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2. The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

Author

Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Blair, Ross W., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L, Cohen-Adad, Julien, D'Ambrosio, Sasha, de Hollander, Gilles, de la iglesia-Vayá, María, de la Vega, Alejandro, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Duff, Eugene Paul, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, galassi, anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G, Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Ioanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, Kincses, Balint, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Maumet, Camille, Mazzamuto, Giacomo, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nikolaidis, Aki, Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W, Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Pollonini, Luca, Raamana, Pradeep Reddy, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Spisak, Tamas, Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Welzel, Julius, Wilson, Martin, Yarkoni, Tal, and Gorgolewski, Krzysztof J.

Subjects
Quantitative Biology - Other Quantitative Biology
Abstract

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

Published
2023
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3. Ensembling Voxel-Based and Box-Based Model Predictions for Robust Lesion Detection

Author

Debs, Noëlie, Routier, Alexandre, Abi-Nader, Clément, Marcoux, Arnaud, Bône, Alexandre, Rohé, Marc-Michel, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Wu, Shandong, editor, Shabestari, Behrouz, editor, and Xing, Lei, editor

Published
2024
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4. Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study

Author

Saha, Anindo, Bosma, Joeran S., Twilt, Jasper J., van Ginneken, Bram, Noordman, Constant R., Slootweg, Ivan, Roest, Christian, Fransen, Stefan J., Sunoqrot, Mohammed R.S., Bathen, Tone F., Rouw, Dennis, Immerzeel, Jos, Geerdink, Jeroen, van Run, Chris, Groeneveld, Miriam, Meakin, James, Karagöz, Ahmet, Bône, Alexandre, Routier, Alexandre, Marcoux, Arnaud, Abi-Nader, Clément, Li, Cynthia Xinran, Feng, Dagan, Alis, Deniz, Karaarslan, Ercan, Ahn, Euijoon, Nicolas, François, Sonn, Geoffrey A., Bhattacharya, Indrani, Kim, Jinman, Shi, Jun, Jahanandish, Hassan, An, Hong, Kan, Hongyu, Oksuz, Ilkay, Qiao, Liang, Rohé, Marc-Michel, Yergin, Mert, Khadra, Mohamed, Şeker, Mustafa E., Kartal, Mustafa S., Debs, Noëlie, Fan, Richard E., Saunders, Sara, Soerensen, Simon J.C., Moroianu, Stefania, Vesal, Sulaiman, Yuan, Yuan, Malakoti-Fard, Afsoun, Mačiūnien, Agnė, Kawashima, Akira, de Sousa Machadov, Ana M.M. de M.G., Moreira, Ana Sofia L., Ponsiglione, Andrea, Rappaport, Annelies, Stanzione, Arnaldo, Ciuvasovas, Arturas, Turkbey, Baris, de Keyzer, Bart, Pedersen, Bodil G., Eijlers, Bram, Chen, Christine, Riccardo, Ciabattoni, Courrech Staal, Ewout F.W., Jäderling, Fredrik, Langkilde, Fredrik, Aringhieri, Giacomo, Brembilla, Giorgio, Son, Hannah, Vanderlelij, Hans, Raat, Henricus P.J., Pikūnienė, Ingrida, Macova, Iva, Schoots, Ivo, Caglic, Iztok, Zawaideh, Jeries P., Wallström, Jonas, Bittencourt, Leonardo K., Khurram, Misbah, Choi, Moon H., Takahashi, Naoki, Tan, Nelly, Franco, Paolo N., Gutierrez, Patricia A., Thimansson, Per Erik, Hanus, Pieter, Puech, Philippe, Rau, Philipp R., de Visschere, Pieter, Guillaume, Ramette, Cuocolo, Renato, Falcão, Ricardo O., van Stiphout, Rogier S.A., Girometti, Rossano, Briediene, Ruta, Grigienė, Rūta, Gitau, Samuel, Withey, Samuel, Ghai, Sangeet, Penzkofer, Tobias, Barrett, Tristan, Tammisetti, Varaha S., Løgager, Vibeke B., Černý, Vladimír, Venderink, Wulphert, Law, Yan M., Lee, Young J., Bjartell, Anders, Padhani, Anwar R., Bonekamp, David, Villeirs, Geert, Salomon, Georg, Giannarini, Gianluca, Kalpathy-Cramer, Jayashree, Barentsz, Jelle, Maier-Hein, Klaus H., Rusu, Mirabela, Obuchowski, Nancy A., Rouvière, Olivier, van den Bergh, Roderick, Panebianco, Valeria, Kasivisvanathan, Veeru, Yakar, Derya, Elschot, Mattijs, Veltman, Jeroen, Fütterer, Jurgen J., de Rooij, Maarten, Huisman, Henkjan, Bosma, Joeran S, Twilt, Jasper J, Padhani, Anwar R, Maier-Hein, Klaus H, Obuchowski, Nancy A, and Fütterer, Jurgen J

Published
2024
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5. Clinica: an open source software platform for reproducible clinical neuroscience studies

Author

Routier, Alexandre, Burgos, Ninon, Díaz, Mauricio, Bacci, Michael, Bottani, Simona, El-Rifai, Omar, Fontanella, Sabrina, Gori, Pietro, Guillon, Jérémy, Guyot, Alexis, Hassanaly, Ravi, Jacquemont, Thomas, Lu, Pascal, Marcoux, Arnaud, Moreau, Tristan, Samper-González, Jorge, Teichmann, Marc, Thibeau--Sutre, Elina, Vaillant, Ghislain, Wen, Junhao, Wild, Adam, Habert, Marie-Odile, Durrleman, Stanley, and Colliot, Olivier

Subjects
Quantitative Biology - Quantitative Methods
Abstract

We present Clinica (www.clinica.run), an open-source software platform designed to make clinical neuroscience studies easier and more reproducible. Clinica aims for researchers to i) spend less time on data management and processing, ii) perform reproducible evaluations of their methods, and iii) easily share data and results within their institution and with external collaborators. The core of Clinica is a set of automatic pipelines for processing and analysis of multimodal neuroimaging data (currently, T1-weighted MRI, diffusion MRI and PET data), as well as tools for statistics, machine learning and deep learning. It relies on the brain imaging data structure (BIDS) for the organization of raw neuroimaging datasets and on established tools written by the community to build its pipelines. It also provides converters of public neuroimaging datasets to BIDS (currently ADNI, AIBL, OASIS and NIFD). Processed data include image-valued scalar fields (e.g. tissue probability maps), meshes, surface-based scalar fields (e.g. cortical thickness maps) or scalar outputs (e.g. regional averages). These data follow the ClinicA Processed Structure (CAPS) format which shares the same philosophy as BIDS. Consistent organization of raw and processed neuroimaging files facilitates the execution of single pipelines and of sequences of pipelines, as well as the integration of processed data into statistics or machine learning frameworks. The target audience of Clinica is neuroscientists or clinicians conducting clinical neuroscience studies involving multimodal imaging, and researchers developing advanced machine learning algorithms applied to neuroimaging data.

Published
2021

7. Convolutional Neural Networks for Classification of Alzheimer's Disease: Overview and Reproducible Evaluation

Author

Wen, Junhao, Thibeau-Sutre, Elina, Diaz-Melo, Mauricio, Samper-Gonzalez, Jorge, Routier, Alexandre, Bottani, Simona, Dormont, Didier, Durrleman, Stanley, Burgos, Ninon, and Colliot, Olivier

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing, Statistics - Machine Learning
Abstract

Over 30 papers have proposed to use convolutional neural network (CNN) for AD classification from anatomical MRI. However, the classification performance is difficult to compare across studies due to variations in components such as participant selection, image preprocessing or validation procedure. Moreover, these studies are hardly reproducible because their frameworks are not publicly accessible and because implementation details are lacking. Lastly, some of these papers may report a biased performance due to inadequate or unclear validation or model selection procedures. In the present work, we aim to address these limitations through three main contributions. First, we performed a systematic literature review and found that more than half of the surveyed papers may have suffered from data leakage. Our second contribution is the extension of our open-source framework for classification of AD using CNN and T1-weighted MRI. Finally, we used this framework to rigorously compare different CNN architectures. The data was split into training/validation/test sets at the very beginning and only the training/validation sets were used for model selection. To avoid any overfitting, the test sets were left untouched until the end of the peer-review process. Overall, the different 3D approaches (3D-subject, 3D-ROI, 3D-patch) achieved similar performances while that of the 2D slice approach was lower. Of note, the different CNN approaches did not perform better than a SVM with voxel-based features. The different approaches generalized well to similar populations but not to datasets with different inclusion criteria or demographical characteristics.

Published
2019
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8. Reproducible evaluation of diffusion MRI features for automatic classification of patients with Alzheimers disease

Author

Wen, Junhao, Samper-Gonzalez, Jorge, Bottani, Simona, Routier, Alexandre, Burgos, Ninon, Jacquemont, Thomas, Fontanella, Sabrina, Durrleman, Stanley, Epelbaum, Stephane, Bertrand, Anne, and Colliot, Olivier

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing, Statistics - Machine Learning
Abstract

Diffusion MRI is the modality of choice to study alterations of white matter. In past years, various works have used diffusion MRI for automatic classification of AD. However, classification performance obtained with different approaches is difficult to compare and these studies are also difficult to reproduce. In the present paper, we first extend a previously proposed framework to diffusion MRI data for AD classification. Specifically, we add: conversion of diffusion MRI ADNI data into the BIDS standard and pipelines for diffusion MRI preprocessing and feature extraction. We then apply the framework to compare different components. First, FS has a positive impact on classification results: highest balanced accuracy (BA) improved from 0.76 to 0.82 for task CN vs AD. Secondly, voxel-wise features generally gives better performance than regional features. Fractional anisotropy (FA) and mean diffusivity (MD) provided comparable results for voxel-wise features. Moreover, we observe that the poor performance obtained in tasks involving MCI were potentially caused by the small data samples, rather than by the data imbalance. Furthermore, no extensive classification difference exists for different degree of smoothing and registration methods. Besides, we demonstrate that using non-nested validation of FS leads to unreliable and over-optimistic results: 0.05 up to 0.40 relative increase in BA. Lastly, with proper FR and FS, the performance of diffusion MRI features is comparable to that of T1w MRI. All the code of the framework and the experiments are publicly available: general-purpose tools have been integrated into the Clinica software package (www.clinica.run) and the paper-specific code is available at: https://github.com/aramis-lab/AD-ML., Comment: 51 pages, 5 figure and 6 tables

Published
2018

9. Reproducible evaluation of classification methods in Alzheimer's disease: framework and application to MRI and PET data

Author

Samper-González, Jorge, Burgos, Ninon, Bottani, Simona, Fontanella, Sabrina, Lu, Pascal, Marcoux, Arnaud, Routier, Alexandre, Guillon, Jérémy, Bacci, Michael, Wen, Junhao, Bertrand, Anne, Bertin, Hugo, Habert, Marie-Odile, Durrleman, Stanley, Evgeniou, Theodoros, and Colliot, Olivier

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

A large number of papers have introduced novel machine learning and feature extraction methods for automatic classification of AD. However, they are difficult to reproduce because key components of the validation are often not readily available. These components include selected participants and input data, image preprocessing and cross-validation procedures. The performance of the different approaches is also difficult to compare objectively. In particular, it is often difficult to assess which part of the method provides a real improvement, if any. We propose a framework for reproducible and objective classification experiments in AD using three publicly available datasets (ADNI, AIBL and OASIS). The framework comprises: i) automatic conversion of the three datasets into BIDS format, ii) a modular set of preprocessing pipelines, feature extraction and classification methods, together with an evaluation framework, that provide a baseline for benchmarking the different components. We demonstrate the use of the framework for a large-scale evaluation on 1960 participants using T1 MRI and FDG PET data. In this evaluation, we assess the influence of different modalities, preprocessing, feature types, classifiers, training set sizes and datasets. Performances were in line with the state-of-the-art. FDG PET outperformed T1 MRI for all classification tasks. No difference in performance was found for the use of different atlases, image smoothing, partial volume correction of FDG PET images, or feature type. Linear SVM and L2-logistic regression resulted in similar performance and both outperformed random forests. The classification performance increased along with the number of subjects used for training. Classifiers trained on ADNI generalized well to AIBL and OASIS. All the code of the framework and the experiments is publicly available at: https://gitlab.icm-institute.org/aramislab/AD-ML.

Published
2018
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11. Prediction of the progression of subcortical brain structures in Alzheimer's disease from baseline

Author

Bône, Alexandre, Louis, Maxime, Routier, Alexandre, Samper, Jorge, Bacci, Michael, Charlier, Benjamin, Colliot, Olivier, and Durrleman, Stanley

Subjects
Computer Science - Computer Vision and Pattern Recognition, Statistics - Machine Learning
Abstract

We propose a method to predict the subject-specific longitudinal progression of brain structures extracted from baseline MRI, and evaluate its performance on Alzheimer's disease data. The disease progression is modeled as a trajectory on a group of diffeomorphisms in the context of large deformation diffeomorphic metric mapping (LDDMM). We first exhibit the limited predictive abilities of geodesic regression extrapolation on this group. Building on the recent concept of parallel curves in shape manifolds, we then introduce a second predictive protocol which personalizes previously learned trajectories to new subjects, and investigate the relative performances of two parallel shifting paradigms. This design only requires the baseline imaging data. Finally, coefficients encoding the disease dynamics are obtained from longitudinal cognitive measurements for each subject, and exploited to refine our methodology which is demonstrated to successfully predict the follow-up visits.

Published
2017
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12. Statistical learning of spatiotemporal patterns from longitudinal manifold-valued networks

Author

Koval, Igor, Schiratti, Jean-Baptiste, Routier, Alexandre, Bacci, Michael, Colliot, Olivier, Allassonnière, Stéphanie, and Durrleman, Stanley

Subjects
Statistics - Machine Learning, Computer Science - Computer Vision and Pattern Recognition, Quantitative Biology - Neurons and Cognition, Quantitative Biology - Quantitative Methods
Abstract

We introduce a mixed-effects model to learn spatiotempo-ral patterns on a network by considering longitudinal measures distributed on a fixed graph. The data come from repeated observations of subjects at different time points which take the form of measurement maps distributed on a graph such as an image or a mesh. The model learns a typical group-average trajectory characterizing the propagation of measurement changes across the graph nodes. The subject-specific trajectories are defined via spatial and temporal transformations of the group-average scenario, thus estimating the variability of spatiotemporal patterns within the group. To estimate population and individual model parameters, we adapted a stochastic version of the Expectation-Maximization algorithm, the MCMC-SAEM. The model is used to describe the propagation of cortical atrophy during the course of Alzheimer's Disease. Model parameters show the variability of this average pattern of atrophy in terms of trajectories across brain regions, age at disease onset and pace of propagation. We show that the personalization of this model yields accurate prediction of maps of cortical thickness in patients.

Published
2017
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13. PET-BIDS, an extension to the brain imaging data structure for positron emission tomography

Author

Norgaard, Martin, Matheson, Granville J., Hansen, Hanne D., Thomas, Adam, Searle, Graham, Rizzo, Gaia, Veronese, Mattia, Giacomel, Alessio, Yaqub, Maqsood, Tonietto, Matteo, Funck, Thomas, Gillman, Ashley, Boniface, Hugo, Routier, Alexandre, Dalenberg, Jelle R., Betthauser, Tobey, Feingold, Franklin, Markiewicz, Christopher J., Gorgolewski, Krzysztof J., Blair, Ross W., Appelhoff, Stefan, Gau, Remi, Salo, Taylor, Niso, Guiomar, Pernet, Cyril, Phillips, Christophe, Oostenveld, Robert, Gallezot, Jean-Dominique, Carson, Richard E., Knudsen, Gitte M., Innis, Robert B., and Ganz, Melanie

Published
2022
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14. The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

Author

Poldrack, R, Markiewicz, C, Appelhoff, S, Ashar, Y, Auer, T, Baillet, S, Bansal, S, Beltrachini, L, Benar, C, Bertazzoli, G, Bhogawar, S, Blair, R, Bortoletto, M, Boudreau, M, Brooks, T, Calhoun, V, Castelli, F, Clement, P, Cohen, A, Cohen-Adad, J, D'Ambrosio, S, de Hollander, G, de la Iglesia-Vayá, M, de la Vega, A, Delorme, A, Devinsky, O, Draschkow, D, Duff, E, Dupre, E, Earl, E, Esteban, O, Feingold, F, Flandin, G, Galassi, A, Gallitto, G, Ganz, M, Gau, R, Gholam, J, Ghosh, S, Giacomel, A, Gillman, A, Gleeson, P, Gramfort, A, Guay, S, Guidali, G, Halchenko, Y, Handwerker, D, Hardcastle, N, Herholz, P, Hermes, D, Honey, C, Innis, R, Ioanas, H, Jahn, A, Karakuzu, A, Keator, D, Kiar, G, Kincses, B, Laird, A, Lau, J, Lazari, A, Legarreta, J, Li, A, Li, X, Love, B, Lu, H, Marcantoni, E, Maumet, C, Mazzamuto, G, Meisler, S, Mikkelsen, M, Mutsaerts, H, Nichols, T, Nikolaidis, A, Nilsonne, G, Niso, G, Norgaard, M, Okell, T, Oostenveld, R, Ort, E, Park, P, Pawlik, M, Pernet, C, Pestilli, F, Petr, J, Phillips, C, Poline, J, Pollonini, L, Raamana, P, Ritter, P, Rizzo, G, Robbins, K, Rockhill, A, Rogers, C, Rokem, A, Rorden, C, Routier, A, Saborit-Torres, J, Salo, T, Schirner, M, Smith, R, Spisak, T, Sprenger, J, Swann, N, Szinte, M, Takerkart, S, Thirion, B, Thomas, A, Torabian, S, Varoquaux, G, Voytek, B, Welzel, J, Wilson, M, Yarkoni, T, Gorgolewski, K, Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Blair, Ross W., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L., Cohen-Adad, Julien, D'Ambrosio, Sasha, de Hollander, Gilles, de la Iglesia-Vayá, María, de la Vega, Alejandro, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Duff, Eugene Paul, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, Galassi, Anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G., Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Ioanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, Kincses, Balint, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Marcantoni, Eleonora, Maumet, Camille, Mazzamuto, Giacomo, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nikolaidis, Aki, Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W., Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Pollonini, Luca, Raamana, Pradeep Reddy, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Spisak, Tamas, Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Welzel, Julius, Wilson, Martin, Yarkoni, Tal, Gorgolewski, Krzysztof J., Poldrack, R, Markiewicz, C, Appelhoff, S, Ashar, Y, Auer, T, Baillet, S, Bansal, S, Beltrachini, L, Benar, C, Bertazzoli, G, Bhogawar, S, Blair, R, Bortoletto, M, Boudreau, M, Brooks, T, Calhoun, V, Castelli, F, Clement, P, Cohen, A, Cohen-Adad, J, D'Ambrosio, S, de Hollander, G, de la Iglesia-Vayá, M, de la Vega, A, Delorme, A, Devinsky, O, Draschkow, D, Duff, E, Dupre, E, Earl, E, Esteban, O, Feingold, F, Flandin, G, Galassi, A, Gallitto, G, Ganz, M, Gau, R, Gholam, J, Ghosh, S, Giacomel, A, Gillman, A, Gleeson, P, Gramfort, A, Guay, S, Guidali, G, Halchenko, Y, Handwerker, D, Hardcastle, N, Herholz, P, Hermes, D, Honey, C, Innis, R, Ioanas, H, Jahn, A, Karakuzu, A, Keator, D, Kiar, G, Kincses, B, Laird, A, Lau, J, Lazari, A, Legarreta, J, Li, A, Li, X, Love, B, Lu, H, Marcantoni, E, Maumet, C, Mazzamuto, G, Meisler, S, Mikkelsen, M, Mutsaerts, H, Nichols, T, Nikolaidis, A, Nilsonne, G, Niso, G, Norgaard, M, Okell, T, Oostenveld, R, Ort, E, Park, P, Pawlik, M, Pernet, C, Pestilli, F, Petr, J, Phillips, C, Poline, J, Pollonini, L, Raamana, P, Ritter, P, Rizzo, G, Robbins, K, Rockhill, A, Rogers, C, Rokem, A, Rorden, C, Routier, A, Saborit-Torres, J, Salo, T, Schirner, M, Smith, R, Spisak, T, Sprenger, J, Swann, N, Szinte, M, Takerkart, S, Thirion, B, Thomas, A, Torabian, S, Varoquaux, G, Voytek, B, Welzel, J, Wilson, M, Yarkoni, T, Gorgolewski, K, Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Blair, Ross W., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L., Cohen-Adad, Julien, D'Ambrosio, Sasha, de Hollander, Gilles, de la Iglesia-Vayá, María, de la Vega, Alejandro, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Duff, Eugene Paul, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, Galassi, Anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G., Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Ioanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, Kincses, Balint, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Marcantoni, Eleonora, Maumet, Camille, Mazzamuto, Giacomo, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nikolaidis, Aki, Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W., Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Pollonini, Luca, Raamana, Pradeep Reddy, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Spisak, Tamas, Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Welzel, Julius, Wilson, Martin, Yarkoni, Tal, and Gorgolewski, Krzysztof J.

Abstract

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

Published
2024

17. Spatio-Temporal Shape Analysis of Cross-Sectional Data for Detection of Early Changes in Neurodegenerative Disease

Author

Cury, Claire, Lorenzi, Marco, Cash, David, Nicholas, Jennifer M., Routier, Alexandre, Rohrer, Jonathan, Ourselin, Sebastien, Durrleman, Stanley, Modat, Marc, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Reuter, Martin, editor, Wachinger, Christian, editor, and Lombaert, Hervé, editor

Published
2016
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18. Joint Morphometry of Fiber Tracts and Gray Matter Structures Using Double Diffeomorphisms

Author

Gori, Pietro, Colliot, Olivier, Marrakchi-Kacem, Linda, Worbe, Yulia, Routier, Alexandre, Poupon, Cyril, Hartmann, Andreas, Ayache, Nicholas, Durrleman, Stanley, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Ourselin, Sebastien, editor, Alexander, Daniel C., editor, Westin, Carl-Fredrik, editor, and Cardoso, M. Jorge, editor

Published
2015
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19. The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

Author

National Institutes of Health (US), National Science Foundation (US), Novo Nordisk Foundation, European Research Council, German Research Foundation, Charité - Universitätsmedizin Berlin, Agence Nationale de la Recherche (France), Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Maumet, Camille, Mazzamuto, Giacomo, Nikolaidis, Aki, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W, Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pollonini, Luca, Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Reddy Raamana, Pradeep, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Spisak, Tamas, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Blair, Ross W., Welzel, Julius, Wilson, Martin, Yarkoni, Tal, Gorgolewski, Krzysztof J., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L, Cohen-Adad, Julien, D'Ambrosio, Sasha, Hollander, D'Ambrosio, iglesia-Vayá, María de la, Vega, Alejandro de la, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Paul Duff, Eugene, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, Galassi, Anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G, Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Loanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, Kincses, Balint, National Institutes of Health (US), National Science Foundation (US), Novo Nordisk Foundation, European Research Council, German Research Foundation, Charité - Universitätsmedizin Berlin, Agence Nationale de la Recherche (France), Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Maumet, Camille, Mazzamuto, Giacomo, Nikolaidis, Aki, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W, Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pollonini, Luca, Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Reddy Raamana, Pradeep, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Spisak, Tamas, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Blair, Ross W., Welzel, Julius, Wilson, Martin, Yarkoni, Tal, Gorgolewski, Krzysztof J., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L, Cohen-Adad, Julien, D'Ambrosio, Sasha, Hollander, D'Ambrosio, iglesia-Vayá, María de la, Vega, Alejandro de la, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Paul Duff, Eugene, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, Galassi, Anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G, Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Loanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, and Kincses, Balint

Abstract

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

Published
2023

20. Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge

Author

Bron, Esther E., Smits, Marion, van der Flier, Wiesje M., Vrenken, Hugo, Barkhof, Frederik, Scheltens, Philip, Papma, Janne M., Steketee, Rebecca M.E., Méndez Orellana, Carolina, Meijboom, Rozanna, Pinto, Madalena, Meireles, Joana R., Garrett, Carolina, Bastos-Leite, António J., Abdulkadir, Ahmed, Ronneberger, Olaf, Amoroso, Nicola, Bellotti, Roberto, Cárdenas-Peña, David, Álvarez-Meza, Andrés M., Dolph, Chester V., Iftekharuddin, Khan M., Eskildsen, Simon F., Coupé, Pierrick, Fonov, Vladimir S., Franke, Katja, Gaser, Christian, Ledig, Christian, Guerrero, Ricardo, Tong, Tong, Gray, Katherine R., Moradi, Elaheh, Tohka, Jussi, Routier, Alexandre, Durrleman, Stanley, Sarica, Alessia, Di Fatta, Giuseppe, Sensi, Francesco, Chincarini, Andrea, Smith, Garry M., Stoyanov, Zhivko V., Sørensen, Lauge, Nielsen, Mads, Tangaro, Sabina, Inglese, Paolo, Wachinger, Christian, Reuter, Martin, van Swieten, John C., Niessen, Wiro J., and Klein, Stefan

Published
2015
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21. Improving Efficiency of Data Assimilation Procedure for a Biomechanical Heart Model by Representing Surfaces as Currents

Author

Imperiale, Alexandre, Routier, Alexandre, Durrleman, Stanley, Moireau, Philippe, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Ourselin, Sébastien, editor, Rueckert, Daniel, editor, and Smith, Nicolas, editor

Published
2013
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22. Cerebral microbleeds and CSF Alzheimer biomarkers in primary progressive aphasias

Author

Mendes, Aline, Bertrand, Anne, Lamari, Foudil, Colliot, Olivier, Routier, Alexandre, Godefroy, Olivier, Etcharry-Bouyx, Frédérique, Moreaud, Olivier, Pasquier, Florence, Couratier, Philippe, Bennys, Karim, Vercelletto, Martine, Martinaud, Olivier, Laurent, Bernard, Pariente, Jérémie, Puel, Michèle, Epelbaum, Stéphane, Belliard, Serge, Kaaouana, Takoua, Fillon, Ludovic, Chupin, Marie, Dubois, Bruno, and Teichmann, Marc

Published
2018
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23. Early Cognitive, Structural, and Microstructural Changes in Presymptomatic C9orf72 Carriers Younger Than 40 Years

Author

Bertrand, Anne, Wen, Junhao, Rinaldi, Daisy, Houot, Marion, Sayah, Sabrina, Camuzat, Agnès, Fournier, Clémence, Fontanella, Sabrina, Routier, Alexandre, Couratier, Philippe, Pasquier, Florence, Habert, Marie-Odile, Hannequin, Didier, Martinaud, Olivier, Caroppo, Paola, Levy, Richard, Dubois, Bruno, Brice, Alexis, Durrleman, Stanley, Colliot, Olivier, and Le Ber, Isabelle

Published
2018
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24. Unravelling the impact of frontal lobe impairment for social dysfunction in myotonic dystrophy type 1

Author

Morin, Alexandre, primary, Funkiewiez, Aurelie, additional, Routier, Alexandre, additional, Le Bouc, Raphael, additional, Borderies, Nicolas, additional, Galanaud, Damien, additional, Levy, Richard, additional, Pessiglione, Mathias, additional, Dubois, Bruno, additional, Eymard, Bruno, additional, Michon, Claire-Cecile, additional, Angeard, Nathalie, additional, Behin, Anthony, additional, Laforet, Pascal, additional, Stojkovic, Tanya, additional, and Azuar, Carole, additional

Published
2022
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25. Clinica: an open-source software platform for reproducible clinical neuroscience studies

Author

Omar El-Rifai, Mauricio Diaz Melo, Ravi Hassanaly, Matthieu Joulot, Routier, Alexandre M., Elina Thibeau-Sutre, Ghislain Vaillant, Stanley Durrleman​, Ninon Burgos, Olivier Colliot, Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), ANR-19-P3IA-0001,PRAIRIE,PaRis Artificial Intelligence Research InstitutE(2019), El-Rifai, Omar, and PaRis Artificial Intelligence Research InstitutE - - PRAIRIE2019 - ANR-19-P3IA-0001 - P3IA - VALID

Subjects
[SCCO.NEUR]Cognitive science/Neuroscience, [SCCO.NEUR] Cognitive science/Neuroscience, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2021

27. Clinica: An Open-Source Software Platform for Reproducible Clinical Neuroscience Studies

Author

Routier, Alexandre, primary, Burgos, Ninon, additional, Díaz, Mauricio, additional, Bacci, Michael, additional, Bottani, Simona, additional, El-Rifai, Omar, additional, Fontanella, Sabrina, additional, Gori, Pietro, additional, Guillon, Jérémy, additional, Guyot, Alexis, additional, Hassanaly, Ravi, additional, Jacquemont, Thomas, additional, Lu, Pascal, additional, Marcoux, Arnaud, additional, Moreau, Tristan, additional, Samper-González, Jorge, additional, Teichmann, Marc, additional, Thibeau-Sutre, Elina, additional, Vaillant, Ghislain, additional, Wen, Junhao, additional, Wild, Adam, additional, Habert, Marie-Odile, additional, Durrleman, Stanley, additional, and Colliot, Olivier, additional

Published
2021
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28. PET-BIDS, an extension to the brain imaging data structure for positron emission tomography

Author

Nørgaard, Martin, Matheson, Granville J, Hansen, Hanne D, Thomas, Adam, Searle, Graham, Rizzo, Gaia, Veronese, Mattia, Giacomel, Alessio, Yaqub, Maqsood, Tonietto, Matteo, Funck, Thomas, Gillman, Ashley, Boniface, Hugo, Routier, Alexandre, Dalenberg, Jelle R, Betthauser, Tobey, Feingold, Franklin, Markiewicz, Christopher J, Gorgolewski, Krzysztof J, Blair, Ross W, Appelhoff, Stefan, Gau, Remi, Salo, Taylor, Niso, Guiomar, Pernet, Cyril, Phillips, Christophe, Oostenveld, Robert, Gallezot, Jean-Dominique, Carson, Richard E, Knudsen, Gitte M, Innis, Robert B, and Ganz, Melanie

Subjects
ComputingMilieux_COMPUTERSANDSOCIETY, heterocyclic compounds, biological phenomena, cell phenomena, and immunity, urologic and male genital diseases, neoplasms, GeneralLiterature_MISCELLANEOUS, digestive system diseases
Abstract

The Brain Imaging Data Structure (BIDS) is a standard for organizing and describing neuroimaging datasets. It serves not only to facilitate the process of data sharing and aggregation, but also to simplify the application and development of new methods and software for working with neuroimaging data. Here, we present an extension of BIDS to include positron emission tomography (PET) data (PET-BIDS). We describe the PET-BIDS standard in detail and share several open-access datasets curated following PET-BIDS. Additionally, we highlight several tools which are already available for converting, validating and analyzing PET-BIDS datasets.Competing Interest StatementThe authors have declared no competing interest.

Published
2021
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29. PET-BIDS, an extension to the brain imaging data structure for positron emission tomography

Author

Norgaard, Martin, primary, Matheson, Granville J., additional, Hansen, Hanne D., additional, Thomas, Adam, additional, Searle, Graham, additional, Rizzo, Gaia, additional, Veronese, Mattia, additional, Giacomel, Alessio, additional, Yaqub, Maqsood, additional, Tonietto, Matteo, additional, Funck, Thomas, additional, Gillman, Ashley, additional, Boniface, Hugo, additional, Routier, Alexandre, additional, Dalenberg, Jelle R., additional, Betthauser, Tobey, additional, Feingold, Franklin, additional, Markiewicz, Christopher J., additional, Gorgolewski, Krzysztof J., additional, Blair, Ross W., additional, Appelhoff, Stefan, additional, Gau, Remi, additional, Salo, Taylor, additional, Niso, Guiomar, additional, Pernet, Cyril, additional, Phillips, Christophe, additional, Oostenveld, Robert, additional, Gallezot, Jean-Dominique, additional, Carson, Richard E., additional, Knudsen, Gitte M., additional, Innis, Robert B., additional, and Ganz, Melanie, additional

Published
2021
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34. Structural, Microstructural, and Metabolic Alterations in Primary Progressive Aphasia Variants

Author

Routier, Alexandre, Habert, Marie-Odile, Bertrand, Anne, Kas, Aurélie, Sundqvist, Martina, Mertz, Justine, David, Pierre-Maxime, Bertin, Hugo, Belliard, Serge, Pasquier, Florence, Bennys, Karim, Martinaud, Olivier, Etcharry-Bouyx, Frédérique, Moreaud, Olivier, Godefroy, Olivier, Pariente, Jérémie, Puel, Michèle, Couratier, Philippe, Boutoleau-Bretonnière, Claire, Laurent, Bernard, Migliaccio, Raphaëlla, Dubois, Bruno, Colliot, Olivier, Teichmann, Marc, Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), FRONTLAB: Fonctions et dysfonctions de systèmes frontaux [ICM Paris] (FRONTlab), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Imagerie Biomédicale [Paris] (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Centre d'Acquisition et de Traitement des Images [Paris], Commissariat à l'énergie atomique et aux énergies alternatives (CEA), CHU Saint-Antoine [AP-HP], Médecine nucléaire [CHU HEGP], Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Service de neurologie [Rennes], Université de Rennes (UR), Neuropsychologie et imagerie de la mémoire humaine (NIMH), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM), Département de neurologie [Lille], Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Département de neurologie [Montpellier], Université Montpellier 1 (UM1)-Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Hôpital Gui de Chauliac [CHU Montpellier], Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Université de Montpellier (UM), Service de neurologie [Rouen], CHU Rouen, Normandie Université (NU)-Normandie Université (NU), Service de neurologie [Angers], Université d'Angers (UA)-Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM)-PRES Université Nantes Angers Le Mans (UNAM), Pôle Psychiatrie et Neurologie [Grenoble], Centre Hospitalier Universitaire [Grenoble] (CHU), Service de neurologie [Amiens], CHU Amiens-Picardie, Laboratoire de Neurosciences Fonctionnelles et Pathologies - UR UPJV 4559 (LNFP), Université de Picardie Jules Verne (UPJV), Neurologie vasculaire, pathologie neuro-dégénérative et explorations fonctionnelles du système nerveux [Toulouse], Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Toulouse Neuro Imaging Center (ToNIC), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT), Service de Neurologie [CHU Limoges], CHU Limoges, Service de neurologie [Nantes], Université de Nantes (UN)-Centre hospitalier universitaire de Nantes (CHU Nantes)-Hôpital Guillaume-et-René-Laennec [Saint-Herblain], Service de Neurologie [CHU de Saint-Étienne], Centre Hospitalier Universitaire de Saint-Etienne [CHU Saint-Etienne] (CHU ST-E)-Université Jean Monnet - Saint-Étienne (UJM), Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Routier, Alexandre, Laboratoire d'Imagerie Biomédicale (LIB), Service de Médecine nucléaire [CHU Pitié-Salpétrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Service de Radiologie [CHU Saint-Antoine], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Saint-Antoine [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Normandie Université (NU)-Normandie Université (NU)-École pratique des hautes études (EPHE), Université Montpellier 1 (UM1)-Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Hôpital Gui de Chauliac [Montpellier]-Université de Montpellier (UM), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées, Service de neurologie [CHU de Saint-Étienne], Centre Hospitalier Universitaire de Saint-Etienne (CHU de Saint-Etienne), Institut de la Mémoire et de la Maladie d'Alzheimer [CHU Pitié-Salpétriêre] (IM2A), Service de Neuroradiologie [CHU Pitié-Salpêtrière], Service de Neurologie [CHU Pitié-Salpêtrière], IFR70-CHU Pitié-Salpêtrière [AP-HP], Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), FRONTlab - Systèmes frontaux : fonctions et dysfonctions (FRONTlab), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), CATI Multicenter Neuroimaging Platform (CATI), Service de médecine nucléaire [CHU Pitié-Salpétrière], Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Département de neurologie[Lille], Université de Lille, Droit et Santé-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Hôpital Purpan [Toulouse], CHU Toulouse [Toulouse], Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Hôpital Purpan [Toulouse], CHU Toulouse [Toulouse]-CHU Toulouse [Toulouse], Institut de la Mémoire et de la Maladie d'Alzheimer [Paris] (IM2A), Sorbonne Université (SU), Service de neurologie 1 [CHU Pitié-Salpétrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), and Hôpital Gui de Chauliac [Montpellier]-Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Université Montpellier 1 (UM1)-Université de Montpellier (UM)

Subjects
PET, Neurology, primary progressive aphasias, tracts, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Neurology (clinical), cortical metabolism, cortical thickness, behavioral disciplines and activities, Original Research, MRI
Abstract

International audience; Neuroimaging studies have described the brain alterations in primary progressive aphasia (PPA) variants (semantic, logopenic, nonfluent/agrammatic). However, few studies combined T1, FDG-PET, and diffusion MRI techniques to study atrophy, hypometabolism, and tract alterations across the three PPA main variants. We therefore explored a large early-stage cohort of semantic, logopenic and nonfluent/agrammatic variants (N = 86) and of 23 matched healthy controls with anatomical MRI (cortical thickness), FDG PET (metabolism) and diffusion MRI (white matter tracts analyses), aiming at identifying cortical and sub-cortical brain alterations, and confronting these alterations across imaging modalities and aphasia variants. In the semantic variant, there was cortical thinning and hypometabolism in anterior temporal cortices, with left-hemisphere predominance, extending toward posterior temporal regions, and affecting tracts projecting to the anterior temporal lobes (inferior longitudinal fasciculus, uncinate fasciculus) and tracts projecting to or running nearby posterior temporal cortices: (superior longitudinal fasciculus, inferior frontal-occipital fasciculus). In the logopenic variant metabolic alterations were more extensive than atrophy affecting mainly the left temporal-parietal junction and extending toward more anterior temporal cortices. Metabolic and tract data were coherent given the alterations of the left superior and inferior longitudinal fasciculus and the left inferior frontal-occipital fasciculus. In the nonfluent/agrammatic variant cortical thinning and hypometabolism were located in the left frontal cortex but Broca's area was only affected on metabolic measures. Metabolic and tract alterations were coherent as reflected by damage to the left uncinate fasciculus connecting with Broca's area. Our findings provide a full-blown statistically robust picture of brain alterations in early-stage variants of primary progressive aphasia which has implications for diagnosis, classification and future therapeutic strategies. They demonstrate that in logopenic and semantic variants patterns of brain damage display a non-negligible overlap in temporal regions whereas they are substantially distinct in the nonfluent/agrammatic variant (frontal regions). These results also indicate that frontal networks (combinatorial syntax/phonology) and temporal networks (lexical/semantic representations) constitute distinct anatomo-functional entities with differential vulnerability to degenerative processes in aphasia variants. Finally, the identification of the specific damage patterns could open an avenue for trans-cranial stimulation approaches by indicating the appropriate target-entry into the damaged language system.

Published
2018
Full Text
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35. Clinica: an open source software platform for reproducible clinical neuroscience studies

Author

Routier, Alexandre, Burgos, Ninon, Guillon, Jérémy, Samper-González, Jorge, Wen, Junhao, Bottani, Simona, Marcoux, Arnaud, Bacci, Michael, Fontanella, Sabrina, Jacquemont, Thomas, Wild, Adam, Gori, Pietro, Guyot, Alexis, Lu, Pascal, Díaz, Mauricio, Thibeau--Sutre, Elina, Moreau, Tristan, Teichmann, Marc, Habert, Marie-Odile, Durrleman, Stanley, Colliot, Olivier, Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Service Expérimentation et Développement [Paris] (SED), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), FRONTlab - Systèmes frontaux : fonctions et dysfonctions (FRONTlab), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut de la Mémoire et de la Maladie d'Alzheimer [Paris] (IM2A), Sorbonne Université (SU), Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), CATI Multicenter Neuroimaging Platform (CATI), CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Service de Neuroradiologie [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université, and The research leading to these results has received funding from the program 'Investissements d’avenir' ANR-10 IAIHU-06 (Agence Nationale de la Recherche-10-IA Institut Hospitalo-Universitaire-6) ANR-11-IDEX-004 (Agence Nationale de la Recherche-11-Initiative d’Excellence-004, project LearnPETMR number SU-16-R-EMR-16), from the European Union H2020 program (project EuroPOND, grant number 666992, project HBP SGA1 grant number 720270), from the joint NSF/NIH/ANR program 'Collaborative Research in Computational Neuroscience' (project HIPLAY7, grant number ANR-16-NEUC-0001-01), from Agence Nationale de la Recherche (project PREVDEMALS, grant number ANR-14-CE15-0016-07), from the ICM Big Brain Theory Program (project DYNAMO), from the Inria Project Lab Program (project Neuromarkers), from the European Research Council (to Dr Durrleman project LEASP, grant number 678304), and from the 'Contrat d’Interface Local' program (to Dr Colliot) from Assistance Publique-Hôpitaux de Paris (AP-HP). N.B. received funding from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007-2013) under REA grant agreement no. PCOFUND-GA-2013-609102, through the PRESTIGE programme coordinated by Campus France.

Subjects
Data processing, Pipeline, Machine learning, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Neuroimaging, Software, BIDS, Reproducibility, Nipype
Published
2019

36. New advances in the Clinica software platform for clinical neuroimaging studies

Author

Routier, Alexandre, Marcoux, Arnaud, Diaz Melo, Mauricio, Guillon, Jérémy, Samper-González, Jorge, Wen, Junhao, Bottani, Simona, Guyot, Alexis, Thibeau-Sutre, Elina, Teichmann, Marc, Habert, Marie-Odile, Durrleman, Stanley, Burgos, Ninon, Colliot, Olivier, Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Service Expérimentation et Développement [Paris] (SED), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), FRONTLAB: Fonctions et dysfonctions de systèmes frontaux [ICM Paris] (FRONTlab), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut de la Mémoire et de la Maladie d'Alzheimer [CHU Pitié-Salpétriêre] (IM2A), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), CATI Multicenter Neuroimaging Platform (CATI), Service de Médecine nucléaire [CHU Pitié-Salpétrière], Service de Neurologie [CHU Pitié-Salpêtrière], IFR70-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), FRONTlab - Systèmes frontaux : fonctions et dysfonctions (FRONTlab), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut de la Mémoire et de la Maladie d'Alzheimer [Paris] (IM2A), Sorbonne Université (SU), Service de médecine nucléaire [CHU Pitié-Salpétrière], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP]-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP]-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-CHU Pitié-Salpêtrière [APHP], Département de Neurologie [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-IFR70-CHU Pitié-Salpêtrière [APHP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), and Laboratoire d'Imagerie Biomédicale [Paris] (LIB)

Subjects
[INFO.INFO-IM]Computer Science [cs]/Medical Imaging, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2019
Full Text
View/download PDF

37. How serious is data leakage in deep learning studies on Alzheimer’s disease classification?

Author

Wen, Junhao, Thibeau-Sutre, Elina, Samper-Gonzalez, Jorge, Routier, Alexandre, Bottani, Simona, Dormont, Didier, Durrleman​, Stanley, Colliot, Olivier, Burgos, Ninon, THIBEAU-SUTRE, Elina, Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], and Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, ComputingMilieux_MISCELLANEOUS, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

International audience

Published
2019

38. Beware of feature selection bias! Example on Alzheimer's disease classification from diffusion MRI

Author

Junhao Wen​, Jorge Samper-González​, Routier, Alexandre M., Simona Bottani​, Stanley Durrleman​, Ninon Burgos, Olivier Colliot, WEN, Junhao, Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], and Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, ComputingMilieux_MISCELLANEOUS, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

International audience

Published
2019

39. An Automated Pipeline for the Analysis of PET Data on the Cortical Surface

Author

Marcoux, Arnaud, Burgos, Ninon, Bertrand, Anne, Teichmann, Marc, Routier, Alexandre, Wen, Junhao, Samper-Gonzalez, Jorge, Bottani, Simona, Durrleman, Stanley, Habert, Marie-Odile, Colliot, Olivier, Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU), Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Service de Neuroradiologie [CHU Pitié-Salpêtrière], CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), FRONTlab - Systèmes frontaux : fonctions et dysfonctions (FRONTlab), Centre de référence sur les démences rares et maladie de Pick, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Centre d'Acquisition et de Traitement des Images [Paris], Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Service de médecine nucléaire [CHU Pitié-Salpétrière], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), FRONTLAB: Fonctions et dysfonctions de systèmes frontaux [ICM Paris] (FRONTlab), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Service de Médecine nucléaire [CHU Pitié-Salpétrière], Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), and Laboratoire d'Imagerie Biomédicale [Paris] (LIB)

Subjects
Surface analysis, Positron emission tomography, PET, Pipeline, [SCCO.NEUR]Cognitive science/Neuroscience, Neurodegenerative diseases, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Brain, [INFO]Computer Science [cs], Workflow
Abstract

International audience; We present a fully automatic pipeline for the analysis of PET data on the cortical surface. Our pipeline combines tools from FreeSurfer and PETPVC, and consists of (i) co-registration of PET and T1-w MRI (T1) images, (ii) intensity normalization, (iii) partial volume correction, (iv) robust projection of the PET signal onto the subject's cortical surface, (v) spatial normalization to a template, and (vi) atlas statistics. We evaluated the performance of the proposed workflow by performing group comparisons and showed that the approach was able to identify the areas of hypometabolism characteristic of different dementia syndromes: Alzheimer's disease (AD) and both the semantic and logopenic variants of primary progressive aphasia. We also showed that these results were comparable to those obtained with a standard volume-based approach. We then performed individual classifications and showed that vertices can be used as features to differentiate cognitively normal and AD subjects. This pipeline is integrated into Clinica, an open-source software platform for neuroscience studies available at www.clinica.run.

Published
2018
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40. Imagerie cérébrale multimodale pour l'étude des aphasies primaires progressives

Author

Routier, Alexandre, Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université, Marc Teichmann, Olivier Colliot, and Marie-Odile Habert

Subjects
PET, IRM anatomique, TEP, Anatomical MRI, Neuroimaging, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], IRM de diffusion, Primary progressive aphasia, Aphasie primaire progressive, Diffusion IRM, Neuroimagerie
Abstract

Progressive primary aphasia (APP) is a group of neurodegenerative diseases affecting language abilities and presenting clinical, anatomical and biological/genetic heterogeneity. We first used anatomical MRI, diffusion MRI and FDG-PET imaging to provide a complete characterization of the different forms of PPA in a large cohort of patients at early stage of the disease. This study allowed to characterize the structural, microstructural and metabolic alteration patterns in each variant of PPA and to compare these alterations between the different imaging modalities. In the second part, we used the lesional model of PPA to study the networks of semantic processes. The use of tractography and the analysis of correlations between semantic deficits and white matter integrity in diffusion MRI allowed the identification of connections involved in verbal and non-verbal processes. These studies required the development of specific image analysis tools. In particular, the development of tools for the analysis of anatomical and diffusion MRI have been integrated into the Clinica software platform to make these tools easily usable by other researchers or clinicians.; L'aphasie primaire progressive (APP) est un groupe de maladies neurodégénératives affectant les fonctions du langage et présentant une importante hétérogénéité sur le plan clinique, anatomique et biologique/génétique. Dans une première partie, nous utilisons l’IRM anatomique, l’IRM de diffusion et l’imagerie TEP-FDG pour fournir une caractérisation complète des différentes formes d’APP dans une grande cohorte de patients au stade débutant de la maladie. Cette étude permet de caractériser les motifs d’altérations structurelles, microstructurelles et métaboliques dans chaque variante d’APP et de confronter ces altérations entre les différentes modalités d’imagerie. Dans une seconde partie, nous avons utilisé le modèle lésionnel des APP pour étudier les réseaux des processus sémantiques. L’utilisation de la tractographie et l’analyse de corrélations entre déficits sémantiques et intégrité des faisceaux de la substance blanche en IRM de diffusion ont permis l’identification de connexions impliquées dans les processus verbaux et non verbaux. Ces études ont nécessité le développement d’outils spécifiques d’analyse d’images. En particulier, le développement d’outils pour l’analyse d’IRM anatomique et de diffusion ont été intégrés au sein de la plate-forme logicielle Clinica afin de rendre ces outils facilement utilisables par d’autres chercheurs ou cliniciens.

Published
2018

41. Spatiotemporal Propagation of the Cortical Atrophy: Population and Individual Patterns

Author

Koval, Igor, Schiratti, Jean-Baptiste, Routier, Alexandre, Bacci, Michael, Colliot, Olivier, Allassonnière, Stéphanie, Durrleman, Stanley, Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138)), École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Université Paris Descartes - Paris 5 (UPD5), Colliot, Olivier, École pratique des hautes études (EPHE), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], and Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Brain networks, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, [SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology, [SDV.NEU.NB] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Alzheimer's disease, Individual variability, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], Cortical atrophy, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Spatiotemporal propagation patterns, Alzheimer’s disease, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Neuroscience, Original Research, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
Abstract

International audience; Repeated failures in clinical trials for Alzheimer's disease (AD) have raised a strong interest for the prodromal phase of the disease. A better understanding of the brain alterations during this early phase is crucial to diagnose patients sooner, to estimate an accurate disease stage, and to give a reliable prognosis. According to recent evidence, structural alterations in the brain are likely to be sensitive markers of the disease progression. Neuronal loss translates in specific spatiotemporal patterns of cortical atrophy, starting in the enthorinal cortex and spreading over other cortical regions according to specific propagation pathways. We developed a digital model of the cortical atrophy in the left hemisphere from prodromal to diseased phases, which is built on the temporal alignment and combination of several short-term observation data to reconstruct the long-term history of the disease. The model not only provides a description of the spatiotemporal patterns of cortical atrophy at the group level but also shows the variability of these patterns at the individual level in terms of difference in propagation pathways, speed of propagation, and age at propagation onset. Longitudinal MRI datasets of patients with mild cognitive impairments who converted to AD are used to reconstruct the cortical atrophy propagation across all disease stages. Each observation is considered as a signal spatially distributed on a network, such as the cortical mesh, each cortex location being associated to a node. We consider how the temporal profile of the signal varies across the network nodes. We introduce a statistical mixed-effect model to describe the evolution of the cortex alterations. To ensure a spatiotemporal smooth propagation of the alterations, we introduce a constrain on the propagation signal in the model such that neighboring nodes have similar profiles of the signal changes. Our generative model enables the reconstruction of personalized patterns of the neurodegenerative spread, providing a way to estimate disease progression stages and predict the age at which the disease will be diagnosed. The model shows that, for instance, APOE carriers have a significantly higher pace of cortical atrophy but not earlier atrophy onset.

Published
2018
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42. Early cognitive, structural and microstructural changes in c9orf72 presymptomatic carriers before 40 years of age

Author

Bertrand, Anne, Wen, Junhao, Rinaldi, Daisy, Houot, Marion, Sayah, Sabrina, Camuzat, Agnès, Fournier, Clémence, Fontanella, Sabrina, Routier, Alexandre, Couratier, Philippe, Pasquier, Florence, Habert, Marie-Odile, Hannequin, Didier, Martinaud, Olivier, Caroppo, Paola, Levy, Richard, Dubois, Bruno, Brice, Alexis, Durrleman, Stanley, Colliot, Olivier, Le Ber, Isabelle, Study, Prevdemals, Service de Neuroradiologie [CHU Pitié-Salpêtrière], CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Chongqing University [Chongqing], Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Service de Neurologie [CHU Pitié-Salpêtrière], IFR70-CHU Pitié-Salpêtrière [AP-HP], Neurologie et thérapeutique expérimentale, IFR70-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Neuroépidémiologie Tropicale (NET), CHU Limoges-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), Université de Limoges (UNILIM)-Université de Limoges (UNILIM), Service de Neurologie [CHU Limoges], CHU Limoges, Département de neurologie [Lille], Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Service de neurologie [Rouen], CHU Rouen, Normandie Université (NU)-Normandie Université (NU), Service de Psychiatrie adultes [CHU Saint-Antoine], CHU Saint-Antoine [AP-HP], Neuro-anatomie fonctionnelle du comportement et de ses troubles, Centre de recherche Informatique et Création Musicale (CICM), Esthétique, musicologie, danse et création musicale (MUSIDANSE), Université Paris 8 Vincennes-Saint-Denis (UP8)-Université Paris 8 Vincennes-Saint-Denis (UP8), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Hôpital Roger Salengro [Lille], Trial Registration clinicaltrials.gov Identifier: NCT02590276, bertrand, anne, Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Laboratoire d'Imagerie Biomédicale [Paris] (LIB), Service de neuroradiologie diagnostique et fonctionnelle [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Service de neurologie 1 [CHU Pitié-Salpétrière], Département de neurologie[Lille], Université de Lille, Droit et Santé-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Service de psychiatrie adulte [CHU Saint-Antoine], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Saint-Antoine [AP-HP], Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-IFR70, Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-CHU Pitié-Salpêtrière [APHP], Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP]-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP]-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP]-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-CHU Saint-Antoine [APHP], Esthétiques, musicologie, danse et créations musicales (MUSIDANSE), CHU Pitié-Salpêtrière [APHP], Hôpital Roger Salengro, Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), Université de Limoges (UNILIM)-Université de Limoges (UNILIM)-CHU Limoges-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-Institut National de la Santé et de la Recherche Médicale (INSERM), and Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)

Subjects
[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], [SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]
Abstract

International audience; Importance Presymptomatic carriers of chromosome 9 open reading frame 72 (C9orf72) mutation, the most frequent genetic cause of frontotemporal lobar degeneration and amyotrophic lateral sclerosis, represent the optimal target population for the development of disease-modifying drugs. Preclinical biomarkers are needed to monitor the effect of therapeutic interventions in this population.Objectives To assess the occurrence of cognitive, structural, and microstructural changes in presymptomatic C9orf72 carriers.Design, Setting, and Participants The PREV-DEMALS study is a prospective, multicenter, observational study of first-degree relatives of individuals carrying the C9orf72 mutation. Eighty-four participants entered the study between October 2015 and April 2017; 80 (95%) were included in cross-sectional analyses of baseline data. All participants underwent neuropsychological testing and magnetic resonance imaging; 63 (79%) underwent diffusion tensor magnetic resonance imaging. Gray matter volumes and diffusion tensor imaging metrics were calculated within regions of interest. Anatomical and microstructural differences between individuals who carried the C9orf72 mutation (C9+) and those who did not carry the C9orf72 mutation (C9−) were assessed using linear mixed-effects models. Data were analyzed from October 2015 to April 2017.Main Outcomes and Measures Differences in neuropsychological scores, gray matter volume, and white matter integrity between C9+ and C9− individuals.Results Of the 80 included participants, there were 41 C9+ individuals (24 [59%] female; mean [SD] age, 39.8 [11.1] years) and 39 C9− individuals (24 [62%] female; mean [SD] age, 45.2 [13.9] years). Compared with C9− individuals, C9+ individuals had lower mean (SD) praxis scores (163.4 [6.1] vs 165.3 [5.9]; P = .01) and intransitive gesture scores (34.9 [1.6] vs 35.7 [1.5]; P = .004), atrophy in 8 cortical regions of interest and in the right thalamus, and white matter alterations in 8 tracts. When restricting the analyses to participants younger than 40 years, compared with C9− individuals, C9+ individuals had lower praxis scores and intransitive gesture scores, atrophy in 4 cortical regions of interest and in the right thalamus, and white matter alterations in 2 tracts.Conclusions and Relevance Cognitive, structural, and microstructural alterations are detectable in young C9+ individuals. Early and subtle praxis alterations, underpinned by focal atrophy of the left supramarginal gyrus, may represent an early and nonevolving phenotype related to neurodevelopmental effects of C9orf72 mutation. White matter alterations reflect the future phenotype of frontotemporal lobar degeneration/amyotrophic lateral sclerosis, while atrophy appears more diffuse. Our results contribute to a better understanding of the preclinical phase of C9orf72 disease and of the respective contribution of magnetic resonance biomarkers.Trial Registration clinicaltrials.gov Identifier: NCT02590276

Published
2018
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43. Reproducible Evaluation of Diffusion MRI Features for Automatic Classification of Patients with Alzheimer's Disease.

Author

Wen, Junhao, Samper-González, Jorge, Bottani, Simona, Routier, Alexandre, Burgos, Ninon, Jacquemont, Thomas, Fontanella, Sabrina, Durrleman, Stanley, Epelbaum, Stéphane, Bertrand, Anne, and Colliot, Olivier

Abstract

Diffusion MRI is the modality of choice to study alterations of white matter. In past years, various works have used diffusion MRI for automatic classification of Alzheimer's disease. However, classification performance obtained with different approaches is difficult to compare because of variations in components such as input data, participant selection, image preprocessing, feature extraction, feature rescaling (FR), feature selection (FS) and cross-validation (CV) procedures. Moreover, these studies are also difficult to reproduce because these different components are not readily available. In a previous work (Samper-González et al. 2018), we propose an open-source framework for the reproducible evaluation of AD classification from T1-weighted (T1w) MRI and PET data. In the present paper, we first extend this framework to diffusion MRI data. Specifically, we add: conversion of diffusion MRI ADNI data into the BIDS standard and pipelines for diffusion MRI preprocessing and feature extraction. We then apply the framework to compare different components. First, FS has a positive impact on classification results: highest balanced accuracy (BA) improved from 0.76 to 0.82 for task CN vs AD. Secondly, voxel-wise features generally gives better performance than regional features. Fractional anisotropy (FA) and mean diffusivity (MD) provided comparable results for voxel-wise features. Moreover, we observe that the poor performance obtained in tasks involving MCI were potentially caused by the small data samples, rather than by the data imbalance. Furthermore, no extensive classification difference exists for different degree of smoothing and registration methods. Besides, we demonstrate that using non-nested validation of FS leads to unreliable and over-optimistic results: 5% up to 40% relative increase in BA. Lastly, with proper FR and FS, the performance of diffusion MRI features is comparable to that of T1w MRI. All the code of the framework and the experiments are publicly available: general-purpose tools have been integrated into the Clinica software package (www.clinica.run) and the paper-specific code is available at: https://github.com/aramis-lab/AD-ML. [ABSTRACT FROM AUTHOR]

Published
2021
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44. Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data

Author

Samper-González, Jorge, primary, Burgos, Ninon, additional, Bottani, Simona, additional, Fontanella, Sabrina, additional, Lu, Pascal, additional, Marcoux, Arnaud, additional, Routier, Alexandre, additional, Guillon, Jérémy, additional, Bacci, Michael, additional, Wen, Junhao, additional, Bertrand, Anne, additional, Bertin, Hugo, additional, Habert, Marie-Odile, additional, Durrleman, Stanley, additional, Evgeniou, Theodoros, additional, and Colliot, Olivier, additional

Published
2018
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45. Neurite density is reduced in the presymptomatic phase ofC9orf72disease

Author

Wen, Junhao, primary, Zhang, Hui, additional, Alexander, Daniel C, additional, Durrleman, Stanley, additional, Routier, Alexandre, additional, Rinaldi, Daisy, additional, Houot, Marion, additional, Couratier, Philippe, additional, Hannequin, Didier, additional, Pasquier, Florence, additional, Zhang, Jiaying, additional, Colliot, Olivier, additional, Le Ber, Isabelle, additional, and Bertrand, Anne, additional

Published
2018
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49. Neurite density is reduced in the presymptomatic phase of disease.

Author

Junhao Wen, Hui Zhang, Alexander, Daniel C., Durrleman, Stanley, Routier, Alexandre, Rinaldi, Daisy, Houot, Marion, Couratier, Philippe, Hannequin, Didier, Pasquier, Florence, Jiaying Zhang, Colliot, Olivier, le Le Ber, Isabel, Bertrand, Anne, Wen, Junhao, Zhang, Hui, Zhang, Jiaying, Le Ber, Isabelle, and Predict to Prevent Frontotemporal Lobar Degeneration and Amyotrophic Lateral Sclerosis (PREV-DEMALS) Study Group

Subjects
FRONTOTEMPORAL lobar degeneration, DIFFUSION tensor imaging, AMYOTROPHIC lateral sclerosis, DIFFUSION magnetic resonance imaging, DENSITY, VALUE orientations
Abstract

Objective: To assess the added value of neurite orientation dispersion and density imaging (NODDI) compared with conventional diffusion tensor imaging (DTI) and anatomical MRI to detect changes in presymptomatic carriers of chromosome 9 open reading frame 72 (C9orf72) mutation.Methods: The PREV-DEMALS (Predict to Prevent Frontotemporal Lobar Degeneration and Amyotrophic Lateral Sclerosis) study is a prospective, multicentre, observational study of first-degree relatives of individuals carrying the C9orf72 mutation. Sixty-seven participants (38 presymptomatic C9orf72 mutation carriers (C9+) and 29 non-carriers (C9-)) were included in the present cross-sectional study. Each participant underwent one single-shell, multishell diffusion MRI and three-dimensional T1-weighted MRI. Volumetric measures, DTI and NODDI metrics were calculated within regions of interest. Differences in white matter integrity, grey matter volume and free water fraction between C9+ and C9- individuals were assessed using linear mixed-effects models.Results: Compared with C9-, C9+ demonstrated white matter abnormalities in 10 tracts with neurite density index and only 5 tracts with DTI metrics. Effect size was significantly higher for the neurite density index than for DTI metrics in two tracts. No tract had a significantly higher effect size for DTI than for NODDI. For grey matter cortical analysis, free water fraction was increased in 13 regions in C9+, whereas 11 regions displayed volumetric atrophy.Conclusions: NODDI provides higher sensitivity and greater tissue specificity compared with conventional DTI for identifying white matter abnormalities in the presymptomatic C9orf72 carriers. Our results encourage the use of neurite density as a biomarker of the preclinical phase.Trial Registration Number: NCT02590276. [ABSTRACT FROM AUTHOR]

Published
2019
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