Familial childhood onset, slowly progressive myopathy plus cardiomyopathy expands the phenotype related to variants in the TTN gene.

This report describes a novel TTN -related phenotype in two brothers, both affected by a childhood onset, very slowly progressive myopathy with cores, associated with dilated cardiomyopathy only in their late disease stages. Clinical exome sequencing documented in both siblings the heterozygous c.2089A>T and c.19426+2T>A variants in TTN. The c.2089A>T, classified in ClinVar as possibly pathogenic, introduces a premature stop codon in exon 14, whereas the c.19426+2T>A affects TTN alternative splicing. The unfeasibility of segregation studies prevented us from establishing the inheritance mode of the muscle disease in this family, although the lack of any reported muscle or heart symptoms in both parents might support an autosomal recessive transmission. In this view, the occurrence of cardiomyopathy in both probands might be related to the c.2089A>T truncating variant in exon 14, and the childhood onset, slowly progressive myopathy to the c.19426+2T>A splicing variant, possibly allowing translation of an almost full length TTN protein.

Hospital admissions from the emergency department of adult patients affected by myopathies.

BACKGROUND AND PURPOSE: Myopathies are associated with classic signs and symptoms, but also with possible life-threatening complications that may require assistance in an emergency setting. This phenomenon is understudied in the literature. We aimed to assess the presentation, management, and outcomes of clinical manifestations potentially related to a muscle disorder requiring referral to the adult emergency department (ED) and hospitalization. METHODS: Anonymized patient data retrieved using the International Classification of Diseases, Ninth Revision codes related to muscle disorders over 4 years were retrospectively analyzed. Medical reports were evaluated to extract demographic and clinical variables, along with outcomes. Two groups were defined based on the presence (known diagnosis [KD] group) or absence (unknown diagnosis [UD] group) of a diagnosed muscle disorder at arrival. RESULTS: A total of 244 patients were included, 51% of whom were affected by a known myopathy, predominantly limb-girdle muscular dystrophies and myotonic dystrophies. The main reasons for ED visits in the KD group were respiratory issues, worsening of muscle weakness, and gastrointestinal problems. Heart complications were less prevalent. In the UD group, 27 patients received a new diagnosis of a specific primary muscle disorder after the ED access, mostly an inflammatory myopathy. Death during hospitalization was recorded in 26 patients, with a higher rate in the KD group and in patients affected by mitochondrial and inflammatory myopathies. Sepsis and dyspnea were associated with increased death risk. CONCLUSIONS: Respiratory complications are the most common reason for myopathic patients accessing the ED, followed by gastrointestinal issues. Infections are severe threats and, once hospitalized, these patients have relatively high mortality.

Characterization of D4Z4 alleles and assessment of de novo cases in Facioscapulohumeral dystrophy (FSHD) in a cohort of Italian families.

Facioscapulohumeral dystrophy (FSHD) is an autosomal dominant disease, although 10%-30% of cases are sporadic. However, this percentage may include truly de novo patients (carrying a reduced D4Z4 allele that is not present in either of the parents) and patients with apparently sporadic disease resulting from mosaicism, non-penetrance, or complex genetic situations in either patients or parents. In this study, we characterized the D4Z4 Reduced Alleles (DRA) and evaluated the frequency of truly de novo cases in FSHD1 in a cohort of DNA samples received consecutively for FSHD-diagnostic from 100 Italian families. The D4Z4 testing revealed that 60 families reported a DRA compatible with FSHD1 (1-10 RU). The DRA co-segregated with the disease in most cases. Five families with truly de novo cases were identified, suggesting that this condition may be slightly lower (8%) than previously reported. In addition, D4Z4 characterization in the investigated families showed 4% of mosaic cases and 2% with translocations. This study further highlighted the importance of performing family studies for clarifying apparently sporadic FSHD cases, with significant implications for genetic counseling, diagnosis, clinical management, and procreative choices for patients and families.

Muscle fibrosis as a prognostic biomarker in facioscapulohumeral muscular dystrophy: a retrospective cohort study.

Facioscapulohumeral muscular dystrophy (FSHD) is an autosomal dominant epigenetic disorder with highly variable muscle involvement and disease progression. Ongoing clinical trials, aimed at counteracting muscle degeneration and disease progression in FSHD patients, increase the need for reliable biomarkers. Muscle magnetic resonance imaging (MRI) studies showed that the appearance of STIR-positive (STIR+) lesions in FSHD muscles represents an initial stage of muscle damage, preceding irreversible adipose changes. Our study aimed to investigate fibrosis, a parameter of muscle degeneration undetectable by MRI, in relation to disease activity and progression of FSHD muscles. We histologically evaluated collagen in FSHD1 patients' (STIR+ n = 27, STIR- n = 28) and healthy volunteers' (n = 12) muscles by picrosirius red staining. All patients (n = 55) performed muscle MRI before biopsy, 45 patients also after 1 year and 36 patients also after 2 years. Fat content (T1 signal) and oedema/inflammation (STIR signal) were evaluated at baseline and at 1- and 2-year MRI follow-up. STIR+ muscles showed significantly higher collagen compared to both STIR- (p = 0.001) and healthy muscles (p < 0.0001). STIR- muscles showed a higher collagen content compared to healthy muscles (p = 0.0194). FSHD muscles with a worsening in fatty infiltration during 1- (P = 0.007) and 2-year (P < 0.0001) MRI follow-up showed a collagen content of 3.6- and 3.7-fold higher compared to FSHD muscles with no sign of progression. Moreover, the fibrosis was significantly higher in STIR+ muscles who showed a worsening in fatty infiltration in a timeframe of 2 years compared to both STIR- (P = 0.0006) and STIR+ muscles with no sign of progression (P = 0.02). Fibrosis is a sign of muscle degeneration undetectable at MRI never deeply investigated in FSHD patients. Our data show that 23/27 of STIR+ and 12/28 STIR- muscles have a higher amount of collagen deposition compared to healthy muscles. Fibrosis is higher in FSHD muscles with a worsening in fatty infiltration thus suggesting that its evaluation with innovative non-invasive techniques could be a candidate prognostic biomarker for FSHD, to be used to stratify patients and to evaluate the efficacy of therapeutic treatments.

Whole exome sequencing highlights rare variants in CTCF, DNMT1, DNMT3A, EZH2 and SUV39H1 as associated with FSHD.

Introduction: Despite the progress made in the study of Facioscapulohumeral Dystrophy (FSHD), the wide heterogeneity of disease complicates its diagnosis and the genotype-phenotype correlation among patients and within families. In this context, the present work employed Whole Exome Sequencing (WES) to investigate known and unknown genetic contributors that may be involved in FSHD and may represent potential disease modifiers, even in presence of a D4Z4 Reduced Allele (DRA). Methods: A cohort of 126 patients with clinical signs of FSHD were included in the study, which were characterized by D4Z4 sizing, methylation analysis and WES. Specific protocols were employed for D4Z4 sizing and methylation analysis, whereas the Illumina® Next-Seq 550 system was utilized for WES. The study included both patients with a DRA compatible with FSHD diagnosis and patients with longer D4Z4 alleles. In case of patients harboring relevant variants from WES, the molecular analysis was extended to the family members. Results: The WES data analysis highlighted 20 relevant variants, among which 14 were located in known genetic modifiers (SMCHD1, DNMT3B and LRIF1) and 6 in candidate genes (CTCF, DNMT1, DNMT3A, EZH2 and SUV39H1). Most of them were found together with a permissive short (4-7 RU) or borderline/long DRA (8-20 RU), supporting the possibility that different genes can contribute to disease heterogeneity in presence of a FSHD permissive background. The segregation and methylation analysis among family members, together with clinical findings, provided a more comprehensive picture of patients. Discussion: Our results support FSHD pathomechanism being complex with a multigenic contribution by several known (SMCHD1, DNMT3B, LRIF1) and possibly other candidate genes (CTCF, DNMT1, DNMT3A, EZH2, SUV39H1) to disease penetrance and expressivity. Our results further emphasize the importance of extending the analysis of molecular findings within the proband's family, with the purpose of providing a broader framework for understanding single cases and allowing finer genotype-phenotype correlations in FSHD-affected families.

Radiomics and machine learning applied to STIR sequence for prediction of quantitative parameters in facioscapulohumeral disease.

Purpose: Quantitative Muscle MRI (qMRI) is a valuable and non-invasive tool to assess disease involvement and progression in neuromuscular disorders being able to detect even subtle changes in muscle pathology. The aim of this study is to evaluate the feasibility of using a conventional short-tau inversion recovery (STIR) sequence to predict fat fraction (FF) and water T2 (wT2) in skeletal muscle introducing a radiomic workflow with standardized feature extraction combined with machine learning algorithms. Methods: Twenty-five patients with facioscapulohumeral muscular dystrophy (FSHD) were scanned at calf level using conventional STIR sequence and qMRI techniques. We applied and compared three different radiomics workflows (WF1, WF2, WF3), combined with seven Machine Learning regression algorithms (linear, ridge and lasso regression, tree, random forest, k-nearest neighbor and support vector machine), on conventional STIR images to predict FF and wT2 for six calf muscles. Results: The combination of WF3 and K-nearest neighbor resulted to be the best predictor model of qMRI parameters with a mean absolute error about ± 5 pp for FF and ± 1.8 ms for wT2. Conclusion: This pilot study demonstrated the possibility to predict qMRI parameters in a cohort of FSHD subjects starting from conventional STIR sequence.

Artificial Intelligence for Evaluation of Retinal Vasculopathy in Facioscapulohumeral Dystrophy Using OCT Angiography: A Case Series.

Facioscapulohumeral muscular dystrophy (FSHD) is a slowly progressive muscular dystrophy with a wide range of manifestations including retinal vasculopathy. This study aimed to analyse retinal vascular involvement in FSHD patients using fundus photographs and optical coherence tomography-angiography (OCT-A) scans, evaluated through artificial intelligence (AI). Thirty-three patients with a diagnosis of FSHD (mean age 50.4 ± 17.4 years) were retrospectively evaluated and neurological and ophthalmological data were collected. Increased tortuosity of the retinal arteries was qualitatively observed in 77% of the included eyes. The tortuosity index (TI), vessel density (VD), and foveal avascular zone (FAZ) area were calculated by processing OCT-A images through AI. The TI of the superficial capillary plexus (SCP) was increased (p < 0.001), while the TI of the deep capillary plexus (DCP) was decreased in FSHD patients in comparison to controls (p = 0.05). VD scores for both the SCP and the DCP results increased in FSHD patients (p = 0.0001 and p = 0.0004, respectively). With increasing age, VD and the total number of vascular branches showed a decrease (p = 0.008 and p < 0.001, respectively) in the SCP. A moderate correlation between VD and EcoRI fragment length was identified as well (r = 0.35, p = 0.048). For the DCP, a decreased FAZ area was found in FSHD patients in comparison to controls (t (53) = -6.89, p = 0.01). A better understanding of retinal vasculopathy through OCT-A can support some hypotheses on the disease pathogenesis and provide quantitative parameters potentially useful as disease biomarkers. In addition, our study validated the application of a complex toolchain of AI using both ImageJ and Matlab to OCT-A angiograms.

D4Z4 Methylation Levels Combined with a Machine Learning Pipeline Highlight Single CpG Sites as Discriminating Biomarkers for FSHD Patients.

The study describes a protocol for methylation analysis integrated with Machine Learning (ML) algorithms developed to classify Facio-Scapulo-Humeral Dystrophy (FSHD) subjects. The DNA methylation levels of two D4Z4 regions (DR1 and DUX4-PAS) were assessed by an in-house protocol based on bisulfite sequencing and capillary electrophoresis, followed by statistical and ML analyses. The study involved two independent cohorts, namely a training group of 133 patients with clinical signs of FSHD and 150 healthy controls (CTRL) and a testing set of 27 FSHD patients and 25 CTRL. As expected, FSHD patients showed significantly reduced methylation levels compared to CTRL. We utilized single CpG sites to develop a ML pipeline able to discriminate FSHD subjects. The model identified four CpGs sites as the most relevant for the discrimination of FSHD subjects and showed high metrics values (accuracy: 0.94, sensitivity: 0.93, specificity: 0.96). Two additional models were developed to differentiate patients with lower D4Z4 size and patients who might carry pathogenic variants in FSHD genes, respectively. Overall, the present model enables an accurate classification of FSHD patients, providing additional evidence for DNA methylation as a powerful disease biomarker that could be employed for prioritizing subjects to be tested for FSHD.

Non-myogenic mesenchymal cells contribute to muscle degeneration in facioscapulohumeral muscular dystrophy patients.

Muscle-resident non-myogenic mesenchymal cells play key roles that drive successful tissue regeneration within the skeletal muscle stem cell niche. These cells have recently emerged as remarkable therapeutic targets for neuromuscular disorders, although to date they have been poorly investigated in facioscapulohumeral muscular dystrophy (FSHD). In this study, we characterised the non-myogenic mesenchymal stromal cell population in FSHD patients' muscles with signs of disease activity, identified by muscle magnetic resonance imaging (MRI), and compared them with those obtained from apparently normal muscles of FSHD patients and from muscles of healthy, age-matched controls. Our results showed that patient-derived cells displayed a distinctive expression pattern of mesenchymal markers, along with an impaired capacity to differentiate towards mature adipocytes in vitro, compared with control cells. We also demonstrated a significant expansion of non-myogenic mesenchymal cells (identified as CD201- or PDGFRA-expressing cells) in FSHD muscles with signs of disease activity, which correlated with the extent of intramuscular fibrosis. In addition, the accumulation of non-myogenic mesenchymal cells was higher in FSHD muscles that deteriorate more rapidly. Our results prompt a direct association between an accumulation, as well as an altered differentiation, of non-myogenic mesenchymal cells with muscle degeneration in FSHD patients. Elucidating the mechanisms and cellular interactions that are altered in the affected muscles of FSHD patients could be instrumental to clarify disease pathogenesis and identifying reliable novel therapeutic targets.

Dynamic magnetic resonance imaging of muscle contraction in facioscapulohumeral muscular dystrophy.

Quantitative muscle MRI (water-T2 and fat mapping) is being increasingly used to assess disease involvement in muscle disorders, while imaging techniques for assessment of the dynamic and elastic muscle properties have not yet been translated into clinics. In this exploratory study, we quantitatively characterized muscle deformation (strain) in patients affected by facioscapulohumeral muscular dystrophy (FSHD), a prevalent muscular dystrophy, by applying dynamic MRI synchronized with neuromuscular electrical stimulation (NMES). We evaluated the quadriceps muscles in 34 ambulatory patients and 13 healthy controls, at 6-to 12-month time intervals. While a subgroup of patients behaved similarly to controls, for another subgroup the median strain decreased over time (approximately 57% over 1.5 years). Dynamic MRI parameters did not correlate with quantitative MRI. Our results suggest that the evaluation of muscle contraction by NMES-MRI is feasible and could potentially be used to explore the elastic properties and monitor muscle involvement in FSHD and other neuromuscular disorders.

Expanding the clinical-pathological and genetic spectrum of RYR1-related congenital myopathies with cores and minicores: an Italian population study.

Mutations in the RYR1 gene, encoding ryanodine receptor 1 (RyR1), are a well-known cause of Central Core Disease (CCD) and Multi-minicore Disease (MmD). We screened a cohort of 153 patients carrying an histopathological diagnosis of core myopathy (cores and minicores) for RYR1 mutation. At least one RYR1 mutation was identified in 69 of them and these patients were further studied. Clinical and histopathological features were collected. Clinical phenotype was highly heterogeneous ranging from asymptomatic or paucisymptomatic hyperCKemia to severe muscle weakness and skeletal deformity with loss of ambulation. Sixty-eight RYR1 mutations, generally missense, were identified, of which 16 were novel. The combined analysis of the clinical presentation, disease progression and the structural bioinformatic analyses of RYR1 allowed to associate some phenotypes to mutations in specific domains. In addition, this study highlighted the structural bioinformatics potential in the prediction of the pathogenicity of RYR1 mutations. Further improvement in the comprehension of genotype-phenotype relationship of core myopathies can be expected in the next future: the actual lack of the human RyR1 crystal structure paired with the presence of large intrinsically disordered regions in RyR1, and the frequent presence of more than one RYR1 mutation in core myopathy patients, require designing novel investigation strategies to completely address RyR1 mutation effect.

Deep learning for automatic segmentation of thigh and leg muscles.

OBJECTIVE: In this study we address the automatic segmentation of selected muscles of the thigh and leg through a supervised deep learning approach. MATERIAL AND METHODS: The application of quantitative imaging in neuromuscular diseases requires the availability of regions of interest (ROI) drawn on muscles to extract quantitative parameters. Up to now, manual drawing of ROIs has been considered the gold standard in clinical studies, with no clear and universally accepted standardized procedure for segmentation. Several automatic methods, based mainly on machine learning and deep learning algorithms, have recently been proposed to discriminate between skeletal muscle, bone, subcutaneous and intermuscular adipose tissue. We develop a supervised deep learning approach based on a unified framework for ROI segmentation. RESULTS: The proposed network generates segmentation maps with high accuracy, consisting in Dice Scores ranging from 0.89 to 0.95, with respect to "ground truth" manually segmented labelled images, also showing high average performance in both mild and severe cases of disease involvement (i.e. entity of fatty replacement). DISCUSSION: The presented results are promising and potentially translatable to different skeletal muscle groups and other MRI sequences with different contrast and resolution.

Diagnostic magnetic resonance imaging biomarkers for facioscapulohumeral muscular dystrophy identified by machine learning.

BACKGROUND: The diagnosis of facioscapulohumeral muscular dystrophy (FSHD) can be challenging in patients not displaying the classical phenotype or with atypical clinical features. Despite the identification by magnetic resonance imaging (MRI) of selective patterns of muscle involvement, their specificity and added diagnostic value are unknown. METHODS: We aimed to identify the radiological features more useful to distinguish FSHD from other myopathies and test the diagnostic accuracy of MRI. A retrospective cohort of 295 patients (187 FSHD, 108 non-FSHD) studied by upper and lower-limb muscle MRI was analyzed. Scans were evaluated for the presence of 15 radiological features. A random forest machine learning algorithm was used to identify the most relevant for FSHD diagnosis. Different patterns were created by their combination and diagnostic accuracy of each of them was tested. RESULTS: The combination of trapezius involvement and bilateral subscapularis muscle sparing achieved the best diagnostic accuracy (0.89, 95% Confidence Interval [0.85-0.92]) with 0.90 [0.85-0.94] sensitivity and 0.88 [0.80-0.93] specificity. This pattern correctly identified 91% atypical FSHD patients of our cohort. The combination of trapezius involvement, bilateral subscapularis and iliopsoas sparing and asymmetric involvement of upper and lower-limb muscles was pathognomonic for FSHD, yielding a specificity of 0.99 [0.95-1.00]. CONCLUSIONS: We identified MRI patterns that showed a high diagnostic power in promptly discriminating FSHD from other muscle disorders, with comparable performance irrespective of typical or atypical clinical features. Upper girdle in addition to lower-limb muscle imaging should be extensively implemented in the diagnostic workup to support or exclude a diagnosis of FSHD.

Muscle magnetic resonance imaging in myotonic dystrophy type 1 (DM1): Refining muscle involvement and implications for clinical trials.

BACKGROUND: Only a few studies have reported muscle imaging data on small cohorts of patients with myotonic dystrophy type 1 (DM1). We aimed to investigate the muscle involvement in a large cohort of patients in order to refine the pattern of muscle involvement, to better understand the pathophysiological mechanisms of muscle weakness, and to identify potential imaging biomarkers for disease activity and severity. METHODS: One hundred and thirty-four DM1 patients underwent a cross-sectional muscle magnetic resonance imaging (MRI) study. Short tau inversion recovery (STIR) and T1 sequences in the lower and upper body were analyzed. Fat replacement, muscle atrophy and STIR positivity were evaluated using three different scales. Correlations between MRI scores, clinical features and genetic background were investigated. RESULTS: The most frequent pattern of muscle involvement in T1 consisted of fat replacement of the tongue, sternocleidomastoideus, paraspinalis, gluteus minimus, distal quadriceps and gastrocnemius medialis. Degree of fat replacement at MRI correlated with clinical severity and disease duration, but not with CTG expansion. Fat replacement was also detected in milder/asymptomatic patients. More than 80% of patients had STIR-positive signals in muscles. Most DM1 patients also showed a variable degree of muscle atrophy regardless of MRI signs of fat replacement. A subset of patients (20%) showed a 'marbled' muscle appearance. CONCLUSIONS: Muscle MRI is a sensitive biomarker of disease severity alsofor the milder spectrum of disease. STIR hyperintensity seems to precede fat replacement in T1. Beyond fat replacement, STIR positivity, muscle atrophy and a 'marbled' appearance suggest further mechanisms of muscle wasting and weakness in DM1, representing additional outcome measures and therapeutic targets for forthcoming clinical trials.

Technology outcome measures in neuromuscular disorders: A systematic review.

BACKGROUND AND PURPOSE: Portable and wearable devices can monitor a number of physical performances and lately have been applied to patients with neuromuscular disorders (NMDs). METHODS: We performed a systematic search of literature databases following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) principles, including all studies reporting the use of technological devices for motor function assessment in NMDs from 2000 to 2021. We also summarized the evidence on measurement properties (validity, reliability, responsiveness) of the analyzed technological outcome measures. RESULTS: One hundred studies fulfilled the selection criteria, most of them published in the past 10 years. We defined four categories that gathered similar technologies: gait analysis tools, for clinical assessment of pace and posture; continuous monitoring of physical activity with inertial sensors, which allow "unsupervised" activity assessment; upper limb evaluation tools, including Kinect-based outcome measures to assess the reachable workspace; and new muscle strength assessment tools, such as Myotools. Inertial sensors have the evident advantage of being applied in the "in-home" setting, which has become especially appealing during the COVID-19 pandemic, although poor evidence from psychometric property assessment and results of the analyzed studies may limit their research application. Both Kinect-based outcome measures and Myotools have already been validated in multicenter studies and different NMDs, showing excellent characteristics for application in clinical trials. CONCLUSIONS: This overview is intended to raise awareness on the potential of the different technology outcome measures in the neuromuscular field and to be an informative source for the design of future clinical trials, particularly in the era of telemedicine.

High-Throughput Digital Image Analysis Reveals Distinct Patterns of Dystrophin Expression in Dystrophinopathy Patients.

Duchenne muscular dystrophy (DMD) is an incurable disease caused by out-of-frame DMD gene deletions while in frame deletions lead to the milder Becker muscular dystrophy (BMD). In the last decade several antisense oligonucleotides drugs have been developed to induce a partially functional internally deleted dystrophin, similar to that produced in BMD, and expected to ameliorate the disease course. The pattern of dystrophin expression and functionality in dystrophinopathy patients is variable due to multiple factors, such as molecular functionality of the dystrophin and its distribution. To benchmark the success of therapeutic intervention, a clear understanding of dystrophin expression patterns in dystrophinopathy patients is vital. Recently, several groups have used innovative techniques to quantify dystrophin in muscle biopsies of children but not in patients with milder BMD. This study reports on dystrophin expression using both Western blotting and an automated, high-throughput, image analysis platform in DMD, BMD, and intermediate DMD/BMD skeletal muscle biopsies. Our results found a significant correlation between Western blot and immunofluorescent quantification indicating consistency between the different methodologies. However, we identified significant inter- and intradisease heterogeneity of patterns of dystrophin expression in patients irrespective of the amount detected on blot, due to variability in both fluorescence intensity and dystrophin sarcolemmal circumference coverage. Our data highlight the heterogeneity of the pattern of dystrophin expression in BMD, which will assist the assessment of dystrophin restoration therapies.

Redox Homeostasis in Muscular Dystrophies.

In recent years, growing evidence has suggested a prominent role of oxidative stress in the pathophysiology of several early- and adult-onset muscle disorders, although effective antioxidant treatments are still lacking. Oxidative stress causes cell damage by affecting protein function, membrane structure, lipid metabolism, and DNA integrity, thus interfering with skeletal muscle homeostasis and functionality. Some features related to oxidative stress, such as chronic inflammation, defective regeneration, and mitochondrial damage are shared among most muscular dystrophies, and Nrf2 has been shown to be a central player in antagonizing redox imbalance in several of these disorders. However, the exact mechanisms leading to overproduction of reactive oxygen species and deregulation in the cellular antioxidants system seem to be, to a large extent, disease-specific, and the clarification of these mechanisms in vivo in humans is the cornerstone for the development of targeted antioxidant therapies, which will require testing in appropriately designed clinical trials.

Long-term Follow-up and Muscle Imaging Findings in Brachio-Cervical Inflammatory Myopathy.

OBJECTIVE: To report on a cohort of patients diagnosed with brachio-cervical inflammatory myopathy (BCIM), with specific focus on muscle MRI and follow-up data. METHODS: Clinical, histopathologic, serologic, and pre- and post-treatment MRI findings of patients diagnosed with BCIM were retrospectively evaluated. RESULTS: Six patients, all females with a mean age at onset of 53 years (range 37-62 years), were identified. Mean diagnostic delay was 17 months, and mean follow-up was 35 months. Most common clinical features encompassed predominant involvement of neck and proximal upper limb muscles, followed by distal upper limb, facial, and bulbar muscle weakness with different severity. Lower limb involvement was rare, although present in severe cases. Muscle biopsies showed a heterogeneous degree of perivascular and endomysial inflammatory changes. Myositis-specific antibodies were absent in all patients, whereas all resulted positive for antinuclear antibodies; half of the patients had anti-acetylcholine receptor antibodies without evidence of muscle fatigability. MRI showed disproportionate involvement of upper girdle and neck muscles compared with lower limbs, with frequent hyperintensities on short-tau inversion recovery sequences. Partial clinical and radiologic improvement with steroid and immunosuppressant therapy was obtained in most patients, especially in proximal upper limb muscles, whereas neck weakness persisted. CONCLUSION: BCIM is an inflammatory myopathy with a peculiar clinical and radiologic presentation and a relatively broad spectrum of severity. Long-term follow-up data suggest that appropriate and early treatment can prevent chronic muscle function impairment. MRI characterization can be helpful in reducing diagnostic and treatment delay with positive consequence on clinical outcome.

Fast Open-Source Toolkit for Water T2 Mapping in the Presence of Fat From Multi-Echo Spin-Echo Acquisitions for Muscle MRI.

Imaging has become a valuable tool in the assessment of neuromuscular diseases, and, specifically, quantitative MR imaging provides robust biomarkers for the monitoring of disease progression. Quantitative evaluation of fat infiltration and quantification of the T2 values of the muscular tissue's water component (wT2) are two of the most essential indicators currently used. As each voxel of the image can contain both water and fat, a two-component model for the estimation of wT2 must be used. In this work, we present a fast method for reconstructing wT2 maps obtained from conventional multi-echo spin-echo (MESE) acquisitions and released as Free Open Source Software. The proposed software is capable of fast reconstruction thanks to extended phase graphs (EPG) simulations and dictionary matching implemented on a general-purpose graphic processing unit. The program can also perform more conventional biexponential least-squares fitting of the data and incorporate information from an external water-fat acquisition to increase the accuracy of the results. The method was applied to the scans of four healthy volunteers and five subjects suffering from facioscapulohumeral muscular dystrophy (FSHD). Conventional multi-slice MESE acquisitions were performed with 17 echoes, and additionally, a 6-echo multi-echo gradient-echo (MEGE) sequence was used for an independent fat fraction calculation. The proposed reconstruction software was applied on the full datasets, and additionally to reduced number of echoes, respectively, to 8, 5, and 3, using EPG and biexponential least-squares fitting, with and without incorporating information from the MEGE acquisition. The incorporation of external fat fraction maps increased the robustness of the fitting with a reduced number of echoes per datasets, whereas with unconstrained fitting, the total of 17 echoes was necessary to retain an independence of wT2 from the level of fat infiltration. In conclusion, the proposed software can successfully be used to calculate wT2 maps from conventional MESE acquisition, allowing the usage of an optimized protocol with similar precision and accuracy as a 17-echo acquisition. As it is freely released to the community, it can be used as a reference for more extensive cohort studies.