Academic Journal
Cortical thickness and grey-matter volume anomaly detection in individual MRI scans: Comparison of two methods
| العنوان: | Cortical thickness and grey-matter volume anomaly detection in individual MRI scans: Comparison of two methods |
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| المؤلفون: | David Romascano, Michael Rebsamen, Piotr Radojewski, Timo Blattner, Richard McKinley, Roland Wiest, Christian Rummel |
| المصدر: | NeuroImage: Clinical, Vol 43, Iss , Pp 103624- (2024) |
| بيانات النشر: | Elsevier, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Computer applications to medicine. Medical informatics LCC:Neurology. Diseases of the nervous system |
| مصطلحات موضوعية: | Normative modeling, MRI, Brain morphometry, Alzheimer’s disease, Personalized medicine, Clinical decision support, Computer applications to medicine. Medical informatics, R858-859.7, Neurology. Diseases of the nervous system, RC346-429 |
| الوصف: | Over the past decades, morphometric analysis of brain MRI has contributed substantially to the understanding of healthy brain structure, development and aging as well as to improved characterisation of disease related pathologies. Certified commercial tools based on normative modeling of these metrics are meanwhile available for diagnostic purposes, but they are cost intensive and their clinical evaluation is still in its infancy. Here we have compared the performance of “ScanOMetrics”, an open-source research-level tool for detection of statistical anomalies in individual MRI scans, depending on whether it is operated on the output of FreeSurfer or of the deep learning based brain morphometry tool DL + DiReCT. When applied to the public OASIS3 dataset, containing patients with Alzheimer’s disease (AD) and healthy controls (HC), cortical thickness anomalies in patient scans were mainly detected in regions that are known as predilection areas of cortical atrophy in AD, regardless of the software used for extraction of the metrics. By contrast, anomaly detections in HCs were up to twenty-fold reduced and spatially unspecific using both DL + DiReCT and FreeSurfer. Progression of the atrophy pattern with clinical dementia rating (CDR) was clearly observable with both methods. DL + DiReCT provided results in less than 25 min, more than 15 times faster than FreeSurfer. This difference in computation time might be relevant when considering application of this or similar methodology as diagnostic decision support for neuroradiologists. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2213-1582 |
| Relation: | http://www.sciencedirect.com/science/article/pii/S2213158224000639; https://doaj.org/toc/2213-1582 |
| DOI: | 10.1016/j.nicl.2024.103624 |
| URL الوصول: | https://doaj.org/article/d88d96c18a3f4d5892f703ebedef44a9 |
| رقم الانضمام: | edsdoj.88d96c18a3f4d5892f703ebedef44a9 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 22131582 |
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| DOI: | 10.1016/j.nicl.2024.103624 |