Automated regional analysis of B-mode ultrasound images of skeletal muscle movement

Quantitative Muscle Fascicle Tractography Using Brightness-Mode Ultrasound

A muscle's architecture, defined as the geometric arrangement of its fibers with respect to its mechanical line of action, impacts its abilities to produce force and shorten or lengthen under load. Ultrasound and other noninvasive imaging methods have contributed significantly to our understanding of these structure-function relationships. The goal of this work was to develop a MATLAB toolbox for tracking and mathematically representing muscle architecture at the fascicle scale, based on brightness-mode ultrasound imaging data. The MuscleUS_Toolbox allows user-performed segmentation of a region of interest and automated modeling of local fascicle orientation; calculation of streamlines between aponeuroses of origin and insertion; and quantification of fascicle length, pennation angle, and curvature. A method is described for optimizing the fascicle orientation modeling process, and the capabilities of the toolbox for quantifying and visualizing fascicle architecture are illustrated in the human tibialis anterior muscle. The toolbox is freely available.

A clustering-based method for estimating pennation angle from B-mode ultrasound images

B-mode ultrasound (US) is often used to noninvasively measure skeletal muscle architecture, which contains human intent information. Extracted features from B-mode images can help improve closed-loop human-robotic interaction control when using rehabilitation/assistive devices. The traditional manual approach to inferring the muscle structural features from US images is laborious, time-consuming, and subjective among different investigators. This paper proposes a clustering-based detection method that can mimic a well-trained human expert in identifying fascicle and aponeurosis and, therefore, compute the pennation angle. The clustering-based architecture assumes that muscle fibers have tubular characteristics. It is robust for low-frequency image streams. We compared the proposed algorithm to two mature benchmark techniques: UltraTrack and ImageJ. The performance of the proposed approach showed higher accuracy in our dataset (frame frequency is 20 Hz), that is, similar to the human expert. The proposed method shows promising potential in automatic muscle fascicle orientation detection to facilitate implementations in biomechanics modeling, rehabilitation robot control design, and neuromuscular disease diagnosis with low-frequency data stream.

Age-Related Reliability of B-Mode Analysis for Tailored Exosuit Assistance

In the field of wearable robotics, assistance needs to be individualized for the user to maximize benefit. Information from muscle fascicles automatically recorded from brightness mode (B-mode) ultrasound has been used to design assistance profiles that are proportional to the estimated muscle force of young individuals. There is also a desire to develop similar strategies for older adults who may have age-altered physiology. This study introduces and validates a ResNet + 2x-LSTM model for extracting fascicle lengths in young and older adults. The labeling was generated in a semimanual manner for young (40,696 frames) and older adults (34,262 frames) depicting B-mode imaging of the medial gastrocnemius. First, the model was trained on young and tested on both young (R2 = 0.85, RMSE = 2.36 ± 1.51 mm, MAPE = 3.6%, aaDF = 0.48 ± 1.1 mm) and older adults (R2 = 0.53, RMSE = 4.7 ± 2.51 mm, MAPE = 5.19%, aaDF = 1.9 ± 1.39 mm). Then, the performances were trained across all ages (R2 = 0.79, RMSE = 3.95 ± 2.51 mm, MAPE = 4.5%, aaDF = 0.67 ± 1.8 mm). Although age-related muscle loss affects the error of the tracking methodology compared to the young population, the absolute percentage error for individual fascicles leads to a small variation of 3-5%, suggesting that the error may be acceptable in the generation of assistive force profiles.

Automated Method for Tracking Human Muscle Architecture on Ultrasound Scans during Dynamic Tasks

Existing approaches for automated tracking of fascicle length (FL) and pennation angle (PA) rely on the presence of a single, user-defined fascicle (feature tracking) or on the presence of a specific intensity pattern (feature detection) across all the recorded ultrasound images. These prerequisites are seldom met during large dynamic muscle movements or for deeper muscles that are difficult to image. Deep-learning approaches are not affected by these issues, but their applicability is restricted by their need for large, manually analyzed training data sets. To address these limitations, the present study proposes a novel approach that tracks changes in FL and PA based on the distortion pattern within the fascicle band. The results indicated a satisfactory level of agreement between manual and automated measurements made with the proposed method. When compared against feature tracking and feature detection methods, the proposed method achieved the lowest average root mean squared error for FL and the second lowest for PA. The strength of the proposed approach is that the quantification process does not require a training data set and it can take place even when it is not possible to track a single fascicle or observe a specific intensity pattern on the ultrasound recording.

Automated semi-real-time detection of muscle activity with ultrasound imaging

Ultrasound imaging (USI) biofeedback is a useful therapeutic tool; however, it relies on qualitative assessment by a trained therapist, while existing automatic analysis techniques are computationally demanding. This study aims to present a computationally inexpensive algorithm based on the difference in pixel intensity between USI frames. During an offline experiment, where data was analyzed after the study, participants performed isometric contractions of the gastrocnemius medialis (GM) muscle, as executed (30% of maximum contraction) or attempted (low force contraction up to a point when the participant is aware of exerting force or contracting the muscle) movements, while USI, EMG, and force data were recorded. The algorithm achieved 99% agreement with EMG and force measurements for executed movements and 93% for attempted movements, with USI detecting 1.9% more contractions than the other methods. In the online study, participants performed GM muscle contractions at 10% and 30% of maximum contraction, while the algorithm provided visual feedback proportional to the muscle activity (based on USI recordings during the maximum contraction) in less than 3 s following each contraction. We show that the participants reached the target consistently, learning to perform precise contractions. The algorithm is reliable and computationally very efficient, allowing real-time applications on standard computing hardware. It is a suitable method for automated detection, quantification of muscle contraction, and to provide biofeedback which can be used for training of targeted muscles, making it suitable for rehabilitation.

Three-dimensional quantitative muscle ultrasound in a healthy population

INTRODUCTION/AIMS

Quantitative muscle ultrasound offers biomarkers that aid in the diagnosis, detection, and follow-up of neuromuscular disorders. At present, quantitative muscle ultrasound methods are 2D and are often operator and device dependent. The aim of this study was to combine an existing device independent method with an automated ultrasound machine and perform 3D quantitative muscle ultrasound, providing new normative data of healthy controls.

METHODS

In total, 123 healthy volunteers were included. After physical examination, 3D ultrasound scans of the tibialis anterior muscle were acquired using an automated ultrasound scanner. Image postprocessing was performed to obtain calibrated echo intensity values based on a phantom reference.

RESULTS

Tibialis anterior muscle volumes of 61.2 ± 24.1 mL and 53.7 ± 22.7 mL were scanned in males and females, respectively. Echo intensity correlated with gender**, age**, fat fraction*, histogram kurtosis**, skewness* and standard deviation** (*P < .05, **P < .01). Outcome measures did not differ significantly for different acquisition presets. The 3D quantitative muscle ultrasound revealed the non-uniformity of echo intensity values over the length of the tibialis anterior muscle.

DISCUSSION

Our method extended 2D measurements and confirmed previous findings. Our method and reported normative data of (potential) biomarkers can be used to study neuromuscular disorders.

MRCP as a biomarker of motor action with varying degree of central and peripheral contribution as defined by ultrasound imaging

Motor imagination is an alternative rehabilitation strategy for people who cannot execute real movements. However, it is still a matter of debate to which degree it involves activation of deeper muscle structures, which cannot be detected by surface electromyography (SEMG). Sixteen able-bodied participants performed cue based isometric ankle plantar flexion (active movement) followed by active relaxation under four conditions: executed movements with two levels of muscle contraction (fully executed and attempted movements, EM and AM) and motor imagination with and without detectable muscle twitches (IT and I). The most prominent peaks and distinctive phases of movement-related cortical potential (MRCP) were compared between conditions. Ultrasound imaging (USI) and SEMG were used to detect movements. IT showed spatially distinctive significant differences compared to both I and AM during active movement preparation and reafferentation phase; further widespread differences were found between IT and AM during active movement execution and posteriorly during preparation for active relaxation. EM and AM showed the largest differences frontally during active movement planning and posteriorly during execution of active relaxation. Movement preparation positivity P1 showed a significant difference in amplitude between IT and AM but not between IT and I. USI can detect subliminal movements (twitches) better than SEMG. MRCP is a biomarker sensitive to different levels of muscle contraction and relaxation. IT is a motor condition distinguishable from both I and AM. EEG biomarkers of movements could be used to identify pathological conditions, that manifest themselves during either active contraction or active relaxation.NEW & NOTEWORTHY Ultrasound imaging can detect subtle muscle movements (twitches) that are not detectable with electromyography. Almost a quarter of trials of imagined movements in able-bodied people are accompanied by twitches. Analysis of movement-related cortical potential showed that motor imagination with twitches is a condition distinguishable from motor imagination without twitches and from motor attempts.

Ultrasound Imaging as a Diagnostic Tool to Assess the Functional Status of Muscles after a Spinal Cord Injury

The aim of this study was to evaluate the use of ultrasound imaging (USI) as a diagnostic tool to assess muscle function after a spinal cord injury (SCI). Ultrasound videos of the gastrocnemius medialis muscle were recorded both at rest and during attempted maximum voluntary contraction (MVC) for fifteen participants with a SCI and fifteen able-bodied controls. Measurements were repeated at monthly intervals for participants in the SCI group during their inpatient stay. Differences in muscle echogenicity and thickness were detected between both able-bodied and SCI groups and subgroups of SCI participants, suggesting USI can detect and monitor changes in muscle structure which are characteristic of atrophy. Decreased muscle movement in the SCI groups was also detected during attempted MVC. The ability of USI to distinguish between different levels of function demonstrates the potential of USI as a quantitative tool to assess muscles.

Comparison between surface electrodes and ultrasound monitoring to measure TMS evoked muscle contraction

INTRODUCTION

Transcranial magnetic stimulation (TMS) is widely used to explore cortical physiology in health and disease. Surface electromyography (sEMG) is appropriate for superficial muscles, but cannot be applied easily to less accessible muscles. Muscle ultrasound (mUS) may provide an elegant solution to this problem, but fundamental questions remain. We explore the relationship between TMS evoked muscle potentials and TMS evoked muscle contractions measured with mUS.

METHODS

In 10 participants, we performed a TMS recruitment curve, simultaneously measuring motor evoked potentials (MEPs) and mUS in biceps (BI), first dorsal interosseous (FDI), tibialis anterior (TA), and the tongue (TO).

RESULTS

Resting motor threshold (RMT) measurements and recruitment curves were found to be consistent across sEMG and mUS.

DISCUSSION

This work supports the use of TMS-US to study less accessible muscles. The implications are broad but could include the study of a new range of muscles in disorders such as amyotrophic lateral sclerosis.

In vivo oscillations of the soleus muscle can be quantified using b-mode ultrasound imaging during walking and running in humans

Impact forces, due to the foot contacting the ground during locomotion, can be considered input signals to the body that must be dissipated to prevent impact-related injuries. One proposed mechanism employed by the body to damp the impact is through vibrations of the skeletal muscles. However, there is yet to be direct in vivo measures of muscle oscillations during locomotion. This study investigated the use of 2D ultrasound imaging to quantify transverse muscle oscillations (deep-superficial displacement of the muscle boundary relative to the skin) in response to impact forces elicited by walking and running at a range of speeds. Increases in vertical impact forces with faster walking and running was consistent with changes in both magnitude and frequency in the measured oscillations of the soleus muscle; one of the main human ankle plantar flexors. Muscle oscillations contained more higher frequency components at fast running (50% signal power in frequencies below ~ 14 Hz) compared with slow walking (50% signal power contained in frequencies below ~ 5 Hz). This study provides a platform for ultrasound imaging to examine muscle oscillation responses to impact forces induced by changes in external interfaces such as shoe material, locomotion type and ground surface properties.

Ultrasound imaging to assess skeletal muscle architecture during movements: a systematic review of methods, reliability, and challenges

B-mode ultrasound is often used to quantify muscle architecture during movements. Our objectives were to 1) systematically review the reliability of fascicle length (FL) and pennation angles (PA) measured using ultrasound during movements involving voluntary contractions; 2) systematically review the methods used in studies reporting reliability, discuss associated challenges, and provide recommendations to improve the reliability and validity of dynamic ultrasound measurements; and 3) provide an overview of computational approaches for quantifying fascicle architecture, their validity, agreement with manual quantification of fascicle architecture, and advantages and drawbacks. Three databases were searched until June 2019. Studies among healthy human individuals aged 17-85 yr that investigated the reliability of FL or PA in lower-extremity muscles during isoinertial movements and that were written in English were included. Thirty studies (n = 340 participants) were included for reliability analyses. Between-session reliability as measured by coefficient of multiple correlations (CMC), and coefficient of variation (CV) was FL CMC: 0.89-0.96; CV: 8.3% and PA CMC: 0.87-0.90; CV: 4.5-9.6%. Within-session reliability was FL CMC: 0.82-0.99; CV: 0.0-6.7% and PA CMC: 0.91; CV: 0.0-15.0%. Manual analysis reliability was FL CMC: 0.89-0.96; CV: 0.0-15.9%; PA CMC: 0.84-0.90; and CV: 2.0-9.8%. Computational analysis FL CMC was 0.82-0.99, and PA CV was 14.0-15.0%. Eighteen computational approaches were identified, and these generally showed high agreement with manual analysis and high validity compared with phantoms or synthetic images. B-mode ultrasound is a reliable method to quantify fascicle architecture during movement. Additionally, computational approaches can provide a reliable and valid estimation of fascicle architecture.

Estimation of absolute states of human skeletal muscle via standard B-mode ultrasound imaging and deep convolutional neural networks

The objective is to test automated in vivo estimation of active and passive skeletal muscle states using ultrasonic imaging. Current technology (electromyography, dynamometry, shear wave imaging) provides no general, non-invasive method for online estimation of skeletal muscle states. Ultrasound (US) allows non-invasive imaging of muscle, yet current computational approaches have never achieved simultaneous extraction or generalization of independently varying active and passive states. We use deep learning to investigate the generalizable content of two-dimensional (2D) US muscle images. US data synchronized with electromyography of the calf muscles, with measures of joint moment/angle, were recorded from 32 healthy participants (seven female; ages: 27.5, 19–65). We extracted a region of interest of medial gastrocnemius and soleus using our prior developed accurate segmentation algorithm. From the segmented images, a deep convolutional neural network was trained to predict three absolute, drift-free components of the neurobiomechanical state (activity, joint angle, joint moment) during experimentally designed, simultaneous independent variation of passive (joint angle) and active (electromyography) inputs. For all 32 held-out participants (16-fold cross-validation) the ankle joint angle, electromyography and joint moment were estimated to accuracy 55 ± 8%, 57 ± 11% and 46 ± 9%, respectively. With 2D US imaging, deep neural networks can encode, in generalizable form, the activity–length–tension state relationship of these muscles. Observation-only, low-power 2D US imaging can provide a new category of technology for non-invasive estimation of neural output, length and tension in skeletal muscle. This proof of principle has value for personalized muscle assessment in pain, injury, neurological conditions, neuropathies, myopathies and ageing.

Semi-automatic methods for tracking the medial gastrocnemius muscle-tendon junction using ultrasound: a validation study

NEW FINDINGS

What is the central question of this study? Is the proposed semi-automatic algorithm suitable for tracking the medial gastrocnemius muscle-tendon junction in ultrasound images collected during passive and active conditions? What is the main finding and its importance? The validation of a method allowing efficient tracking of the muscle-tendon junction in both passive and active conditions, in healthy as well as in pathological conditions. This method was tested in common acquisition conditions and the developed software made freely available.

ABSTRACT

Clinically relevant information can be extracted from ultrasound (US) images by tracking the displacement of the junction between muscle and tendon. This paper validated automatic methods for tracking the location of muscle-tendon junction (MTJ) between the medial gastrocnemius and the Achilles tendon during passive slow and fast stretches, and active ankle rotations while walking on a treadmill. First, an automatic algorithm based on an optical flow approach was applied on collected US images. Second, results of the automatic algorithm were evaluated and corrected using a quality measure that indicated which critical images need to be manually corrected. US images from 12 typically developed (TD) children, 12 children with spastic cerebral palsy (SCP) and eight healthy adults were analysed. Automatic and semi-automatic tracking methods were compared to manual tracking using root mean square errors (RMSE). For the automatic tracking, RMSE was less than 3.1 mm for the slow stretch and 5.2 mm for the fast stretch, the worst case being for SCP. The tracking results in the fast stretch condition were improved (especially in SCP) by using the semi-automatic approach, with an RMSE reduction of about 30%. During walking, the semi-automatic method also reduced errors, with a final RMSE of 3.6 mm. In all cases, data processing was considerably shorter using the semi-automatic method (2 min) compared to manual tracking (20 min). A quick manual correction considerably improves tracking of the MTJ during gait and allows to achieve results suitable for further analyses. The proposed algorithm is freely available.

Ultrasound-derived changes in thickness of human ankle plantar flexor muscles during walking and running are not homogeneous along the muscle mid-belly region

Skeletal muscle thickness is a valuable indicator of several aspects of a muscle’s functional capabilities. We used computational analysis of ultrasound images, recorded from 10 humans walking and running at a range of speeds (0.7–5.0 m s⁻¹), to quantify interactions in thickness change between three ankle plantar flexor muscles (soleus, medial and lateral gastrocnemius) and quantify thickness changes at multiple muscle sites within each image. Statistical analysis of thickness change as a function of stride cycle (1d statistical parametric mapping) revealed significant differences between soleus and both gastrocnemii across the whole stride cycle as they bulged within the shared anatomical space. Within each muscle, changes in thickness differed between measurement sites but not locomotor condition. For some of the stride, thickness measures taken from the distal-mid image region represented the mean muscle thickness, which may therefore be a reliable region for these measures. Assumptions that muscle thickness is constant during a task, often made in musculoskeletal models, do not hold for the muscles and locomotor conditions studied here and researchers should not assume that a single thickness measure, from one point of the stride cycle or a static image, represents muscle thickness during dynamic movements.

Automatic ROI Placement in the Upper Trapezius Muscle in B-mode Ultrasound Images

Research involving B-mode ultrasound imaging often requires user defined regions of interest (ROIs) for analysis, traditionally drawn/selected by a trained operator. This manual process is incredibly time consuming and subjective. Here, we propose a fast and simple method of detecting the average location of aponeurosis layers in ultrasound images of the upper trapezius to place a rectangular ROI for quantitative image analysis. A total of 56 B-mode ultrasound images were analyzed, where rectangular ROIs were manually placed in the skeletal muscle by two trained operators. Interoperator agreement was determined between the ROI border locations using intercorrelation coefficient (ICC). Next, our automatic algorithm was applied (image thresholding, binary masking, and pixel intensity peak detection), estimating the mean position of both aponeurosis layers for rectangular ROI placement. The automatic estimation method was compared with the manual (visual) method by various statistics ( t test, linear correlation, Bland-Altman plot). The performance was also evaluated under additive noise conditions (Speckle). Finally, agreement of the overlapping ROI area between the manual and automatic methods was also computed. Performance of the automatic method compared with manual placement was excellent for both the superficial and deep ROI borders, performing consistently even with additive noise (error <0.674 ± 1.69 mm). Manual measurements indicated excellent consensus (ICC = 0.902) between operators. The overlapping area between the manual and automatic measurements demonstrated good agreement (90.65 ± 11.3%). With constraints, our method is robust even under large levels of noise addition making the automatic algorithm an acceptable replacement for manual ROI placement in the upper trapezius.

Investigation of different stimulation patterns with doublet pulses to reduce muscle fatigue

Introduction: Functional electrical stimulation is a common technique used in the rehabilitation of individuals with a spinal cord injury to produce functional movement of paralysed muscles. However, it is often associated with rapid muscle fatigue which limits its applications. Methods: The objective of this study is to investigate the effects on the onset of fatigue of different multi-electrode patterns of stimulation via multiple pairs of electrodes using doublet pulses: Synchronous stimulation is compared to asynchronous stimulation patterns which are activated sequentially (AsynS) or randomly (AsynR), mimicking voluntary muscle activation by targeting different motor units. We investigated these three different approaches by applying stimulation to the gastrocnemius muscle repeatedly for 10 min (300 ms stimulation followed by 700 ms of no-stimulation) with 40 Hz effective frequency for all protocols and doublet pulses with an inter-pulse-interval of 6 ms. Eleven able-bodied volunteers (28 ± 3 years old) participated in this study. Ultrasound videos were recorded during stimulation to allow evaluation of changes in muscle morphology. The main fatigue indicators we focused on were the normalised fatigue index, fatigue time interval and pre-post twitch–tetanus ratio. Results: The results demonstrate that asynchronous stimulation with doublet pulses gives a higher normalised fatigue index (0.80 ± 0.08 and 0.87 ± 0.08) for AsynS and AsynR, respectively, than synchronous stimulation (0.62 ± 0.06). Furthermore, a longer fatigue time interval for AsynS (302.2 ± 230.9 s) and AsynR (384.4 ± 279.0 s) compared to synchronous stimulation (68.0 ± 30.5 s) indicates that fatigue occurs later during asynchronous stimulation; however, this was only found to be statistically significant for one of two methods used to calculate the group mean. Although no significant difference was found in pre-post twitch–tetanus ratio, there was a trend towards these effects. Conclusion: In this study, we proposed an asynchronous stimulation pattern for the application of functional electrical stimulation and investigated its suitability for reducing muscle fatigue compared to previous methods. The results show that asynchronous multi-electrode stimulation patterns with doublet pulses may improve fatigue resistance in functional electrical stimulation applications in some conditions.

Foreground Detection Analysis of Ultrasound Image Sequences Identifies Markers of Motor Neurone Disease across Diagnostically Relevant Skeletal Muscles

Diagnosis of motor neurone disease (MND) includes detection of small, involuntary muscle excitations, termed fasciculations. There is need to improve diagnosis and monitoring of MND through provision of objective markers of change. Fasciculations are visible in ultrasound image sequences. However, few approaches that objectively measure their occurrence have been proposed; their performance has been evaluated in only a few muscles; and their agreement with the clinical gold standard for fasciculation detection, intramuscular electromyography, has not been tested. We present a new application of adaptive foreground detection using a Gaussian mixture model (GMM), evaluating its accuracy across five skeletal muscles in healthy and MND-affected participants. The GMM provided good to excellent accuracy with the electromyography ground truth (80.17%-92.01%) and was robust to different ultrasound probe orientations. The GMM provides objective measurement of fasciculations in each of the body segments necessary for MND diagnosis and hence could provide a new, clinically relevant disease marker.

Automatic Myotendinous Junction Tracking in Ultrasound Images with Phase-Based Segmentation

Displacement of the myotendinous junction (MTJ) obtained by ultrasound imaging is crucial to quantify the interactive length changes of muscles and tendons for understanding the mechanics and pathological conditions of the muscle-tendon unit during motion. However, the lack of a reliable automatic measurement method restricts its application in human motion analysis. This paper presents an automated measurement of MTJ displacement using prior knowledge on tendinous tissues and MTJ, precluding the influence of nontendinous components on the estimation of MTJ displacement. It is based on the perception of tendinous features from musculoskeletal ultrasound images using Radon transform and thresholding methods, with information about the symmetric measures obtained from phase congruency. The displacement of MTJ is achieved by tracking manually marked points on tendinous tissues with the Lucas-Kanade optical flow algorithm applied over the segmented MTJ region. The performance of this method was evaluated on ultrasound images of the gastrocnemius obtained from 10 healthy subjects (26.0 ± 2.9 years of age). Waveform similarity between the manual and automatic measurements was assessed by calculating the overall similarity with the coefficient of multiple correlation (CMC). In vivo experiments demonstrated that MTJ tracking with the proposed method (CMC = 0.97 ± 0.02) was more consistent with the manual measurements than existing optical flow tracking methods (CMC = 0.79 ± 0.11). This study demonstrated that the proposed method was robust to the interference of nontendinous components, resulting in a more reliable measurement of MTJ displacement, which may facilitate further research and applications related to the architectural change of muscles and tendons.

Management and control of isotonic contraction generated stress: evaluation of masseter muscle deformation pattern by means of ecography

PURPOSE

The objective of the following study is to observe the behavior of the six layers of the masseter during an isometric contraction at maximum exertion with the deformation pattern analysis method.

MATERIALS AND METHODS

This study has been conducted by use of an ultrasound machine (MicrUs ext-1H Telemed Medical Systems Milano) and a linear probe (L12-5l40S-3 5-12 MHz 40 mm) which allowed us to record a video (DCM) comprised of 45 frames per second. The probe was fixed to a brace and the patient was asked to clench their teeth as hard as possible, obtain the muscle's maximum exertion, for 5 seconds three times, with 30 seconds intervals in between. Both right and left masseter muscles were analyzed. Then we applied to the resulting video a software (Mudy 1.7.7.2 AMID Sulmona Italy) for the analysis of muscle deformation patterns (contraction, dilatation, cross-plane, vertical strain, horizontal strain, vertical shear, horizontal shear, horizontal displacement, vertical displacement). The number of videos of masseter muscles in contraction at maximum exertion due to dental clenching made during this research is around 12,000. Out of these we chose 1,200 videos which examine 200 patients (100 females, 100 males).

RESULTS

The analysis of the deformation patterns of the masseter allows us to observe how the six layers of the muscle have different and specific functions each, which vary depending on the applied force (application point, magnitude and direction) so that we find it impossible to assign to one of the three sections of the muscle a mechanical predominance. Therefore it appears that the three parts of the muscle have specific and synergistic tasks.

Ultrasound and analysis of the deformation patterns of the masseter muscle: comparing surgical anatomy, ultrasound and functional anatomy

PURPOSE

We have tried to demonstrate whether the analysis of the muscle strain allows us to identify the three distinct functional areas of the architecture of the masseter, as one would see them by performing or viewing an anatomical dissection of said muscle, and whether these sections have behave differently in terms of origin and coping of the strain they face (quantitative analysis).

MATERIALS AND METHODS

This work has been elaborated by the use of an ultrasound machine (MicrUs ext-1H Telemed Medical Systems Milano) and a linear probe (L12-5l40S-3 5-12 MHz 40 mm) which allowed us to record a 45 frame per second video (DCM). Videos has been elaborated by use of an ultrasound machine (MicrUs ext-1H Telemed Medical Systems Milano) and a linear probe (L12-5l40S-3 5-12 MHz 40 mm) which allowed us to record a 45 frame per second video (DCM). We applied to the resulting video a software (Mudy 1.7.7.2 AMID Sulmona Italy) for the analysis of muscle deformation patters (contraction, dilatation, cross-plane, vertical strain, horizontal strain, vertical shear, horizontal shear, horizontal displacement, vertical displacement). The number of videos of masseter muscles in contraction at maximum exertion due to dental clenching made during this research is around 12,000. Out of these we chose 1,200 videos which examine 200 patients (100 females, 100 males).

RESULTS

The deformation pattern analysis of the skeletal muscle on ultrasound basis seems to be an adequate instrument to use during the investigation of the functional structure of the masseter muscle given its ability to highlight the distinct activity of each separate part of the muscle.

CONCLUSIONS

Moreover the strain does not apply to the muscle uniformly; instead it varies according to the observed area.

Real-Time Ultrasound Segmentation, Analysis and Visualisation of Deep Cervical Muscle Structure

Despite widespread availability of ultrasound and a need for personalised muscle diagnosis (neck/back pain-injury, work related disorder, myopathies, neuropathies), robust, online segmentation of muscles within complex groups remains unsolved by existing methods. For example, Cervical Dystonia (CD) is a prevalent neurological condition causing painful spasticity in one or multiple muscles in the cervical muscle system. Clinicians currently have no method for targeting/monitoring treatment of deep muscles. Automated methods of muscle segmentation would enable clinicians to study, target, and monitor the deep cervical muscles via ultrasound. We have developed a method for segmenting five bilateral cervical muscles and the spine via ultrasound alone, in real-time. Magnetic Resonance Imaging (MRI) and ultrasound data were collected from 22 participants (age: 29.0±6.6, male: 12). To acquire ultrasound muscle segment labels, a novel multimodal registration method was developed, involving MRI image annotation, and shape registration to MRI-matched ultrasound images, via approximation of the tissue deformation. We then applied polynomial regression to transform our annotations and textures into a mean space, before using shape statistics to generate a texture-to-shape dictionary. For segmentation, test images were compared to dictionary textures giving an initial segmentation, and then we used a customized Active Shape Model to refine the fit. Using ultrasound alone, on unseen participants, our technique currently segments a single image in [Formula: see text] to over 86% accuracy (Jaccard index). We propose this approach is applicable generally to segment, extrapolate and visualise deep muscle structure, and analyse statistical features online.

UltraTrack: Software for semi-automated tracking of muscle fascicles in sequences of B-mode ultrasound images

BACKGROUND

Dynamic measurements of human muscle fascicle length from sequences of B-mode ultrasound images have become increasingly prevalent in biomedical research. Manual digitisation of these images is time consuming and algorithms for automating the process have been developed. Here we present a freely available software implementation of a previously validated algorithm for semi-automated tracking of muscle fascicle length in dynamic ultrasound image recordings, "UltraTrack".

METHODS

UltraTrack implements an affine extension to an optic flow algorithm to track movement of the muscle fascicle end-points throughout dynamically recorded sequences of images. The underlying algorithm has been previously described and its reliability tested, but here we present the software implementation with features for: tracking multiple fascicles in multiple muscles simultaneously; correcting temporal drift in measurements; manually adjusting tracking results; saving and re-loading of tracking results and loading a range of file formats.

RESULTS

Two example runs of the software are presented detailing the tracking of fascicles from several lower limb muscles during a squatting and walking activity.

CONCLUSION

We have presented a software implementation of a validated fascicle-tracking algorithm and made the source code and standalone versions freely available for download.

Analysis of masseter deformation patterns during a maximum exertion clenching in patients with unilateral chewing

PURPOSE

The aim of the following study is to examine both masseter muscles (left/right) in a group of patients suffering from unilateral chewing during a maximum exertion isometric contraction using the deformation pattern analysis of ultrasound videos and compare them with the results obtained by studying patients with alternate bilateral chewing patterns.

MATERIALS AND METHODS

This study has been conducted by use of an ultrasound machine and a linear probe which allowed us to record a video (DCM) comprised of 45 frames per second (MicrUs ext-1H Telemed Medical Systems Milano) and a linear probe (L12-5l40S-3 5-12 MHz 40 mm). The probe was fixed to a brace and the patients were asked to clench their teeth as hard as possible, obtain the muscle's maximum exertion, for 5 seconds three times, with 30 seconds intervals in between. Both right and left masseter muscles were analyzed. We applied to the ultrasound video a dedicated software (Mudy 1.7.7.2 AMID Sulmona Italy) for the analysis of muscle deformation patterns. The total number of patients for this study is 150. Out of this number, 50 belong to Group A, mono lateral chewing on the left side arch, and 50 to Group B, mono lateral chewing on the right side arch. The remains patients belong to Group C, bilateral alternate chewing. The deformation pattern analysis of the skeletal muscles on ultrasound videos allows us to highlight with ease the clear difference in the clenching capabilities and strain management between the dominant masseter and the subordinate masseter in a unilaterally chewing patient.

RESULTS

In the sample investigated both in Group A and Group B the unilateral chewing is associated with a series of parameters (number, shape, volume, position and orientation of the teeth) and is also associated with the extension of the cutting surface really available.

Automatic Fascicle Length Estimation on Muscle Ultrasound Images With an Orientation-Sensitive Segmentation

GOAL

The fascicle length obtained by ultrasound imaging is one of the crucial muscle architecture parameters for understanding the contraction mechanics and pathological conditions of muscles. However, the lack of a reliable automatic measurement method restricts the application of the fascicle length for the analysis of the muscle function, as frame-by-frame manual measurement is time-consuming. In this study, we propose an automatic measurement method to preclude the influence of nonfascicle components on the estimation of the fascicle length by using motion estimation of fascicle structures.

METHODS

The method starts with image segmentation using the cohesiveness of fascicle orientation as a feature, obtaining the fascicle change by tracking manually marked points on the fascicular path with the Lucas-Kanade optical flow algorithm applied on the segmented image.

RESULTS

The performance of this method was evaluated on ultrasound images of the gastrocnemius obtained from seven healthy subjects (34.4 ± 5.0 years). Waveform similarity between the manual and dynamic measurements was assessed by calculating the overall similarity with the coefficient of multiple correlations (CMC). In vivo experiments demonstrated that fascicle tracking with the orientation-sensitive segmentation (CMC = 0.97 ± 0.01) was more consistent with the manual measurements than existing automatic methods (CMC = 0.87 ± 0.10).

CONCLUSION

Our method was robust to the interference of nonfascicle components, resulting in a more reliable measurement of the fascicle length.

SIGNIFICANCE

The proposed method may facilitate further research and applications related to real-time architectural change of muscles.

Automatic measurement of pennation angle and fascicle length of gastrocnemius muscles using real-time ultrasound imaging

Muscle imaging is a promising field of research to understand the biological and bioelectrical characteristics of muscles through the observation of muscle architectural change. Sonomyography (SMG) is a technique which can quantify the real-time architectural change of muscles under different contractions and motions with ultrasound imaging. The pennation angle and fascicle length are two crucial SMG parameters to understand the contraction mechanics at muscle level, but they have to be manually detected on ultrasound images frame by frame. In this study, we proposed an automatic method to quantitatively identify pennation angle and fascicle length of gastrocnemius (GM) muscle based on multi-resolution analysis and line feature extraction, which could overcome the limitations of tedious and time-consuming manual measurement. The method started with convolving Gabor wavelet specially designed for enhancing the line-like structure detection in GM ultrasound image. The resulting image was then used to detect the fascicles and aponeuroses for calculating the pennation angle and fascicle length with the consideration of their distribution in ultrasound image. The performance of this method was tested on computer simulated images and experimental images in vivo obtained from normal subjects. Tests on synthetic images showed that the method could identify the fascicle orientation with an average error less than 0.1°. The result of in vivo experiment showed a good agreement between the results obtained by the automatic and the manual measurements (r=0.94±0.03; p<0.001, and r=0.95±0.02, p<0.001). Furthermore, a significant correlation between the ankle angle and pennation angle (r=0.89±0.05; p<0.001) and fascicle length (r=-0.90±0.04; p<0.001) was found for the ankle plantar flexion. This study demonstrated that the proposed method was able to automatically measure the pennation angle and fascicle length of GM ultrasound images, which made it feasible to investigate muscle-level mechanics more comprehensively in vivo.

Transverse Strains in Muscle Fascicles during Voluntary Contraction: A 2D Frequency Decomposition of B-Mode Ultrasound Images

When skeletal muscle fibres shorten, they must increase in their transverse dimensions in order to maintain a constant volume. In pennate muscle, this transverse expansion results in the fibres rotating to greater pennation angle, with a consequent reduction in their contractile velocity in a process known as gearing. Understanding the nature and extent of this transverse expansion is necessary to understand the mechanisms driving the changes in internal geometry of whole muscles during contraction. Current methodologies allow the fascicle lengths, orientations, and curvatures to be quantified, but not the transverse expansion. The purpose of this study was to develop and validate techniques for quantifying transverse strain in skeletal muscle fascicles during contraction from B-mode ultrasound images. Images were acquired from the medial and lateral gastrocnemii during cyclic contractions, enhanced using multiscale vessel enhancement filtering and the spatial frequencies resolved using 2D discrete Fourier transforms. The frequency information was resolved into the fascicle orientations that were validated against manually digitized values. The transverse fascicle strains were calculated from their wavelengths within the images. These methods showed that the transverse strain increases while the longitudinal fascicle length decreases; however, the extent of these strains was smaller than expected.

Estimation and visualization of longitudinal muscle motion using ultrasonography: a feasibility study

Ultrasonography is a convenient and widely used technique to look into the longitudinal muscle motion as it is radiation-free and real-time. The motion of localized parts of the muscle, disclosed by ultrasonography, spatially reflects contraction activities of the corresponding muscles. However, little attention was paid to the estimation of longitudinal muscle motion, especially towards estimation of dense deformation field at different depths under the skin. Yet fewer studies on the visualization of such muscle motion or further clinical applications were reported in the literature. A primal-dual algorithm was used to estimate the motion of gastrocnemius muscle (GM) in longitudinal direction in this study. To provide insights into the rules of longitudinal muscle motion, we proposed a novel framework including motion estimation, visualization and quantitative analysis to interpret synchronous activities of collaborating muscles with spatial details. The proposed methods were evaluated on ultrasound image sequences, captured at a rate of 25 frames per second from eight healthy subjects. In order to estimate and visualize the GM motion in longitudinal direction, each subject was asked to perform isometric plantar flexion twice. Preliminary results show that the proposed visualization methods provide both spatial and temporal details and they are helpful to study muscle contractions. One of the proposed quantitative measures was also tested on a patient with unilateral limb dysfunction caused by cerebral infarction. The measure revealed distinct patterns between the normal and the dysfunctional lower limb. The proposed framework and its associated quantitative measures could potentially be used to complement electromyography (EMG) and torque signals in functional assessment of skeletal muscles.

Use of optical flow to estimate continuous changes in muscle thickness from ultrasound image sequences

Muscle thickness is one of the most widely used parameters for quantifying muscle function. Ultrasonography is frequently used to estimate changes in muscle thickness in both static and dynamic contractions. Conventionally, most such measurements are conducted by manual analysis of ultrasound images. This manual approach is time consuming, subjective, susceptible to error and not suitable for measuring dynamic change. In this study, we developed an automated tracking method based on an optical flow algorithm using an affine motion model. The goal of the study was to evaluate the performance of the proposed method by comparing it with the manual approach and by determining its repeatability. Real-time B-mode ultrasound was used to examine the rectus femoris during voluntary contraction. The coefficient of multiple correlation (CMC) was used to quantify the level of agreement between the two methods and the repeatability of the proposed method. The two methods were also compared by linear regression and Bland-Altman analysis. The findings indicated that the results obtained using the proposed method were in good agreement with those obtained using the manual approach (CMC = 0.97 ± 0.02, difference = -0.06 ± 0.22 mm) and were highly repeatable (CMC = 0.91 ± 0.07). In conclusion, the automated method proposed here provides an accurate, highly repeatable and efficient approach to the estimation of muscle thickness during muscle contraction.

An efficient framework for estimation of muscle fiber orientation using ultrasonography

BACKGROUND

Muscle fiber orientation (MFO) is an important parameter related to musculoskeletal functions. The traditional manual method for MFO estimation in sonograms was labor-intensive. The automatic methods proposed in recent years also involved voting procedures which were computationally expensive.

METHODS

In this paper, we proposed a new framework to efficiently estimate MFO in sonograms. We firstly employed Multi-scale Vessel Enhancement Filtering (MVEF) to enhance fascicles in the sonograms and then the enhanced images were binarized. Finally, line-shaped patterns in the binary map were detected one by one, according to their shape properties. Specifically speaking, for the long-and-thinner regions, the orientation of the targeted muscle fibre was directly computed, without voting procedures, as the orientation of the ellipse that had the same normalized second central moments as the region. For other cases, the Hough voting procedure might be employed for orientation estimation. The performance of the algorithm was evaluated using four various group of sonograms, which are a dataset used in previous reports, 33 sonograms of gastrocnemius from 11 young healthy subjects, one sonogram sequence including 200 frames from a subject and 256 frames from an aged subject with cerebral infarction respectively.

RESULTS

It was demonstrated in the experiments that measurements of the proposed method agreed well with those of the manual method and achieved much more efficiency than the previous Re-voting Hough Transform (RVHT) algorithm.

CONCLUSIONS

Results of the experiments suggested that, without compromising the accuracy, in the proposed framework the previous orientation estimation algorithm was accelerated by reduction of its dependence on voting procedures.

A novel system of electrodes transparent to ultrasound for simultaneous detection of myoelectric activity and B-mode ultrasound images of skeletal muscles

Application of two-dimensional surface electrode arrays can provide a means of mapping motor unit action potentials on the skin surface above a muscle. The resulting muscle tissue displacement can be quantified, in a single plane, using ultrasound (US) imaging. Currently, however, it is not possible to simultaneously map spatio-temporal propagation of activation and resulting tissue strain. In this paper, we developed and tested a material that will enable concurrent measurement of two-dimensional surface electromyograms (EMGs) with US images. Specific protocols were designed to test the compatibility of this new electrode material, both with EMG recording and with US analysis. Key results indicate that, for this new electrode material, 1) the electrode-skin impedance is similar to that of arrays of electrodes reported in literature; 2) the reflection of US at the electrode-skin interface is negligible; 3) the likelihood of observing missing contacts, short-circuits, and artifacts in EMGs is not affected by the US probe; 4) movement of tissues sampled by US can be tracked accurately. We, therefore, conclude this approach will facilitate multimodal imaging of muscle to provide new spatio-temporal information regarding electromechanical function of muscle. This is relevant to basic physiology-biomechanics of active and passive force transmission through and between muscles, of motor unit spatio-temporal activity patterns, of their variation with architecture and task-related function, and of their adaptation with aging, training-exercise-disuse, neurological disease, and injury.

Estimating skeletal muscle fascicle curvature from B-mode ultrasound image sequences

We address the problem of tracking in vivo muscle fascicle shape and length changes using ultrasound video sequences. Quantifying fascicle behavior is required to improve understanding of the functional significance of a muscle's geometric properties. Ultrasound imaging provides a noninvasive means of capturing information on fascicle behavior during dynamic movements; to date however, computational approaches to assess such images are limited. Our approach to the problem is novel because we permit fascicles to take up nonlinear shape configurations. We achieve this using a Bayesian tracking framework that is: 1) robust, conditioning shape estimates on the entire history of image observations; and 2) flexible, enforcing only a very weak Gaussian Process shape prior that requires fascicles to be locally smooth. The method allows us to track and quantify fascicle behavior in vivo during a range of movements, providing insight into dynamic changes in muscle geometric properties which may be linked to patterns of activation and intramuscular forces and pressures.