Striatal shape alteration as a staging biomarker for Parkinson’s Disease☆
| العنوان: | Striatal shape alteration as a staging biomarker for Parkinson’s Disease☆ |
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| المؤلفون: | PERALTA, Maxime, Baxter, John, Khan, Ali, Haegelen, Claire, Jannin, Pierre |
| المساهمون: | Université de Rennes (UNIV-RENNES), Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Robarts Research Institute [Canada], University of Western Ontario (UWO), Fondation pour la Recherche Médicale, Université de Rennes (UR), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), PERALTA, Maxime |
| المصدر: | NeuroImage : Clinical Neuroimage-Clinical Neuroimage-Clinical, Elsevier, 2020, 27, ⟨10.1016/j.nicl.2020.102272⟩ Neuroimage-Clinical, 2020, 27, ⟨10.1016/j.nicl.2020.102272⟩ NeuroImage: Clinical, Vol 27, Iss, Pp 102272-(2020) Neuroimage-Clinical, Elsevier, In press |
| بيانات النشر: | Elsevier, 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], Male, lcsh:Computer applications to medicine. Medical informatics, lcsh:RC346-429, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Morphometric biomarkers, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], Machine learning, Humans, Gray Matter, lcsh:Neurology. Diseases of the nervous system, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, Aged, Putamen, Regular Article, Parkinson Disease, Middle Aged, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], Corpus Striatum, Parkinson’s disease, lcsh:R858-859.7, Staging biomarker, Female, Medical imaging, Caudate Nucleus, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Biomarkers |
| الوصف: | Highlights • Subcortical shape displacement can be used as a diagnosis and staging biomarker. • Brain morphometry allows to detect pre-symptomatic Parkinson’s disease. • Putamen and caudate atrophies are differently informative. • Subcortical shape alteration is orthogonal to the clinical symptomatology. • Stacking classifier is effective to classify subcortical displacement fields. Parkinson’s Disease provokes alterations of subcortical deep gray matter, leading to subtle changes in the shape of several subcortical structures even before the manifestation of motor and non-motor clinical symptoms. We used an automated registration and segmentation pipeline to measure this structural alteration in one early and one advanced Parkinson’s Disease (PD) cohorts, one prodromal stage cohort and one healthy control cohort. These structural alterations are then passed to a machine learning pipeline to classify these populations. Our workflow is able to distinguish different stages of PD based solely on shape analysis of the bilateral caudate nucleus and putamen, with balanced accuracies in the range of 59% to 85%. Furthermore, we compared the significance of each of these subcortical structure, compared the performances of different classifiers on this task, thus quantifying the informativeness of striatal shape alteration as a staging bio-marker for PD. |
| وصف الملف: | application/pdf |
| اللغة: | English |
| تدمد: | 2213-1582 |
| DOI: | 10.1016/j.nicl.2020.102272⟩ |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::d49ba0eabda46f6f8f1ea29965fd7af8 http://europepmc.org/articles/PMC7260673 |
| Rights: | OPEN |
| رقم الانضمام: | edsair.pmid.dedup....d49ba0eabda46f6f8f1ea29965fd7af8 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 22131582 |
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| DOI: | 10.1016/j.nicl.2020.102272⟩ |