Texture analysis using T1-weighted images for muscles in Charcot-Marie-Tooth disease patients and volunteers

Machine learning-based radiomics to differentiate immune-mediated necrotizing myopathy from limb-girdle muscular dystrophy R2 using MRI

Objectives

This study aimed to assess the feasibility of a machine learning-based radiomics tools to discriminate between Limb-girdle muscular dystrophy R2 (LGMDR2) and immune-mediated necrotizing myopathy (IMNM) using lower-limb muscle magnetic resonance imaging (MRI) examination.

Methods

After institutional review board approval, 30 patients with genetically proven LGMDR2 (12 females; age, 34.0 ± 11.3) and 45 patients with IMNM (28 females; age, 49.2 ± 16.6) who underwent lower-limb MRI examination including T1-weighted and interactive decomposition water and fat with echos asymmetric and least-squares estimation (IDEAL) sequences between July 2014 and August 2022 were included. Radiomics features of muscles were obtained, and four machine learning algorithms were conducted to select the optimal radiomics classifier for differential diagnosis. This selected algorithm was performed to construct the T1-weighted (TM), water-only (WM), or the combined model (CM) for calf-only, thigh-only, or the calf and thigh MR images, respectively. And their diagnostic performance was studied using area under the curve (AUC) and compared to the semi-quantitative model constructed by the modified Mercuri scale of calf and thigh muscles scored by two radiologists specialized in musculoskeletal imaging.

Results

The logistic regression (LR) model was the optimal radiomics model. The performance of the WM and CM for thigh-only images (AUC 0.893, 0.913) was better than those for calf-only images (AUC 0.846, 0.880) except the TM. For "calf + thigh" images, the TM, WM, and CM models always performed best (AUC 0.953, 0.907, 0.953) with excellent accuracy (92.0, 84.0, 88.0%). The AUCs of the Mercuri model of the calf, thigh, and "calf + thigh" images were 0.847, 0.900, and 0.953 with accuracy (84.0, 84.0, 88.0%).

Conclusion

Machine learning-based radiomics models can differentiate LGMDR2 from IMNM, performing better than visual assessment. The model built by combining calf and thigh images presents excellent diagnostic efficiency.

Hamstring Muscle Quality Properties Using Texture Analysis of Ultrasound Images

The aim of this study was to examine the intra- and inter-muscular differences of the hamstring muscles using textural analysis of ultrasound (US) images, and the relationship between textural indicators with hamstring torque. Transverse US scans were obtained from 10 young males from four different measurement sites along the thigh of each individual hamstring muscle at rest. Maximum-knee-flexion isometric torque measurements were also obtained. Texture analysis was applied to US images, and five gray-level co-occurrence matrix (GLCM) features were quantified: entropy (ENT), angular second moment (ASM), inverse difference moment (IDM), contrast (CON) and correlation (COR). The intraclass correlation coefficients ranged from 0.77 to 0.99, and the standard error of measurement ranged from 0.06 to 10.05%, indicating high test-retest reliability. Analysis of the variance indicated significant differences between measurement sites and individual muscles, with the proximal measurement sites having greater values for ASM, IDM and COR and lower values for ENT and CON compared with the distal sites. Additionally, only the COR at the proximal measurement site exhibited a significant relationship (r = -0.66) with strength. The present study indicated significant differences among hamstrings and measurement locations with respect to the textural analysis and may provide a novel indicator of hamstring functional properties.

Hypothesis generation: Quantitative research to levator ani muscle injury based on MRI texture analysis

AIM

Patients with pelvic organ prolapse (POP) mostly have injury to the levator ani muscle (LAM). We aimed to assess LAM injury in POP patients by quantifying texture feature (TF) ratios between the LAM and the obturator internus muscle (OIM) using texture analysis.

METHODS

This study retrospectively enrolled 32 participants, including 24 patients with POP and eight people with normal pelvic floor muscles. TFs of the LAM and the OIM were extracted using LIFEx version 6.30, and an independent samples t-test was performed to determine TF ratios characterizing LAM injury. After dimension reduction and binary logic analysis, the optimal TF ratio was obtained and the LAM injury quantitative evaluation was proposed. Spearman's correlation was performed to explore the correlations between TF ratios and clinical characteristics. We compared the diagnostic performance of quantitative evaluation and visual evaluation.

RESULTS

There were significant differences in 13 TF ratios between the POP and control groups. The area under the receiver operating characteristic curve of the integrated TF ratio was 0.948. Integrated TF ratio was significantly correlated with body mass index, pregnancies, and vaginal deliveries but had no correlation with LAM volume, hiatal area or abortions. Compared with the visual evaluation, the diagnostic accuracy of the quantitative evaluation had improved by 63.2% and 14.3% in the "minor defect" and "major defect" categories, respectively.

CONCLUSION

The integrated TF ratio can be used as a new quantifiable index to characterize LAM injury. The TF evaluation provides a potential role in LAM injury noninvasive diagnostic.

Evaluation of lateral pterygoid muscle in patients with temporomandibular joint anterior disk displacement using T1-weighted Dixon sequence: a retrospective study

Background

Pathological alterations of lateral pterygoid muscle (LPM) are implicated in temporomandibular joint anterior disk displacement (ADD). However, quantification of the fatty infiltration of LPM and its correlation with ADD have rarely been reported. The aim of this study was to evaluate the fatty infiltration, morphological features and texture features of LPM in patients with ADD using T1-weighted Dixon sequence.

Methods

This retrospective study included patients who underwent temporomandibular joint MRI with T1-weighted Dixon sequence between December 2018 and August 2020. The temporomandibular joints of the included patients were divided into three groups according to the position of disk: Normal position disk (NP) group, Anterior disk displacement with reduction (ADDWR) group and Anterior disk displacement without reduction (ADDWOR) group. Fat fraction, morphological features (Length; Width; Thickness), and texture features (Angular second moment; Contrast; Correlation; Inverse different moment; Entropy) extracted from in-phase image of LPM were evaluated. One-way ANOVA, Welch’s ANOVA, Kruskal–Wallis test, Spearman and Pearson correlation analysis were performed. Intra-class correlation coefficient was used to evaluate the reproducibility.

Results

A total of 53 patients with 106 temporomandibular joints were evaluated. Anterior disk displacement without reduction group showed higher fat fraction than normal position disk group (P = 0.024). Length of LPM was negatively correlated with fat fraction (r = -0.22, P = 0.026). Angular second moment (ρ = -0.32, P < 0.001), correlation (ρ = -0.28, P = 0.003) and inverse different moment (ρ = -0.27, P = 0.005) were negatively correlated with fat fraction, while positive correlation was found between entropy and fat fraction (ρ = 0.31, P = 0.001). The intra-class correlation coefficients for all values were ranged from 0.80 to 0.97.

Conclusions

Patients with ADDWOR present more fatty infiltration in the LPM compared to NP or ADDWR patients. Fatty infiltration of LPM was associated with more atrophic and higher intramuscular heterogeneity in patients with ADD. Fat fraction of LPM quantitatively and noninvasively evaluated by Dixon sequence may has utility as an imaging-based marker of the structural severity of ADD disease process, which could be clinical helpful for the early diagnose of ADD and predication of disease progression.

Association of Paraspinal Muscle CSA and PDFF Measurements With Lumbar Intervertebral Disk Degeneration in Patients With Chronic Low Back Pain

There is an interaction between the lumbar spine and paraspinal muscles, which may play a role in the development of intervertebral disc (IVD) degeneration and may affect CLBP. The study aims to assess the relationship between IVD degeneration and paraspinal muscle fat infiltration in CLBP patients by quantitative MR imaging, and to evaluate the influence of sex and age on CLBP muscle fat infiltration. Sixty CLBP patients (46.3 years ±17.0) and thirty-two healthy subjects (44.9 years ±17.6) were recruited for this study. 3.0 T MRI was used to perform the sagittal and axial T1, T2 of the lumbar spine, and axial paraspinal muscle IDEAL imaging at the L4/5 and L5/S1 levels. Proton density fat fraction (PDFF) of the multifidus and erector spinae at two IVD levels were measured. The Pfirrmann grades of IVD degeneration, Oswestry Disability Index (ODI), and Visual Analog Scale (VAS) were also evaluated. Compare the cross-sectional area (CSA) and PDFF of the paraspinal muscles between CLBP patients and healthy subjects, and analyze the relationship between the muscle PDFF and Pfirrmann grades, gender, and age of CLBP patients. Compared with healthy subjects, the CSA of the multifidus muscle in CLBP patients decreased (1320.2±188.1mm²vs. 1228.7±191.0 mm², p<0.05) at the L4/5 level, the average PDFF increased, (7.7±2.6% vs. 14.79±5.3%, 8.8±4.2% vs. 16.03±5.3%, all p<0.05) at both L4/5 and L5/S1 levels. The PDFF of paraspinal muscles were correlated with adjacent IVD degeneration, ODI and VSA in CLBP patients (all p<0.05). After using age and body mass index (BMI) as control variables, significance was retained (all p<0.05). Multiple regression analysis revealed sex and age also were significantly associated with multifidus PDFF (all p < 0.05). This study confirmed that the CSA decreased and the PDFF increased of the paraspinal muscles in CLBP patients. It reveals a significant correlation between the PDFF of CLBP paraspinal muscles and the grade of IVD degeneration. Sex and age are also important factors influencing CLBP paraspinal muscle infiltration.