Quantitative reliability assessment of brain MRI volumetric measurements in type II GM1 gangliosidosis patients

Front Neuroimaging. 2024 Sep 13:3:1410848. doi: 10.3389/fnimg.2024.1410848. eCollection 2024.

Abstract

Purpose: GM1-gangliosidosis (GM1) leads to extensive neurodegenerative changes and atrophy that precludes the use of automated MRI segmentation techniques for generating brain volumetrics. We developed a standardized segmentation protocol for brain MRIs of patients with type II GM1 and then assessed the inter- and intra-rater reliability of this methodology. The volumetric data may be used as a biomarker of disease burden and progression, and standardized methodology may support research into the natural history of the disease which is currently lacking in the literature.

Approach: Twenty-five brain MRIs were included in this study from 22 type II GM1 patients of which 8 were late-infantile subtype and 14 were juvenile subtype. The following structures were segmented by two rating teams on a slice-by-slice basis: whole brain, ventricles, cerebellum, lentiform nucleus, thalamus, corpus callosum, and caudate nucleus. The inter- and intra-rater reliability of the segmentation method was assessed with an intraclass correlation coefficient as well as Sorensen-Dice and Jaccard coefficients.

Results: Based on the Sorensen-Dice and Jaccard coefficients, the inter- and intra-rater reliability of the segmentation method was significantly better for the juvenile patients compared to late-infantile (p < 0.01). In addition, the agreement between the two rater teams and within themselves can be considered good with all p-values < 0.05.

Conclusions: The standardized segmentation approach described here has good inter- and intra-rater reliability and may provide greater accuracy and reproducibility for neuromorphological studies in this group of patients and help to further expand our understanding of the natural history of this disease.

Keywords: GM1 gangliosidosis; brain MRI; inter/intra-rater reliability; segmentation; volumetrics.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was partially funded by Sio Gene Therapeutics, Image Processing and Analysis Core (iPAC) at the University of Massachusetts Chan Medical School, and Office of the Clinical Director at the National Human Genome Research Institute of the National Institutes of Health.