Sub-millimeter imaging of brain-free water for rapid volume assessment in atrophic brains

Introduction: Cerebral atrophy occurs in healthy aging, and in disease processes such as multiple sclerosis (MS), it correlates with disability accumulation. Imaging measurements of brain atrophy are commonly based on tissue segmentation, which is susceptible to classification errors and inconsistencies. High-resolution imaging techniques with strong contrast between brain parenchyma and cerebrospinal fluid (CSF) might allow fully automated, rapid, threshold-based determination of the free water in the brain. We hypothesized that total brain-free-water (BFW) volume and BFW volume expressed as a normalized fraction of the intracranial volume ("BFW fraction"), determined from heavily T2-weighted images, would be useful surrogates for cerebral atrophy and therefore would correlate with clinical measures of disability in MS.

Methods: Whole brains of 83 MS cases and 7 healthy volunteers were imaged with a 4.7-min, heavily T2-weighted sequence on a 3T MRI scanner, acquiring 650-μm isotropic voxels. MS cases were clinically assessed on the Expanded Disability Status Scale (EDSS), Scripps Neurological Rating Scale (SNRS), Paced Auditory Serial Addition Test (PASAT), 9-Hole Peg Test (9HPT), Symbol Digit Modalities Test (SDMT), and 25-Foot Timed Walk. Twelve of the MS cases were rescanned within an average of 1.8 months to assess reproducibility. Automated calculations of BFW volume and BFW fraction were correlated with clinical measures of disability upon adjusting for age and sex. Results were compared to data from T1-based approaches (SIENAX and Lesion-TOADS).

Results and discussion: BFW volume was automatically derived from heavily T2-weighted images with no need for separate skull stripping. BFW volume and fraction had mean scan-rescan coefficients of variation of 1.5% and 1.9%, respectively, similar to the T1-based approaches tested here. BFW fraction more strongly correlated with clinical measures than T1-derived results. Among those clinical measures, modality-specific disability scores, such as SDMT and 9HPT, were more strongly associated with BFW fraction than composite measures, such as EDSS and SNRS.

Conclusion: The BFW method robustly estimates cerebral atrophy in an automated, fast, and reliable manner, and as such may prove a useful addition to imaging protocols for clinical practice and trials.