Shear Wave Elastography for Detecting Calf Muscle Stiffness: An Effective Tool for Assessing Sarcopenia

Establishment and Validation of a Predictive Model for Sarcopenia Based on 2-D Ultrasound and Shear Wave Elastography in the Medial Gastrocnemius Muscle

OBJECTIVE

To develop and validate a predictive model for sarcopenia.

METHODS

A total of 240 subjects who visited our hospital between August 2021 and May 2023 were randomly divided by time of entry into a training set containing 2/3 of patients and a validation set containing 1/3 of patients. The muscle thickness (MT), echo intensity (EI), and shear wave velocity (SWV) of the medial gastrocnemius muscle were measured. Indicators that were meaningful in the univariate analysis in the training set were included in a binary logistic regression to derive a regression model, and the model was evaluated using a consistency index, calibration plot, and clinical validity curve. Diagnostic efficacy and clinical applicability were compared between the model and unifactorial indicators.

RESULTS

Four meaningful variables, age, body mass index (BMI), MT, and SWV, were screened into the predictive model. The model was Logit Y = 21.292 + 0.065 × Age - 0.411 × BMI - 0.524 × MT - 3.072 × SWV. The model was well differentiated with an internally validated C-index of 0.924 and an external validation C-index of 0.914. The calibration plot predicted probabilities against actual probabilities showed excellent agreement. The specificity, sensitivity, and Youden's index of the model were 73.80%, 97.40%, and 71.20%, respectively, when using the diagnostic cut-off value of >0.279 for sarcopenia. The logistic model had higher diagnostic efficacy (p < 0.001) and higher net clinical benefit (p < 0.001) over the same threshold range compared to indicators.

CONCLUSION

The logistic model of sarcopenia has been justified to have good discriminatory, calibrated, and clinical validity, and has higher diagnostic value than indicators.

A systematic review on sonoelastography for rotator-cuff post-repair assessment

Surgical repair of rotator cuff tears is performed routinely; however, the risks of re-tears and the associated consequences are significant. Sonoelastography, an imaging modality that evaluates the mechanical properties of tissues, can examine the dynamic transitions in rotator cuff stiffness following retear and investigate the relationship between these changes and the occurrences of retears. This systematic review aimed to summarize the role of perioperative sonoelastography in repaired rotator cuffs. A comprehensive search of the PubMed, Embase, and Cochrane databases was conducted, covering studies published until June 19, 2023. The Newcastle-Ottawa scale was used for quality assessment. The key information extracted from each study included the injury/surgery type, follow-up duration, sonoelastography mode, and main sonoelastographic findings. Eleven eligible studies comprising 355 patients were included. All studies focused on supraspinatus muscles and tendons with previous arthroscopic repairs. During the postoperative 1st - 6th months, muscle stiffness increased in the supraspinatus and decreased in the ipsilateral deltoid. Failure to recover supraspinatus muscle elasticity might be indicative of potential tendon re-tear; however, it is imperative to first establish correlations with other imaging modalities. Conflicting findings have been observed regarding stiffening or softening of the supraspinatus tendon after surgical repair. The preoperative stiffness of the supraspinatus tendon did not correlate with postoperative tendon integrity or function.

Impact of preterm birth on muscle mass and function: a systematic review and meta-analysis

Individuals born preterm present lower exercise capacity. Along with the cardiopulmonary responses and activity level, muscle strength is a key determinant of exercise capacity. This systematic review aimed to summarize the current knowledge on the impact of preterm birth on skeletal muscle mass and function across the lifespan. The databases PubMed, MEDLINE, EBM, Embase, CINAHL Plus, Global Index Medicus, and Google Scholar were searched using keywords and MeSH terms related to skeletal muscle, preterm birth, and low birth weight. Two independent reviewers undertook study selection, data extraction, and quality appraisal using Covidence review management. Data were pooled to estimate the prematurity effect on muscle mass and function using the R software. From 4378 studies retrieved, 132 were full-text reviewed and 25 met the inclusion/exclusion criteria. Five studies presented a low risk of bias, and 5 had a higher risk of bias due to a lack of adjustment for confounding factors and presenting incomplete outcomes. Meta-analyses of pooled data from homogenous studies indicated a significant reduction in muscle thickness and jump test (muscle power) in individuals born preterm versus full-term with standardized mean difference and confidence interval of - 0.58 (0.27, 0.89) and - 0.45 (0.21, 0.69), respectively.    Conclusion: Overall, this systematic review summarizing the existing literature on the impact of preterm birth on skeletal muscle indicates emerging evidence that individuals born preterm, display alteration in the development of their skeletal muscle mass and function. This work also highlights a clear knowledge gap in understanding the effect of preterm birth on skeletal muscle development. What is Known: • Preterm birth, which occurs at a critical time of skeletal muscle development and maturation, impairs the development of different organs and tissues leading to a higher risk of comorbidities such as cardiovascular diseases. • Preterm birth is associated with reduced exercise capacity. What is New: • Individuals born preterm display alterations in muscle mass and function compared to individuals born at term from infancy to adulthood. • There is a need to develop preventive or curative interventions to improve skeletal muscle health in preterm-born individuals.

Sarcopenia prediction using shear-wave elastography, grayscale ultrasonography, and clinical information with machine learning fusion techniques: feature-level fusion vs. score-level fusion

This study aimed to develop and evaluate a sarcopenia prediction model by fusing numerical features from shear-wave elastography (SWE) and gray-scale ultrasonography (GSU) examinations, using the rectus femoris muscle (RF) and categorical/numerical features related to clinical information. Both cohorts (development, 70 healthy subjects; evaluation, 81 patients) underwent ultrasonography (SWE and GSU) and computed tomography. Sarcopenia was determined using skeletal muscle index calculated from the computed tomography. Clinical and ultrasonography measurements were used to predict sarcopenia based on a linear regression model with the least absolute shrinkage and selection operator (LASSO) regularization. Furthermore, clinical and ultrasonography features were combined at the feature and score levels to improve sarcopenia prediction performance. The accuracies of LASSO were 70.57 ± 5.00-81.54 ± 4.83 (clinical) and 69.00 ± 4.52-69.73 ± 5.47 (ultrasonography). Feature-level fusion of clinical and ultrasonography (accuracy, 70.29 ± 6.63 and 83.55 ± 4.32) showed similar performance with clinical features. Score-level fusion by AdaBoost showed the best performance (accuracy, 73.43 ± 6.57-83.17 ± 5.51) in the development and evaluation cohorts, respectively. This study might suggest the potential of machine learning fusion techniques to enhance the accuracy of sarcopenia prediction models and improve clinical decision-making in patients with sarcopenia.

Update on Lean Body Mass Diagnostic Assessment in Critical Illness

Acute critical illnesses can alter vital functions with profound biological, biochemical, metabolic, and functional modifications. Despite etiology, patient's nutritional status is pivotal to guide metabolic support. The assessment of nutritional status remains complex and not completely elucidated. Loss of lean body mass is a clear marker of malnutrition; however, the question of how to investigate it still remains unanswered. Several tools have been implemented to measure lean body mass, including a computed tomography scan, ultrasound, and bioelectrical impedance analysis, although such methods unfortunately require validation. A lack of uniform bedside measurement tools could impact the nutrition outcome. Metabolic assessment, nutritional status, and nutritional risk have a pivotal role in critical care. Therefore, knowledge about the methods used to assess lean body mass in critical illnesses is increasingly required. The aim of the present review is to update the scientific evidence regarding lean body mass diagnostic assessment in critical illness to provide the diagnostic key points for metabolic and nutritional support.