Change of classification of lesions from DIR to PSIR (based on morphology of lesions).

<p>[number (percentage)] Each row corresponds to a lesion type seen on DIR, and each column how the same lesion was classified on PSIR. E.g. of the IC lesions so classified on DIR, 60% remained so on PSIR.</p

Change of classification of lesions from DIR to PSIR (based on lesion type).

<p>[number (percentage)] Each row corresponds to a lesion type seen on DIR, and each column how the same lesion was classified on PSIR. E.g. of the IC lesions so classified on DIR, 60% remained so on PSIR.</p

Acquisition parameters.

<p>FOV = field of view, TR = repetition time, TE = echo time, TI = inversion time, SENSE = sensitivity encoding factor.</p

Corresponding DIR and PSIR images showing change of classification of CGM lesions.

<p>DIR LC lesions (blocked chevron) in panel A, appear as JC-WM lesions on PSIR in panel B; DIR LC lesion in panel C is seen to be a pure IC lesion on PSIR in panel D; DIR LC lesion (blocked chevron) and IC lesion (open chevron) in panel E appear as JC WM and LC on PSIR respectively, in panel F.</p

Table_1_The Diagnostic Value of MRI Pattern Recognition in Distal Myopathies.DOCX

<p>Objective: Distal myopathies are a diagnostically challenging group of diseases. We wanted to understand the value of MRI in the current clinical setting and explore the potential for optimizing its clinical application.</p><p>Methods: We retrospectively audited the diagnostic workup in a distal myopathy patient cohort, reassessing the diagnosis, whilst documenting the usage of MRI. We established a literature based distal myopathies MRI pattern template and assessed its diagnostic utility in terms of sensitivity, specificity, and potential impact on the diagnostic workup.</p><p>Results: Fifty-five patients were included; in 38 with a comprehensive set of data the diagnostic work-up was audited. The median time from symptoms onset to diagnosis was 12.1 years. The initial genetic diagnostic rate was 39%; 18% were misdiagnosed as neuropathies and 13% as inclusion body myositis (IBM). Based on 21 publications we established a MRI pattern template. Its overall sensitivity (50%) and specificity (32%) were low. However in some diseases (e.g., MYOT-related myopathy, TTN-HMERF) MRI correctly identified the causative gene. The number of genes suggested by MRI pattern analysis was smaller compared to clinical work up (median 1 vs. 9, p < 0.0001) but fewer genes were correctly predicted (5/10 vs. 7/10). MRI analysis ruled out IBM in all cases.</p><p>Conclusion: In the diagnostic work-up of distal myopathies, MRI is useful in assisting genetic testing and avoiding misdiagnosis (IBM). The overall low sensitivity and specificity limits its generalized use when traditional single gene test methods are applied. However, in the context of next generation sequencing MRI may represent a valuable tool for interpreting complex genetic results.</p

Upper Limb Evaluation in Duchenne Muscular Dystrophy: Fat-Water Quantification by MRI, Muscle Force and Function Define Endpoints for Clinical Trials

<div><p>Objective</p><p>A number of promising experimental therapies for Duchenne muscular dystrophy (DMD) are emerging. Clinical trials currently rely on invasive biopsies or motivation-dependent functional tests to assess outcome. Quantitative muscle magnetic resonance imaging (MRI) could offer a valuable alternative and permit inclusion of non-ambulant DMD subjects. The aims of our study were to explore the responsiveness of upper-limb MRI muscle-fat measurement as a non-invasive objective endpoint for clinical trials in non-ambulant DMD, and to investigate the relationship of these MRI measures to those of muscle force and function.</p><p>Methods</p><p>15 non-ambulant DMD boys (mean age 13.3 y) and 10 age-gender matched healthy controls (mean age 14.6 y) were recruited. 3-Tesla MRI fat-water quantification was used to measure forearm muscle fat transformation in non-ambulant DMD boys compared with healthy controls. DMD boys were assessed at 4 time-points over 12 months, using 3-point Dixon MRI to measure muscle fat-fraction (f.f.). Images from ten forearm muscles were segmented and mean f.f. and cross-sectional area recorded. DMD subjects also underwent comprehensive upper limb function and force evaluation.</p><p>Results</p><p>Overall mean baseline forearm f.f. was higher in DMD than in healthy controls (p<0.001). A progressive f.f. increase was observed in DMD over 12 months, reaching significance from 6 months (p<0.001, n = 7), accompanied by a significant loss in pinch strength at 6 months (p<0.001, n = 9) and a loss of upper limb function and grip force observed over 12 months (p<0.001, n = 8).</p><p>Conclusions</p><p>These results support the use of MRI muscle f.f. as a biomarker to monitor disease progression in the upper limb in non-ambulant DMD, with sensitivity adequate to detect group-level change over time intervals practical for use in clinical trials. Clinical validity is supported by the association of the progressive fat transformation of muscle with loss of muscle force and function.</p></div

3-point Dixon fat-fraction (f.f.) maps of dominant forearm central slice at baseline (left images) and 12 months (right images).

<p><b>Top:</b> 13 y.o. DMD, non-ambulant for 40 months, and on daily steroids. Overall mean f.f. at baseline = 7.6% (A) and 12 months = 9.7% (B). <b>Bottom:</b> 11 y.o. DMD, non-ambulant for 14 months, not on steroid therapy. Mean f.f. at baseline = 30.7% (C) and 12 months = 43.3% (D). (Grey-level bars represent f.f. from 0 to 100%).</p

MRI and clinical indices mean changes (95% CI) from baseline from analysis of variance.

<p>MRI and clinical indices mean changes (95% CI) from baseline from analysis of variance.</p

Plots of individual trajectories for (A) central slice overall muscle %fat fraction, (B) proximal slice overall muscle %fat fraction, (C) distal slice overall muscle %fat fraction, (D) MyoPinch, (E) total score for Performance of Upper limb, (F) PUL Shoulder domain score, (G) MoviPlate and (H) MyoGrip.

<p>f.f. = fat fraction. PUL = Performance of upper limb.</p

Muscle segmentation (A) and raw 3-point Dixon (B) of the central slice in the dominant forearm of a healthy control.

<p><b>DORSAL compartment</b>: Extensor carpi ulnaris (ECU), extensor digiti minimi (EDM), extensor digitorum (ED), extensor pollicis longus (EPL), abductor pollicis longus (APL), extensor carpi radialis longus/brevis and brachioradialis (ECRLB Br). <b>VOLAR compartment</b>: flexor digitorum profundus and flexor pollicis longus (FDP), flexor digitorum superficialis and palmaris longus (FDS), flexor carpi ulnaris (FCU), flexor carpi radialis (FCR).</p