Multiple sclerosis lesions influence the process of image analysis, leading to tissue segmentation problems and biased morphometric estimates. Existing techniques try to reduce this bias by filling all lesions as normal-appearing white matter on T1-weighted images, considering each time-point separately. However, due to lesion segmentation errors and the presence of structures adjacent to the lesions, such as the ventricles and deep grey matter nuclei, filling all lesions with white matter-like intensities introduces errors and artefacts. In this paper, we present a novel lesion filling strategy inspired by in-painting techniques used in computer graphics applications for image completion. The proposed technique uses a five-dimensional (5D), patch-based (multi-modality and multi-time-point), Non-Local Means algorithm that fills lesions with the most plausible texture. We demonstrate that this strategy introduces less bias, fewer artefacts and spurious edges than the current, publicly available techniques. The proposed method is modality-agnostic and can be applied to multiple time-points simultaneously. In addition, it preserves anatomical structures and signal-to-noise characteristics even when the lesions are neighbouring grey matter or cerebrospinal fluid, and avoids excess of blurring or rasterisation due to the choice of the segmentation plane, shape of the lesions, and their size and/or location.

Many studies report an overlap of MRI and clinical findings between patients with relapsing-remitting multiple sclerosis (RRMS) and secondary progressive multiple sclerosis (SPMS), which in part is reflective of inclusion of subjects with variable disease duration and short periods of follow-up. To overcome these limitations, we examined the differences between RRMS and SPMS and the relationship between MRI measures and clinical outcomes 30 years after first presentation with clinically isolated syndrome suggestive of multiple sclerosis. Sixty-three patients were studied 30 years after their initial presentation with a clinically isolated syndrome; only 14% received a disease modifying treatment at any time point. Twenty-seven patients developed RRMS, 15 SPMS and 21 experienced no further neurological events; these groups were comparable in terms of age and disease duration. Clinical assessment included the Expanded Disability Status Scale, 9-Hole Peg Test and Timed 25-Foot Walk and the Brief International Cognitive Assessment For Multiple Sclerosis. All subjects underwent a comprehensive MRI protocol at 3 T measuring brain white and grey matter (lesions, volumes and magnetization transfer ratio) and cervical cord involvement. Linear regression models were used to estimate age- and gender-adjusted group differences between clinical phenotypes after 30 years, and stepwise selection to determine associations between a large sets of MRI predictor variables and physical and cognitive outcome measures. At the 30-year follow-up, the greatest differences in MRI measures between SPMS and RRMS were the number of cortical lesions, which were higher in SPMS (the presence of cortical lesions had 100% sensitivity and 88% specificity), and grey matter volume, which was lower in SPMS. Across all subjects, cortical lesions, grey matter volume and cervical cord volume explained 60% of the variance of the Expanded Disability Status Scale; cortical lesions alone explained 43%. Grey matter volume, cortical lesions and gender explained 43% of the variance of Timed 25-Foot Walk. Reduced cortical magnetization transfer ratios emerged as the only significant explanatory variable for the symbol digit modality test and explained 52% of its variance. Cortical involvement, both in terms of lesions and atrophy, appears to be the main correlate of progressive disease and disability in a cohort of individuals with very long follow-up and homogeneous disease duration, indicating that this should be the target of therapeutic interventions.

Fractional intracellular volume–derived Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumor analysis of multiparametric MRI findings resulted in better classification of clinic... Background In men suspected of having prostate cancer (PCa), up to 50% of men with positive multiparametric MRI (mpMRI) findings (Prostate Imaging Reporting and Data System [PI-RADS] or Likert scor...

Cerebral white matter pathology is a common CNS manifestation of Fabry disease, visualized as white matter hyperintensities on MRI in 42–81% of patients. Diffusion tensor imaging (DTI) MRI is a sensitive technique to quantify microstructural damage within the white matter with potential value as a disease biomarker. We evaluated the pattern of DTI abnormalities in Fabry disease, and their correlations with cognitive impairment, mood, anxiety, disease severity and plasma lyso-Gb3 levels in 31 patients with genetically proven Fabry disease and 19 age-matched healthy control subjects. We obtained average values of fractional anisotropy and mean diffusivity within the white matter and performed voxelwise analysis with tract-based spatial statistics. Using a standardized neuropsychological test battery, we assessed processing speed, executive function, anxiety, depression and disease severity. The mean age (% male) was 44.1 (45%) for patients with Fabry disease and 37.4 (53%) for the healthy control group. In patients with Fabry disease, compared to healthy controls the mean average white matter fractional anisotropy was lower in [0.423 (standard deviation, SD 0.023) versus 0.446 (SD 0.016), P = 0.002] while mean average white matter mean diffusivity was higher (749 × 10⁻⁶ mm²/s (SD 32 × 10⁻⁶) versus 720 × 10⁻⁶ mm²/s (SD 21 × 10⁻⁶), P = 0.004]. Voxelwise statistics showed that the diffusion abnormalities for both fractional anisotropy and mean diffusivity were anatomically widespread. A lesion probability map showed that white matter hyperintensities also had a wide anatomical distribution with a predilection for the posterior centrum semiovale. However, diffusion abnormalities in Fabry disease were not restricted to lesional tissue; compared to healthy controls, the normal appearing white matter in patients with Fabry disease had reduced fractional anisotropy [0.422 (SD 0.022) versus 0.443 (SD 0.017) P = 0.003] and increased mean diffusivity [747 × 10⁻⁶ mm²/s (SD 26 × 10⁻⁶) versus 723 × 10⁻⁶ mm²/s (SD 22 × 10⁻⁶), P = 0.008]. Within patients, average white matter fractional anisotropy and white matter lesion volume showed statistically significant correlations with Digit Symbol Coding Test score (r = 0.558, P = 0.001; and r = −0.633, P ≤ 0.001, respectively). Average white matter fractional anisotropy correlated with the overall Mainz Severity Score Index (r = −0.661, P ≤ 0.001), while average white matter mean diffusivity showed a strong correlation with plasma lyso-Gb3 levels (r = 0.559, P = 0.001). Our findings using DTI confirm widespread areas of microstructural white matter disruption in Fabry disease, extending beyond white matter hyperintensities seen on conventional MRI. Moreover, diffusion measures show strong correlations with cognition (processing speed), clinical disease severity and a putative plasma biomarker of disease activity, making them promising quantitative biomarkers for monitoring Fabry disease severity and progression.