Quantitative ultrasound of trapezius muscle involvement in myofascial pain: comparison of clinical and healthy population using texture analysis

Age-related changes in ultrasound-assessed muscle composition and postural stability

While the simultaneous degradation of muscle composition and postural stability in aging are independently highly investigated due to their association with fall risk, the interplay between the two has received little attention. Thus, the purpose of this study is to explore how age-related changes in muscle composition relate to postural stability. To that aim, we collected posturography measures and ultrasound images of the dominant Vastus Lateralis and Biceps Brachii from 32 young (18-35 year old) and 34 older (65-85 year old) participants. Muscle properties were quantified with echo-intensity and texture-based metrics derived from gray-level co-occurrence matrix analysis, and postural stability with the variability of the center of pressure during bipedal stance tasks. Ultrasound parameters revealed that young muscle possessed lower echo-intensity and higher homogeneity compared to the elderly. Echo-intensity and muscle thickness, and several texture-based parameters possessed outstanding young versus older classification performance. A canonical correlation analysis demonstrated a significant relationship between ultrasound and postural measures only within the young group (r = 0.53, p < 0.002), where those with 'better' muscle composition displayed larger postural sways. Our results indicate that, in older individuals, postural stability and muscle composition, two common fall risk factors, are unrelated. In view of this decoupling, both may contribute independently to fall risk. Furthermore, our data support the view that texture-based parameters provide a robust alternative to echo-intensity in providing markers of muscle composition.

Identification of Myofascial Trigger Point Using the Combination of Texture Analysis in B-Mode Ultrasound with Machine Learning Classifiers

Myofascial pain syndrome is a chronic pain disorder characterized by myofascial trigger points (MTrPs). Quantitative ultrasound (US) techniques can be used to discriminate MTrPs from healthy muscle. In this study, 90 B-mode US images of upper trapezius muscles were collected from 63 participants (left and/or right side(s)). Four texture feature approaches (individually and a combination of them) were employed that focused on identifying spots, and edges were used to explore the discrimination between the three groups: active MTrPs (n = 30), latent MTrPs (n = 30), and healthy muscle (n = 30). Machine learning (ML) and one-way analysis of variance were used to investigate the discrimination ability of the different approaches. Statistically significant results were seen in almost all examined features for each texture feature approach, but, in contrast, ML techniques struggled to produce robust discrimination. The ML techniques showed that two texture features (i.e., correlation and mean) within the combination of texture features were most important in classifying the three groups. This discrepancy between traditional statistical analysis and ML techniques prompts the need for further investigation of texture-based approaches in US for the discrimination of MTrPs.

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.

Quantitative Ultrasound Texture Feature Changes With Conservative Treatment of the Trapezius Muscle in Female Patients With Myofascial Pain Syndrome

OBJECTIVE

We set out to assess whether quantitative ultrasound could be used to assess changes that occur after physical therapy in patients experiencing myofascial pain syndrome.

METHODS

We consecutively recruited female subjects experiencing myofascial pain syndrome of the neck and shoulder region and provided 10 sessions of conservative physical therapy. A control group was recruited for textural analyses. We measured change in pain ratings, range of motion, and ultrasound texture features before and after the intervention and after 3 mos.

RESULTS

We recruited 63 female myofascial pain syndrome subjects and 20 healthy controls. After treatment, the mean blob size (an ultrasound texture feature) value for each subject decreased from 30.84 ± 5.00 to 25.86 ± 5.67 on the right and decreased from 31.70 ± 5.51 to 28.08 ± 5.53 on the left (P < 0.0005). The blob count showed a significant increase only on the left side (P < 0.01). Corresponding to this were reductions in pain and disability scores after treatment and at 3 mos compared with retreatment (P < 0.0005 for all checkpoints). Cervical range of motion values were significantly increased only at 3 mos compared with pretreatment except for mean flexion range of motion.

CONCLUSIONS

Ultrasound texture feature of blob size and count changes correspond to routine clinical outcomes after conservative physical therapy of myofascial pain syndrome in female individuals.

Assessment of Myofascial Trigger Points via Imaging: A Systematic Review

ABSTRACT

This study systematically reviewed the published literature on the objective characterization of myofascial pain syndrome and myofascial trigger points using imaging methods. PubMed, Embase, Ovid, and the Cochrane Library databases were used, whereas citation searching was conducted in Scopus. Citations were restricted to those published in English and in peer-reviewed journals between 2000 and 2021. Of 1762 abstracts screened, 69 articles underwent full-text review, and 33 were included. Imaging data assessing myofascial trigger points or myofascial pain syndrome were extracted, and important qualitative and quantitative information on general study methodologies, study populations, sample sizes, and myofascial trigger point/myofascial pain syndrome evaluation were tabulated. Methodological quality of eligible studies was assessed based on the Quality Assessment of Diagnostic Accuracy Studies criteria. Biomechanical properties and blood flow of active and latent myofascial trigger points assessed via imaging were found to be quantifiably distinct from those of healthy tissue. Although these studies show promise, more studies are needed. Future studies should focus on assessing diagnostic test accuracy and testing the reproducibility of results to establish the best performing methods. Increasing methodological consistency would further motivate implementing imaging methods in larger clinical studies. Considering the evidence on efficacy, cost, ease of use and time constraints, ultrasound-based methods are currently the imaging modalities of choice for myofascial pain syndrome/myofascial trigger point assessment.

A decision support system based on radiomics and machine learning to predict the risk of malignancy of ovarian masses from transvaginal ultrasonography and serum CA-125

BACKGROUND

To evaluate the performance of a decision support system (DSS) based on radiomics and machine learning in predicting the risk of malignancy of ovarian masses (OMs) from transvaginal ultrasonography (TUS) and serum CA-125.

METHODS

A total of 274 consecutive patients who underwent TUS (by different examiners and with different ultrasound machines) and surgery, with suspicious OMs and known CA-125 serum level were used to train and test a DSS. The DSS was used to predict the risk of malignancy of these masses (very low versus medium-high risk), based on the US appearance (solid, liquid, or mixed) and radiomic features (morphometry and regional texture features) within the masses, on the shadow presence (yes/no), and on the level of serum CA-125. Reproducibility of results among the examiners, and performance accuracy, sensitivity, specificity, and area under the curve were tested in a real-world clinical setting.

RESULTS

The DSS showed a mean 88% accuracy, 99% sensitivity, and 77% specificity for the 239 patients used for training, cross-validation, and testing, and a mean 91% accuracy, 100% sensitivity, and 80% specificity for the 35 patients used for independent testing.

CONCLUSIONS

This DSS is a promising tool in women diagnosed with OMs at TUS, allowing to predict the individual risk of malignancy, supporting clinical decision making.

Re-Examining Myofascial Pain Syndrome: Toward Biomarker Development and Mechanism-Based Diagnostic Criteria

PURPOSE OF REVIEW

We discuss the need for a mechanism-based diagnostic framework with a focus on the development of objective measures (e.g., biomarkers) that can potentially be added to the diagnostic criteria of the syndrome. Potential biomarkers are discussed in relation to current knowledge on the pathophysiology of myofascial pain syndrome (MPS), including alterations in redox status, inflammation, and the myofascial trigger point (MTrP) biochemical milieu, as well as imaging and neurophysiological outcomes. Finally, we discuss the long-term goal of conducting a Delphi survey, to assess the influence of putative MPS biomarkers on clinician opinion, in order to ultimately develop new criteria for the diagnosis of MPS.

RECENT FINDINGS

Myofascial pain syndrome (MPS) is a prevalent healthcare condition associated with muscle weakness, impaired mood, and reduced quality of life. MPS is characterized by the presence of myofascial trigger points (MTrPs): stiff and discrete nodules located within taut bands of skeletal muscle that are painful upon palpation. However, physical examination of MTrPs often yields inconsistent results, and there is no gold standard by which to diagnose MPS. The current MPS diagnostic paradigm has an inherent subjectivity and the absence of correlation with the underlying pathophysiology. Recent advancements in ultrasound imaging, systemic biomarkers, MTrP-specific biomarkers, and the assessment of dysfunction in the somatosensorial system may all contribute to improved diagnostic effectiveness of MPS.

Using rADioMIcs and machine learning with ultrasonography for the differential diagnosis of myometRiAL tumors (the ADMIRAL pilot study). Radiomics and differential diagnosis of myometrial tumors

OBJECTIVE

To develop and evaluate the performance of a radiomics and machine learning model applied to ultrasound (US) images in predicting the risk of malignancy of a uterine mesenchymal lesion.

METHODS

Single-center retrospective evaluation of consecutive patients who underwent surgery for a malignant uterine mesenchymal lesion (sarcoma) and a control group of patients operated on for a benign uterine mesenchymal lesion (myoma). Radiomics was applied to US preoperative images according to the International Biomarker Standardization Initiative guidelines to create, validate and test a classification model for the differential diagnosis of myometrial tumors. The TRACE4 radiomic platform was used thus obtaining a full-automatic radiomic workflow. Definitive histology was considered as gold standard. Accuracy, sensitivity, specificity, AUC and standard deviation of the created classification model were defined.

RESULTS

A total of 70 women with uterine mesenchymal lesions were recruited (20 with histological diagnosis of sarcoma and 50 myomas). Three hundred and nineteen radiomics IBSI-compliant features were extracted and 308 radiomics features were found stable. Different machine learning classifiers were created and the best classification system showed Accuracy 0.85 ± 0.01, Sensitivity 0.80 ± 0.01, Specificity 0.87 ± 0.01, AUC 0.86 ± 0.03.

CONCLUSIONS

Radiomics applied to US images shows a great potential in differential diagnosis of mesenchymal tumors, thus representing an interesting decision support tool for the gynecologist oncologist in an area often characterized by uncertainty.

Muscle Composition Analysis of Ultrasound Images: A Narrative Review of Texture Analysis

Skeletal muscle composition, often characterized by the degree of intramuscular adipose tissue, deteriorates with aging and disease and contributes to impairments in function and metabolism. Ultrasound can provide surrogate measures of muscle composition through measurement of echo intensity; however, there are several limitations associated with its analysis. More complex image processing features, broadly known as texture analysis, can also provide surrogates of muscle composition and may circumvent some of the limitations associated with muscle echo intensity. Here, texture features from the intensity histogram, gray-level co-occurrence matrix, run-length matrix, local binary pattern, blob analysis, texture anisotropy index and wavelet analysis are discussed. The purpose of this review was to provide a conceptual understanding of texture analysis as it pertains to muscle composition of ultrasound images.

Rectus abdominis muscle tear diagnosed with sonography and its conservative management

PURPOSE

This is a rare case of a post-traumatic rectus abdominis muscle tear in an adolescent female diagnosed by ultrasonography (US). Conservative management is also described.

METHODS

A 14-year-old female presented to a chiropractic clinic with extreme pain and tenderness in the right lower quadrant (RLQ) after post-plyometric power kneel box jumps. Movement aggravated her pain and she demonstrated active abdominal guarding with RLQ palpation. Ultrasonography revealed a subacute Grade 2 right rectus abdominis muscle tear, without evidence of hyperemia or a hematoma. Following the diagnosis of a right rectus abdominis muscle tear, she was treated with spinal manipulation and a course of musculoskeletal rehabilitation directed at truncal stabilization.

RESULTS

After treatment, the patient was able to return to play 5 week post-injury without any pain or discomfort. A follow-up US at 3 months provided evidence of muscle healing without complications.

CONCLUSION

This case demonstrates the diagnosis of a rare rectus abdominis muscle tear managed conservatively. To our knowledge, less than a dozen cases are reported using US in the evaluation and diagnosis of a rectus abdominis tear.