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1. Quantitative Susceptibility Mapping through Model-based Deep Image Prior (MoDIP)

Author

Xiong, Zhuang, Gao, Yang, Liu, Yin, Fazlollahi, Amir, Nestor, Peter, Liu, Feng, and Sun, Hongfu

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

The data-driven approach of supervised learning methods has limited applicability in solving dipole inversion in Quantitative Susceptibility Mapping (QSM) with varying scan parameters across different objects. To address this generalization issue in supervised QSM methods, we propose a novel training-free model-based unsupervised method called MoDIP (Model-based Deep Image Prior). MoDIP comprises a small, untrained network and a Data Fidelity Optimization (DFO) module. The network converges to an interim state, acting as an implicit prior for image regularization, while the optimization process enforces the physical model of QSM dipole inversion. Experimental results demonstrate MoDIP's excellent generalizability in solving QSM dipole inversion across different scan parameters. It exhibits robustness against pathological brain QSM, achieving over 32% accuracy improvement than supervised deep learning and traditional iterative methods. It is also 33% more computationally efficient and runs 4 times faster than conventional DIP-based approaches, enabling 3D high-resolution image reconstruction in under 4.5 minutes.

Published
2023

2. Plasma extracellular vesicle tau and TDP-43 as diagnostic biomarkers in FTD and ALS

Author

Chatterjee, Madhurima, Özdemir, Selcuk, Fritz, Christian, Möbius, Wiebke, Kleineidam, Luca, Mandelkow, Eckhard, Biernat, Jacek, Doğdu, Cem, Peters, Oliver, Cosma, Nicoleta Carmen, Wang, Xiao, Schneider, Luisa-Sophia, Priller, Josef, Spruth, Eike, Kühn, Andrea A., Krause, Patricia, Klockgether, Thomas, Vogt, Ina R., Kimmich, Okka, Spottke, Annika, Hoffmann, Daniel C., Fliessbach, Klaus, Miklitz, Carolin, McCormick, Cornelia, Weydt, Patrick, Falkenburger, Björn, Brandt, Moritz, Guenther, René, Dinter, Elisabeth, Wiltfang, Jens, Hansen, Niels, Bähr, Mathias, Zerr, Inga, Flöel, Agnes, Nestor, Peter J., Düzel, Emrah, Glanz, Wenzel, Incesoy, Enise, Bürger, Katharina, Janowitz, Daniel, Perneczky, Robert, Rauchmann, Boris S., Hopfner, Franziska, Wagemann, Olivia, Levin, Johannes, Teipel, Stefan, Kilimann, Ingo, Goerss, Doreen, Prudlo, Johannes, Gasser, Thomas, Brockmann, Kathrin, Mengel, David, Zimmermann, Milan, Synofzik, Matthis, Wilke, Carlo, Selma-González, Judit, Turon-Sans, Janina, Santos-Santos, Miguel Angel, Alcolea, Daniel, Rubio-Guerra, Sara, Fortea, Juan, Carbayo, Álvaro, Lleó, Alberto, Rojas-García, Ricardo, Illán-Gala, Ignacio, Wagner, Michael, Frommann, Ingo, Roeske, Sandra, Bertram, Lucas, Heneka, Michael T., Brosseron, Frederic, Ramirez, Alfredo, Schmid, Matthias, Beschorner, Rudi, Halle, Annett, Herms, Jochen, Neumann, Manuela, Barthélemy, Nicolas R., Bateman, Randall J., Rizzu, Patrizia, Heutink, Peter, Dols-Icardo, Oriol, Höglinger, Günter, Hermann, Andreas, and Schneider, Anja

Published
2024
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3. Instant tissue field and magnetic susceptibility mapping from MR raw phase using Laplacian enabled deep neural networks

Author

Gao, Yang, Xiong, Zhuang, Fazlollahi, Amir, Nestor, Peter J, Vegh, Viktor, Nasrallah, Fatima, Winter, Craig, Pike, G. Bruce, Crozier, Stuart, Liu, Feng, and Sun, Hongfu

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Physics - Medical Physics
Abstract

Quantitative susceptibility mapping (QSM) is a valuable MRI post-processing technique that quantifies the magnetic susceptibility of body tissue from phase data. However, the traditional QSM reconstruction pipeline involves multiple non-trivial steps, including phase unwrapping, background field removal, and dipole inversion. These intermediate steps not only increase the reconstruction time but amplify noise and errors. This study develops a large-stencil Laplacian preprocessed deep learning-based neural network for near instant quantitative field and susceptibility mapping (i.e., iQFM and iQSM) from raw MR phase data. The proposed iQFM and iQSM methods were compared with established reconstruction pipelines on simulated and in vivo datasets. In addition, experiments on patients with intracranial hemorrhage and multiple sclerosis were also performed to test the generalization of the novel neural networks. The proposed iQFM and iQSM methods yielded comparable results to multi-step methods in healthy subjects while dramatically improving reconstruction accuracies on intracranial hemorrhages with large susceptibilities. The reconstruction time was also substantially shortened from minutes using multi-step methods to only 30 milliseconds using the trained iQFM and iQSM neural networks.

Published
2021
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5. Demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy: an international cohort study and individual participant data meta-analysis

Author

Abdi, Zeinab, Agosta, Federica, Ahmed, Samrah, Alcolea, Daniel, Allen, Isabel Elaine, Allinson, Kieren S.J., Apostolova, Liana G., Arighi, Andrea, Balasa, Mircea, Barkhof, Frederik, Best, John, Boon, Baayla D., Brandt, Katherine D., Brosch, Jared, Burrell, James, Butler, Christopher R., Calandri, Ismael, Caminiti, Silvia Paola, Canu, Elisa, Carrillo, Maria C., Caso, Francesca, Chapleau, Marianne, Chrem Mendez, Patricio, Chu, Min, Crutch, Sebastian, Cordato, Nicholas, Costa, Ana Sofia, Cui, Yue, Dickerson, Bradford, Dickson, Dennis W., Duara, Ranjan, Dubois, Bruno, Eldaief, Mark, Farlow, Martin, Fenoglio, Chiara, Filippi, Massimo, Fliessbach, Klaus, Formaglio, Maïté, Fortea, Juan, Fox, Nick, Foxe, David, Tilikete, Caroline Froment, Frosch, Matthew P., Fumagalli, Giorgio Giulio, Galasko, Douglas, Galimberti, Daniela, Garat, Oscar, Giardinieri, Giulia, Graff-Radford, Jonathan, Graff-Radford, Neill R., Grinberg, Lea, Groot, Colin, Hake, Ann Marie, Hansson, Oskar, Headley, Alison, Hernandez, Micaela, Hochberg, Daisy, Hodges, John R., Hof, Patrick R., Holton, Janice, Hromas, Gabrielle, Gala, Ignacio Illán, Irwin, David J., Jaunmuktane, Zane, Jing, Donglai, Josephs, Keith, Kagerer, Sonja M., Kasuga, Kensaku, Kong, Yu, Kövari, Enikö, Lacombe-Thibault, Mégane, Lleó, Alberto, Laforce, Robert, La Joie, Renaud, Lashley, Tammaryn, Leger, Gabriel, Levin, Netta, Levy, Richard, Liu, Yang, Liu, Li, Lladó Plarrumaní, Albert, Lucente, Diane E., Machulda, Mary M., Magnani, Giuseppe, Magnin, Eloi, Malpetti, Maura, Matthews, Brandy, McGinnis, Scott, Mendez, Mario F., Mesulam, Marsel, Migliaccio, Raffaella, Miklitz, Carolin, Miller, Zachary A., Montembeault, Maxime, Murray, Melissa E., Mundada, Nidhi, Nemes, Sara, Nestor, Peter J., Ocal, Dilek, Ossenkoppele, Rik, Paterson, Ross, Pelak, Victoria, Perani, Daniela, Phillips, Jeffrey, Piguet, Olivier, Pijnenburg, Yolande, Putcha, Deepti, Quimby, Megan, Rabinovici, Gil D., Reetz, Kathrin, Rein, Netaniel, Revesz, Tamas, Rezaii, Neguine, Rodriguez-Porcel, Federico, Rogalski, Emily, Rowe, James B., Ryan, Natalie, Sanchez-Valle, Raquel, Sacchi, Luca, Santos-Santos, Miguel Ángel, Schott, Jonathan M., Seeley, William, Sherman, Janet, Spina, Salvatore, Stomrud, Erik, Sullivan, A. Campbell, Tanner, Jeremy, Tideman, Pontus, Tokutake, Takayoshi, Tondo, Giacomo, Touroutoglou, Alexandra, Tousi, Babak, Vandenberghe, Rik, van der Flier, Wiesje, Walker, Jamie M., Weintraub, Sandra, Whitwell, Jennifer L., Wolk, David A., Wong, Bonnie, Wu, Liyong, Xie, Kexin, Yong, Keir, Apostolova, Liana, Boon, Baayla D C, Grinberg, Lea T, Irwin, David J, Josephs, Keith A, Mendez, Mario F, Mendez, Patricio Chrem, Miller, Zachary A, Murray, Melissa E, Nemes, Sára, Schott, Jonathan M, Sullivan, A Campbell, Walker, Jamie, Whitwell, Jennifer L, Wolk, David A, and Rabinovici, Gil D

Published
2024
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6. A multi-contrast MRI approach to thalamus segmentation

Author

Corona, Veronica, Lellmann, Jan, Nestor, Peter, Schoenlieb, Carola-Bibiane, and Acosta-Cabronero, Julio

Subjects
Computer Science - Computer Vision and Pattern Recognition, Mathematics - Numerical Analysis
Abstract

Thalamic alterations are relevant to many neurological disorders including Alzheimer's disease, Parkinson's disease and multiple sclerosis. Routine interventions to improve symptom severity in movement disorders, for example, often consist of surgery or deep brain stimulation to diencephalic nuclei. Therefore, accurate delineation of grey matter thalamic subregions is of the upmost clinical importance. MRI is highly appropriate for structural segmentation as it provides different views of the anatomy from a single scanning session. Though with several contrasts potentially available, it is also of increasing importance to develop new image segmentation techniques that can operate multi-spectrally. We hereby propose a new segmentation method for use with multi-modality data, which we evaluated for automated segmentation of major thalamic subnuclear groups using T1-, T2*-weighted and quantitative susceptibility mapping (QSM) information. The proposed method consists of four steps: highly iterative image co-registration, manual segmentation on the average training-data template, supervised learning for pattern recognition, and a final convex optimisation step imposing further spatial constraints to refine the solution. This led to solutions in greater agreement with manual segmentation than the standard Morel atlas based approach. Furthermore, we show that the multi-contrast approach boosts segmentation performances. We then investigated whether prior knowledge using the training-template contours could further improve convex segmentation accuracy and robustness, which led to highly precise multi-contrast segmentations in single subjects. This approach can be extended to most 3D imaging data types and any region of interest discernible in single scans or multi-subject templates.

Published
2018

7. Support vector machine learning and diffusion-derived structural networks predict amyloid quantity and cognition in adults with Down's syndrome

Author

Brown, Stephanie S.G., Mak, Elijah, Clare, Isabel, Grigorova, Monika, Beresford-Webb, Jessica, Walpert, Madeline, Jones, Elizabeth, Hong, Young T., Fryer, Tim D., Coles, Jonathan P., Aigbirhio, Franklin I., Tudorascu, Dana, Cohen, Annie, Christian, Bradley T., Handen, Benjamin L., Klunk, William E., Menon, David K., Nestor, Peter J., Holland, Anthony J., and Zaman, Shahid H.

Published
2022
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8. Using cerebrospinal fluid biomarkers to diagnose Alzheimer's disease: an Australian perspective.

Author

Eratne, Dhamidhu, Collins, Steven, Nestor, Peter J., Pond, Dimity, Velakoulis, Dennis, Yates, Mark, and Masters, Colin L.

Subjects
ALZHEIMER'S disease, TAU proteins, CEREBROSPINAL fluid, PEPTIDES, LUMBAR puncture
Abstract

Cerebrospinal fluid (CSF) biomarkers are currently the only clinically validated biofluid diagnostic test for Alzheimer's Disease (AD) available in Australia. Testing of CSF biomarkers via lumbar puncture (LP), including quantification of amyloid-β peptide, total tau protein, and phosphorylated tau, can give insight into underlying pathophysiological changes and provide greater certainty in confirming or excluding the presence of Alzheimer's disease changes compared to standard clinical and radiological assessments. Despite CSF analysis being a safe and cost-effective diagnostic method, the use of CSF biomarkers in the evaluation of potential AD remains limited in Australian clinical practice due to a variety of factors, including regional access challenges, concerns over the perceived invasiveness of LP and a lack of confidence among clinicians in interpreting the results. The advent of disease-modifying therapies as a potential new treatment strategy to reduce the rate of progression in people with AD will drive the demand for early diagnosis of AD. This perspective argues for broader adoption of CSF biomarker testing by providing evidence-based, clinically informed expert guidance on when and why to consider CSF biomarker testing. [ABSTRACT FROM AUTHOR]

Published
2024
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10. Left frontal hub connectivity delays cognitive impairment in autosomal-dominant and sporadic Alzheimer’s disease

Author

Franzmeier, Nicolai, Düzel, Emrah, Jessen, Frank, Buerger, Katharina, Levin, Johannes, Duering, Marco, Dichgans, Martin, Haass, Christian, Suárez-Calvet, Marc, Fagan, Anne M, Paumier, Katrina, Benzinger, Tammie, Masters, Colin L, Morris, John C, Perneczky, Robert, Janowitz, Daniel, Catak, Cihan, Wolfsgruber, Steffen, Wagner, Michael, Teipel, Stefan, Kilimann, Ingo, Ramirez, Alfredo, Rossor, Martin, Jucker, Mathias, Chhatwal, Jasmeer, Spottke, Annika, Boecker, Henning, Brosseron, Frederic, Falkai, Peter, Fliessbach, Klaus, Heneka, Michael T, Laske, Christoph, Nestor, Peter, Peters, Oliver, Fuentes, Manuel, Menne, Felix, Priller, Josef, Spruth, Eike J, Franke, Christiana, Schneider, Anja, Kofler, Barbara, Westerteicher, Christine, Speck, Oliver, Wiltfang, Jens, Bartels, Claudia, Caballero, Miguel Ángel Araque, Metzger, Coraline, Bittner, Daniel, Weiner, Michael, Lee, Jae-Hong, Salloway, Stephen, Danek, Adrian, Goate, Alison, Schofield, Peter R, Bateman, Randall J, and Ewers, Michael

Subjects
Clinical Trials and Supportive Activities, Brain Disorders, Aging, Basic Behavioral and Social Science, Dementia, Neurosciences, Behavioral and Social Science, Acquired Cognitive Impairment, Clinical Research, Alzheimer's Disease, Neurodegenerative, Biomedical Imaging, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Aetiology, 2.1 Biological and endogenous factors, Neurological, Adult, Alzheimer Disease, Amyloid beta-Protein Precursor, Brain Mapping, Cognitive Dysfunction, Female, Frontal Lobe, Functional Laterality, Humans, Imaging, Three-Dimensional, Magnetic Resonance Imaging, Male, Middle Aged, Mutation, Nerve Net, Presenilin-1, Presenilin-2, Alzheimer's disease, cognitive reserve, resting state connectivity, memory, dementia biomarkers, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery
Abstract

Patients with Alzheimer's disease vary in their ability to sustain cognitive abilities in the presence of brain pathology. A major open question is which brain mechanisms may support higher reserve capacity, i.e. relatively high cognitive performance at a given level of Alzheimer's pathology. Higher functional MRI-assessed functional connectivity of a hub in the left frontal cortex is a core candidate brain mechanism underlying reserve as it is associated with education (i.e. a protective factor often associated with higher reserve) and attenuated cognitive impairment in prodromal Alzheimer's disease. However, no study has yet assessed whether such hub connectivity of the left frontal cortex supports reserve throughout the evolution of pathological brain changes in Alzheimer's disease, including the presymptomatic stage when cognitive decline is subtle. To address this research gap, we obtained cross-sectional resting state functional MRI in 74 participants with autosomal dominant Alzheimer's disease, 55 controls from the Dominantly Inherited Alzheimer's Network and 75 amyloid-positive elderly participants, as well as 41 amyloid-negative cognitively normal elderly subjects from the German Center of Neurodegenerative Diseases multicentre study on biomarkers in sporadic Alzheimer's disease. For each participant, global left frontal cortex connectivity was computed as the average resting state functional connectivity between the left frontal cortex (seed) and each voxel in the grey matter. As a marker of disease stage, we applied estimated years from symptom onset in autosomal dominantly inherited Alzheimer's disease and cerebrospinal fluid tau levels in sporadic Alzheimer's disease cases. In both autosomal dominant and sporadic Alzheimer's disease patients, higher levels of left frontal cortex connectivity were correlated with greater education. For autosomal dominant Alzheimer's disease, a significant left frontal cortex connectivity × estimated years of onset interaction was found, indicating slower decline of memory and global cognition at higher levels of connectivity. Similarly, in sporadic amyloid-positive elderly subjects, the effect of tau on cognition was attenuated at higher levels of left frontal cortex connectivity. Polynomial regression analysis showed that the trajectory of cognitive decline was shifted towards a later stage of Alzheimer's disease in patients with higher levels of left frontal cortex connectivity. Together, our findings suggest that higher resilience against the development of cognitive impairment throughout the early stages of Alzheimer's disease is at least partially attributable to higher left frontal cortex-hub connectivity.

Published
2018

11. Performance evaluation of automated white matter hyperintensity segmentation algorithms in a multicenter cohort on cognitive impairment and dementia

Author

Malo Gaubert, Andrea Dell’Orco, Catharina Lange, Antoine Garnier-Crussard, Isabella Zimmermann, Martin Dyrba, Marco Duering, Gabriel Ziegler, Oliver Peters, Lukas Preis, Josef Priller, Eike Jakob Spruth, Anja Schneider, Klaus Fliessbach, Jens Wiltfang, Björn H. Schott, Franziska Maier, Wenzel Glanz, Katharina Buerger, Daniel Janowitz, Robert Perneczky, Boris-Stephan Rauchmann, Stefan Teipel, Ingo Kilimann, Christoph Laske, Matthias H. Munk, Annika Spottke, Nina Roy, Laura Dobisch, Michael Ewers, Peter Dechent, John Dylan Haynes, Klaus Scheffler, Emrah Düzel, Frank Jessen, Miranka Wirth, for the DELCODE study group, Amthauer Holger, Cetindag Arda Can, Cosma Nicoleta Carmen, Diesing Dominik, Ehrlich Marie, Fenski Frederike, Freiesleben Silka Dawn, Fuentes Manuel, Hauser Dietmar, Hujer Nicole, Incesoy Enise Irem, Kainz Christian, Lange Catharina, Lindner Katja, Megges Herlind, Peters Oliver, Preis Lukas, Altenstein Slawek, Lohse Andrea, Franke Christiana, Priller Josef, Spruth Eike, Villar Munoz Irene, Barkhoff Miriam, Boecker Henning, Brosseron Frederic, Daamen Marcel, Engels Tanja, Faber Jennifer, Fließbach Klaus, Frommann Ingo, Grobe-Einsler Marcus, Hennes Guido, Herrmann Gabi, Jost Lorraine, Kalbhen Pascal, Kimmich Okka, Kobeleva Xenia, Kofler Barbara, McCormick Cornelia, Miebach Lisa, Miklitz Carolin, Müller Anna, Oender Demet, Polcher Alexandra, Purrer Veronika, Röske Sandra, Schneider Christine, Schneider Anja, Spottke Annika, Vogt Ina, Wagner Michael, wolfsgruber Steffen, Yilmaz Sagik, Bartels Claudia, Dechent Peter, Hansen Niels, Hassoun Lina, Hirschel Sina, Nuhn Sabine, Pfahlert Ilona, Rausch Lena, Schott Björn, Timäus Charles, Werner Christine, Wiltfang Jens, Zabel Lioba, Zech Heike, Bader Abdelmajid, Baldermann Juan Carlos, Dölle Britta, Drzezga Alexander, Escher Claus, Ghiasi Nasim Roshan, Hardenacke Katja, Jessen Frank, Lützerath Hannah, Maier Franziska, Marquardt Benjamin, Martikke Anja, Meiberth Dix, Petzler Snjezana, Rostamzadeh Ayda, Sannemann Lena, Schild Ann-Katrin, Sorgalla Susanne, Stockter Simone, Thelen Manuela, Tscheuschler Maike, Uhle Franziska, Zeyen Philip, Bittner Daniel, Cardenas-Blanco Arturo, Dobisch Laura, Düzel Emrah, Grieger-Klose Doreen, Hartmann Deike, Metzger Coraline, Nestor Peter, Ruß Christin, Schulze Franziska, Speck Oliver, Yakupov Renat, Ziegler Gabriel, Brauneis Christine, Bürger Katharina, Catak Cihan, Coloma Andrews Lisa, Dichgans Martin, Dörr Angelika, Ertl-Wagner Birgit, Frimmer Daniela, Huber Brigitte, Janowitz Daniel, Kreuzer Max, Markov Eva, Müller Claudia, Rominger Axel, Schmid (ehemals Spreider) Jennifer, Seegerer Anna, Stephan Julia, Zollver Adelgunde, Burow Lena, de Jonge Sylvia, Falkai Peter, Garcia Angarita Natalie, Görlitz Thomas, Gürsel Selim Üstün, Horvath Ildiko, Kurz Carolin, Meisenzahl-Lechner Eva, Perneczky Robert, Utecht Julia, Dyrba Martin, Janecek-Meyer Heike, Kilimann Ingo, Lappe Chris, Lau Esther, Pfaff Henrike, Raum Heike, Sabik Petr, Schmidt Monika, Schulz Heike, Schwarzenboeck Sarah, Teipel Stefan, Weber Marc-Andre, Buchmann Martina, Heger Tanja, Hinderer Petra, Kuder-Buletta Elke, Laske Christoph, Munk Matthias, Mychajliw Christian, Soekadar Surjo, sulzer Patricia, and Trunk Theresia

Subjects
white matter hyperintensities segmentation, evaluation, FLAIR, deep learning, aging, Alzheimer’s disease, Psychiatry, RC435-571
Abstract

BackgroundWhite matter hyperintensities (WMH), a biomarker of small vessel disease, are often found in Alzheimer’s disease (AD) and their advanced detection and quantification can be beneficial for research and clinical applications. To investigate WMH in large-scale multicenter studies on cognitive impairment and AD, appropriate automated WMH segmentation algorithms are required. This study aimed to compare the performance of segmentation tools and provide information on their application in multicenter research.MethodsWe used a pseudo-randomly selected dataset (n = 50) from the DZNE-multicenter observational Longitudinal Cognitive Impairment and Dementia Study (DELCODE) that included 3D fluid-attenuated inversion recovery (FLAIR) images from participants across the cognitive continuum. Performances of top-rated algorithms for automated WMH segmentation [Brain Intensity Abnormality Classification Algorithm (BIANCA), lesion segmentation toolbox (LST), lesion growth algorithm (LGA), LST lesion prediction algorithm (LPA), pgs, and sysu_media] were compared to manual reference segmentation (RS).ResultsAcross tools, segmentation performance was moderate for global WMH volume and number of detected lesions. After retraining on a DELCODE subset, the deep learning algorithm sysu_media showed the highest performances with an average Dice’s coefficient of 0.702 (±0.109 SD) for volume and a mean F1-score of 0.642 (±0.109 SD) for the number of lesions. The intra-class correlation was excellent for all algorithms (>0.9) but BIANCA (0.835). Performance improved with high WMH burden and varied across brain regions.ConclusionTo conclude, the deep learning algorithm, when retrained, performed well in the multicenter context. Nevertheless, the performance was close to traditional methods. We provide methodological recommendations for future studies using automated WMH segmentation to quantify and assess WMH along the continuum of cognitive impairment and AD dementia.

Published
2023
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12. Data-driven classification of patients with primary progressive aphasia

Author

Hoffman, Paul, Sajjadi, Seyed Ahmad, Patterson, Karalyn, and Nestor, Peter J

Subjects
Linguistics, Biological Psychology, Cognitive and Computational Psychology, Language, Communication and Culture, Psychology, Alzheimer's Disease Related Dementias (ADRD), Aging, Acquired Cognitive Impairment, Clinical Research, Frontotemporal Dementia (FTD), Neurodegenerative, Behavioral and Social Science, Aphasia, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Brain Disorders, Dementia, Aetiology, 2.1 Biological and endogenous factors, Aged, Algorithms, Aphasia, Primary Progressive, Case-Control Studies, Cluster Analysis, Cognitive Dysfunction, Female, Humans, Language, Male, Principal Component Analysis, Semantics, Speech, Primary progressive aphasia, Semantic dementia, Non-fluent aphasia, Logopenic aphasia, Frontotemporal dementia, Alzheimer's disease, Alzheimer’s disease, Medical and Health Sciences, Psychology and Cognitive Sciences, Experimental Psychology, Biomedical and clinical sciences, Language, communication and culture
Abstract

Current diagnostic criteria classify primary progressive aphasia into three variants-semantic (sv), nonfluent (nfv) and logopenic (lv) PPA-though the adequacy of this scheme is debated. This study took a data-driven approach, applying k-means clustering to data from 43 PPA patients. The algorithm grouped patients based on similarities in language, semantic and non-linguistic cognitive scores. The optimum solution consisted of three groups. One group, almost exclusively those diagnosed as svPPA, displayed a selective semantic impairment. A second cluster, with impairments to speech production, repetition and syntactic processing, contained a majority of patients with nfvPPA but also some lvPPA patients. The final group exhibited more severe deficits to speech, repetition and syntax as well as semantic and other cognitive deficits. These results suggest that, amongst cases of non-semantic PPA, differentiation mainly reflects overall degree of language/cognitive impairment. The observed patterns were scarcely affected by inclusion/exclusion of non-linguistic cognitive scores.

Published
2017

13. Consensus classification of posterior cortical atrophy

Author

Crutch, Sebastian J, Schott, Jonathan M, Rabinovici, Gil D, Murray, Melissa, Snowden, Julie S, van der Flier, Wiesje M, Dickerson, Bradford C, Vandenberghe, Rik, Ahmed, Samrah, Bak, Thomas H, Boeve, Bradley F, Butler, Christopher, Cappa, Stefano F, Ceccaldi, Mathieu, de Souza, Leonardo Cruz, Dubois, Bruno, Felician, Olivier, Galasko, Douglas, Graff‐Radford, Jonathan, Graff‐Radford, Neill R, Hof, Patrick R, Krolak‐Salmon, Pierre, Lehmann, Manja, Magnin, Eloi, Mendez, Mario F, Nestor, Peter J, Onyike, Chiadi U, Pelak, Victoria S, Pijnenburg, Yolande, Primativo, Silvia, Rossor, Martin N, Ryan, Natalie S, Scheltens, Philip, Shakespeare, Timothy J, González, Aida Suárez, Tang‐Wai, David F, Yong, Keir XX, Carrillo, Maria, Fox, Nick C, and Area, Alzheimer's Association ISTAART Atypical Alzheimer's Disease and Associated Syndromes Professional Interest

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Neurodegenerative, Rare Diseases, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurosciences, Aging, Dementia, Acquired Cognitive Impairment, Brain Disorders, Neurological, Brain, Brain Diseases, Humans, Posterior cortical atrophy, Alzheimer's disease, Clinico-radiological syndrome, Pathophysiology, Biomarker, Alzheimer's Association ISTAART Atypical Alzheimer's Disease and Associated Syndromes Professional Interest Area, Geriatrics, Clinical sciences, Biological psychology
Abstract

IntroductionA classification framework for posterior cortical atrophy (PCA) is proposed to improve the uniformity of definition of the syndrome in a variety of research settings.MethodsConsensus statements about PCA were developed through a detailed literature review, the formation of an international multidisciplinary working party which convened on four occasions, and a Web-based quantitative survey regarding symptom frequency and the conceptualization of PCA.ResultsA three-level classification framework for PCA is described comprising both syndrome- and disease-level descriptions. Classification level 1 (PCA) defines the core clinical, cognitive, and neuroimaging features and exclusion criteria of the clinico-radiological syndrome. Classification level 2 (PCA-pure, PCA-plus) establishes whether, in addition to the core PCA syndrome, the core features of any other neurodegenerative syndromes are present. Classification level 3 (PCA attributable to AD [PCA-AD], Lewy body disease [PCA-LBD], corticobasal degeneration [PCA-CBD], prion disease [PCA-prion]) provides a more formal determination of the underlying cause of the PCA syndrome, based on available pathophysiological biomarker evidence. The issue of additional syndrome-level descriptors is discussed in relation to the challenges of defining stages of syndrome severity and characterizing phenotypic heterogeneity within the PCA spectrum.DiscussionThere was strong agreement regarding the definition of the core clinico-radiological syndrome, meaning that the current consensus statement should be regarded as a refinement, development, and extension of previous single-center PCA criteria rather than any wholesale alteration or redescription of the syndrome. The framework and terminology may facilitate the interpretation of research data across studies, be applicable across a broad range of research scenarios (e.g., behavioral interventions, pharmacological trials), and provide a foundation for future collaborative work.

Published
2017

14. Which ante mortem clinical features predict progressive supranuclear palsy pathology?

Author

Respondek, Gesine, Kurz, Carolin, Arzberger, Thomas, Compta, Yaroslau, Englund, Elisabet, Ferguson, Leslie W, Gelpi, Ellen, Giese, Armin, Irwin, David J, Meissner, Wassilios G, Nilsson, Christer, Pantelyat, Alexander, Rajput, Alex, van Swieten, John C, Troakes, Claire, Josephs, Keith A, Lang, Anthony E, Mollenhauer, Brit, Müller, Ulrich, Whitwell, Jennifer L, Antonini, Angelo, Bhatia, Kailash P, Bordelon, Yvette, Corvol, Jean‐Christophe, Colosimo, Carlo, Dodel, Richard, Grossman, Murray, Kassubek, Jan, Krismer, Florian, Levin, Johannes, Lorenzl, Stefan, Morris, Huw, Nestor, Peter, Oertel, Wolfgang H, Rabinovici, Gil D, Rowe, James B, van Eimeren, Thilo, Wenning, Gregor K, Boxer, Adam, Golbe, Lawrence I, Litvan, Irene, Stamelou, Maria, Höglinger, Günter U, and Group, for the Movement Disorder Society‐Endorsed PSP Study

Subjects
Biomedical and Clinical Sciences, Ophthalmology and Optometry, Frontotemporal Dementia (FTD), Neurodegenerative, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Rare Diseases, Aging, Parkinson's Disease, Dementia, Brain Disorders, Neurosciences, Pick's Disease, Alzheimer's Disease Related Dementias (ADRD), Acquired Cognitive Impairment, 4.2 Evaluation of markers and technologies, 2.1 Biological and endogenous factors, Neurological, Humans, Supranuclear Palsy, Progressive, Progressive supranuclear palsy, clinical features, diagnosis, clinico-pathological series, systematic review, Movement Disorder Society-Endorsed PSP Study Group, Clinical Sciences, Human Movement and Sports Sciences, Neurology & Neurosurgery, Clinical sciences
Abstract

BackgroundProgressive supranuclear palsy (PSP) is a neuropathologically defined disease presenting with a broad spectrum of clinical phenotypes.ObjectiveTo identify clinical features and investigations that predict or exclude PSP pathology during life, aiming at an optimization of the clinical diagnostic criteria for PSP.MethodsWe performed a systematic review of the literature published since 1996 to identify clinical features and investigations that may predict or exclude PSP pathology. We then extracted standardized data from clinical charts of patients with pathologically diagnosed PSP and relevant disease controls and calculated the sensitivity, specificity, and positive predictive value of key clinical features for PSP in this cohort.ResultsOf 4166 articles identified by the database inquiry, 269 met predefined standards. The literature review identified clinical features predictive of PSP, including features of the following 4 functional domains: ocular motor dysfunction, postural instability, akinesia, and cognitive dysfunction. No biomarker or genetic feature was found reliably validated to predict definite PSP. High-quality original natural history data were available from 206 patients with pathologically diagnosed PSP and from 231 pathologically diagnosed disease controls (54 corticobasal degeneration, 51 multiple system atrophy with predominant parkinsonism, 53 Parkinson's disease, 73 behavioral variant frontotemporal dementia). We identified clinical features that predicted PSP pathology, including phenotypes other than Richardson's syndrome, with varying sensitivity and specificity.ConclusionsOur results highlight the clinical variability of PSP and the high prevalence of phenotypes other than Richardson's syndrome. The features of variant phenotypes with high specificity and sensitivity should serve to optimize clinical diagnosis of PSP. © 2017 International Parkinson and Movement Disorder Society.

Published
2017

15. Clinical diagnosis of progressive supranuclear palsy: The movement disorder society criteria.

Author

Höglinger, Günter U, Respondek, Gesine, Stamelou, Maria, Kurz, Carolin, Josephs, Keith A, Lang, Anthony E, Mollenhauer, Brit, Müller, Ulrich, Nilsson, Christer, Whitwell, Jennifer L, Arzberger, Thomas, Englund, Elisabet, Gelpi, Ellen, Giese, Armin, Irwin, David J, Meissner, Wassilios G, Pantelyat, Alexander, Rajput, Alex, van Swieten, John C, Troakes, Claire, Antonini, Angelo, Bhatia, Kailash P, Bordelon, Yvette, Compta, Yaroslau, Corvol, Jean-Christophe, Colosimo, Carlo, Dickson, Dennis W, Dodel, Richard, Ferguson, Leslie, Grossman, Murray, Kassubek, Jan, Krismer, Florian, Levin, Johannes, Lorenzl, Stefan, Morris, Huw R, Nestor, Peter, Oertel, Wolfgang H, Poewe, Werner, Rabinovici, Gil, Rowe, James B, Schellenberg, Gerard D, Seppi, Klaus, van Eimeren, Thilo, Wenning, Gregor K, Boxer, Adam L, Golbe, Lawrence I, Litvan, Irene, and Movement Disorder Society-endorsed PSP Study Group

Subjects
Movement Disorder Society-endorsed PSP Study Group, Humans, Supranuclear Palsy, Progressive, Societies, Medical, Practice Guidelines as Topic, clinical diagnostic criteria, consensus-based, evidence-based, progressive supranuclear palsy, Brain Disorders, Neurosciences, Neurological, Clinical Sciences, Human Movement and Sports Sciences, Neurology & Neurosurgery
Abstract

BackgroundPSP is a neuropathologically defined disease entity. Clinical diagnostic criteria, published in 1996 by the National Institute of Neurological Disorders and Stroke/Society for PSP, have excellent specificity, but their sensitivity is limited for variant PSP syndromes with presentations other than Richardson's syndrome.ObjectiveWe aimed to provide an evidence- and consensus-based revision of the clinical diagnostic criteria for PSP.MethodsWe searched the PubMed, Cochrane, Medline, and PSYCInfo databases for articles published in English since 1996, using postmortem diagnosis or highly specific clinical criteria as the diagnostic standard. Second, we generated retrospective standardized clinical data from patients with autopsy-confirmed PSP and control diseases. On this basis, diagnostic criteria were drafted, optimized in two modified Delphi evaluations, submitted to structured discussions with consensus procedures during a 2-day meeting, and refined in three further Delphi rounds.ResultsDefined clinical, imaging, laboratory, and genetic findings serve as mandatory basic features, mandatory exclusion criteria, or context-dependent exclusion criteria. We identified four functional domains (ocular motor dysfunction, postural instability, akinesia, and cognitive dysfunction) as clinical predictors of PSP. Within each of these domains, we propose three clinical features that contribute different levels of diagnostic certainty. Specific combinations of these features define the diagnostic criteria, stratified by three degrees of diagnostic certainty (probable PSP, possible PSP, and suggestive of PSP). Clinical clues and imaging findings represent supportive features.ConclusionsHere, we present new criteria aimed to optimize early, sensitive, and specific clinical diagnosis of PSP on the basis of currently available evidence. © 2017 International Parkinson and Movement Disorder Society.

Published
2017

16. Demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy: an international cohort study and individual participant data meta-analysis

Author

Chapleau, Marianne, primary, La Joie, Renaud, additional, Yong, Keir, additional, Agosta, Federica, additional, Allen, Isabel Elaine, additional, Apostolova, Liana, additional, Best, John, additional, Boon, Baayla D C, additional, Crutch, Sebastian, additional, Filippi, Massimo, additional, Fumagalli, Giorgio Giulio, additional, Galimberti, Daniela, additional, Graff-Radford, Jonathan, additional, Grinberg, Lea T, additional, Irwin, David J, additional, Josephs, Keith A, additional, Mendez, Mario F, additional, Mendez, Patricio Chrem, additional, Migliaccio, Raffaella, additional, Miller, Zachary A, additional, Montembeault, Maxime, additional, Murray, Melissa E, additional, Nemes, Sára, additional, Pelak, Victoria, additional, Perani, Daniela, additional, Phillips, Jeffrey, additional, Pijnenburg, Yolande, additional, Rogalski, Emily, additional, Schott, Jonathan M, additional, Seeley, William, additional, Sullivan, A Campbell, additional, Spina, Salvatore, additional, Tanner, Jeremy, additional, Walker, Jamie, additional, Whitwell, Jennifer L, additional, Wolk, David A, additional, Ossenkoppele, Rik, additional, Rabinovici, Gil D, additional, Abdi, Zeinab, additional, Ahmed, Samrah, additional, Alcolea, Daniel, additional, Allinson, Kieren S.J., additional, Arighi, Andrea, additional, Balasa, Mircea, additional, Barkhof, Frederik, additional, Brandt, Katherine D., additional, Brosch, Jared, additional, Burrell, James, additional, Butler, Christopher R., additional, Calandri, Ismael, additional, Caminiti, Silvia Paola, additional, Canu, Elisa, additional, Carrillo, Maria C., additional, Caso, Francesca, additional, Chu, Min, additional, Cordato, Nicholas, additional, Costa, Ana Sofia, additional, Cui, Yue, additional, Dickerson, Bradford, additional, Dickson, Dennis W., additional, Duara, Ranjan, additional, Dubois, Bruno, additional, Eldaief, Mark, additional, Farlow, Martin, additional, Feneglio, Chiara, additional, Fliessbach, Klaus, additional, Formaglio, Maïté, additional, Fortea, Juan, additional, Fox, Nick, additional, Foxe, David, additional, Tilikete, Caroline Froment, additional, Frosch, Matthew P., additional, Galasko, Douglas, additional, Garat, Oscar, additional, Giardinieri, Giulia, additional, Graff-Radford, Neill R., additional, Groot, Colin, additional, Hake, Ann Marie, additional, Hansson, Oskar, additional, Headley, Alison, additional, Hernandez, Micaela, additional, Hochberg, Daisy, additional, Hodges, John R., additional, Hof, Patrick R., additional, Holton, Janice, additional, Hromas, Gabrielle, additional, Illán Gala, Ignacio, additional, Jaunmuktane, Zane, additional, Jing, Donglai, additional, Kagerer, Sonja M., additional, Kasuga, Kensaku, additional, Kong, Yu, additional, Kövari, Enikö, additional, Lacombe-Thibault, Mégane, additional, Lleó Plarrumaní, Alberto, additional, Lucente, Diane E., additional, Machulda, Mary M., additional, Magnani, Giuseppe, additional, Magnin, Eloi, additional, Malpetti, Maura, additional, Matthews, Brandy, additional, McGinnis, Scott, additional, Mesulam, Marsel, additional, Miklitz, Carolin, additional, Mundada, Nidhi, additional, Nestor, Peter J., additional, Ocal, Dilek, additional, Paterson, Ross, additional, Piguet, Olivier, additional, Putcha, Deepti, additional, Quimby, Megan, additional, Reetz, Kathrin, additional, Rein, Netaniel, additional, Revesz, Tamas, additional, Rezaii, Neguine, additional, Rodriguez-Porcel, Federico, additional, Rowe, James B., additional, Ryan, Natalie, additional, Sanchez-Valle, Raquel, additional, Sacchi, Luca, additional, Santos-Santos, Miguel Ángel, additional, Sherman, Janet, additional, Stomrud, Erik, additional, Tideman, Pontus, additional, Tokutake, Takayoshi, additional, Tondo, Giacomo, additional, Touroutoglou, Alexandra, additional, Tousi, Babak, additional, Vandenberghe, Rik, additional, van der Flier, Wiesje, additional, Weintraub, Sandra, additional, Wong, Bonnie, additional, Wu, Liyong, additional, and Xie, Kexin, additional

Published
2024
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17. The BDNFVal66Met SNP modulates the association between beta-amyloid and hippocampal disconnection in Alzheimer’s disease

Author

Franzmeier, Nicolai, Ren, Jinyi, Damm, Alexander, Monté-Rubio, Gemma, Boada, Mercè, Ruiz, Agustín, Ramirez, Alfredo, Jessen, Frank, Düzel, Emrah, Rodríguez Gómez, Octavio, Benzinger, Tammie, Goate, Alison, Karch, Celeste M., Fagan, Anne M., McDade, Eric, Buerger, Katharina, Levin, Johannes, Duering, Marco, Dichgans, Martin, Suárez-Calvet, Marc, Haass, Christian, Gordon, Brian A., Lim, Yen Ying, Masters, Colin L., Janowitz, Daniel, Catak, Cihan, Wolfsgruber, Steffen, Wagner, Michael, Milz, Esther, Moreno-Grau, Sonia, Teipel, Stefan, Grothe, Michel J, Kilimann, Ingo, Rossor, Martin, Fox, Nick, Laske, Christoph, Chhatwal, Jasmeer, Falkai, Peter, Perneczky, Robert, Lee, Jae-Hong, Spottke, Annika, Boecker, Henning, Brosseron, Frederic, Fliessbach, Klaus, Heneka, Michael T., Nestor, Peter, Peters, Oliver, Fuentes, Manuel, Menne, Felix, Priller, Josef, Spruth, Eike J., Franke, Christiana, Schneider, Anja, Westerteicher, Christine, Speck, Oliver, Wiltfang, Jens, Bartels, Claudia, Araque Caballero, Miguel Ángel, Metzger, Coraline, Bittner, Daniel, Salloway, Stephen, Danek, Adrian, Hassenstab, Jason, Yakushev, Igor, Schofield, Peter R., Morris, John C., Bateman, Randall J., and Ewers, Michael

Published
2021
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26. CSF total tau levels are associated with hippocampal novelty irrespective of hippocampal volume

Author

Düzel, Emrah, Berron, David, Schütze, Hartmut, Cardenas-Blanco, Arturo, Metzger, Coraline, Betts, Matthew, Ziegler, Gabriel, Chen, Yi, Dobisch, Laura, Bittner, Daniel, Glanz, Wenzel, Reuter, Martin, Spottke, Annika, Rudolph, Janna, Brosseron, Frederic, Buerger, Katharina, Janowitz, Daniel, Fliessbach, Klaus, Heneka, Michael, Laske, Christoph, Buchmann, Martina, Nestor, Peter, Peters, Oliver, Diesing, Dominik, Li, Siyao, Priller, Josef, Spruth, Eike Jakob, Altenstein, Slawek, Ramirez, Alfredo, Schneider, Anja, Kofler, Barbara, Speck, Oliver, Teipel, Stefan, Kilimann, Ingo, Dyrba, Martin, Wiltfang, Jens, Bartels, Claudia, Wolfsgruber, Steffen, Wagner, Michael, and Jessen, Frank

Published
2018
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34. The European DTI Study on Dementia — A multicenter DTI and MRI study on Alzheimer's disease and Mild Cognitive Impairment

Author

Brueggen, Katharina, Grothe, Michel J., Dyrba, Martin, Fellgiebel, Andreas, Fischer, Florian, Filippi, Massimo, Agosta, Federica, Nestor, Peter, Meisenzahl, Eva, Blautzik, Janusch, Frölich, Lutz, Hausner, Lucrezia, Bokde, Arun L.W., Frisoni, Giovanni, Pievani, Michela, Klöppel, Stefan, Prvulovic, David, Barkhof, Frederik, Pouwels, Petra J.W., Schröder, Johannes, Hampel, Harald, Hauenstein, Karlheinz, and Teipel, Stefan

Published
2017
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35. Significance of CSF NfL and tau in ALS

Author

Schreiber, Stefanie, Spotorno, Nicola, Schreiber, Frank, Acosta-Cabronero, Julio, Kaufmann, Jörn, Machts, Judith, Debska-Vielhaber, Grazyna, Garz, Cornelia, Bittner, Daniel, Hensiek, Nathalie, Dengler, Reinhard, Petri, Susanne, Nestor, Peter J., and Vielhaber, Stefan

Published
2018
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37. Diagnostic utility of FDG-PET in the differential diagnosis between different forms of primary progressive aphasia

Author

Bouwman, Femke, Orini, Stefania, Gandolfo, Federica, Altomare, Daniele, Festari, Cristina, Agosta, Federica, Arbizu, Javier, Drzezga, Alexander, Nestor, Peter, Nobili, Flavio, Walker, Zuzana, Morbelli, Silvia, Boccardi, Marina, and for the EANM-EAN Task Force for the Prescription of FDG-PET for Dementing Neurodegenerative Disorders

Published
2018
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38. Diagnostic utility of 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET) in asymptomatic subjects at increased risk for Alzheimer’s disease

Author

Drzezga, Alexander, Altomare, Daniele, Festari, Cristina, Arbizu, Javier, Orini, Stefania, Herholz, Karl, Nestor, Peter, Agosta, Federica, Bouwman, Femke, Nobili, Flavio, Walker, Zuzana, Frisoni, Giovanni Battista, Boccardi, Marina, and for the EANM-EAN Task Force for the Prescription of FDG-PET for Dementing Neurodegenerative Disorders

Published
2018
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41. Clinical utility of FDG-PET for the clinical diagnosis in MCI

Author

Arbizu, Javier, Festari, Cristina, Altomare, Daniele, Walker, Zuzana, Bouwman, Femke, Rivolta, Jasmine, Orini, Stefania, Barthel, Henryk, Agosta, Federica, Drzezga, Alexander, Nestor, Peter, Boccardi, Marina, Frisoni, Giovanni Battista, Nobili, Flavio, and for the EANM-EAN Task Force for the Prescription of FDG-PET for Dementing Neurodegenerative Disorders

Published
2018
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42. Clinical utility of FDG-PET for the differential diagnosis among the main forms of dementia

Author

Nestor, Peter J., Altomare, Daniele, Festari, Cristina, Drzezga, Alexander, Rivolta, Jasmine, Walker, Zuzana, Bouwman, Femke, Orini, Stefania, Law, Ian, Agosta, Federica, Arbizu, Javier, Boccardi, Marina, Nobili, Flavio, Frisoni, Giovanni Battista, and for the EANM-EAN Task Force for the Prescription of FDG-PET for Dementing Neurodegenerative Disorders

Published
2018
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43. Plasma extracellular vesicle Tau isoform ratios and TDP-43 inform about molecular pathology in Frontotemporal Dementia and Amyotrophic Lateral Sclerosis

Author

Chatterjee, Madhurima, primary, Özdemir, Selcuk, additional, Fritz, Christian, additional, Möbius, Wiebke, additional, Kleineidam, Luca, additional, Mandelkow, Eckhard, additional, Biernat, Jacek, additional, Dogdu, Cem, additional, Peters, Oliver, additional, Cosma, Nicoleta Carmen, additional, Wang, Xiao, additional, Schneider, Luisa-Sophia, additional, Priller, Josef, additional, Spruth, Eicke, additional, Kühn, Andrea, additional, Krause, Patricia, additional, Klockgether, Thomas, additional, Vogt, Ina, additional, Kimmich, Okka, additional, Spottke, Annika, additional, Hoffmann, Daniel, additional, Fliessbach, Klaus, additional, Miklitz, Carolin, additional, McCormick, Cornelia, additional, Falkenburger, Björn, additional, Brandt, Moritz, additional, Günther, Rene, additional, Dinter, Elisabeth, additional, Wiltfang, Jens, additional, Hansen, Niels, additional, Baehr, Mathias, additional, Zerr, Inga, additional, Flöel, Agnes, additional, Nestor, Peter, additional, Düzel, Emrah, additional, Glanz, Wenzel, additional, Incesoy, Enise, additional, Buerger, Katharina, additional, Janowitz, Daniel, additional, Perneczky, Robert, additional, Rauchmann, Boris-Stephan, additional, Hopfner, Franziska, additional, Levin, Johannes, additional, Teipel, Stefan, additional, Kilimann, Ingo, additional, Goerss, Doreen, additional, Prudlo, Johannes, additional, Gasser, Thomas, additional, Brockmann, Kathrin, additional, Synofzik, Matthis, additional, Wilke, Carlo, additional, Wagner, Michael, additional, Frommann, Ingo, additional, Roeske, Sandra, additional, Betram, Lucas, additional, Heneka, Michael, additional, Brosseron, Frederic, additional, Ramirez, Alfredo, additional, Schmid, Matthias, additional, Beschorner, Rudi, additional, Halle, Annett, additional, Herms, Jochen, additional, Neuman, Manuela, additional, Barthelemy, Nicolas, additional, Bateman, Randall, additional, Rizzu, Patrizia, additional, Heutink, Peter, additional, Höglinger, Günter, additional, Hermann, Andreas, additional, and Schneider, Anja, additional

Published
2023
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