TY - JOUR
T1 - Machine Learning–Based Perivascular Space Volumetry in Alzheimer Disease
AU - Deike, Katerina
AU - Decker, Andreas
AU - Scheyhing, Paul
AU - Harten, Julia
AU - Zimmermann, Nadine
AU - Paech, Daniel
AU - Peters, Oliver
AU - Freiesleben, Silka D.
AU - Schneider, Luisa Sophie
AU - Preis, Lukas
AU - Priller, Josef
AU - Spruth, Eike
AU - Altenstein, Slawek
AU - Lohse, Andrea
AU - Fliessbach, Klaus
AU - Kimmich, Okka
AU - Wiltfang, Jens
AU - Bartels, Claudia
AU - Hansen, Niels
AU - Jessen, Frank
AU - Rostamzadeh, Ayda
AU - Düzel, Emrah
AU - Glanz, Wenzel
AU - Incesoy, Enise I.
AU - Butryn, Michaela
AU - Buerger, Katharina
AU - Janowitz, Daniel
AU - Ewers, Michael
AU - Perneczky, Robert
AU - Rauchmann, Boris Stephan
AU - Teipel, Stefan
AU - Kilimann, Ingo
AU - Goerss, Doreen
AU - Laske, Christoph
AU - Munk, Matthias H.
AU - Spottke, Annika
AU - Roy, Nina
AU - Wagner, Michael
AU - Roeske, Sandra
AU - Heneka, Michael T.
AU - Brosseron, Frederic
AU - Ramirez, Alfredo
AU - Dobisch, Laura
AU - Wolfsgruber, Steffen
AU - Kleineidam, Luca
AU - Yakupov, Renat
AU - Stark, Melina
AU - Schmid, Matthias C.
AU - Berger, Moritz
AU - Hetzer, Stefan
AU - Dechent, Peter
AU - Scheffler, Klaus
AU - Petzold, Gabor C.
AU - Schneider, Anja
AU - Effland, Alexander
AU - Radbruch, Alexander
N1 - Publisher Copyright:
Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.
PY - 2024/9/1
Y1 - 2024/9/1
N2 - Objectives: Impaired perivascular clearance has been suggested as a contributing factor to the pathogenesis of Alzheimer disease (AD). However, it remains unresolved when the anatomy of the perivascular space (PVS) is altered during AD progression. Therefore, this study investigates the association between PVS volume and AD progression in cognitively unimpaired (CU) individuals, both with and without subjective cognitive decline (SCD), and in those clinically diagnosed with mild cognitive impairment (MCI) or mild AD. Materials and Methods: A convolutional neural network was trained using manually corrected, filter-based segmentations (n = 1000) to automatically segment the PVS in the centrum semiovale from interpolated, coronal T2-weighted magnetic resonance imaging scans (n = 894). These scans were sourced from the national German Center for Neurodegenerative Diseases Longitudinal Cognitive Impairment and Dementia Study. Convolutional neural network–based segmentations and those performed by a human rater were compared in terms of segmentation volume, identified PVS clusters, as well as Dice score. The comparison revealed good segmentation quality (Pearson correlation coefficient r = 0.70 with P < 0.0001 for PVS volume, detection rate in cluster analysis = 84.3%, and Dice score = 59.0%). Subsequent multivariate linear regression analysis, adjusted for participants' age, was performed to correlate PVS volume with clinical diagnoses, disease progression, cerebrospinal fluid biomarkers, lifestyle factors, and cognitive function. Cognitive function was assessed using the Mini-Mental State Examination, the Comprehensive Neuropsychological Test Battery, and the Cognitive Subscale of the 13-Item Alzheimer’s Disease Assessment Scale. Results: Multivariate analysis, adjusted for age, revealed that participants with AD and MCI, but not those with SCD, had significantly higher PVS volumes compared with CU participants without SCD (P = 0.001 for each group). Furthermore, CU participants who developed incident MCI within 4.5 years after the baseline assessment showed significantly higher PVS volumes at baseline compared with those who did not progress to MCI (P = 0.03). Cognitive function was negatively correlated with PVS volume across all participant groups (P ≤ 0.005 for each). No significant correlation was found between PVS volume and any of the following parameters: cerebrospinal fluid biomarkers, sleep quality, body mass index, nicotine consumption, or alcohol abuse. Conclusions: The very early changes of PVS volume may suggest that alterations in PVS function are involved in the pathophysiology of AD. Overall, the volumetric assessment of centrum semiovale PVS represents a very early imaging biomarker for AD.
AB - Objectives: Impaired perivascular clearance has been suggested as a contributing factor to the pathogenesis of Alzheimer disease (AD). However, it remains unresolved when the anatomy of the perivascular space (PVS) is altered during AD progression. Therefore, this study investigates the association between PVS volume and AD progression in cognitively unimpaired (CU) individuals, both with and without subjective cognitive decline (SCD), and in those clinically diagnosed with mild cognitive impairment (MCI) or mild AD. Materials and Methods: A convolutional neural network was trained using manually corrected, filter-based segmentations (n = 1000) to automatically segment the PVS in the centrum semiovale from interpolated, coronal T2-weighted magnetic resonance imaging scans (n = 894). These scans were sourced from the national German Center for Neurodegenerative Diseases Longitudinal Cognitive Impairment and Dementia Study. Convolutional neural network–based segmentations and those performed by a human rater were compared in terms of segmentation volume, identified PVS clusters, as well as Dice score. The comparison revealed good segmentation quality (Pearson correlation coefficient r = 0.70 with P < 0.0001 for PVS volume, detection rate in cluster analysis = 84.3%, and Dice score = 59.0%). Subsequent multivariate linear regression analysis, adjusted for participants' age, was performed to correlate PVS volume with clinical diagnoses, disease progression, cerebrospinal fluid biomarkers, lifestyle factors, and cognitive function. Cognitive function was assessed using the Mini-Mental State Examination, the Comprehensive Neuropsychological Test Battery, and the Cognitive Subscale of the 13-Item Alzheimer’s Disease Assessment Scale. Results: Multivariate analysis, adjusted for age, revealed that participants with AD and MCI, but not those with SCD, had significantly higher PVS volumes compared with CU participants without SCD (P = 0.001 for each group). Furthermore, CU participants who developed incident MCI within 4.5 years after the baseline assessment showed significantly higher PVS volumes at baseline compared with those who did not progress to MCI (P = 0.03). Cognitive function was negatively correlated with PVS volume across all participant groups (P ≤ 0.005 for each). No significant correlation was found between PVS volume and any of the following parameters: cerebrospinal fluid biomarkers, sleep quality, body mass index, nicotine consumption, or alcohol abuse. Conclusions: The very early changes of PVS volume may suggest that alterations in PVS function are involved in the pathophysiology of AD. Overall, the volumetric assessment of centrum semiovale PVS represents a very early imaging biomarker for AD.
KW - Alzheimer disease
KW - brain clearance
KW - machine learning
KW - mild cognitive impairment
KW - neurodegeneration
KW - neuroimaging
KW - perivascular space
KW - subjective cognitive decline
UR - http://www.scopus.com/inward/record.url?scp=85200427027&partnerID=8YFLogxK
U2 - 10.1097/RLI.0000000000001077
DO - 10.1097/RLI.0000000000001077
M3 - Article
C2 - 38652067
AN - SCOPUS:85200427027
SN - 0020-9996
VL - 59
SP - 667
EP - 676
JO - Investigative Radiology
JF - Investigative Radiology
IS - 9
ER -