N., Valdes-Hernandez, Maria C., van ′t Ent, Dennis, van Bokhoven, Hans, van der Meer, Dennis, van der Wee, Nic J. A., Vázquez-Bourgon, Javier, Veltman, Dick J., Vernooij, Meike W., Villringer, Arno, Vinke, Louis N., Völzke, Henry, Walter, Henrik, Wardlaw, Joanna M., Weinberger, Daniel R., Weiner, Michael W., Wen, Wei, Westlye, Lars T., Westman, Eric, White, Tonya, Witte, A. Veronica, Wolf, Christiane, Yang, Jingyun, Zwiers, Marcel P., Ikram, M. Arfan, Seshadri, Sudha, Thompson, Paul M., Satizabal, Claudia L., Medland, Sarah E., and Rentería, Miguel E.

Published
2024
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10. Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data

Author

Kaddurah-Daouk, Rima, Kueider-Paisley, Alexandra, Doraiswamy, P. Murali, Blach, Colette, Moseley, Arthur, Thompson, Will, St John-Williams, Lisa, Mahmoudiandehkhordi, Siamak, Tenenbaum, Jessica, Welsh-Balmer, Kathleen, Plassman, Brenda, Saykin, Andrew J., Nho, Kwangsik, Risacher, Shannon L., Kastenmüller, Gabi, Arnold, Matthias, Han, Xianlin, Baillie, Rebecca, Knight, Rob, Dorrestein, Pieter, Brewer, James, Mayer, Emeran, Labus, Jennifer, Baldi, Pierre, Gupta, Arpana, Fiehn, Oliver, Barupal, Dinesh, Meikle, Peter, Mazmanian, Sarkis, Rader, Dan, Kling, Mitchel, Shaw, Leslie, Trojanowski, John, van Duijin, Cornelia, Nevado-Holgado, Alejo, Bennett, David, Krishnan, Ranga, Keshavarzian, Ali, Vogt, Robin, Ikram, Arfan, Hankemeier, Thomas, Thiele, Ines, Price, Nathan, Funk, Cory, Baloni, Priyanka, Jia, Wei, Wishart, David, Brinton, Roberta, Chang, Rui, Farrer, Lindsay, Au, Rhoda, Qiu, Wendy, Würtz, Peter, Koal, Therese, Mangravite, Lara, Krumsiek, Jan, Suhre, Karsten, Newman, John, Moreno, Herman, Foroud, Tatania, Sacks, Frank, Jansson, Janet, Weiner, Michael W., Aisen, Paul, Petersen, Ronald, Jack, Clifford R., Jr., Jagust, William, Trojanowki, John Q., Toga, Arthur W., Beckett, Laurel, Green, Robert C., Morris, John C., Perrin, Richard J., Shaw, Leslie M., Khachaturian, Zaven, Carrillo, Maria, Potter, William, Barnes, Lisa, Bernard, Marie, Gonzalez, Hector, Ho, Carole, Hsiao, John K., Jackson, Jonathan, Masliah, Eliezer, Masterman, Donna, Okonkwo, Ozioma, Perrin, Richard, Ryan, Laurie, Silverberg, Nina, Fleisher, Adam, Sacrey, Diana Truran, Fockler, Juliet, Conti, Cat, Veitch, Dallas, Neuhaus, John, Jin, Chengshi, Nosheny, Rachel, Ashford, Miriam, Flenniken, Derek, Kormos, Adrienne, Montine, Tom, Rafii, Michael, Raman, Rema, Jimenez, Gustavo, Donohue, Michael, Gessert, Devon, Salazar, Jennifer, Zimmerman, Caileigh, Cabrera, Yuliana, Walter, Sarah, Miller, Garrett, Coker, Godfrey, Clanton, Taylor, Hergesheimer, Lindsey, Smith, Stephanie, Adegoke, Olusegun, Mahboubi, Payam, Moore, Shelley, Pizzola, Jeremy, Shaffer, Elizabeth, Sloan, Brittany, Harvey, Danielle, Forghanian-Arani, Arvin, Borowski, Bret, Ward, Chad, Schwarz, Christopher, Jones, David, Gunter, Jeff, Kantarci, Kejal, Senjem, Matthew, Vemuri, Prashanthi, Reid, Robert, Fox, Nick C., Malone, Ian, Thompson, Paul, Thomopoulos, Sophia I., Nir, Talia M., Jahanshad, Neda, DeCarli, Charles, Knaack, Alexander, Fletcher, Evan, Tosun-Turgut, Duygu, Chen, Stephanie Rossi, Choe, Mark, Crawford, Karen, Yushkevich, Paul A., Das, Sandhitsu, Koeppe, Robert A., Reiman, Eric M., Chen, Kewei, Mathis, Chet, Landau, Susan, Cairns, Nigel J., Householder, Erin, Franklin, Erin, Bernhardt, Haley, Taylor-Reinwald, Lisa, Korecka, Magdalena, Figurski, Michal, Neu, Scott, Apostolova, Liana G., Shen, Li, Foroud, Tatiana M., Nudelman, Kelly, Faber, Kelley, Wilmes, Kristi, Thal, Leon, Silbert, Lisa C., Lind, Betty, Crissey, Rachel, Kaye, Jeffrey A., Carter, Raina, Dolen, Sara, Quinn, Joseph, Schneider, Lon S., Pawluczyk, Sonia, Becerra, Mauricio, Teodoro, Liberty, Dagerman, Karen, Spann, Bryan M., Vanderswag, Helen, Ziolkowski, Jaimie, Heidebrink, Judith L., Zbizek-Nulph, Lisa, Lord, Joanne L., Mason, Sara S., Albers, Colleen S., Knopman, David, Johnson, Kris, Villanueva-Meyer, Javier, Pavlik, Valory, Pacini, Nathaniel, Lamb, Ashley, Kass, Joseph S., Doody, Rachelle S., Shibley, Victoria, Chowdhury, Munir, Rountree, Susan, Dang, Mimi, Stern, Yaakov, Honig, Lawrence S., Mintz, Akiva, Ances, Beau, Winkfield, David, Carroll, Maria, Stobbs-Cucchi, Georgia, Oliver, Angela, Creech, Mary L., Mintun, Mark A., Schneider, Stacy, Geldmacher, David, Love, Marissa Natelson, Griffith, Randall, Clark, David, Brockington, John, Marson, Daniel, Grossman, Hillel, Goldstein, Martin A., Greenberg, Jonathan, Mitsis, Effie, Shah, Raj C., Lamar, Melissa, Samuels, Patricia, Duara, Ranjan, Greig-Custo, Maria T., Rodriguez, Rosemarie, Albert, Marilyn, Onyike, Chiadi, Farrington, Leonie, Rudow, Scott, Brichko, Rottislav, Kielb, Stephanie, Smith, Amanda, Raj, Balebail Ashok, Fargher, Kristin, Sadowski, Martin, Wisniewski, Thomas, Shulman, Melanie, Faustin, Arline, Rao, Julia, Castro, Karen M., Ulysse, Anaztasia, Chen, Shannon, Sheikh, Mohammed O., Singleton-Garvin, Jamika, Petrella, JeffreyR., James, Olga, Wong, Terence Z., Borges-Neto, Salvador, Karlawish, Jason H., Wolk, David A., Vaishnavi, Sanjeev, Clark, Christopher M., Arnold, Steven E., Smith, Charles D., Jicha, Gregory A., Raslau, Flavius D., Lopez, Oscar L., Oakley, MaryAnn, Simpson, Donna M., Porsteinsson, Anton P., Martin, Kim, Kowalski, Nancy, Keltz, Melanie, Goldstein, Bonnie S., Makino, Kelly M., Ismail, M. Saleem, Brand, Connie, Thai, Gaby, Pierce, Aimee, Yanez, Beatriz, Sosa, Elizabeth, Witbracht, Megan, Kelley, Brendan, Nguyen, Trung, Womack, Kyle, Mathews, Dana, Quiceno, Mary, Levey, Allan I., Lah, James J., Hajjar, Ihab, Cellar, Janet S., Burns, Jeffrey M., Swerdlow, Russell H., Brooks, William M., Silverman, Daniel H.S., Kremen, Sarah, Apostolova, Liana, Tingus, Kathleen, Lu, Po H., Bartzokis, George, Woo, Ellen, Teng, Edmond, Graff-Radford, Neill R., Parfitt, Francine, Poki-Walker, Kim, Farlow, Martin R., Hake, Ann Marie, Matthews, Brandy R., Brosch, Jared R., Herring, Scott, van, Christopher H., Mecca, Adam P., Good, Susan P., MacAvoy, Martha G., Carson, Richard E., Varma, Pradeep, Chertkow, Howard, Vaitekunis, Susan, Hosein, Chris, Black, Sandra, Stefanovic, Bojana, Heyn, Chris (Chinthaka), Robin Hsiung, Ging-Yuek, Kim, Ellen, Mudge, Benita, Sossi, Vesna, Feldman, Howard, Assaly, Michele, Finger, Elizabeth, Pasternak, Stephen, Rachinsky, Irina, Kertesz, Andrew, Drost, Dick, Rogers, John, Grant, Ian, Muse, Brittanie, Rogalski, Emily, Robson, Jordan, Mesulam, M.-Marsel, Kerwin, Diana, Wu, Chuang-Kuo, Johnson, Nancy, Lipowski, Kristine, Weintraub, Sandra, Bonakdarpour, Borna, Pomara, Nunzio, Hernando, Raymundo, Sarrael, Antero, Rosen, Howard J., Miller, Bruce L., Perry, David, Turner, Raymond Scott, Johnson, Kathleen, Reynolds, Brigid, MCCann, Kelly, Poe, Jessica, Sperling, Reisa A., Johnson, Keith A., Marshall, Gad A., Yesavage, Jerome, Taylor, Joy L., Chao, Steven, Coleman, Jaila, White, Jessica D., Lane, Barton, Rosen, Allyson, Tinklenberg, Jared, Belden, Christine M., Atri, Alireza, Clark, Kelly A., Zamrini, Edward, Sabbagh, Marwan, Killiany, Ronald, Stern, Robert, Mez, Jesse, Kowall, Neil, Budson, Andrew E., Obisesan, Thomas O., Ntekim, Oyonumo E., Wolday, Saba, Khan, Javed I., Nwulia, Evaristus, Nadarajah, Sheeba, Lerner, Alan, Ogrocki, Paula, Tatsuoka, Curtis, Fatica, Parianne, Maillard, Pauline, Olichney, John, Carmichael, Owen, Bates, Vernice, Capote, Horacio, Rainka, Michelle, Borrie, Michael, Lee, T.-Y., Bartha, Dr Rob, Johnson, Sterling, Asthana, Sanjay, Carlsson, Cynthia M., Perrin, Allison, Burke, Anna, Scharre, Douglas W., Kataki, Maria, Tarawneh, Rawan, Hart, David, Zimmerman, Earl A., Celmins, Dzintra, Miller, Delwyn D., BolesPonto, Laura L., Smith, Karen Ekstam, Koleva, Hristina, Shim, Hyungsub, Nam, Ki Won, Schultz, Susan K., Williamson, Jeff D., Craft, Suzanne, Cleveland, Jo, Yang, Mia, Sink, Kaycee M., Ott, Brian R., Drake, Jonathan, Tremont, Geoffrey, Daiello, Lori A., Drake, Jonathan D., Ritter, Aaron, Bernick, Charles, Munic, Donna, O'Connelll, Abigail, Mintzer, Jacobo, Wiliams, Arthur, Masdeu, Joseph, Shi, Jiong, Garcia, Angelica, Newhouse, Paul, Potkin, Steven, Salloway, Stephen, Malloy, Paul, Correia, Stephen, Kittur, Smita, Pearlson, Godfrey D., Blank, Karen, Anderson, Karen, Flashman, Laura A., Seltzer, Marc, Hynes, Mary L., Santulli, Robert B., Relkin, Norman, Chiang, Gloria, Lee, Athena, Lin, Michael, Ravdin, Lisa, Petersen, Ron, Neylan, Thomas, Grafman, Jordan, Danowski, Sarah, Nguyen-Barrera, Catherine, Hayes, Jacqueline, Finley, Shannon, Bernstein, Matthew, Senjem, Matt, Foster, Norm, Kim, Sungeun, Sood, Ajay, Blanchard, Kimberly S., Fleischman, Debra, Arfanakis, Konstantinos, Varon, Daniel, Greig, Maria T., Petrella, Jeffrey R., Goldstein, Bonnie, Martin, Kimberly S., Reist, Christopher, Sadowsky, Carl, Martinez, Walter, Villena, Teresa, Rosen, Howard, Marshall, Gad, Peskind, Elaine R., Petrie, Eric C., Li, Gail, Mackin, Scott, Jimenez-Maggiora, Gustavo, Drake, Erin, Donohue, Mike, Nelson, Craig, Bickford, David, Butters, Meryl, Zmuda, Michelle, Reyes, Denise, Faber, Kelley M., Nudelman, Kelly N., Au, Yiu Ho, Scherer, Kelly, Catalinotto, Daniel, Stark, Samuel, Ong, Elise, Fernandez, Dariella, Jo, Taeho, Kim, Junpyo, Bice, Paula, Huynh, Kevin, Wang, Tingting, Meikle, Peter J., and Giles, Corey

Published
2023
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12. LATE-NC staging in routine neuropathologic diagnosis: an update

Author

Nelson, Peter T., Lee, Edward B., Cykowski, Matthew D., Alafuzoff, Irina, Arfanakis, Konstantinos, Attems, Johannes, Brayne, Carol, Corrada, Maria M., Dugger, Brittany N., Flanagan, Margaret E., Ghetti, Bernardino, Grinberg, Lea T., Grossman, Murray, Grothe, Michel J., Halliday, Glenda M., Hasegawa, Masato, Hokkanen, Suvi R. K., Hunter, Sally, Jellinger, Kurt, Kawas, Claudia H., Keene, C. Dirk, Kouri, Naomi, Kovacs, Gabor G., Leverenz, James B., Latimer, Caitlin S., Mackenzie, Ian R., Mao, Qinwen, McAleese, Kirsty E., Merrick, Richard, Montine, Thomas J., Murray, Melissa E., Myllykangas, Liisa, Nag, Sukriti, Neltner, Janna H., Newell, Kathy L., Rissman, Robert A., Saito, Yuko, Sajjadi, S. Ahmad, Schwetye, Katherine E., Teich, Andrew F., Thal, Dietmar R., Tomé, Sandra O., Troncoso, Juan C., Wang, Shih-Hsiu J., White, III, Charles L., Wisniewski, Thomas, Yang, Hyun-Sik, Schneider, Julie A., Dickson, Dennis W., and Neumann, Manuela

Published
2023
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22. Cerebral arteriolosclerosis, lacunar infarcts, and cognition in older Black adults.

Author

Fleischman, Debra A., Arfanakis, Konstantinos, Leurgans, Sue E., Arvanitakis, Zoe, Lamar, Melissa, Han, S. Duke, Poole, Victoria N., Bennett, David A., and Barnes, Lisa L.

Abstract

INTRODUCTION: Older Black adults are at risk of cerebral small vessel disease (CSVD), which contributes to dementia risk. Two subtypes of CSVD, arteriolosclerosis and ischemic lacunar infarcts, have been independently linked to lower cognition and higher dementia risk, but their combined effects on cognition in older Black adults are unclear. METHODS: Mixed models were used to examine the associations of in vivo measures of arteriolosclerosis (ARTS) and ischemic lacunar infarcts to cognitive level and change in 370 older Black adults without dementia. RESULTS: Modeled together, higher ARTS load accounted for lower levels of global cognition, episodic memory, semantic memory, and perceptual speed, whereas higher infarct load accounted for lower levels of working memory. There were no associations with rate of cognitive change. DISCUSSION: Both arteriolosclerosis and ischemic infarcts impact the cognitive health of older Black adults, but arteriolosclerosis affects cognition more broadly and offers promise as an in vivo biomarker of dementia risk. Highlights: Older Black adults are at risk of cerebral small vessel disease (CSVD) and dementia.Examined magnetic resonance imaging‐derived measure of arteriolosclerosis (ARTS), infarcts, and cognition.ARTS load was widely associated with lower cognition after adjusting for infarct load.Infarct load was specifically associated with lower complex attention.More within‐Black in vivo studies of CSVD subtypes and cognition are needed. [ABSTRACT FROM AUTHOR]

Published
2024
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23. Cross-Vendor Test-Retest Validation of Diffusion Tensor Image Analysis along the Perivascular Space (DTI-ALPS) for Evaluating Glymphatic System Function.

Author

Xiaodan Liu, Barisano, Giuseppe, Xingfeng Shao, Jann, Kay, Ringman, John M., Hanzhang Lu, Arfanakis, Konstantinos, Caprihan, Arvind, DeCarli, Charles, Gold, Brian T., Maillard, Pauline, Satizabal, Claudia L., Fadaee, Elyas, Habes, Mohamad, Stables, Lara, Singh, Herpreet, Fischl, Bruce, van der Kouwe, Andre, Schwab, Kristin, and Helmer, Karl G.

Subjects
DIFFUSION tensor imaging, BIOMARKERS
Abstract

The diffusion tensor image analysis along the perivascular space (DTI-ALPS) method was proposed to evaluate glymphatic system (GS) function. However, few studies have validated its reliability and reproducibility. Fifty participants’ DTI data from the MarkVCID consortium were included in this study. Two pipelines by using DSI studio and FSL software were developed for data processing and ALPS index calculation. The ALPS index was obtained by the average of bilateral ALPS index and was used for testing the cross-vendor, inter-rater and test-retest reliability by using R studio software. The ALPS index demonstrated favorable inter-scanner reproducibility (ICC=0.77 to 0.95, P< 0.001), inter-rater reliability (ICC=0.96 to 1, P< 0.001) and test-retest repeatability (ICC=0.89 to 0.95, P< 0.001), offering a potential biomarker for in vivo evaluation of GS function. [ABSTRACT FROM AUTHOR]

Published
2024
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24. In vivo effect of LATE‐NC on integrity of white matter connections to the hippocampus.

Author

Heywood, Ashley, Stocks, Jane, Schneider, Julie A., Arfanakis, Konstantinos, Bennett, David A., Beg, Mirza Faisal, and Wang, Lei

Abstract

INTRODUCTION: TAR DNA‐binding protein 43 (TDP‐43) is a highly prevalent proteinopathy that is involved in neurodegenerative processes, including axonal damage. To date, no ante mortem biomarkers exist for TDP‐43, and few studies have directly assessed its impact on neuroimaging measures utilizing pathologic quantification. METHODS: Ante mortem diffusion‐weighted images were obtained from community‐dwelling older adults. Regression models calculated the relationship between post mortem TDP‐43 burden and ante mortem fractional anisotropy (FA) within each voxel in connection with the hippocampus, controlling for coexisting Alzheimer's disease and demographics. RESULTS: Results revealed a significant negative relationship (false discovery rate [FDR] corrected p <.05) between post mortem TDP‐43 and ante mortem FA in one cluster within the left medial temporal lobe connecting to the parahippocampal cortex, entorhinal cortex, and cingulate, aligning with the ventral subdivision of the cingulum. FA within this cluster was associated with cognition. DISCUSSION: Greater TDP‐43 burden is associated with lower FA within the limbic system, which may contribute to impairment in learning and memory. Highlights: Post mortem TDP‐43 pathological burden is associated with reduced ante mortem fractional anisotropy.Reduced FA located in the parahippocampal portion of the cingulum.FA in this area was associated with reduced episodic and semantic memory.FA in this area was associated with increased inward hippocampal surface deformation. [ABSTRACT FROM AUTHOR]

Published
2024
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35. Genetic architecture of subcortical brain structures in 38,851 individuals

Author

Satizabal, Claudia L., Adams, Hieab H. H., Hibar, Derrek P., White, Charles C., Knol, Maria J., Stein, Jason L., Scholz, Markus, Sargurupremraj, Muralidharan, Jahanshad, Neda, Roshchupkin, Gennady V., Smith, Albert V., Bis, Joshua C., Jian, Xueqiu, Luciano, Michelle, Hofer, Edith, Teumer, Alexander, van der Lee, Sven J., Yang, Jingyun, Yanek, Lisa R., Lee, Tom V., Li, Shuo, Hu, Yanhui, Koh, Jia Yu, Eicher, John D., Desrivières, Sylvane, Arias-Vasquez, Alejandro, Chauhan, Ganesh, Athanasiu, Lavinia, Rentería, Miguel E., Kim, Sungeun, Hoehn, David, Armstrong, Nicola J., Chen, Qiang, Holmes, Avram J., den Braber, Anouk, Kloszewska, Iwona, Andersson, Micael, Espeseth, Thomas, Grimm, Oliver, Abramovic, Lucija, Alhusaini, Saud, Milaneschi, Yuri, Papmeyer, Martina, Axelsson, Tomas, Ehrlich, Stefan, Roiz-Santiañez, Roberto, Kraemer, Bernd, Håberg, Asta K., Jones, Hannah J., Pike, G. Bruce, Stein, Dan J., Stevens, Allison, Bralten, Janita, Vernooij, Meike W., Harris, Tamara B., Filippi, Irina, Witte, A. Veronica, Guadalupe, Tulio, Wittfeld, Katharina, Mosley, Thomas H., Becker, James T., Doan, Nhat Trung, Hagenaars, Saskia P., Saba, Yasaman, Cuellar-Partida, Gabriel, Amin, Najaf, Hilal, Saima, Nho, Kwangsik, Mirza-Schreiber, Nazanin, Arfanakis, Konstantinos, Becker, Diane M., Ames, David, Goldman, Aaron L., Lee, Phil H., Boomsma, Dorret I., Lovestone, Simon, Giddaluru, Sudheer, Le Hellard, Stephanie, Mattheisen, Manuel, Bohlken, Marc M., Kasperaviciute, Dalia, Schmaal, Lianne, Lawrie, Stephen M., Agartz, Ingrid, Walton, Esther, Tordesillas-Gutierrez, Diana, Davies, Gareth E., Shin, Jean, Ipser, Jonathan C., Vinke, Louis N., Hoogman, Martine, Jia, Tianye, Burkhardt, Ralph, Klein, Marieke, Crivello, Fabrice, Janowitz, Deborah, Carmichael, Owen, Haukvik, Unn K., Aribisala, Benjamin S., Schmidt, Helena, Strike, Lachlan T., Cheng, Ching-Yu, Risacher, Shannon L., Pütz, Benno, Fleischman, Debra A., Assareh, Amelia A., Mattay, Venkata S., Buckner, Randy L., Mecocci, Patrizia, Dale, Anders M., Cichon, Sven, Boks, Marco P., Matarin, Mar, Penninx, Brenda W. J. H., Calhoun, Vince D., Chakravarty, M. Mallar, Marquand, Andre F., Macare, Christine, Kharabian Masouleh, Shahrzad, Oosterlaan, Jaap, Amouyel, Philippe, Hegenscheid, Katrin, Rotter, Jerome I., Schork, Andrew J., Liewald, David C. M., de Zubicaray, Greig I., Wong, Tien Yin, Shen, Li, Sämann, Philipp G., Brodaty, Henry, Roffman, Joshua L., de Geus, Eco J. C., Tsolaki, Magda, Erk, Susanne, van Eijk, Kristel R., Cavalleri, Gianpiero L., van der Wee, Nic J. A., McIntosh, Andrew M., Gollub, Randy L., Bulayeva, Kazima B., Bernard, Manon, Richards, Jennifer S., Himali, Jayandra J., Loeffler, Markus, Rommelse, Nanda, Hoffmann, Wolfgang, Westlye, Lars T., Valdés Hernández, Maria C., Hansell, Narelle K., van Erp, Theo G. M., Wolf, Christiane, Kwok, John B. J., Vellas, Bruno, Heinz, Andreas, Olde Loohuis, Loes M., Delanty, Norman, Ho, Beng-Choon, Ching, Christopher R. K., Shumskaya, Elena, Singh, Baljeet, Hofman, Albert, van der Meer, Dennis, Homuth, Georg, Psaty, Bruce M., Bastin, Mark E., Montgomery, Grant W., Foroud, Tatiana M., Reppermund, Simone, Hottenga, Jouke-Jan, Simmons, Andrew, Meyer-Lindenberg, Andreas, Cahn, Wiepke, Whelan, Christopher D., van Donkelaar, Marjolein M. J., Yang, Qiong, Hosten, Norbert, Green, Robert C, Thalamuthu, Anbupalam, Mohnke, Sebastian, Hulshoff Pol, Hilleke E., Lin, Honghuang, Jack, Jr, Clifford R., Schofield, Peter R., Mühleisen, Thomas W., Maillard, Pauline, Potkin, Steven G., Wen, Wei, Fletcher, Evan, Toga, Arthur W., Gruber, Oliver, Huentelman, Matthew, Davey Smith, George, Launer, Lenore J., Nyberg, Lars, Jönsson, Erik G., Crespo-Facorro, Benedicto, Koen, Nastassja, Greve, Douglas N., Uitterlinden, André G., Weinberger, Daniel R., Steen, Vidar M., Fedko, Iryna O., Groenewold, Nynke A., Niessen, Wiro J., Toro, Roberto, Tzourio, Christophe, Longstreth, Jr, William T., Ikram, M. Kamran, Smoller, Jordan W., van Tol, Marie-Jose, Sussmann, Jessika E., Paus, Tomas, Lemaître, Hervé, Schroeter, Matthias L., Mazoyer, Bernard, Andreassen, Ole A., Holsboer, Florian, Depondt, Chantal, Veltman, Dick J., Turner, Jessica A., Pausova, Zdenka, Schumann, Gunter, van Rooij, Daan, Djurovic, Srdjan, Deary, Ian J., McMahon, Katie L., Müller-Myhsok, Bertram, Brouwer, Rachel M., Soininen, Hilkka, Pandolfo, Massimo, Wassink, Thomas H., Cheung, Joshua W., Wolfers, Thomas, Martinot, Jean-Luc, Zwiers, Marcel P., Nauck, Matthias, Melle, Ingrid, Martin, Nicholas G., Kanai, Ryota, Westman, Eric, Kahn, René S., Sisodiya, Sanjay M., White, Tonya, Saremi, Arvin, van Bokhoven, Hans, Brunner, Han G., Völzke, Henry, Wright, Margaret J., van ‘t Ent, Dennis, Nöthen, Markus M., Ophoff, Roel A., Buitelaar, Jan K., Fernández, Guillén, Sachdev, Perminder S., Rietschel, Marcella, van Haren, Neeltje E. M., Fisher, Simon E., Beiser, Alexa S., Francks, Clyde, Saykin, Andrew J., Mather, Karen A., Romanczuk-Seiferth, Nina, Hartman, Catharina A., DeStefano, Anita L., Heslenfeld, Dirk J., Weiner, Michael W., Walter, Henrik, Hoekstra, Pieter J., Nyquist, Paul A., Franke, Barbara, Bennett, David A., Grabe, Hans J., Johnson, Andrew D., Chen, Christopher, van Duijn, Cornelia M., Lopez, Oscar L., Fornage, Myriam, Wardlaw, Joanna M., Schmidt, Reinhold, DeCarli, Charles, De Jager, Philip L., Villringer, Arno, Debette, Stéphanie, Gudnason, Vilmundur, Medland, Sarah E., Shulman, Joshua M., Thompson, Paul M., Seshadri, Sudha, and Ikram, M. Arfan

Published
2019
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38. Development and comprehensive evaluation of high‐resolution 0.5 mm isotropic T2‐weighted, PD‐weighted, T2 map and FLAIR templates of the MIITRA atlas.

Author

Ridwan, Abdur Raquib, Niaz, Mohammad Rakeen, Wu, Yingjuan, Zhang, Shengwei, Bennett, David A. A, and Arfanakis, Konstantinos

Abstract

Background: Voxel‐wise, disease‐monitoring and other MRI investigations involving T2‐weighted(T2w), PD‐weighted(PDw), T2 map and FLAIR templates typically utilize young adult templates such as those of the ICBM atlas. Moreover, a comprehensive assessment of how such available standardized templates perform on aging population has not yet been performed. Here, a high‐resolution older‐adult population based T2w, PDw T2 map and FLAIR templates of the MIITRA atlas was developed using theories of super‐resolution and sparse‐representation and compared to other available standardized templates in terms of image quality, spatial normalization accuracy and representativeness of the older adult brain. Method: T1‐weighted MPRAGE of isotropic 1mm resolution, five spin‐echo(0.5×0.5×0.5 mm3,TE = 20,40,60,80,100ms) and FLAIR data (0.5×0.5×4 mm3) were collected on 3T MRI scanners for 400 non‐demented older adults (50% male; 65‐95 years of age, 54% white and 43% black) participating in the construction of the MIITRA atlas. The subject T2 maps and PD‐weighted data were computed by fitting the T2 decay equation. The template construction technique involved upsampling the images to 0.5×0.5×0.5 mm3 using non‐local upsampling, and converting the T2‐weighted(TE = 60ms) to synthetic T1‐weighted, followed by linear registration to upsampled T1‐weighted data using ANTs. Next, the resulting transformations concatenated with the combined iterative T1w and DTI driven MIITRA atlas deformations were used to forward map each participant to exact physical locations in the MIITRA space. Finally, sparse representation data fusion technique was utilized on the transformed signals to construct the templates at isotropic 0.5mm resolution (Figure.1). MIITRA third echo T2‐weighted and FLAIR template was compared to available standardized templates (Figure. 2) in terms of inter‐subject spatial normalization accuracy when used for spatial normalization of 400 ADNI T2‐weighted and FLAIR participants respectively. Result: The T2‐weighted and FLAIR templates of the MIITRA atlas exhibited higher image sharpness exemplified by higher spatial frequency content of the normalized power spectra(Figure. 2). MIITRA templates demonstrated higher inter‐subject spatial normalization accuracy and required the least deformations for spatial normalization of ADNI data(Figure. 3) Conclusion: The new T2w, PDw, and FLAIR templates of the MIITRA atlas exhibited superior image quality, required lower deformations, facilitating higher spatial normalization accuracy for use in studies on older adults such as the ADNI datasets. [ABSTRACT FROM AUTHOR]

Published
2023
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39. MIITRA atlas: high resolution FOD template of the older adult brain.

Author

Wu, Yingjuan, Ridwan, Abdur Raquib, Niaz, Mohammad Rakeen, Bennett, David A. A, and Arfanakis, Konstantinos

Abstract

Background: High quality fiber orientation distribution (FOD) template of the older adult brain facilitates white matter studies in older adults. This work compared several methods to construct an FOD template of the older adult brain in the space of the MIITRA atlas(Wu et al.,2022). Method: T1w and DWI data from 400 non‐demented older adults (50% male;64.9‐98.9 yrs;54% white,43% black)(Bennett et al.,2018;Barnes et al.,2012) participating in the construction of the MIITRA atlas were used. Method 1: FOD‐based single modality registration(cost function:mean squared difference)(MRtrix3). Method 2: The nonlinear transformations generated from MIITRA T1w and DTI template construction were applied to the FODs(Wu et al.,2021). Method 3: Multichannel registration based on T1w, T2w, FA and MD information with equal weights(cost function:cross‐correlation)(ANTs). Method 4: Multichannel registration based on T1w and FOD information with equal weights(cost function:cross‐correlation)(MRtrix3). Method 5: Multichannel registration based on T1w, FA and FOD information with weights of 4,3,3 respectively(cost function:cross‐correlation)(MRtrix3). Method 6: Same as Method 5 followed by FOD registration performed on the FOD data that were already transformed by Method 5(cost function:cross‐correlation)(MRtrix3). The FOD templates generated with different methods were compared by visual inspection, image sharpness of the total apparent fiber density (AFD) map, precision of spatial normalization of FOD data used in template construction, and spatial matching with the existing MIITRA T1w and DTI templates. Result: The FOD templates generated with Methods 2, 3 and 6 exhibited higher image sharpness(Fig.1A). Fiber crossings were more clearly defined in the FOD templates generated with Methods 1,4,5,6(Fig.1B). Method 6 allowed higher ACC and lower MSD of spatially normalized FOD data, indicating higher precision in spatial normalization(Fig.2A,B). Method 2 provided the highest spatial matching with the existing MIITRA templates, followed closely by Methods 4,5,6(Fig.2C,D). Overall, the FOD template generated with Method 6 achieved high image quality, was constructed based on precisely matched FOD data, and exhibited high spatial matching to the existing MIITRA templates(Fig.3). Conclusion: An FOD template of the older adult brain was constructed for the MIITRA atlas. The new template exhibits high image quality, is constructed based on precisely matched FOD data, and exhibits high spatial matching to other existing MIITRA templates. [ABSTRACT FROM AUTHOR]

Published
2023
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40. Cross vendor test‐retest validation of diffusion tensor analysis along the perivascular space (DTI‐ALPS) method for evaluating glymphatic system function in vascular cognitive impairment and dementia (VCID).

Author

Liu, Xiaodan, Barisano, Giuseppe, Shao, Xingfeng, Jann, Kay, Ringman, John M, Lu, Hanzhang, Arfanakis, Konstantinos, Arvind, Caprihan, Decarli, Charles, Gold, Brian T., Maillard, Pauline, Satizabal, Clandia L., Fadaee, Elyas, Habes, Mohamad, Stables, Lara, Singh, Herpreet, Fischl, Bruce, van der Kouwe, Andre J., Schwab, Kristin, and Helmer, Karl G.

Abstract

Background: Glymphatic system (GS) is a recently discovered brain‐wide perivascular fluid transport system in the cerebral nervous system (CNS)(Benveniste H et al., 2019) The impairment of glymphatic transport has been demonstrated to be associated with several neurological diseases, in particular the vascular cognitive impairment and dementia (VCID)(Tang J et al., 2022). The diffusion tensor analysis along the perivascular space (DTI‐ALPS) was proposed to non‐invasively evaluate the GS clearance dysfunction which has been used to investigate the GS in various pathologies(Taoka T et al., 2017, Hsu JL et al., 2022). However, studies on the cross‐vendor and test‐retest reliability of DTI‐ALPS method are lacking. The current study aimed to perform cross‐vendor, inter‐rater and test‐retest validations of DTI‐ALPS method by using a cohort from the MarkVCID consortium. Method: Fifty participants' DTI data from the MarkVCID consortium (consists of 7 sites) were included in this study: 15 participants were scanned on four MRI scanners; 35 participants underwent two MR scans within 14 days. The DTI data were acquired used a single shell, b = 1000s/mm2, 40‐direction with a voxel size of 2.02.02.0mm3 and six b = 0 s/mm2 on 3T MR scanners from seven sites, including two Siemens systems, one Philips system and one GE system. Two pipelines by using DSI studio and FSL software were developed for data processing and ALPS index calculation (Figure 1). The mean ALPS (mALPS) index was obtained by the average of bilateral ALPS index and was used for testing the inter‐rater, cross‐vendor and test‐retest reliability. The association between mALPS index and Montreal Cognitive assessment (MoCA) scores were evaluated using a general linear model with age and gender as covariate. Result: The Bland‐Altman plot and scatterplot illustrated the validation results of the mALPS index analyzed using DSI studio and FSL pipelines (Figure 2). The mALPS index demonstrated favorable inter‐scanner reproducibility (ICC = 0.77 to 0.95, P< 0.001), inter‐rater reliability (ICC = 0.96 to 1, P< 0.001) and test‐retest repeatability (ICC = 0.89 to 0.95, P< 0.001). A significantly positive correlation was observed between mALPS index and MoCA scores (r = 0.502, P< 0.01) (Figure 3). Conclusion: The mALPS index offers a robust potential biomarker for evaluating GS clearance function in VCID. [ABSTRACT FROM AUTHOR]

Published
2023
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41. Interoperability of the MIITRA atlas with complementary atlases: development of a comprehensive array of gray matter labels.

Author

Niaz, Mohammad Rakeen, Ridwan, Abdur Raquib, Wu, Yingjuan, Zhang, Shengwei, Bennett, David A. A, and Arfanakis, Konstantinos

Abstract

Background: In order to enhance the functionality of the MIITRA atlas and its interoperability with complementary atlases, a comprehensive set of gyral‐based, cytoarchitecture‐based, and functional connectivity‐based gray matter labels were constructed in MIITRA space. Method: T1w images from the 400 older‐adults included in the construction of MIITRA atlas were nonlinearly registered using ANTs SyN to the MNI152 6thgen,MNI Colin, and the ICBM2009c templates, and volumetric labels from Harvard‐Oxford,Julich,AAL3,Buckner,CoBrALab,Hammersmith and Princeton Visual atlases were warped to the space of each participant. The ANTs‐derived transformations used to build the MIITRA T1w template were used to map the corresponding gray matter labels from raw space to exact physical locations in the final MIITRA space following a multi‐atlas correction scheme to correct for residual misregistration. T1w images from a separate group of 100 older‐adults for evaluation were nonlinearly normalized to the MIITRA template and the inverse transformation was applied to the gray matter labels to transform them to each individual's space. The T1w image of each individual was nonlinearly registered to every other individual and the labels from the 99 other older‐adults were transformed to each individual. Pair‐wise Jaccard index for each label was calculated in every individual's native space. The same procedure was followed for the labels obtained directly from the respective source templates. Result: The overlap was higher for the AAL3 labels obtained from MIITRA with an average pair‐wise Jaccard index of 0.59 and standard deviation of 0.08, compared to 0.55±0.1 for the AAL3(Fig1A) labels obtained from the MNI Colin template. The pair‐wise Jaccard index for the Julich(Fig1C) and CoBrALab labels(Fig2A) was 0.54±0.13 and 0.75±0.17 from MIITRA and, 0.53±0.14 and 0.74±0.17 from ICBM2009c. For the Harvard‐Oxford(Fig2B), Buckner(Fig2C), Hammersmith(Fig1B) and Princeton Visual(Fig2D), the pairwise Jaccard was 0.68±0.14, 0.61±0.07, 0.71±0.10 and 0.35±0.06 respectively from MIITRA and 0.66±0.11, 0.61±0.08, 0.67±0.11 and 0.32±0.08 respectively from MNI152 template. Heat maps representing the Jaccard‐index for each template are shown in Fig3. Conclusion: Gray matter labels from MIITRA showed higher pair‐wise overlap suggesting that labels from MIITRA space allows more consistent segmentation of the gray matter of the older‐adult brain compared to the labels obtained from templates constructed using younger or middle‐aged data. [ABSTRACT FROM AUTHOR]

Published
2023
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42. Cerebral amyloid angiopathy is associated with higher gray matter regional R2 relaxation rate: An ex‐vivo MRI and pathology study.

Author

Yasar, Md Tahmid, Evia, Arnold M, Bennett, David A. A, Schneider, Julie A, and Arfanakis, Konstantinos

Abstract

Background: Cerebral amyloid angiopathy (CAA) is characterized by accumulation of amyloid‐β (Aβ) protein in the walls of cortical and meningeal small vessels. CAA is common in older adults. It has been linked to intracerebral hemorrhage and cognitive decline. In this study, the association of CAA with the transverse relaxation rate R2 values was investigated in gray matter regions from a large number of community‐based older adults. Method: Cerebral hemispheres from 802 older adults participating in four cohort studies of aging, the Rush Memory and Aging Project, the Minority Aging Research Study, the Religious Orders Study, and the Clinical Core of the Rush Alzheimer's Disease Research Center (Fig. 1a) were included in this work. All hemispheres were imaged ex‐vivo using 3T MRI scanners. R2 maps were generated from multi‐echo spin‐echo images. Gray matter was segmented into 34 cortical and 8 subcortical regions. Median R2 values were obtained from each region. Following ex‐vivo MRI, all hemispheres underwent detailed neuropathologic assessment (Fig. 1b). Evaluated neuropathologies included: CAA, Aβ plaques, neurofibrillary tangles, gross infarcts, microinfarcts, TDP‐43 pathology, hippocampal sclerosis, Lewy bodies, atherosclerosis, and arteriolosclerosis. Multiple linear regression was conducted in each segmented gray matter region separately to test the association of the corresponding median R2 value with the global CAA score, controlling for all other neuropathologies, age at death, sex, education, postmortem interval to fixation and to imaging, and scanners. False discovery rate (FDR) was used to correct for multiple comparisons. Statistical significance was set at p<0.05. Result: A significant positive association of median R2 with CAA pathology was found in several cortical regions of the temporal and frontal lobes as well as in subcortical structures (Fig. 2,3). No gray matter region showed lower median R2 for higher CAA score. Furthermore, we obtained similar findings when also controlling in the linear regression models for normalized regional volume and for clinical variables such as history of hypertension, diabetes, smoking, blood pressure levels, and the presence of the APOE‐ε4 allele. Conclusion: This investigation showed that CAA is independently associated with elongated R2 in cortical regions of the temporal and frontal lobes as well as in subcortical structures. [ABSTRACT FROM AUTHOR]

Published
2023
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43. Graph Theory Analysis of Structural Connectivity in Limbic‐predominant Age‐related TDP‐43 Encephalopathy Neuropathological Change (LATE‐NC).

Author

Tazwar, Mahir, Evia, Arnold M, Ridwan, Abdur Raquib, Bennett, David A. A, Schneider, Julie A, and Arfanakis, Konstantinos

Abstract

Background: The anatomical distribution of limbic‐predominant age‐related TDP‐43 encephalopathy neuropathological change (LATE‐NC) typically involves the amygdala, hippocampus, and other subcortical, temporal and frontal lobe regions. But its impact on the structural integrity of this network of regions remains unknown. In this study, we tested the hypothesis that LATE‐NC is associated with abnormalities in graph theoretic measures of structural connectivity in the network of regions known to be involved in LATE‐NC. Method: This study included 148 deceased older adults participating in Rush Memory and Aging Project and Religious Orders Study (Fig.1A). Ex‐vivo diffusion tensor imaging (DTI) scans were acquired on 3T scanners, followed by detailed neuropathologic examination by a board‐certified neuropathologist (Fig.1B). Fractional anisotropy (FA) maps derived from DTI scans were used to define region‐to‐region structural connectivity in a network of 19 regions known to be involved in LATE‐NC using graph theory‐based network measures (Fig.2). General linear models were used to investigate the association of global and local graph measures with LATE‐NC stages, controlling for other neuropathologies (Alzheimer's disease, Lewy bodies, arteriolosclerosis, atherosclerosis, cerebral amyloid angiopathy, gross and microscopic infarcts), demographics (age at death, sex, education), total white matter hyperintensity volume, postmortem intervals and scanner variables. Statistical significance was set at p<0.05. Result: Linear regression revealed that greater LATE‐NC stage was associated with increased characteristic path length and with lower values of the remaining global network measures (p<0.05) (Fig.3A). LATE‐NC was also associated with lower local efficiency, increased path length, lower nodal strength, and lower clustering coefficient in 74%, 79%, 32%, and 63% of the nodes, respectively (p<0.05) (Fig.3B). Finally, LATE‐NC was associated with both greater (in 21% of nodes) and lower (in 16% of nodes) eigenvector centrality, and with both greater and lower betweenness centrality in 21% of nodes, respectively (p<0.05) (Fig.3B). Conclusion: Using graph theory and a hypothesis‐driven approach, we found significant degradation of structural integrity in white matter of the network of regions affected by LATE‐NC. These findings may shed light on the effects of LATE‐NC on brain connectivity, and in combination with other imaging and clinical information, may aid towards the development of tools for in‐vivo detection of this devastating neuropathology. [ABSTRACT FROM AUTHOR]

Published
2023
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44. Development of the MIITRA QSM template: a high‐resolution magnetic susceptibility template of the older adult brain in the MIITRA atlas space.

Author

Abid, Rasheed, Ridwan, Abdur Raquib, Wu, Yingjuan, Niaz, Mohammad Rakeen, Zhang, Shengwei, Evia, Arnold M, Bennett, David A. A, and Arfanakis, Konstantinos

Abstract

Background: A QSM template of the older‐adult brain is not yet available. This study constructed a high resolution QSM template of the older‐adult brain for the MITRA atlas using data from a large, diverse, community cohort of non‐demented older‐adults. Method: Magnetic susceptibility maps were generated for the 400 older‐adult paricipants used in the construction of MIITRA using the Morphology Enabled Dipole Inversion(MEDI) on the 3D 5‐echo GRE data(0.7×0.7×1.3mm3) and upsampled to 0.7×0.7×0.65mm3 using nonlocal upsampling. The first GRE echo of each participant were N4 bias field corrected, then upsampled to 0.7×0.7×0.65mm3 using non‐local upsampling and converted to synthetic T1w images using mri_synthsr. The original 3D T1w MPRAGE(1×1×1mm3) data were upsampled to 0.5×0.5×0.5mm3. The synthetic T1w images were linearly registered to the upsampled T1w data and the resulting transformations were used to forward‐map magnetic susceptibility values from the native space of each participant to exact physical locations in MIITRA space. A sparse representation based data‐fusion approach was used on the transformed signals to generate the final 0.5×0.5×0.5mm3 resolution template, denoted as MIITRA_QSM(Fig.1). Since no other magnetic susceptibility template of the older‐adult brain is currently available, we compared MIITRA_QSM to a young adult template named MuSus‐100(1×1×1mm3,100 participants,mean age 24 years) in terms of image quality and magnetic susceptibility properties. Result: Visual showed that MIITRA_QSM template includes fine details, has the expected QSM contrast, highest values in subcortical, brainstem, and cerebellar structures known for their high magnetic susceptibility(especially in older adults), lower values in the white compared to gray matter, and higher values in white matter of the frontal lobe compared to parietal and occipital lobes. When compared to MuSus‐100, MIITRA_QSM showed better delineation of cortical structures and higher image sharpness(Fig.2), as well as higher magnetic susceptibility values in most subcortical brain structures(Fig.3A), Cortical structures from the two templates exhibited more similar magnetic susceptibility values(Fig.3B). Conclusion: Magnetic susceptibility values in specific subcortical, brainstem and cerebellar structures are higher in the MIITRA_QSM template compared to a young adult template, probably due to increased metal deposition in these structures with aging. The new template is expected to greatly enhance the accuracy of voxel‐wise and atlas‐based QSM studies on older‐adults. [ABSTRACT FROM AUTHOR]

Published
2023
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49. A genome-wide association study identifies genetic loci associated with specific lobar brain volumes

Author

van der Lee, Sven J., Knol, Maria J., Chauhan, Ganesh, Satizabal, Claudia L., Smith, Albert Vernon, Hofer, Edith, Bis, Joshua C., Hibar, Derrek P., Hilal, Saima, van den Akker, Erik B., Arfanakis, Konstantinos, Bernard, Manon, Yanek, Lisa R., Amin, Najaf, Crivello, Fabrice, Cheung, Josh W., Harris, Tamara B., Saba, Yasaman, Lopez, Oscar L., Li, Shuo, van der Grond, Jeroen, Yu, Lei, Paus, Tomas, Roshchupkin, Gennady V., Amouyel, Philippe, Jahanshad, Neda, Taylor, Kent D., Yang, Qiong, Mathias, Rasika A., Boehringer, Stefan, Mazoyer, Bernard, Rice, Ken, Cheng, Ching Yu, Maillard, Pauline, van Heemst, Diana, Wong, Tien Yin, Niessen, Wiro J., Beiser, Alexa S., Beekman, Marian, Zhao, Wanting, Nyquist, Paul A., Chen, Christopher, Launer, Lenore J., Psaty, Bruce M., Ikram, M. Kamran, Vernooij, Meike W., Schmidt, Helena, Pausova, Zdenka, Becker, Diane M., De Jager, Philip L., Thompson, Paul M., van Duijn, Cornelia M., Bennett, David A., Slagboom, P. Eline, Schmidt, Reinhold, Longstreth, W. T., Ikram, M. Arfan, Seshadri, Sudha, Debette, Stéphanie, Gudnason, Vilmundur, Adams, Hieab H. H., and DeCarli, Charles

Published
2019
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50. Multi-Site Cross-Site Inter-Rater and Test-Retest Reliability and Construct Validity of the MarkVCID White Matter Hyperintensity Growth and Regression Protocol.

Author

Bahrani, Ahmed A., Abner, Erin L., DeCarli, Charles S., Barber, Justin M., Sutton, Abigail C., Maillard, Pauline, Sandoval, Francisco, Arfanakis, Konstantinos, Yang, Yung-Chuan, Evia, Arnold M., Schneider, Julie A., Habes, Mohamad, Franklin, Crystal G., Seshadri, Sudha, Satizabal, Claudia L., Caprihan, Arvind, Thompson, Jeffrey F., Rosenberg, Gary A., Wang, Danny J.J., and Jann, Kay

Subjects
WHITE matter (Nerve tissue), STATISTICAL reliability, TEST validity, ALZHEIMER'S disease, VASCULAR dementia, EXPERIMENTAL design
Abstract

Background: White matter hyperintensities (WMH) that occur in the setting of vascular cognitive impairment and dementia (VCID) may be dynamic increasing or decreasing volumes or stable over time. Quantifying such changes may prove useful as a biomarker for clinical trials designed to address vascular cognitive-impairment and dementia and Alzheimer's Disease. Objective: Conducting multi-site cross-site inter-rater and test-retest reliability of the MarkVCID white matter hyperintensity growth and regression protocol. Methods: The NINDS-supported MarkVCID Consortium evaluated a neuroimaging biomarker developed to track WMH change. Test-retest and cross-site inter-rater reliability of the protocol were assessed. Cognitive test scores were analyzed in relation to WMH changes to explore its construct validity. Results: ICC values for test-retest reliability of WMH growth and regression were 0.969 and 0.937 respectively, while for cross-site inter-rater ICC values for WMH growth and regression were 0.995 and 0.990 respectively. Word list long-delay free-recall was negatively associated with WMH growth (p < 0.028) but was not associated with WMH regression. Conclusions: The present data demonstrate robust ICC validity of a WMH growth/regression protocol over a one-year period as measured by cross-site inter-rater and test-retest reliability. These data suggest that this approach may serve an important role in clinical trials of disease-modifying agents for VCID that may preferentially affect WMH growth, stability, or regression. [ABSTRACT FROM AUTHOR]

Published
2023
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