Pelizaeus-Merzbacher disease (PMD) is a rare leukodystrophy caused by mutation of the proteolipid protein 1 gene. Defective oligodendrocytes in PMD fail to myelinate axons, causing global neurological dysfunction. Human central nervous system stem cells (HuCNS-SCs) can develop into oligodendrocytes and confer structurally normal myelin when transplanted into a hypomyelinating mouse model. A 1-year open-label phase 1 study was undertaken to evaluate safety and to detect evidence of myelin formation after HuCNS-SC transplantation. Allogeneic HuCNS-SCs were surgically implanted into the frontal lobe white matter in four male subjects with an early-onset severe form of PMD. Immunosuppression was administered for 9 months. Serial neurological evaluations, developmental assessments, and cranial magnetic resonance imaging (MRI) and MR spectroscopy, including high-angular resolution diffusion tensor imaging (DTI), were performed at baseline and after transplantation. The neurosurgical procedure, immunosuppression regimen, and HuCNS-SC transplantation were well tolerated. Modest gains in neurological function were observed in three of the four subjects. No clinical or radiological adverse effects were directly attributed to the donor cells. Reduced T1 and T2 relaxation times were observed in the regions of transplantation 9 months after the procedure in the three subjects. Normalized DTI showed increasing fractional anisotropy and reduced radial diffusivity, consistent with myelination, in the region of transplantation compared to control white matter regions remote to the transplant sites. These phase 1 findings indicate a favorable safety profile for HuCNS-SCs in subjects with PMD. The MRI results suggest durable cell engraftment and donor-derived myelin in the transplanted host white matter.

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In routine practice, nuclear pleomorphism of tumours is assessed by haematoxylin staining of the membrane-bound heterochromatin. However, decoration of the nuclear envelope (NE) through the immunofluorescence staining of NE proteins such as lamin B and emerin can provide a more objective appreciation of the nuclear shape. In breast cancer, nuclear pleomorphism is one of the least reproducible parameters to score histological grade, thus we sought to use NE proteins to improve the reproducibility of nuclear grading. First, immuno-fluorescence staining of NE as well as confocal microscopy and three-dimensional reconstruction of nuclei in cultured cells showed a smooth and uniform NE of normal breast epithelium in contrast to an irregular foldings of the membrane and the presence of deep invaginations leading to the formation of an intranuclear scaffold of NE-bound tubules in breast cancer cells. Following the above methods and criteria, we recorded the degree of NE pleomorphism (NEP) in a series of 273 invasive breast cancers tested by immunofluorescence. A uniform nuclear shape with few irregularities (low NEP) was observed in 135 cases or, alternatively, marked folds of the NE and an intranuclear tubular scaffold (high NEP cases) were observed in 138 cases. The latter features were significantly correlated (P-value <0.002) with lymph node metastases in 54 histological grade 1 and in 173 cancers with low mitotic count. Decoration of the NE might thus be regarded as a novel diagnostic parameter to define the grade of malignancy, which parallels and enhances that provided by routine histological procedures.

SCV loss is a strong predictor of clinical outcomes in PPMS and has shown to be faster and independent of brain MRI metrics compared to relapse-onset MS.

Fingolimod significantly reduced dGM volume loss (including thalamus) vs placebo in patients with RRMS. Reducing dGM and thalamic volume loss might improve long-term outcome.

BackgroundPrevious studies have demonstrated that white matter (WM) lesions bias automated brain tissue classifications and cerebral volume measurements. However, filling WM lesions using the intensity of neighbouring normal-appearing WM has been shown to increase the accuracy of automated volume measurements in the brain. In the present study, we investigate the influence of WM lesions on cortical thickness (CTh) measures and assessed the impact of lesion filling on both cross-sectional/longitudinal and global/regional measurements of CTh in multiple sclerosis (MS) patients.MethodsFifty MS patients were studied at baseline as well as after three and six years of follow-up. CTh was estimated using a fully automated pipeline (CIVET) on T1-weighted magnetic resonance images data acquired at 1.5 Tesla without (original) and with WM lesion filling (filled). WM lesions were semi-automatically segmented and then filled with the mean intensity of the neighbouring voxels. For both original and filled T1 images we investigated and compared the main CIVET’s steps: tissue classification, surfaces generation and CTh measurement.ResultsOn the original T1 images, the majority of WM lesion volume (72%) was wrongly classified as gray matter (GM). After lesion filling the accuracy of WM lesions classification improved significantly (p < 0.001, 94% of WM lesion volume correctly classified) as well as the WM surface generation (p < 0.0001). The mean CTh computed on the original T1 images, overall time points, was significantly thinner (p < 0.001) compared the CTh estimated on the filled T1 images. The vertex-wise longitudinal analysis performed on the filled T1 images showed an increased number of vertices in the fronto-temporal region with a significantly decrease of CTh over time compared the analysis performed on the original images.ConclusionThese results indicate that WM lesions bias the CTh estimation both cross-sectionally as well as longitudinally. The lesion filling approach significantly improved the accuracy of the regional CTh estimation and has an impact also on the global estimation of CTh.

A concern for researchers planning multisite studies is that scanner and T1-weighted sequence-related biases on regional volumes could overshadow true effects, especially for studies with a heterogeneous set of scanners and sequences. Current approaches attempt to harmonize data by standardizing hardware, pulse sequences, and protocols, or by calibrating across sites using phantom-based corrections to ensure the same raw image intensities. We propose to avoid harmonization and phantom-based correction entirely. We hypothesized that the bias of estimated regional volumes is scaled between sites due to the contrast and gradient distortion differences between scanners and sequences. Given this assumption, we provide a new statistical framework and derive a power equation to define inclusion criteria for a set of sites based on the variability of their scaling factors. We estimated the scaling factors of 20 scanners with heterogeneous hardware and sequence parameters by scanning a single set of 12 subjects at sites across the United States and Europe. Regional volumes and their scaling factors were estimated for each site using Freesurfer’s segmentation algorithm and ordinary least squares, respectively. The scaling factors were validated by comparing the theoretical and simulated power curves, performing a leave-one-out calibration of regional volumes, and evaluating the absolute agreement of all regional volumes between sites before and after calibration. Using our derived power equation, we were able to define the conditions under which harmonization is not necessary to achieve 80% power. This approach can inform choice of processing pipelines and outcome metrics for multisite studies based on scaling factor variability across sites, enabling collaboration between clinical and research institutions.

SCV loss over time relates to the number of clinical relapses in RRMS, but overall does not differ between RRMS and SPMS. SCV proved to be a strong predictor of physical disability and disease progression, indicating that SCV may be a suitable marker for monitoring disease activity and severity.