Journal Article

DZNE-2024-00066

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Influence of threshold selection and image sequence in in-vivo segmentation of enlarged perivascular spaces

Valdés Hernández, M. d. C. ; Duarte Coello, R. ; Xu, W. ; Bernal, J.DZNE* ; Cheng, Y. ; Ballerini, L. ; Wiseman, S. J. ; Chappell, F. M. ; Clancy, U. ; Jaime García, D. ; Arteaga Reyes, C. ; Zhang, J.-F. ; Liu, X. ; Hewins, W. ; Stringer, M. ; Doubal, F. ; Thrippleton, M. J. ; Jochems, A. ; Brown, R. ; Wardlaw, J. M.

2024
Elsevier Science Amsterdam [u.a.]

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Please use a persistent id in citations: doi:10.1016/j.jneumeth.2023.110037

Abstract: Growing interest surrounds perivascular spaces (PVS) as a clinical biomarker of brain dysfunction given their association with cerebrovascular risk factors and disease. Neuroimaging techniques allowing quick and reliable quantification are being developed, but, in practice, they require optimisation as their limits of validity are usually unspecified.We evaluate modifications and alternatives to a state-of-the-art (SOTA) PVS segmentation method that uses a vesselness filter to enhance PVS discrimination, followed by thresholding of its response, applied to brain magnetic resonance images (MRI) from patients with sporadic small vessel disease acquired at 3 T.The method is robust against inter-observer differences in threshold selection, but separate thresholds for each region of interest (i.e., basal ganglia, centrum semiovale, and midbrain) are required. Noise needs to be assessed prior to selecting these thresholds, as effect of noise and imaging artefacts can be mitigated with a careful optimisation of these thresholds. PVS segmentation from T1-weighted images alone, misses small PVS, therefore, underestimates PVS count, may overestimate individual PVS volume especially in the basal ganglia, and is susceptible to the inclusion of calcified vessels and mineral deposits. Visual analyses indicated the incomplete and fragmented detection of long and thin PVS as the primary cause of errors, with the Frangi filter coping better than the Jerman filter.Limits of validity to a SOTA PVS segmentation method applied to 3 T MRI with confounding pathology are given.Evidence presented reinforces the STRIVE-2 recommendation of using T2-weighted images for PVS assessment wherever possible. The Frangi filter is recommended for PVS segmentation from MRI, offering robust output against variations in threshold selection and pathology presentation.

Keyword(s): Humans (MeSH) ; Cerebral Small Vessel Diseases: diagnostic imaging (MeSH) ; Cerebral Small Vessel Diseases: complications (MeSH) ; Cerebral Small Vessel Diseases: pathology (MeSH) ; Brain: diagnostic imaging (MeSH) ; Brain: pathology (MeSH) ; Magnetic Resonance Imaging: methods (MeSH) ; Neuroimaging (MeSH) ; Basal Ganglia: diagnostic imaging (MeSH) ; Brain ; Lacunes ; MRI ; Perivascular spaces ; Small vessel disease ; Virchow-Robin spaces ; White matter hyperintensities

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Contributing Institute(s):

1. Clinical Neurophysiology and Memory (AG Düzel)

Research Program(s):

1. 353 - Clinical and Health Care Research (POF4-353) (POF4-353)

Appears in the scientific report 2024

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Database coverage:
; ; ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; Ebsco Academic Search ; Essential Science Indicators ; IF < 5 ; JCR ; Nationallizenz ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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