MRI‐based thalamic volumetry in multiple sclerosis using FSL‐FIRST: Systematic assessment of common error modes

Autor: Cassondra Lyman, Dongchan Lee, Hannah Ferrari, Bianca Weinstock-Guttmann, Michael G. Dwyer, Tom A. Fuchs, Niels Bergsland, Robert Zivadinov, Dejan Jakimovski
Rok vydání: 2021
Předmět:
Zdroj: Journal of Neuroimaging. 32:245-252
ISSN: 1552-6569
1051-2284
DOI: 10.1111/jon.12947
Popis: BACKGROUND AND PURPOSE FSL's FMRIB's Integrated Registration and Segmentation Tool (FSL-FIRST) is a widely used and well-validated tool. Automated thalamic segmentation is a common application and an important longitudinal measure for multiple sclerosis (MS). However, FSL-FIRST's algorithm is based on shape models derived from non-MS groups. As such, the present study sought to systematically assess common thalamic segmentation errors made by FSL-FIRST on MRIs from people with multiple sclerosis (PwMS). METHODS FSL-FIRST was applied to generate thalamic segmentation masks for 890 MR images in PwMS. Images and masks were reviewed systematically to classify and quantify errors, as well as associated anatomical variations and MRI abnormalities. For cases with overt errors (n = 362), thalamic masks were corrected and quantitative volumetric differences were calculated. RESULTS In the entire quantitative volumetric group, the mean volumetric error of FSL-FIRST was 2.74% (0.360 ml): among only corrected cases, the mean volumetric error was 6.79% (0.894 ml). The average percent volumetric error associated with seven error types, two anatomical variants, and motions artifacts are reported. Additional analyses showed that the presence of motion artifacts or anatomical variations significantly increased the probability of error (χ2 = 18.14, p
Databáze: OpenAIRE
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