Diagnostic Performance of Automated MRI Volumetry by icobrain dm for Alzheimer’s Disease in a Clinical Setting: A REMEMBER Study
| Autor: | Gaëtane Picard, Jos Tournoy, Eric Mormont, Hanne Struyfs, Eric Triau, Sebastiaan Engelborghs, Annemie Ribbens, Maria Bjerke, Jean Christophe Bier, Erik Fransen, Peter Paul De Deyn, Evert Thiery, Olivier Deryck, Mandy Melissa Jane Wittens, Ruben Houbrechts, Anne Sieben, Jan Versijpt, Christine Bastin, Eric Salmon, Kurt Segers, Adrian Ivanoiu, Bruno Bergmans, Diana M. Sima, Ellis Niemantsverdriet, Bernard Hanseeuw, Florence Benoit, Anne-Marie Vanbinst, Dirk Smeets, Ezequiel de la Rosa, Jean-Claude Lemper |
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| Přispěvatelé: | UCL - SSS/IREC/MONT - Pôle Mont Godinne, UCL - SSS/IONS/NEUR - Clinical Neuroscience, UCL - (MGD) Service de neurologie, UCL - (SLuc) Service de neurologie, Clinical sciences, Neuroprotection & Neuromodulation, Neurology, Geriatrics, Medicine and Pharmacy academic/administration, Supporting clinical sciences, Radiology, Clinical Biology |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
NATIONAL INSTITUTE
0301 basic medicine Male PREDICTION Diagnostic accuracy Disease GUIDELINES Hippocampus RECOMMENDATIONS Lateral ventricles 0302 clinical medicine MARKERS Image Processing Computer-Assisted magnetic resonance imaging Cognitive decline Cognitive impairment medicine.diagnostic_test General Neuroscience Brain General Medicine Alzheimer's disease Magnetic Resonance Imaging Psychiatry and Mental health Clinical Psychology ASYMMETRY Female Radiology ASSOCIATION WORKGROUPS Life Sciences & Biomedicine Alzheimer’s disease Research Article medicine.medical_specialty HIPPOCAMPAL SEGMENTATION Imaging data 03 medical and health sciences mild cognitive impairment Alzheimer Disease medicine Dementia Humans Cognitive Dysfunction Biology Aged Retrospective Studies Science & Technology business.industry neurology Neurosciences biomarkers Magnetic resonance imaging medicine.disease automated volumetry CONVERSION 030104 developmental biology Neurosciences & Neurology Human medicine Geriatrics and Gerontology business 030217 neurology & neurosurgery Software |
| Zdroj: | Journal of Alzheimer's Disease Journal of Alzheimer's disease Journal of Alzheimer's disease, Vol. 83, no. 2, p. 623-639 (2021) |
| ISSN: | 1875-8908 1387-2877 |
| Popis: | BACKGROUND: Magnetic resonance imaging (MRI) has become important in the diagnostic work-up of neurodegenerative diseases. icobrain dm, a CE-labeled and FDA-cleared automated brain volumetry software, has shown potential in differentiating cognitively healthy controls (HC) from Alzheimer's disease (AD) dementia (ADD) patients in selected research cohorts. OBJECTIVE: This study examines the diagnostic value of icobrain dm for AD in routine clinical practice, including a comparison to the widely used FreeSurfer software, and investigates if combined brain volumes contribute to establish an AD diagnosis. METHODS: The study population included HC (n = 90), subjective cognitive decline (SCD, n = 93), mild cognitive impairment (MCI, n = 357), and ADD (n = 280) patients. Through automated volumetric analyses of global, cortical, and subcortical brain structures on clinical brain MRI T1w (n = 820) images from a retrospective, multi-center study (REMEMBER), icobrain dm's (v.4.4.0) ability to differentiate disease stages via ROC analysis was compared to FreeSurfer (v.6.0). Stepwise backward regression models were constructed to investigate if combined brain volumes can differentiate between AD stages. RESULTS: icobrain dm outperformed FreeSurfer in processing time (15-30 min versus 9-32 h), robustness (0 versus 67 failures), and diagnostic performance for whole brain, hippocampal volumes, and lateral ventricles between HC and ADD patients. Stepwise backward regression showed improved diagnostic accuracy for pairwise group differentiations, with highest performance obtained for distinguishing HC from ADD (AUC = 0.914; Specificity 83.0%; Sensitivity 86.3%). CONCLUSION: Automated volumetry has a diagnostic value for ADD diagnosis in routine clinical practice. Our findings indicate that combined brain volumes improve diagnostic accuracy, using real-world imaging data from a clinical setting. ispartof: JOURNAL OF ALZHEIMERS DISEASE vol:83 issue:2 pages:623-639 ispartof: location:Netherlands status: published |
| Databáze: | OpenAIRE |
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