Article
Clinical Neurology
Vasilios C. Constantinides, Vasileios Tentolouris-Piperas, George P. Paraskevas, Efstratios-Stylianos Pyrgelis, Georgios Velonakis, Efstratios Karavasilis, Panagiotis Toulas, Fotini Boufidou, Leonidas Stefanis, Elisabeth Kapaki
Summary: This study compared hippocampal subfield atrophy patterns between corticobasal syndrome Alzheimer's disease (CBS-AD), corticobasal syndrome non-AD pathologies (CBS-nAD), typical amnestic AD patients, and control subjects. The results showed that CBS-AD and amnestic AD patients exhibited greater hippocampal subfield atrophy compared to CBS-nAD patients. The hippocampal subfield volumetry in CBS is indicative of an underlying AD pathology.
JOURNAL OF NEUROLOGY
(2023)
Article
Clinical Neurology
Akila Pai, Lara V. Marcuse, Judy Alper, Bradley N. Delman, John W. Rutland, Rebecca E. Feldman, Patrick R. Hof, Madeline Fields, James Young, Priti Balchandani
Summary: The study utilized automated segmentation technology combined with 7T MRI to detect hippocampal pathology in epilepsy patients, revealing that 7T MRI improved visualization of structural abnormalities in patients with unilateral mesial temporal lobe epilepsy and automated segmentation algorithm could detect structural differences in volume and asymmetry across hippocampal subfields.
FRONTIERS IN NEUROLOGY
(2021)
Article
Geriatrics & Gerontology
Melissa Gentreau, Jerome J. Maller, Chantal Meslin, Fabienne Cyprien, Jorge Lopez-Castroman, Sylvaine Artero
Summary: The study found that reduced hippocampal volume, measured manually or automatically, was significantly associated with higher dementia risk and cognitive decline. However, only automatically measured hippocampal volume was related to cognitive decline in dementia-free individuals.
AMERICAN JOURNAL OF GERIATRIC PSYCHIATRY
(2023)
Article
Geriatrics & Gerontology
Niels Hansen, Aditya Singh, Claudia Bartels, Frederic Brosseron, Katharina Buerger, Arda C. Cetindag, Laura Dobisch, Peter Dechent, Birgit B. Ertl-Wagner, Klaus Fliessbach, John D. Haynes, Michael T. Heneka, Daniel Janowitz, Ingo Kilimann, Christoph Laske, Coraline D. Metzger, Matthias H. Munk, Oliver Peters, Josef Priller, Nina Roy, Klaus Scheffler, Anja Schneider, Annika Spottke, Eike J. Spruth, Stefan Teipel, Maike Tscheuschler, Ruth Vukovich, Jens Wiltfang, Emrah Duezel, Frank Jessen, Roberto Goya-Maldonado
Summary: The study found significant differences in hippocampal volumes among patients with different diseases, particularly between AD patients and those with mood disorders. A linear relationship was observed between left hippocampal volume and duration since the first depressive episode.
FRONTIERS IN AGING NEUROSCIENCE
(2021)
Article
Neurosciences
Artemis Zavaliangos-Petropulu, Meral A. Tubi, Elizabeth Haddad, Alyssa Zhu, Meredith N. Braskie, Neda Jahanshad, Paul M. Thompson, Sook-Lei Liew
Summary: As stroke mortality rates decrease, research on poststroke dementia (PSD) is increasing. This study compared different methods for hippocampal segmentation in stroke populations and found that Hippodeep, a convolutional neural network-based method, performed better than other methods, suggesting its potential utility in stroke research.
HUMAN BRAIN MAPPING
(2022)
Article
Geriatrics & Gerontology
Shuntai Chen, Dian Zhang, Honggang Zheng, Tianyu Cao, Kun Xia, Mingwan Su, Qinggang Meng
Summary: The thickness of the retina is found to degenerate in the pathological process of Alzheimer's disease (AD), while hippocampal atrophy is a typical feature of AD. The association between retinal thickness and hippocampal atrophy in AD is unclear. This study aims to quantify the correlation between these two parameters and explore the potential of using retinal thickness as a biomarker for early AD detection.
FRONTIERS IN AGING NEUROSCIENCE
(2023)
Article
Geriatrics & Gerontology
Amy N. Murray, Hannah L. Chandler, Thomas M. Lancaster
Summary: Preclinical models of Alzheimer's disease show that AD polygenic risk scores are linked to reduced MTL volumes before clinical onset. In a study of young participants, the AD-PRS was found to predict specific hippocampal subregions and demonstrate associations with whole hippocampal/amygdala volumes. This research provides novel insights into the relationship between AD-PRS and specific MTL subfields, potentially informing preclinical models of AD risk.
NEUROBIOLOGY OF AGING
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Qiang Zheng, Yiyu Zhang, Honglun Li, Xiangrong Tong, Minhui Ouyang
Summary: This study investigates how different hippocampal segmentation methods affect the accuracy of hippocampal radiomic features (HRFs) in Alzheimer's disease (AD) analysis. The results show that HRFs exhibit high consistency across different segmentation methods and the best performance in AD classification is obtained when HRFs are extracted using the naive majority voting method with a more sufficient segmentation and relatively low hippocampal segmentation accuracy.
EUROPEAN RADIOLOGY
(2022)
Article
Psychiatry
Thomas L. Athey, Can Ceritoglu, Daniel J. Tward, Kwame S. Kutten, J. Raymond DePaulo, Kara Glazer, Fernando S. Goes, John R. Kelsoe, Francis Mondimore, Caroline M. Nievergelt, Kelly Rootes-Murdy, Peter P. Zandi, J. Tilak Ratnanather, Pamela B. Mahon
Summary: Research has shown that predictors of lithium response in bipolar disorder patients are difficult to pinpoint. However, this study has demonstrated potential for using detailed neuroimaging to fill this gap. Findings suggest that there are significant anatomical differences, particularly in the left hippocampus, between lithium responders and non-responders, which may help in future investigations of neuroimaging predictors for lithium response in bipolar disorder.
FRONTIERS IN PSYCHIATRY
(2021)
Editorial Material
Neurosciences
Laura E. M. Wisse, Gael Chetelat, Ana M. Daugherty, Robin de Flores, Renaud la Joie, Susanne G. Mueller, Craig E. L. Stark, Lei Wang, Paul A. Yushkevich, David Berron, Naftali Raz, Arnold Bakker, Rosanna K. Olsen, Valerie A. Carr
Summary: In recent years, in vivo MRI investigations of human hippocampal subfield volumes have increased due to the availability of automatic segmentation software. However, the majority of these studies use automatic segmentation on MRI scans with resolutions of approximately 1 x 1 x 1 mm(3), which is insufficient for visualizing the internal structure of the hippocampus. As a result, the findings of these studies are often contradictory and surprising, particularly regarding the involvement of hippocampal subfields in normal brain function, aging, and disease.
HUMAN BRAIN MAPPING
(2021)
Article
Psychiatry
Judy Alper, Rui Feng, Gaurav Verma, Sarah Rutter, Kuang-han Huang, Long Xie, Paul Yushkevich, Yael Jacob, Stephanie Brown, Marin Kautz, Molly Schneider, Hung-Mo Lin, Lazar Fleysher, Bradley N. Delman, Patrick R. Hof, James W. Murrough, Priti Balchandani
Summary: This study aimed to assess volumetric differences in hippocampal subfields between patients with major depressive disorder (MDD), treatment-resistant depression (TRD) and healthy controls (HC) using high-resolution MRI data. The results showed that MDD and TRD patients had reduced volume in the right-hemisphere CA2/3 subfield compared to HC. Negative correlations between subfield volumes and life-stressor checklist scores were also found. This study provides valuable insights into the pathophysiology of depression.
FRONTIERS IN PSYCHIATRY
(2023)
Review
Radiology, Nuclear Medicine & Medical Imaging
Yi-En Quek, Yi Leng Fung, Mike W-L Cheung, Simon J. Vogrin, Steven J. Collins, Stephen C. Bowden
Summary: The study compared automated methods and manual segmentation in measuring regional brain volumes on MRI across healthy controls, patients with mild cognitive impairment, and patients with dementia due to AD. The results showed that automated methods are generally comparable to manual segmentation for measuring hippocampal, lateral ventricle, and parahippocampal gyrus volumes, but with substantial uncontrolled variance. Therefore, caution should be used when utilizing automated methods in measuring these regions in AD patients.
JOURNAL OF MAGNETIC RESONANCE IMAGING
(2022)
Article
Veterinary Sciences
Borbala A. Lorincz, Agustina Anson, Stephan Handschuh, Alexander Tichy, Conor Rowan, Balazs B. Lorincz, Rita Garamvolgyi
Summary: The study aimed to compare hippocampal volumes in epileptic and healthy dogs, finding a positive association between body weight and hemispheric volume, as well as between hemispheric volume and ipsilateral hippocampal volume. However, no significant correlation was found between age and the volume of brain structures measured. There was also no statistically significant difference in hippocampal volumes between the two groups, and extrapolation of hippocampal volume based on body weight was not feasible in this study population.
ACTA VETERINARIA HUNGARICA
(2021)
Article
Geriatrics & Gerontology
Lidia Glodzik, Henry Rusinek, Tracy Butler, Yi Li, Pippa Storey, Elizabeth Sweeney, Ricardo S. Osorio, Adrienne Biskaduros, Emily Tanzi, Patrick Harvey, Christopher Woldstad, Thomas Maloney, Mony J. de Leon
Summary: Obesity is associated with hippocampal hemodynamic impairment, suggesting that targeting obesity is an important prevention strategy.
FRONTIERS IN AGING NEUROSCIENCE
(2022)
Article
Clinical Neurology
Michael Rebsamen, Piotr Radojewski, Richard McKinley, Mauricio Reyes, Roland Wiest, Christian Rummel
Summary: This study compared the sensitivity of different automated segmentation methods for assessing hippocampal sclerosis. The results showed that the deep learning-based segmentation method was the most sensitive in detecting hippocampal sclerosis. Additionally, shape features derived from the segmentations were able to accurately identify patients with hippocampal sclerosis. These findings have important implications for quantitative imaging of hippocampal sclerosis.
FRONTIERS IN NEUROLOGY
(2022)
Article
Clinical Neurology
Vincent Planche, Vincent Bouteloup, Isabelle Pellegrin, Jean-Francois Mangin, Bruno Dubois, Pierre-Jean Ousset, Florence Pasquier, Frederic Blanc, Claire Paquet, Olivier Hanon, Karim Bennys, Mathieu Ceccaldi, Cedric Annweiler, Pierre Krolak-Salmon, Olivier Godefroy, David Wallon, Mathilde Sauvee, Claire Boutoleau-Bretonniere, Isabelle Bourdel-Marchasson, Isabelle Jalenques, Genevieve Chene, Carole Dufouil
Summary: Blood biomarkers for Alzheimer's disease can effectively discriminate AD from other neurodegenerative diseases and may serve as hallmarks of underlying pathology, but they add little to 5-year dementia risk prediction models.
Article
Radiology, Nuclear Medicine & Medical Imaging
Chaithya Giliyar Radhakrishna, Guillaume Daval-Frerot, Aurelien Massire, Alexandre Vignaud, Philippe Ciuciu
Summary: This study proposes an improvement to the SPARKLING algorithm to address off-resonance artifacts in non-Cartesian MRI. The algorithm generates temporally smooth k-space sampling patterns by modifying the cost function using a temporal weighting factor. In silico and in vivo experiments demonstrate the effectiveness of the improved trajectories in reducing signal losses and blurring caused by B-0 inhomogeneities.
MAGNETIC RESONANCE IN MEDICINE
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Thaddee Delebarre, Vincent Gras, Franck Mauconduit, Alexandre Vignaud, Nicolas Boulant, Luisa Ciobanu
Summary: The purpose of this study is to optimize the homogeneity of presaturation module in a CEST acquisition using pTx at 7T. An optimized pTx-CEST presaturation scheme is designed based on precomputed universal pulses, and the optimization is performed by minimizing the L2-norm between the effective B1,RMS+ and a given target under VOPs supervision. The proposed method is evaluated through simulations and experiments and shows superior performance compared to CP and other pTx approaches.
MAGNETIC RESONANCE IN MEDICINE
(2023)
Article
Clinical Neurology
Lydia Chougar, Francois-Xavier Lejeune, Johann Faouzi, Benjamin Morino, Alice Faucher, Nadine Hoyek, David Grabli, Florence Cormier, Marie Vidailhet, Jean-Christophe Corvol, Olivier Colliot, Bertrand Degos, Stephane Lehericy
Summary: This study evaluates the value of combining clinically feasible manual measurements and morphometric measurements to improve the discrimination of parkinsonian syndromes. The results show that combining R2* and MD measurements with morphometric biomarkers can better differentiate parkinsonian syndromes.
PARKINSONISM & RELATED DISORDERS
(2023)
Article
Computer Science, Artificial Intelligence
Simona Bottani, Ninon Burgos, Aurelien Maire, Dario Saracino, Sebastian Stroer, Didier Dormont, Olivier Colliot, Alzheimers Dis Neuroimaging Initiat, APPRIMAGE Study Grp
Summary: This study examines the performance of computer-aided diagnosis methods on clinical routine data and compares it to research data. The results indicate that the performance is strongly biased upward due to confounding factors like image quality and contrast agent injection, and overall much lower than on research data.
MEDICAL IMAGE ANALYSIS
(2023)
Editorial Material
Anesthesiology
Theodore Soulier, Olivier Colliot, Nicholas Ayache, Benjamin Rohaut
ANAESTHESIA CRITICAL CARE & PAIN MEDICINE
(2023)
Article
Anatomy & Morphology
Kevin de Matos, Claire Cury, Lydia T. Chougar, Lachlan Strike, Thibault Rolland, Maximilien Riche, Lisa Hemforth, Alexandre Martin, Tobias Banaschewski, Arun L. W. Bokde, Sylvane Desrivieres, Herta Flor, Antoine Grigis, Hugh Garavan, Penny Gowland, Andreas Heinz, Rudiger Bruhl, Jean-Luc Martinot, Marie-Laure Paillere Martinot, Eric Artiges, Frauke Nees, Dimitri Papadopoulos Orfanos, Herve Lemaitre, Tomas Paus, Luise Poustka, Sarah Hohmann, Sabina H. Millenet, Juliane N. Frohner, Michael Smolka, Nilakshi Vaidya, Henrik Walter, Robert Whelan, Gunter Schumann, Vincent Frouin, Meritxell Bach Cuadra, Olivier Colliot, Baptiste Couvy-Duchesne
Summary: The temporo-basal region of the human brain consists of the collateral, occipito-temporal, and rhinal sulci. In this study, we manually evaluated the connections between these sulci using MRI data from nearly 3400 individuals, including twins. We found hemisphere-dependent frequency and sexual dimorphism in these connections, with differences between males and females.
BRAIN STRUCTURE & FUNCTION
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Guanghui Fu, Rosana El Jurdi, Lydia Chougar, Didier Dormont, Romain Valabregue, Stephane Lehericy, Olivier Colliot
Summary: Deep learning methods have achieved impressive results in 3D medical image segmentation. However, when guided by voxel-level information alone, the resulting segmentations may contain anatomically aberrant structures. To address this issue, a novel loss function is proposed in this paper to introduce topological priors in deep learning-based segmentation. The proposed method is computationally efficient and easy to implement.
MEDICAL IMAGING 2023
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Ravi Hassanaly, Simona Bottani, Benoit Sauty, Olivier Colliot, Ninon Burgos
Summary: Unsupervised anomaly detection using deep learning models is a popular approach for computer-aided diagnosis, especially in neuroimaging. In this work, the focus is on detecting anomalies from FDG PET images of patients with Alzheimer's disease, which can be subtle and difficult to evaluate. To address this, the researchers propose a framework for evaluating unsupervised anomaly detection approaches by simulating realistic anomalies from healthy images. They demonstrate the use of this framework by evaluating an approach based on a 3D variational autoencoder.
MEDICAL IMAGING 2023
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Sophie Loizillon, Simona Bottani, Aurelien Maire, Sebastian Stroer, Didier Dormont, Olivier Colliot, Ninon Burgos
Summary: Clinical data warehouses (CDWs) provide an opportunity for developing computational tools by containing the medical data of millions of patients. This paper proposes a CNN for the automatic detection of motion in 3D T1-weighted brain MRI to fully exploit CDWs. The framework achieved excellent accuracy in excluding images with severe motion, but weaker performance in detecting mild motion artefacts compared to human raters.
MEDICAL IMAGING 2023
(2023)
Article
Neuroimaging
Arya Yazdan-Panah, Marius Schmidt-Mengin, Vito A. G. Ricigliano, Theodore Soulier, Bruno Stankoff, Olivier Colliot
Summary: Choroid Plexuses (ChP) play a crucial role in producing cerebrospinal fluid (CSF) and have been found to undergo volumetric changes in various neurological diseases. To investigate their role, an automated and reliable ChP segmentation tool is needed for large-scale studies. In this study, we propose a novel 2-step 3D U-Net-based automatic method for ChP segmentation, which minimizes preprocessing steps for ease of use and lower memory requirements.
NEUROIMAGE-CLINICAL
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Blanche Bapst, Aurelien Massire, Franck Mauconduit, Vincent Gras, Nicolas Boulant, Juliette Dufour, Benedetta Bodini, Bruno Stankoff, Alain Luciani, Alexandre Vignaud
Summary: This study redefined the optimization of MP2RAGE parameters to achieve more time-efficient MR acquisitions and used a T-1-based synthetic imaging framework to obtain on-demand T-1-weighted contrasts. The experimental results showed that the proposed time-efficient MP2RAGE protocols significantly reduced acquisition time or improved spatial resolution scans, while generating all typical brain contrasts derived from MP2RAGE.
MAGNETIC RESONANCE IN MEDICINE
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Natalia Dudysheva, Franck Mauconduit, Redha Abdeddaim, Paul-Francois Gapais, Sajad Hosseinnezhadian, Marc Dubois, Nicolas Boulant, Lucie Hertz-Pannier, Alexandre Vignaud, Alexis Amadon
Summary: The restricted specific absorption rate (SAR) (rS) mode allows for coil evaluation within a short time while ensuring safety.
MAGNETIC RESONANCE IN MEDICINE
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Paul-Francois Gapais, Michel Luong, Francois Nizery, Gabriel Maitre, Eric Giacomini, Jules Guillot, Alexandre Vignaud, Djamel Berrahou, Marc Dubois, Redha Abdeddaim, Elodie Georget, Sajad Hosseinnezhadian, Alexis Amadon
Summary: A comprehensive workflow for designing and building fully customized dense receive arrays for MRI is proposed. The workflow includes numerical simulations and circuit model co-simulations to ensure accurate and efficient results. Additive manufacturing is used to efficiently implement arbitrary loop configurations. The experimental results show that the proposed design has comparable SNR and g-factor with a commercial coil, and in vivo imaging results confirm the absence of any unexpected artifacts.
MAGNETIC RESONANCE IN MEDICINE
(2023)
Article
Clinical Neurology
Vincent Planche, Vincent Bouteloup, Isabelle Pellegrin, Jean-Francois Mangin, Bruno Dubois, Pierre-Jean Ousset, Florence Pasquier, Frederic Blanc, Claire Paquet, Olivier Hanon, Karim Bennys, Mathieu Ceccaldi, Cedric Annweiler, Pierre Krolak-Salmon, Olivier Godefroy, David Wallon, Mathilde Sauvee, Claire Boutoleau-Bretonniere, Isabelle Bourdel-Marchasson, Isabelle Jalenques, Genevieve Chene, Carole Dufouil, MEMENTO Study Grp
Summary: In a clinic-based cohort of patients with subjective cognitive complaint or mild cognitive impairment, blood biomarkers may serve as good indicators of underlying pathology but do not contribute significantly to 5-year dementia risk prediction models that include traditional predictors.
