Testing soft tissue radiodensity parameters interplay with age and self-reported physical activity

Scapular muscle dynamic stiffness of asymptomatic subjects and subjects with chronic shoulder pain, at rest and isometric contraction conditions

Muscle stiffness had a crucial role in joint stability, particularly, at the shoulder complex. Although changes in upper trapezius muscle stiffness have been described for shoulder pain, contradictory findings have been obtained. Also, existing data regarding scapular muscles are, majorly, about trapezius. Myotonometry is a method used to assess stiffness; however, the reliability values of scapular muscle stiffness through this method have not been assessed in shoulder pain conditions. The present study aims to compare scapular muscles' stiffness (trapezius, serratus anterior, and levator scapulae) between subjects with and without chronic shoulder pain and to evaluate the related test-retest reliability. Twenty-two symptomatic and twenty-two asymptomatic subjects participated in a cross-sectional study. The dynamic muscular stiffness of scapular muscles, at rest and during an isometric contraction, was measured bilaterally with myotonometry, in two moments. The differences in bilateral averaged values between symptomatic and asymptomatic subjects and the effect of the group (group presenting pain in the dominant or non-dominant side, and asymptomatic group) and of the limb (unilateral painful or asymptomatic limb, and bilateral asymptomatic limbs) were investigated. Test-retest intra-rater reliability was determined. An effect of the group was observed at rest, for middle trapezius stiffness, and during contraction, for middle and lower trapezius stiffness. For middle trapezius, increased values were observed in the group presenting pain in non-dominant side comparing to both groups or to group presenting pain in dominant side. The intraclass correlation coefficient, majorly, ranged between 0.775 and 0.989. Participants with pain in the non-dominant side presented an increased middle trapezius' stiffness. Globally, high reliability was observed for scapular muscles dynamic stiffness.

Correlation between trunk function improvement and recovery of activities of daily living after stroke in older adult patients

OBJECTIVES

To examine the impact of improved trunk function on activities of daily living in stroke patients using the Functional Independence Measure (FIM).

METHODS

This retrospective observational study was conducted on patients aged ≥ 65 years who had cerebral infarction. Patients were divided into a group with improved trunk function and a group without trunk function improvement based on the difference between the calculated Functional Assessment for Control of Trunk (FACT) gain at discharge and admission.

RESULTS

Of the 218 patients (mean age, 79.5 ± 7.9 years; 56.9% were men) included, 110 patients had improved FACT scores. Multiple linear regression analysis revealed that the group with improved FACT scores had higher FIM gain (coefficient = 7.562, 95% confidence interval = 3.870-11.253, P < 0.001). Multivariate logistic regression showed that the factors associated with FACT score improvement were the Mini Nutritional Assessment Short-Form score at admission, National Institutes of Health Stroke Scale score at admission, FACT score at admission, length of hospital stay, and period of rehabilitation.

DISCUSSIONS

Improvement in trunk function suggests a positive correlation with the recovery of activities of daily living in patients with cerebral infarction. This relationship should be further validated through prospective observational studies.

Development of soft tissue asymmetry indicators to characterize aging and functional mobility

Introduction: The aging population poses significant challenges to healthcare systems globally, necessitating a comprehensive understanding of age-related changes affecting physical function. Age-related functional decline highlights the urgency of understanding how tissue composition changes impact mobility, independence, and quality of life in older adults. Previous research has emphasized the influence of muscle quality, but the role of tissue composition asymmetry across various tissue types remains understudied. This work develops asymmetry indicators based on muscle, connective and fat tissue extracted from cross-sectional CT scans, and shows their interplay with BMI and lower extremity function among community-dwelling older adults. Methods: We used data from 3157 older adults from 71 to 98 years of age (mean: 80.06). Tissue composition asymmetry was defined by the differences between the right and left sides using CT scans and the non-Linear Trimodal Regression Analysis (NTRA) parameters. Functional mobility was measured through a 6-meter gait (Normal-GAIT and Fast-GAIT) and the Timed Up and Go (TUG) performance test. Statistical analysis included paired t-tests, polynomial fitting curves, and regression analysis to uncover relationships between tissue asymmetry, age, and functional mobility. Results: Findings revealed an increase in tissue composition asymmetry with age. Notably, muscle and connective tissue width asymmetry showed significant variation across age groups. BMI classifications and gait tasks also influenced tissue asymmetry. The Fast-GAIT task demonstrated a substantial separation in tissue asymmetry between normal and slow groups, whereas the Normal-GAIT and the TUG task did not exhibit such distinction. Muscle quality, as reflected by asymmetry indicators, appears crucial in understanding age-related changes in muscle function, while fat and connective tissue play roles in body composition and mobility. Discussion: Our study emphasizes the importance of tissue asymmetry indicators in understanding how muscle function changes with age in older individuals, demonstrating their role as risk factor and their potential employment in clinical assessment. We also identified the influence of fat and connective tissue on body composition and functional mobility. Incorporating the NTRA technology into clinical evaluations could enable personalized interventions for older adults, promoting healthier aging and maintaining physical function.

Toward New Assessment of Knee Cartilage Degeneration

OBJECTIVE

Assessment of human joint cartilage is a crucial tool to detect and diagnose pathological conditions. This exploratory study developed a workflow for 3D modeling of cartilage and bone based on multimodal imaging. New evaluation metrics were created and, a unique set of data was gathered from healthy controls and patients with clinically evaluated degeneration or trauma.

DESIGN

We present a novel methodology to evaluate knee bone and cartilage based on features extracted from magnetic resonance imaging (MRI) and computed tomography (CT) data. We developed patient specific 3D models of the tibial, femoral, and patellar bones and cartilages. Forty-seven subjects with a history of degenerative disease, traumatic events, or no symptoms or trauma (control group) were recruited in this study. Ninety-six different measurements were extracted from each knee, 78 2D and 18 3D measurements. We compare the sensitivity of different metrics to classify the cartilage condition and evaluate degeneration.

RESULTS

Selected features extracted show significant difference between the 3 groups. We created a cumulative index of bone properties that demonstrated the importance of bone condition to assess cartilage quality, obtaining the greatest sensitivity on femur within medial and femoropatellar compartments. We were able to classify degeneration with a maximum recall value of 95.9 where feature importance analysis showed a significant contribution of the 3D parameters.

CONCLUSION

The present work demonstrates the potential for improving sensitivity in cartilage assessment. Indeed, current trends in cartilage research point toward improving treatments and therefore our contribution is a first step toward sensitive and personalized evaluation of cartilage condition.

Effects of transcranial direct current stimulation on lower limb function, balance and quality of life after stroke: a systematic review and meta-analysis

OBJECTIVE

This systematic review with meta-analysis aimed to evaluate the effectiveness of tDCS on lower limb function, balance and quality of life in stroke patients.

METHODS

The search included PubMed, CENTRAL, PEDro, Web of Science, SCOPUS, PsycINFO Ovid, CINAHL EBSCO, EMBASE, ScienceDirect, reference lists of relevant reviews, clinical trials registries and academic google, in June and July 2021. Randomized controlled trials were selected, which present the effect of tDCS on lower limb motor function recovery in stroke patients, comparing any type of active tDCS versus sham; parallel or crossover study design; adult patients; stimulation on the primary motor cortex; articles published in any language; without restriction of publication period.

RESULTS

Nineteen studies were included. The treatment with active tDCS did not improve motor function (Chi2 = 32,87, I2 = 76%, SMD = 0,36 e 95% CI -0,18-0,90). Subgroup analyzes showed a significant effect favorable to tDCS, in relation to motor function, in the acute and subacute post stroke phases. However, the quality of evidence for this outcome was very low. Regarding balance outcome, a meta-analysis showed a significant difference in favor of active tDCS, but the quality of the evidence was considered very low. As for the quality of life outcome, no statistically significant difference was found in favor of tDCS.

DISCUSSION

There is a lack of evidence in recommending the use of tDCS in isolation in the treatment of patients after stroke, aiming at improving motor function, balance and quality of life. However, it is possible that tDCS can be beneficial when associated with other therapies or interventions.

Evaluating the Asymmetry of Muscle Activation and Strength in Paralympic Powerlifting Athletes

BACKGROUND

Strength training is a complex task, as it requires a combination of many variables. In paralympic powerlifting (PP) asymmetries for the evaluation of activation, and static force indicators have been increasingly studied.

OBJECTIVE

To investigate the asymmetries in the strength and muscle activation indicators, before and after a training session of PP athletes.

METHODOLOGY

Twelve elite athletes from the PP participated in the study, and asymmetry was evaluated through surface electromyography (sEMG) and static strength indicators. Evaluations were made before and after a protocol of five series of five repetitions (5 × 5), with 80% of 1-Maximum Repetition (1RM).

RESULTS

In the pectoral muscles, there were differences in the non-dominant limbs between the before and after in the sEMG. There were differences in the pectoralis muscle in the non-dominant limb between moments before (110.75 ± 59.52%) and after (130.53 ± 98.48%, p < 0.001), and there was no difference in triceps activation. In the Maximum Isometric Strength (MIF), there was a difference in the non-dominant limb between before (710.36 ± 129.36) and after (620.27 ± 69.73; p < 0.030). There was a difference before in the dominant (626.89 ± 120.16; 95% CI 550.55-703.24) and non-dominant (710.36 ± 129.36; p = 0.011) limbs. There was no difference in time to MIF.

CONCLUSION

PP athletes showed small levels of asymmetry before and after training, and adaptation to training tends to promote fewer asymmetries.

Methods for automated delineation and assessment of EMG responses evoked by peripheral nerve stimulation in diagnostic and closed-loop therapeutic applications

Objective.Surface electromyography measurements of the Hoffmann (H-) reflex are essential in a wide range of neuroscientific and clinical applications. One promising emerging therapeutic application is H-reflex operant conditioning, whereby a person is trained to modulate the H-reflex, with generalized beneficial effects on sensorimotor function in chronic neuromuscular disorders. Both traditional diagnostic and novel realtime therapeutic applications rely on accurate definitions of the H-reflex and M-wave temporal bounds, which currently depend on expert case-by-case judgment. The current study automates such judgments.Approach.Our novel wavelet-based algorithm automatically determines temporal extent and amplitude of the human soleus H-reflex and M-wave. In each of 20 participants, the algorithm was trained on data from a preliminary 3 or 4 min recruitment-curve measurement. Output was evaluated on parametric fits to subsequent sessions' recruitment curves (92 curves across all participants) and on the conditioning protocol's subsequent baseline trials (∼1200 per participant) performed nearHmax. Results were compared against the original temporal bounds estimated at the time, and against retrospective estimates made by an expert 6 years later.Main results.Automatic bounds agreed well with manual estimates: 95% lay within ±2.5 ms. The resulting H-reflex magnitude estimates showed excellent agreement (97.5% average across participants) between automatic and retrospective bounds regarding which trials would be considered successful for operant conditioning. Recruitment-curve parameters also agreed well between automatic and manual methods: 95% of the automatic estimates of the current required to elicitHmaxfell within±1.4%of the retrospective estimate; for the 'threshold' current that produced an M-wave 10% of maximum, this value was±3.5%.Significance.Such dependable automation of M-wave and H-reflex definition should make both established and emerging H-reflex protocols considerably less vulnerable to inter-personnel variability and human error, increasing translational potential.

Assessment of Therapeutic Potential of a Dual AAV Approach for Duchenne Muscular Dystrophy

Duchenne muscular dystrophy (DMD) is a yet incurable rare genetic disease that affects the skeletal and cardiac muscles, leading to progressive muscle wasting and premature death. DMD is caused by the lack of dystrophin, a muscle protein essential for the biochemical support and integrity of muscle fibers. Gene replacement strategies for Duchenne muscular dystrophy (DMD) employing the adeno-associated virus (AAV) face the challenge imposed by the limited packaging capacity of AAV, only allowing the accommodation of a short version of dystrophin (µDys) that is still far removed from correcting human disease. The need to develop strategies leading to the expression of a best performing dystrophin variant led to only few studies reporting on the use of dual vectors, but none reported on a method to assess in vivo transgene reconstitution efficiency, the degree of which directly affects the use of safe AAV dosing. We report here on the generation of a dual AAV vector approach for the expression of a larger dystrophin version (quasidystrophin) based on homologous recombination, and the development of a methodology employing a strategic droplet digital PCR design, to determine the recombination efficiency as well as the occurrence of unwanted concatemerization events or aberrant expression from the single vectors. We demonstrated that, upon systemic delivery in the dystrophic D2.B10-Dmd^mdx/J (DBA2mdx) mice, our dual AAV approach led to high transgene reconstitution efficiency and negligible Inverted Terminal Repeats (ITR)-dependent concatemerization, with consequent remarkable protein restoration in muscles and improvement of muscle pathology. This evidence supports the suitability of our system for gene therapy application and the potential of this methodology to assess and improve the feasibility for therapeutic translation of multiple vector approaches.

Accumulation of Dystrophin-Positive Muscle Fibers and Improvement of Neuromuscular Junctions in mdx Mouse Muscles after Bone Marrow Transplantation under Different Conditions

Duchenne muscular dystrophy (DMD) is a severe muscular disorder caused by mutations in the dystrophin gene. It leads to respiratory and cardiac failure and premature death at a young age. Although recent studies have greatly deepened the understanding of the primary and secondary pathogenetic mechanisms of DMD, an effective treatment remains elusive. In recent decades, stem cells have emerged as a novel therapeutic product for a variety of diseases. In this study, we investigated nonmyeloablative bone marrow cell (BMC) transplantation as a method of cell therapy for DMD in an mdx mouse model. By using BMC transplantation from GFP-positive mice, we confirmed that BMCs participate in the muscle restoration of mdx mice. We analyzed both syngeneic and allogeneic BMC transplantation under different conditions. Our data indicated that 3 Gy X-ray irradiation with subsequent BMC transplantation improved dystrophin synthesis and the structure of striated muscle fibers (SMFs) in mdx mice as well as decreasing the death rate of SMFs. In addition, we observed the normalization of neuromuscular junctions (NMJs) in mdx mice after nonmyeloablative BMC transplantation. In conclusion, we demonstrated that nonmyeloablative BMC transplantation could be considered a method for DMD treatment.

Controversial Outcomes in Neck Rehabilitation between Surgically and Conservatively Treated Patients-Results of an Observational Study

The present study aimed to compare changes during inpatient rehabilitation between conservatively and surgically treated patients. A total of n = 162 patients with cervical spine complaints were included in the study (n = 107 conservatively treated, n = 55 after surgery). Patients completed disease-specific (NDI) and generic (NPRS, EQ-5D-5L, HAQ) patient reported outcome measures (PROMs) before and after rehabilitation. In addition, the range of motion (ROM) in the transversal plane of the cervical spine was measured. Changes and correlations between PROMs and ROM values during rehabilitation were assessed. The influence of moderating factors on NDI outcomes was examined. Significant improvements with large effect sizes were found in PROMs and ROM (all p < 0.001). The conservatively treated patients showed significantly greater NDI improvements than operated patients (p = 0.050), but a greater proportion of poor performance in ROM (p = 0.035). Baseline NDI (β = 0.66), HAQ (β = 0.14), and ROM scores (β = -0.17) explained 63.7% of the variance in NDI after rehabilitation. Both patient groups showed different outcomes. The findings of this study indicate that the unique needs of patients may require different therapeutic interventions and highlight the importance of using multidimensional outcome measures when implementing a multimodal rehabilitation approach.

Specification of Neck Muscle Dysfunction through Digital Image Analysis Using Machine Learning

Everyone has or will have experienced some degree of neck pain. Typically, neck pain is associated with the sensation of tense, tight, or stiff neck muscles. However, it is unclear whether the neck muscles are objectively stiffer with neck pain. This study used 1099 ultrasound elastography images (elastograms) obtained from 38 adult women, 20 with chronic neck pain and 18 asymptomatic. For training machine learning algorithms, 28 numerical characteristics were extracted from both the original and transformed shear wave velocity color-coded images as well as from respective image segments. Overall, a total number of 323 distinct features were generated from the data. A supervised binary classification was performed, using six machine-learning algorithms. The random forest algorithm produced the most accurate model to distinguish the elastograms of women with chronic neck pain from asymptomatic women with an AUC of 0.898. When evaluating features that can be used as biomarkers for muscle dysfunction in neck pain, the region of the deepest neck muscles (M. multifidus) provided the most features to support the correct classification of elastograms. By constructing summary images and associated Hotelling's T² maps, we enabled the visualization of group differences and their statistical confirmation.

An Experimental and Virtual Approach to Hip Revision Prostheses

(1) Introduction: The changes in the joint morphology inevitably lead to prosthesis, but the hip pathology is complex. The hip arthroplasty is a therapeutic solution and can be caused, most frequently, by primary and secondary coxarthrosis due to or followed by traumatic conditions. The main aim of this study was to find the method of revision hip prosthesis that preserves as much bone material as possible and has sufficiently good mechanical strength. (2) Materials and Methods: In this study, in a first step, the two revision prostheses were performed on bone components taken from an animal (cow), and then, they were tested on a mechanical testing machine until the prostheses physically failed, and the force causing their failure was determined. (3) Results: These prostheses were then modelled in a virtual environment and tested using the finite element method (FEM) in order to determine their behaviour under loading from normal human gait. Displacement, strain, and stress maps were obtained. (4) Discussion: Discussions on hip revision prostheses, method, and theory analysis are presented at the end of the paper. (5) Conclusions: Important conclusions are drawn based on comparative analyses. The main conclusion shows that the both orthopaedic prostheses provide a very good resistance.

Using Machine Learning to Identify Intravenous Contrast Phases on Computed Tomography

PURPOSE

The purpose of the present work is to demonstrate the application of machine learning (ML) techniques to automatically identify the presence and physiologic phase of intravenous (IV) contrast in Computed Tomography (CT) scans of the Chest, Abdomen and Pelvis.

MATERIALS AND METHODS

Training, testing and validation data were acquired from a dataset of 82,690 chest and abdomen CT examinations performed at 17 different institutions. Free text in DICOM metadata was utilized as weak labels for semi-supervised classification training. Contrast phase identification was approached as a classification task, using a 12-layer CNN and ResNet18 with four contrast-phase output. The model was reformulated to fit a regression task aimed to predict actual seconds from time of IV contrast administration to series image acquisition. Finally, transfer learning was used to optimize the model to predict contrast presence on CT Chest.

RESULTS

By training based on labels inferred from noisy, free text DICOM information, contrast phase was predicted with 93.3% test accuracy (95% CI: 89.3%, 96.6%) . Regression analysis resulted in delineation of early vs late arterial phases and a nephrogenic phase in between the portal venous and delayed excretory phase. Transfer learning applied to Chest CT achieved an AUROC of 0.776 (95% CI: 0.721, 0.832) directly using the model trained for abdomen CT and 0.999 (95% CI: 0.998, 1.000) by fine-tuning.

CONCLUSIONS

The presence and phase of contrast on CT examinations of the Abdomen-pelvis accurately and automatically be ascertained by a machine learning algorithm. Transfer learning applied to CT Chest achieves high precision with as little as 100 labeled samples.