Severity classification in cases of Collagen VI-related myopathy with Convolutional Neural Networks and handcrafted texture features

(C) 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Magnetic Resonance Imaging (MRI) is a non-invasive tool for the clinical assessment of low-prevalence neuromuscular disorders. Automated diagnosis methods might reduce the need for biopsies and provide valuable information on disease follow-up. In this paper, three methods are proposed to classify target muscles in Collagen VI-related myopathy cases, based on their degree of involvement, notably a Convolutional Neural Network, a Fully Connected Network to classify texture features, and a hybrid method combining the two feature sets. The proposed methods were evaluated on axial T1-weighted Turbo Spin-Echo MRI from 26 subjects, including Ullrich Congenital Muscular Dystrophy and Bethlem Myopathy patients at different evolution stages. The hybrid model achieved the best cross-validation results, with a global accuracy of 93.8%, and F-scores of 0.99, 0.82, and 0.95, for healthy, mild and moderate/severe cases, respectively.info:eu-repo/semantics/acceptedVersio

Severity classification in cases of Collagen VI-related myopathy with Convolutional Neural Networks and handcrafted texture features

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Magnetic Resonance Imaging (MRI) is a non-invasive tool for the clinical assessment of low-prevalence neuromuscular disorders. Automated diagnosis methods might reduce the need for biopsies and provide valuable information on disease follow-up. In this paper, three methods are proposed to classify target muscles in Collagen VI-related myopathy cases, based on their degree of involvement, notably a Convolutional Neural Network, a Fully Connected Network to classify texture features, and a hybrid method combining the two feature sets. The proposed methods were evaluated on axial T1-weighted Turbo Spin-Echo MRI from 26 subjects, including Ullrich Congenital Muscular Dystrophy and Bethlem Myopathy patients at different evolution stages. The hybrid model achieved the best cross-validation results, with a global accuracy of 93.8%, and F-scores of 0.99, 0.82, and 0.95, for healthy, mild and moderate/severe cases, respectively.info:eu-repo/semantics/acceptedVersio

Texture Analysis of T1-weighted Turbo Spin-Echo MRI for the Diagnosis and Follow-up of Collagen VI-related Myopathy

Muscle texture analysis in Magnetic Resonance Imaging (MRI) has revealed a good correlation with typical histological changes resulting from neuromuscular disorders. In this research, we assess the effectiveness of several features in describing intramuscular texture alterations in cases of Collagen VI-related myopathy. A T1-weighted Turbo Spin-Echo MRI dataset was used (Nsubj = 26), consisting of thigh scans from subjects diagnosed with Ullrich Congenital Muscular Dystrophy or Bethlem Myopathy, with different severity levels, as well as healthy subjects. A total of 355 texture features were studied, including attributes derived from the Gray-Level Co-occurrence Matrix, the Run-Length Matrix, Wavelet and Gabor filters. The extracted features were ranked using the Support Vector Machine Recursive Feature Elimination (SVM-RFE) algorithm with Correlation Bias Reduction, prior to cross-validated classification with a Gaussian kernel SVM.info:eu-repo/semantics/acceptedVersionhttps://ieeexplore.ieee.org/document/9433942

Prospective exploratory muscle biopsy, imaging, and functional assessment in patients with late-onset Pompe disease treated with alglucosidase alfa: The EMBASSY Study

Background Late-onset Pompe disease is characterized by progressive skeletal myopathy followed by respiratory muscle weakness, typically leading to loss of ambulation and respiratory failure. In this population, enzyme replacement therapy (ERT) with alglucosidase alfa has been shown to stabilize respiratory function and improve mobility and muscle strength. Muscle pathology and glycogen clearance from skeletal muscle in treatment-naïve adults after ERT have not been extensively examined. Methods This exploratory, open-label, multicenter study evaluated glycogen clearance in muscle tissue samples collected pre- and post- alglucosidase alfa treatment in treatment-naïve adults with late-onset Pompe disease. The primary endpoint was the quantitative reduction in percent tissue area occupied by glycogen in muscle biopsies from baseline to 6 months. Secondary endpoints included qualitative histologic assessment of tissue glycogen distribution, secondary pathology changes, assessment of magnetic resonance images (MRIs) for intact muscle and fatty replacement, and functional assessments. Results Sixteen patients completed the study. After 6 months of ERT, the percent tissue area occupied by glycogen in quadriceps and deltoid muscles decreased in 10 and 8 patients, respectively. No changes were detected on MRI from baseline to 6 months. A majority of patients showed improvements on functional assessments after 6 months of treatment. All treatment-related adverse events were mild or moderate. Conclusions This exploratory study provides novel insights into the histopathologic effects of ERT in late-onset Pompe disease patients. Ultrastructural examination of muscle biopsies demonstrated reduced lysosomal glycogen after ERT. Findings are consistent with stabilization of disease by ERT in treatment-naïve patients with late-onset Pompe disease

Assessing Dysferlinopathy Patients Over Three Years With a New Motor Scale

The Jain COS Consortium.[Objective] Dysferlinopathy is a muscular dystrophy with a highly variable clinical presentation and currently unpredictable progression. This variability and unpredictability presents difficulties for prognostication and clinical trial design. The Jain Clinical Outcomes Study of Dysferlinopathy aims to establish the validity of the North Star Assessment for Limb Girdle Type Muscular Dystrophies (NSAD) scale and identify factors that influence the rate of disease progression using NSAD.[Methods] We collected a longitudinal series of functional assessments from 187 patients with dysferlinopathy over 3 years. Rasch analysis was used to develop the NSAD, a motor performance scale suitable for ambulant and nonambulant patients. Generalized estimating equations were used to evaluate the impact of patient factors on outcome trajectories.[Results] The NSAD detected significant change in clinical progression over 1 year. The steepest functional decline occurred during the first 10 years after symptom onset, with more rapid decline noted in patients who developed symptoms at a younger age (p = 0.04). The most rapidly deteriorating group over the study was patients 3 to 8 years post symptom onset at baseline.[Interpretation] The NSAD is the first validated limb girdle specific scale of motor performance, suitable for use in clinical practice and clinical trials. Longitudinal analysis showed it may be possible to identify patient factors associated with greater functional decline both across the disease course and in the short-term for clinical trial preparation. Through further work and validation in this cohort, we anticipate that a disease model incorporating functional performance will allow for more accurate prognosis for patients with dysferlinopathy. ANN NEUROL 2021;89:967–978The estimated US $4 million needed to fund this study was provided by the Jain Foundation. (www.jain-foundation.org) The Jain COS consortium would like to thank the study participants and their families for their invaluable contribution. The John Walton Centre Muscular Dystrophy Research Centre is part of the MRC Centre for Neuromuscular Diseases (Grant number MR/K000608/1).Peer reviewe

Table_2_Assessing the Relationship of Patient Reported Outcome Measures With Functional Status in Dysferlinopathy: A Rasch Analysis Approach.docx

Appendix B. Coinvestigators - The Jain COS Consortium.Dysferlinopathy is a muscular dystrophy with a highly variable functional disease progression in which the relationship of function to some patient reported outcome measures (PROMs) has not been previously reported. This analysis aims to identify the suitability of PROMs and their association with motor performance.Two-hundred and four patients with dysferlinopathy were identified in the Jain Foundation's Clinical Outcome Study in Dysferlinopathy from 14 sites in 8 countries. All patients completed the following PROMs: Individualized Neuromuscular Quality of Life Questionnaire (INQoL), International Physical Activity Questionnaire (IPAQ), and activity limitations for patients with upper and/or lower limb impairments (ACTIVLIMs). In addition, nonambulant patients completed the Egen Klassifikation Scale (EK). Assessments were conducted annually at baseline, years 1, 2, 3, and 4. Data were also collected on the North Star Assessment for Limb Girdle Type Muscular Dystrophies (NSAD) and Performance of Upper Limb (PUL) at these time points from year 2. Data were analyzed using descriptive statistics and Rasch analysis was conducted on ACTIVLIM, EK, INQoL. For associations, graphs (NSAD with ACTIVLIM, IPAQ and INQoL and EK with PUL) were generated from generalized estimating equations (GEE). The ACTIVLIM appeared robust psychometrically and was strongly associated with the NSAD total score (Pseudo R2 0.68). The INQoL performed less well and was poorly associated with the NSAD total score (Pseudo R2 0.18). EK scores were strongly associated with PUL (Pseudo R2 0.69). IPAQ was poorly associated with NSAD scores (Pseudo R2 0.09). This study showed that several of the chosen PROMs demonstrated change over time and a good association with functional outcomes. An alternative quality of life measure and method of collecting data on physical activity may need to be selected for assessing dysferlinopathy.Peer reviewe

Assessing dysferlinopathy patients over three years with a new motor scale

OBJECTIVE: Dysferlinopathy is a muscular dystrophy with a highly variable clinical presentation and currently unpredictable progression. This variability and unpredictability presents difficulties for prognostication and clinical trial design. The Jain Clinical Outcomes Study of Dysferlinopathy aims to establish the validity of the North Star Assessment for Limb Girdle Type Muscular Dystrophies (NSAD) scale and identify factors that influence the rate of disease progression using NSAD. METHODS: We collected a longitudinal series of functional assessments from 187 dysferlinopathy patients over three years. Rasch analysis was used to develop the NSAD, a motor performance scale suitable for ambulant and non-ambulant patients. Generalized estimating equations were used to evaluate the impact of patient factors on outcome trajectories. RESULTS: The NSAD detected significant change in clinical progression over 1 year. The steepest functional decline occurred during the first 10 years after symptom onset, with more rapid decline noted in patients who developed symptoms at a younger age (p = 0.04). The most rapidly deteriorating group over the study was patients 3-8 years post symptom onset at baseline. INTERPRETATION: The NSAD is the first validated limb girdle specific scale of motor performance, suitable for use in clinics practice and clinical trials. Longitudinal analysis showed it may be possible to identify patient factors associated with greater functional decline both across the disease course and in the short-term for clinical trial preparation. Through further work and validation in this cohort, we anticipate that a disease model incorporating functional performance will allow for more accurate prognosis for patients with dysferlinopathy