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Objective With potential therapies for many forms of Charcot‐Marie‐Tooth disease (CMT), responsive outcome measures are urgently needed for clinical trials. Quantitative lower limb MRI demonstrated progressive calf intramuscular fat accumulation in the commonest form, CMT1A with large responsiveness. In this study, we evaluated the responsiveness and validity in the three other common forms, due to variants in GJB1 (CMTX1), MPZ (CMT1B) and MFN2 (CMT2A). Methods 22 CMTX1, 21 CMT1B and 21 CMT2A patients and matched controls were assessed at a 1‐year interval. Intramuscular fat fraction (FF) was evaluated using three‐point Dixon MRI at thigh and calf level along with clinical measures including CMT examination score, clinical strength assessment, CMT‐HI and plasma neurofilament light chain. Results All patient groups had elevated muscle fat fraction at thigh and calf levels, with highest thigh FF and atrophy in CMT2A. There was moderate correlation between calf muscle FF and clinical measures (CMTESv2 rho = 0.405; p = 0.001, ankle MRC strength rho = −0.481; p < 0.001). Significant annualised progression in calf muscle FF was seen in all patient groups (CMTX1 2.0 ± 2.0%, p < 0.001, CMT1B 1.6 ± 2.1% p = 0.004 and CMT2A 1.6 ± 2.1% p = 0.002). Greatest increase was seen in patients with 10–70% FF at baseline (calf 2.7 ± 2.3%, p < 0.0001 and thigh 1.7 ± 2.1%, p = 0.01). Interpretation Our results confirm that calf muscle FF is highly responsive over 12 months in three additional common forms of CMT which together with CMT1A account for 90% of genetically confirmed cases. Calf muscle MRI FF should be a valuable outcome measure in upcoming CMT clinical trials.

Background Magnetic resonance imaging (MRI) quantification of intramuscular fat accumulation is a responsive biomarker in neuromuscular diseases. Despite emergence of automated methods, manual muscle segmentation remains an essential foundation. We aimed to develop a training programme for new observers to demonstrate competence in lower limb muscle segmentation and establish reliability benchmarks for future human observers and machine learning segmentation packages. Methods The learning phase of the training programme comprised a training manual, direct instruction, and eight lower limb MRI scans with reference standard large and small regions of interest (ROIs). The assessment phase used test–retest scans from two patients and two healthy controls. Interscan and interobserver reliability metrics were calculated to identify underperforming outliers and to determine competency benchmarks. Results Three experienced observers undertook the assessment phase, whilst eight new observers completed the full training programme. Two of the new observers were identified as underperforming outliers, relating to variation in size or consistency of segmentations; six had interscan and interobserver reliability equivalent to those of experienced observers. The calculated benchmark for the Sørensen-Dice similarity coefficient between observers was greater than 0.87 and 0.92 for individual thigh and calf muscles, respectively. Interscan and interobserver reliability were significantly higher for large than small ROIs (all p  < 0.001). Conclusions We developed, implemented, and analysed the first formal training programme for manual lower limb muscle segmentation. Large ROI showed superior reliability to small ROI for fat fraction assessment. Relevance statement Observers competent in lower limb muscle segmentation are critical to application of quantitative muscle MRI biomarkers in neuromuscular diseases. This study has established competency benchmarks for future human observers or automated segmentation methods. Key points • Observers competent in muscle segmentation are critical for quantitative muscle MRI biomarkers. • A training programme for muscle segmentation was undertaken by eight new observers. • We established competency benchmarks for future human observers or automated segmentation methods. Graphical Abstract

BackgroundLower limb muscle magnetic resonance imaging (MRI) obtained fat fraction (FF) can detect disease progression in patients with Charcot-Marie-Tooth disease 1A (CMT1A). However, analysis is time-consuming and requires manual segmentation of lower limb muscles. We aimed to assess the responsiveness, efficiency and accuracy of acquiring FF MRI using an artificial intelligence-enabled automated segmentation technique.MethodsWe recruited 20 CMT1A patients and 7 controls for assessment at baseline and 12 months. The three-point-Dixon fat water separation technique was used to determine thigh-level and calf-level muscle FF at a single slice using regions of interest defined using Musclesense, a trained artificial neural network for lower limb muscle image segmentation. A quality control (QC) check and correction of the automated segmentations was undertaken by a trained observer.ResultsThe QC check took on average 30 seconds per slice to complete. Using QC checked segmentations, the mean calf-level FF increased significantly in CMT1A patients from baseline over an average follow-up of 12.5 months (1.15%±1.77%, paired t-test p=0.016). Standardised response mean (SRM) in patients was 0.65. Without QC checks, the mean FF change between baseline and follow-up, at 1.15%±1.68% (paired t-test p=0.01), was almost identical to that seen in the corrected data, with a similar overall SRM at 0.69.ConclusionsUsing automated image segmentation for the first time in a longitudinal study in CMT, we have demonstrated that calf FF has similar responsiveness to previously published data, is efficient with minimal time needed for QC checks and is accurate with minimal corrections needed.

Twitter is a free, open access social media platform that is widely used in medicine by physicians, scientists, and patients. It provides an opportunity for advocacy, education, and collaboration. However, it is likely not utilized to its full advantage by many disciplines in medicine, and pitfalls exist in its use. In particular, there has not been a review of Twitter use and its applications in the field of neurology. This review seeks to provide an understanding of the current use of Twitter in the field of neurology to assist neurologists in engaging with this potentially powerful application to support their work.

The histiocytoses are a group of rare disorders characterised by the accumulation of neoplastic or non-neoplastic activated histiocytes in various tissues. Phenotypes vary widely from cutaneous lesions or lymphadenopathy that regress spontaneously to disseminated disease with poor prognosis. Neurological symptoms can be a presenting feature or appear during the course of disease. We present a challenging diagnostic and management case of Rosai-Dorfman-Destombes disease in a 48-year-old woman with a relapsing, partially steroid-responsive syndrome comprising patchy, non-length-dependent radiculoneuropathy with diffuse pachymeningitis and widespread systemic disease, and recent dramatic response to novel mitogen-activated kinase pathway inhibition. We discuss the clinical characteristics, diagnosis, recent breakthroughs in pathogenesis and emerging treatment options for Rosai-Dorfman disease and for the histiocytoses with neurological sequelae, including Langerhans cell histiocytosis and Erdheim-Chester disease.

BackgroundA problem frequently faced by neurologists is the interpretation of genetic variants of unknown significance(VUS). Unlike in many muscle diseases, specific patterns of muscle involvement are not typically demonstrated on muscle MRI of inherited neuropathy patients. Imaging muscle involvement can be of assistance when assessing VUS.Case ExamplesTwo unrelated individuals with axonal CMT were identified to have a novel p.Lys554Glu DNM2 mutation. Neuromuscular MRI was consistent with the clinical findings and similar to literature descriptions, supporting the pathogenicity of this variant.Spinal Muscular Atrophy Lower Extremity Dominant (SMA-LED) due to DYNC1H1 mutations can be associ- ated with sparing and relative hypertrophy of the adductor longus and semitendinosus muscles at the thigh level, with diffuse involvement at the calf level, sparing the anterior-medial muscles1 on MRI. These features were demonstrated in the imaging of a proband with SMA-LED has two mutations in DYNC1H1, one of which is novel. The novel p.His75Pro mutation was also found in his mother who has normal clinical examination and neuromuscular MRI, suggesting that the previously described p.Arg251His mutation2 was the cause of the neuromuscular phenotype in the proband.DiscussionMRI has a role supporting the diagnosis of inherited neuropathies, and in evaluating VUS.Scoto et al. Novel mutations expand the clinical spectrum of DYNC1H1-associated SMA. Neurology.2015Feb17;84:668–679Antoniadi et al. Application of targeted multi-gene panel testing for the diagnosis of inherited peripheral neuropathy provides high diagnostic yield.BMCMedGenet.2015Sep21;16:84.c.doherty@ucl.ac.uk

BackgroundA 22-year-old woman was initially assessed in the context of a family history of distal wasting and weakness, typically with upper limb onset, then lower limb involvement. When assessed as a child her phenotype was recognised to be atypical compared to her sister, but she was thought to be affected. Ultimately the family was diagnosed with distal hereditary motor neuropathy due to a GARS mutation. However, this patient did not carry the mutation, prompting further evaluation.CaseAt age 11 the left foot was smaller with some toe clawing and cavus deformity. Left sided wasting of tibialis anterior and the posterior compartment was seen, ankle dorsiflexors were grade 3.ResultsNerve conduction studies and EMG were normal in the right leg and arms. Chronic denervation was identified in L4, L5 and S1. MRI of lumbar spine was normal. However, 2 areas of marked thickening and enhancement were seen in the left sciatic nerve in the upper thigh and a further lesion in the mid- thigh. Fascicular preservation of the nerve was felt to be strongly suggestive of a perineurioma.DiscussionThis case highlights the importance of careful phenotyping when validating novel variants in potentially causative genes.c.doherty@ucl.ac.uk

Charcot-Marie-Tooth (CMT) disease and related disorders encompass a phenotypically and genetically heterogeneous group of disorders. Our diagnostic approach to CMT has been revolutionised by the advent and use of next-generation sequencing (NGS) technologies with applications in CMT gene panels, whole exome and whole genome sequencing, mitochondrial sequencing and high-throughput transcriptome sequencing.We present the up to date evidence pertaining to the application of these technologies in CMT diagnostics and also discuss what challenges they bring in relation to variant interpretation. Phenotypic, genetic and bioinformatic evidence should be used to overcome these challenges, and we discuss how setting a maximum credible population allele frequency for pathogenic variants in dominant and recessive CMT genes is crucial in filtering efficiently NGS-derived variants.Whole genome sequencing as a single molecular genetic test is very appealing and, in the context of the 100,000 Genome Project, we suggest how its application into CMT clinical practice can happen with a balance between improved diagnostic yield and burden of variant analysis.