The role of ultrasonographically measured rectus femoris muscle on falls in community-dwelling older adults: a single-center study

BACKGROUND

There are many risk factors for falls and sarcopenia has emerged as an important risk factor. Measuring muscle mass is a useful method to determine sarcopenia. Our aim was to determine the difference in muscle mass between older adults with (fallers) and without history of falls (non-fallers) using ultrasonography (US).

METHODS

Two hundred ten geriatric patients were enrolled. Fall was defined as an event declared by the person who fell. Sarcopenia was defined by EWGSOP2 criteria. Muscle mass was assessed by muscle ultrasonography of five different muscles.

RESULTS

The mean age of the whole study group was 74.1 ± 6.3 years and 58.1% (n = 122) of the total study population was female. Among the participants, 69 patients (31.3%) had a fall history. The sarcopenia ratio was 23.2% in the fallers, and it was 13.7% in the non-fallers, the difference was statistically insignificant (p > 0.05), the measurement of rectus femoris muscle (RF) thickness and cross-sectional area (RFCSA) were significantly smaller among the fallers than non-fallers (p < 0.05). The ROC analysis revealed that RF and RFCSA could determine the history of falls [for RF area under curve (AUC): 0.606, 95% confidence interval (CI) 0.526-0.686, p = 0.010 and for RFCSA AUC: 0.621, 95% CI 0.538-0.704, p = 0.004]. RFCSA was statistically relevant with a history of falls, regardless of age, sex, multimorbidity, incontinence, nutritional status, and frailty status.

CONCLUSION

Decreased RF and RFCSA determined by muscle US is a potentially modifiable risk factor for falls in older adults. Muscle US may be used for determining the risk of falls in older adults.

Quantitative assessment of muscle echogenicity in Charcot-Marie-Tooth disease type 1A by automatic thresholding methods

OBJECTIVE

To investigate the utility of automatic thresholding methods for quantitative muscle echogenicity assessment as a marker of disease severity in Charcot-Marie-Tooth disease type 1A (CMT1A).

METHODS

Muscle ultrasound was performed in 15 CMT1A patients and 7 healthy controls. Muscle echogenicity of six limb muscles in each subject was assessed by 16 automatic thresholding methods and conventional grey-scale analysis. Echogenicity of each method in CMT1A patients was compared with that in controls. A correlation between the echogenicity and CMT neuropathy score (CMTNS) was also analysed in CMT1A patients.

RESULTS

Significant differences in mean echogenicity of the 6 muscles between CMT1A patients and controls were found both in grey-scale analysis (p < 0.01) and 11 of the 16 automatic thresholding methods (p < 0.05 in each method). In CMT1A patients, mean echogenicity of the 6 muscles was positively correlated with CMTNS in 8 of the 16 automatic thresholding methods, but not in grey-scale analysis.

CONCLUSION

Automatic thresholding methods can be used to detect the difference in muscle echogenicity between CMT1A patients and controls. Echogenicity parameters correlate with the disease severity.

SIGNIFICANCE

Quantitative muscle echogenicity assessment by automatic thresholding methods shows potential as a surrogate marker of disease progression in CMT1A.

Evaluation of cervical spine muscles thickness in patients with cervical vertigo and healthy controls through ultrasonography

[Purpose] Cervical vertigo as a common complaint is associated with some musculoskeletal disorders. However, to date, ultrasonographical parameters of cervical muscles in patients with cervical vertigo have not been investigated. This study was conducted to investigate size of cervical muscles in patients with cervical vertigo compared to healthy controls. [Participants and Methods] Thicknesses of cervical flexor and extensor muscles were evaluated through ultrasonography and results were compared between the patients and healthy controls by Independent Samples t-test or Mann-Whitney U nonparametric test. [Results] Results showed that, thickness of Longus Colli muscle was significantly different between the patients and healthy controls. [Conclusion] According to findings of the study, size of Longus Colli muscle is likely to be associated with etiology of cervical vertigo.

Relationship between EMG-detected and ultrasound-detected fasciculations in amyotrophic lateral sclerosis: A prospective cohort study

OBJECTIVES

Fasciculation potentials (FP) are an important consideration in the electrophysiological diagnosis of ALS. Muscle ultrasonography (MUS) has a higher sensitivity in detecting fasciculations than electromyography (EMG), while in some cases, it is unable to detect EMG-detected fasciculations. We aimed to investigate the differences of FP between the muscles with and without MUS-detected fasciculations (MUS-fas).

METHODS

Thirty-one consecutive patients with sporadic ALS were prospectively recruited and in those, both needle EMG and MUS were performed. Analyses of the amplitude, duration, and number of phases of EMG-detected FPs were performed for seven muscles per patient, and results were compared between the muscles with and without MUS-fas in the total cohort.

RESULTS

The mean amplitude and phase number of FP were significantly lower in patients with EMG-detected FP alone (0.39 ± 0.25 mV and 3.21 ± 0.88, respectively) than in those with both FP and MUS-fas (1.22 ± 0.92 mV and 3.74 ± 1.39, respectively; p < 0.0001 and p = 0.017, Welch's t-test).

CONCLUSION

Small FP may be undetectable with MUS. MUS cannot replace EMG in the diagnostic approach for ALS.

SIGNIFICANCE

Clinicians should use a combination of EMG and MUS for the detection and quantitative analysis of fasciculation in ALS.

Muscle Type and Gender Recognition Utilising High-Level Textural Representation in Musculoskeletal Ultrasonography

Human assistive technology and computer-aided diagnosis is an emerging field in the area of medical imaging. Following the recent advances in this domain, a study for integrating machine learning techniques in musculoskeletal ultrasonography images was conducted. The goal of this attempt was to investigate how feature extraction techniques, that capture higher-level information, perform in identifying human characteristics. The potential success of these techniques could lead to significant improvement of the current assessment methods-as the gray-scale image analysis-for distinguishing healthy and pathologic conditions, that are heavily dependent on the image-acquisition system. The contribution of this work is threefold. First, a new privately held data set of 74 healthy patients was presented. This data set included musculoskeletal ultrasound images from four muscles of the human body, namely the biceps brachii, tibialis anterior, gastrocnemius medialis and rectus femoris, recorded in the transverse and longitudinal plane. Second, two classification tasks were performed, namely, gender and muscle-type recognition, to assess the performance of the proposed method for successfully identifying differences in the texture of the examined muscle sections. Third, a novel method used with great success in the computer vision domain was presented, allowing the extraction of a high-level feature representation, by encoding the distribution of locally invariant texture descriptors. On the muscle-type recognition our method achieved an 87.07% classification rate, and on the task of gender recognition it surpassed state-of-the-art textural representations, reported in the literature in almost all the examined muscle sections.

Ultrasound-based detection of glucocorticoid-induced impairments of muscle mass and structure in Cushing's disease

PURPOSE

To investigate the glucocorticoid-induced impairments of muscle mass and structure in patients presenting different stages of steroid myopathy progression.

METHODS

Thirty-three patients (28 women) affected by active (N = 20) and remitted (N = 13) Cushing's disease were recruited and the following variables were assessed: walking speed, handgrip strength, total body and appendicular muscle mass by bioelectrical impedance analysis (BIA), thickness and echo intensity of lower limb muscles by ultrasonography.

RESULTS

The two groups of patients showed comparable values of both handgrip strength [median (interquartile range) values: active disease: 27.4 (7.5) kg vs. remitted disease: 26.4 (9.4) kg; P = 0.58] and walking speed [active disease: 1.0 (0.2) m/s vs. remitted disease: 1.1 (0.3) m/s; P = 0.43]. Also, the thickness of the four muscles and all BIA-derived sarcopenic indices were comparable (P > 0.05 for all comparisons) between the two groups. On the contrary, the echo intensity of vastus lateralis, tibialis anterior (lower portion), and medial gastrocnemius was significantly (P < 0.05 for all comparisons) higher in patients with active disease compared to patients with remitted disease. Finally, significant negative correlations were found in the whole group of patients between muscle echo intensity and muscle function assessments.

CONCLUSIONS

We provided preliminary evidence that the ultrasound-derived measurements of muscle thickness and echo intensity can be useful to detect and track the changes of muscle mass and structure in patients with steroid myopathy and we suggest that the combined assessment of muscle mass, strength, and performance should be systematically applied in the routine examination of steroid myopathy patients.

Transverse Muscle Ultrasound Analysis (TRAMA): Robust and Accurate Segmentation of Muscle Cross-Sectional Area

Ultrasonography allows non-invasive and real time-measurement of the visible cross-sectional area (CSA) of muscles, which is a clinically relevant descriptor of muscle size. The aim of this study was to develop and validate a fully automatic method called transverse muscle ultrasound analysis (TRAMA) for segmentation of the muscle in B-mode transverse ultrasound images and measurement of muscle CSA. TRAMA was tested on a database of 200 ultrasound images of the rectus femoris, vastus lateralis, tibialis anterior and medial gastrocnemius muscles. The automatic CSA measurements were compared with manual measurements obtained by two operators. There were no statistical differences between the automatic and manual measurements of CSA of the four muscles, and TRAMA performance was comparable to intra-operator variability in terms of the Dice similarity coefficient and Hausdorff distance between the automatic and manual segmentations. Compared with manual segmentation, the Dice similarity coefficient for the proposed method was always higher than 93%; the Hausdorff distance never exceeded 4 mm, and the maximum absolute error was 62 mm². TRAMA is the first automated algorithm that analyzes and segments ultrasound scans of the muscle in the transverse plane. It can be adopted in future studies for automatic segmentation of muscle regions of interest to enhance and automatize a multitexture analysis of muscle structure.

Ultrasound assessment of rectus femoris and anterior tibialis muscles in young trauma patients

Purpose

Quantitative and qualitative changes of skeletal muscle are typical and early findings in trauma patients, being possibly associated with functional impairment. Early assessment of muscle changes—as evaluated by muscle ultrasonography—could yield important information about patient’s outcome.

Methods

In this prospective observational study, we used ultrasonography to evaluate the morphological changes of rectus femoris (RF) and anterior tibialis (AT) muscles in a group of young, previously healthy trauma patients on enteral feeding.

Results

We studied 38 severely injured patients (median Injury Severity Score = 34; median age = 40 y.o.) over the course of the ICU stay up to 3 weeks after trauma. We found a progressive loss of muscle mass from day 0 to day 20, that was more relevant for the RF (45%) than for the AT (22%); this was accompanied by an increase in echogenicity (up to 2.5 by the Heckmatt Scale, where normal echogenicity = 1), which is an indicator of myofibers depletion.

Conclusions

Ultrasound evaluation of skeletal muscles is inexpensive, noninvasive, simple and easily repeatable. By this method, we were able to quantify the morphological changes of skeletal muscle in trauma patients. Further studies may rely on this technicque to evaluate the impact of different therapeutic strategies on muscle wasting.

Fully Automated Muscle Ultrasound Analysis (MUSA): Robust and Accurate Muscle Thickness Measurement

Musculoskeletal ultrasound imaging allows non-invasive measurement of skeletal muscle thickness. Current techniques generally suffer from manual operator dependency, while all the computer-aided approaches are limited to be semi-automatic or specifically optimized for a single muscle. The aim of this study was to develop and validate a fully automatic method, named MUSA (Muscle UltraSound Analysis), for measurement of muscle thickness on longitudinal ultrasound images acquired from different skeletal muscles. The MUSA algorithm was tested on a database of 200 B-mode ultrasound images of rectus femoris, vastus lateralis, tibialis anterior and medial gastrocnemius. The automatic muscle thickness measurements were compared to the manual measurements obtained by three operators. The MUSA algorithm achieved a 100% segmentation success rate, with mean differences between the automatic and manual measurements in the range of 0.06-0.45 mm. MUSA performance was statistically equal to the operators and its measurement accuracy was independent of the muscle thickness value.

Advances in quantitative muscle ultrasonography using texture analysis of ultrasound images

Musculoskeletal ultrasound imaging can be used to investigate the skeletal muscle structure in terms of architecture (thickness, cross-sectional area, fascicle length and fascicle pennation angle) and texture. Gray-scale analysis is commonly used to characterize transverse scans of the muscle. Gray mean value is used to distinguish between normal and pathologic muscles, but it depends on the image acquisition system and its settings. In this study, quantitative ultrasonography was performed on five muscles (biceps brachii, vastus lateralis, rectus femoris, medial gastrocnemius and tibialis anterior) of 20 healthy patients (10 women, 10 men) to assess the characterization performance of higher-order texture descriptors to differentiate genders and muscle types. A total of 53 features (7 first-order descriptors, 24 Haralick features, 20 Galloway features and 2 local binary pattern features) were extracted from each muscle region of interest (ROI) and were used to perform the multivariate linear regression analysis (MANOVA). Our results show that first-order descriptors, Haralick features (energy, entropy and correlation measured along different angles) and local binary pattern (LBP) energy and entropy were highly linked to the gender, whereas Haralick entropy and symmetry, Galloway texture descriptors and LBP entropy helped to distinguish muscle types. Hence, the combination of first-order and higher-order texture descriptors (Haralick, Galloway and LBP) can be used to discriminate gender and muscle types. Therefore, multi-texture analysis may be useful to investigate muscle damage and myopathic disorders.