Postmortem Validation of MRI Cortical Volume Measurements in MS

Veronica Popescu, Roel Klaver, Adriaan Versteeg, Pieter Voorn, Jos W. R. Twisk, Frederik Barkhof, Jeroen J. G. Geurts, Hugo Vrenken

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Grey matter (GM) atrophy is a prominent aspect of multiple sclerosis pathology and an important outcome in studies. GM atrophy measurement requires accurate GM segmentation. Several methods are used in vivo for measuring GM volumes in MS, but assessing their validity in vivo remains challenging. In this postmortem study, we evaluated the correlation between postmortem MRI cortical volume or thickness and the cortical thickness measured on histological sections. Sixteen MS brains were scanned in situ using 3DT1‐weighted MRI and these images were used to measure regional cortical volume using FSL‐SIENAX, FreeSurfer, and SPM, and regional cortical thickness using FreeSurfer. Subsequently, cortical thickness was measured histologically in 5 systematically sampled cortical areas. Linear regression analyses were used to evaluate the relation between MRI regional cortical volume or thickness and histological cortical thickness to determine which postprocessing technique was most valid. After correction for multiple comparisons, we observed a significant correlation with the histological cortical thickness for FSL‐SIENAX cortical volume with manual editing (std. β = 0.345, adjusted R2 = 0.105, P = 0.005), and FreeSurfer cortical volume with manual editing (std. β = 0.379, adjusted R2 = 0.129, P = 0.003). In addition, there was a significant correlation between FreeSurfer cortical thickness with manual editing and histological cortical thickness (std. β = 0.381, adjusted R2 = 0.130, P = 0.003). The results support the use of FSL‐SIENAX and FreeSurfer in cases of severe MS pathology. Interestingly none of the methods were significant in automated mode, which supports the use of manual editing to improve the automated segmentation.
Original languageEnglish
Pages (from-to)2223-2233
JournalHuman Brain Mapping
Volume37
Issue number6
DOIs
Publication statusPublished - Jun 2016

Cite this