A soft tissue artefact model driven by proximal and distal joint kinematics

When analysing human movement through stereophotogrammetry, skin-markers are used. Their movement relative to the underlying bone is known as a soft tissue artefact (STA). A mathematical model to estimate subject- and marker-specific STAs generated during a given motor task, is required for both skeletal kinematic estimators and comparative assessment using simulation. This study devises and assesses such a mathematical model using the paradigmatic case of thigh STAs. The model was based on two hypotheses: (1) that the artefact mostly depends on skin sliding, and thus on the angles of hip and knee; (2) that the relevant relationship is linear. These hypotheses were tested using data obtained from passive hip and knee movements in non-obese specimens and from running volunteers endowed with both skin- and pin-markers.     

Soft tissue displacement over pelvic anatomical landmarks during 3-D hip movements

The position, in a pelvis-embedded anatomical coordinate system, of skin points located over the following anatomical landmarks (AL) was determined while the hip assumed different spatial postures: right and left anterior superior and posterior superior iliac spines, and the sacrum. Postures were selected as occurring during walking and during a flexion–extension and circumduction movement, as used to determine the hip joint centre position (star-arc movement). Five volunteers, characterised by a wide range of body mass indices (22–37), were investigated. Subject-specific MRI pelvis digital bone models were obtained. For each posture, the pose of the pelvis-embedded anatomical coordinate system was determined by registering this bone model with points digitised over bony prominences of the pelvis, using a wand carrying a marker-cluster and stereophotogrammetry. The knowledge of how the position of the skin points varies as a function of the hip posture provided information regarding the soft tissue artefact (STA) that would affect skin markers located over those points during stereophotogrammetric movement analysis. The STA was described in terms of amplitude (relative to the position of the AL during an orthostatic posture), diameter (distance between the positions of the AL which were farthest away from each other), and pelvis orientation. The STA amplitude, exhibited, over all postures, a median [inter-quartile] value of 9[6] and 16[11] mm, for normal and overweight volunteers, respectively. STA diameters were larger for the star-arc than for the walking postures, and the direction was predominantly upwards. Consequent errors in pelvic orientation were in the range 1–9 and 4–11 degrees, for the two groups respectively.     

Effect of various upper limb multibody models on soft tissue artefact correction: A case study

Soft tissue artefacts (STA) introduce errors in joint kinematics when using cutaneous markers, especially on the scapula. Both segmental optimisation and multibody kinematics optimisation (MKO) algorithms have been developed to improve kinematics estimates. MKO based on a chain model with joint constraints avoids apparent joint dislocation but is sensitive to the biofidelity of chosen joint constraints. Since no recommendation exists for the scapula, our objective was to determine the best models to accurately estimate its kinematics. One participant was equipped with skin markers and with an intracortical pin screwed in the scapula. Segmental optimisation and MKO for 24-chain models (including four variations of the scapulothoracic joint) were compared against the pin-derived kinematics using root mean square error (RMSE) on Cardan angles. Segmental optimisation led to an accurate scapula kinematics (1.1° ≤ RMSE ≤ 3.3°) even for high arm elevation angles. When MKO was applied, no clinically significant difference was found between the different scapulothoracic models (0.9° ≤ RMSE ≤ 4.1°) except when a free scapulothoracic joint was modelled (1.9° ≤ RMSE ≤ 9.6°). To conclude, using MKO as a STA correction method was not more accurate than segmental optimisation for estimating scapula kinematics.     

Comparative assessment of knee joint models used in multi-body kinematics optimisation for soft tissue artefact compensation

Estimating joint kinematics from skin-marker trajectories recorded using stereophotogrammetry is complicated by soft tissue artefact (STA), an inexorable source of error. One solution is to use a bone pose estimator based on multi-body kinematics optimisation (MKO) embedding joint constraints to compensate for STA. However, there is some debate over the effectiveness of this method. The present study aimed to quantitatively assess the degree of agreement between reference (i.e., artefact-free) knee joint kinematics and the same kinematics estimated using MKO embedding six different knee joint models. The following motor tasks were assessed: level walking, hopping, cutting, running, sit-to-stand, and step-up. Reference knee kinematics was taken from pin-marker or biplane fluoroscopic data acquired concurrently with skin-marker data, made available by the respective authors. For each motor task, Bland-Altman analysis revealed that the performance of MKO varied according to the joint model used, with a wide discrepancy in results across degrees of freedom (DoFs), models and motor tasks (with a bias between −10.2° and 13.2° and between −10.2 mm and 7.2 mm, and with a confidence interval up to ±14.8° and ±11.1 mm, for rotation and displacement, respectively). It can be concluded that, while MKO might occasionally improve kinematics estimation, as implemented to date it does not represent a reliable solution to the STA issue.     

Evaluation of knee functional calibration with and without the effect of soft tissue artefact

Functional calibration methods were devised to improve repeatability and accuracy of the knee flexion–extension axis, which is used to define the medio-lateral axis of the femur coordinate system in gait analysis. Repeatability of functional calibration methods has been studied extensively in healthy individuals, but not accuracy in the absence of a benchmark knee axis. We captured bi-plane fluoroscopy data of the knee joint in 17 subjects with unilateral total knee arthroplasty during treadmill walking. The prosthesis provided a benchmark knee axis to evaluate the functional calibration methods. Stereo-photogrammetry data of thigh and shank marker clusters were captured simultaneously to investigate the effect of soft tissue artefact (STA). Three methods were tested, the Axis Transformation Technique (ATT) finds the best single fixed axis of rotation, 2DofKnee finds the axis that minimises knee varus–valgus and trajAJC finds the axis perpendicular to the trajectory, in the transverse plane of the femur, of a point located on the longitudinal axis of the tibia. Using fluoroscopy data, functional axes formed an angle of less than 2° in the transverse plane with the benchmark axis. True internal–external range of movement was correlated with decreased accuracy for ATT, while varus–valgus range of movement was correlated with decreased accuracy for 2DofKnee and trajAJC. STA had negative impact on accuracy and variability. Using stereo-photogrammetry data, the accuracy of 2DofKnee was 1.7°(SD: 5.1°), smaller than ATT 2.9°(SD: 5.1°) but not to trajAJC 1.7°(SD: 5.2°). Our results confirm that of previous studies, which utilised the femur condylar axis as reference.     

CAT & MAUS: A novel system for true dynamic motion measurement of underlying bony structures with compensation for soft tissue movement

Optoelectronic motion capture systems are widely employed to measure the movement of human joints. However, there can be a significant discrepancy between the data obtained by a motion capture system (MCS) and the actual movement of underlying bony structures, which is attributed to soft tissue artefact. In this paper, a computer-aided tracking and motion analysis with ultrasound (CAT & MAUS) system with an augmented globally optimal registration algorithm is presented to dynamically track the underlying bony structure during movement. The augmented registration part of CAT & MAUS was validated with a high system accuracy of 80%. The Euclidean distance between the marker-based bony landmark and the bony landmark tracked by CAT & MAUS was calculated to quantify the measurement error of an MCS caused by soft tissue artefact during movement. The average Euclidean distance between the target bony landmark measured by each of the CAT & MAUS system and the MCS alone varied from 8.32 mm to 16.87 mm in gait. This indicates the discrepancy between the MCS measured bony landmark and the actual underlying bony landmark. Moreover, Procrustes analysis was applied to demonstrate that CAT & MAUS reduces the deformation of the body segment shape modeled by markers during motion. The augmented CAT & MAUS system shows its potential to dynamically detect and locate actual underlying bony landmarks, which reduces the MCS measurement error caused by soft tissue artefact during movement.     

An ultrasound based non-invasive method for the measurement of intrinsic foot kinematics during gait

Soft tissue artefact (STA) and marker placement variability are sources of error when measuring the intrinsic kinematics of the foot. This study aims to demonstrate a non-invasive, combined ultrasound and motion capture (US/MC) technique to directly measure foot skeletal motion. The novel approach is compared to a standard motion capture protocol. Fourteen participants underwent instrumented barefoot analysis of foot motion during gait. Markers were attached to foot allowing medial longitudinal arch angle and navicular height to be determined. For the US/MC technique, the navicular marker was replaced by an ultrasound transducer which was secured to the foot allowing the skeletal landmark to be imaged. Ultrasound cineloops showing the location of the navicular tuberosity during the walking trials were synchronised with motion capture measurements and markers mounted on the probe allowed the true position of the bony landmark to be determined throughout stance phase. Two discrete variables, minimum navicular height and maximum MLA angle, were compared between the standard and US/MC protocols. Significant differences between minimum navicular height (P=0.004, 95% CI (1.57, 6.54)) and maximum medial longitudinal arch angle (P=0.0034, 95% CI (13.8, 3.4)) were found between the measurement methods. The individual effects of STA and marker placement error were also assessed. US/MC is a non-invasive technique which may help to provide more accurate measurements of intrinsic foot kinematics.     

Assessment of the lower limb soft tissue artefact at marker-cluster level with a high-density marker set during walking

The estimation of joint kinematics from skin markers is hindered by the soft tissue artefact (STA), a well-known phenomenon although not fully characterized. While most assessments of the STA have been performed based on the individual skin markers displacements, recent assessments were based on the marker-cluster geometrical transformations using, e.g., principal component or modal analysis. However, these marker-clusters were generally made of 4–6 markers and the current findings on the STA could have been biased by the limited number of skin makers analysed. The objective of the present study was therefore to confirm them with a high-density marker set, i.e. 40 markers placed on the segments.A larger number of modes than found in the literature was required to describe the STA. Nevertheless, translations and rotations of the marker-cluster remained the main STA modes, archetypally the translation along the proximal-distal and anterior-posterior axes for the shank and the translation along the proximal-distal axis and the rotation about the medial-lateral axis for the thigh. High correlations were also found between the knee flexion angle and the amplitude of these modes for the thigh whereas moderate ones were found for the shank.These findings support the current re-orientation of the STA compensation methods, from bone pose estimators which typically address the non-rigid components of the marker-cluster to kinematic-driven rigid-component STA models.     

Bone orientation and position estimation errors using Cosserat point elements and least squares methods: Application to gait

The aim of this study was to analyze the accuracy of bone pose estimation based on sub-clusters of three skin-markers characterized by triangular Cosserat point elements (TCPEs) and to evaluate the capability of four instantaneous physical parameters, which can be measured non-invasively in vivo, to identify the most accurate TCPEs. Moreover, TCPE pose estimations were compared with the estimations of two least squares minimization methods applied to the cluster of all markers, using rigid body (RBLS) and homogeneous deformation (HDLS) assumptions. Analysis was performed on previously collected in vivo treadmill gait data composed of simultaneous measurements of the gold-standard bone pose by bi-plane fluoroscopy tracking the subjects' knee prosthesis and a stereophotogrammetric system tracking skin-markers affected by soft tissue artifact. Femur orientation and position errors estimated from skin-marker clusters were computed for 18 subjects using clusters of up to 35 markers. Results based on gold-standard data revealed that instantaneous subsets of TCPEs exist which estimate the femur pose with reasonable accuracy (median root mean square error during stance/swing: 1.4/2.8 deg for orientation, 1.5/4.2 mm for position). A non-invasive and instantaneous criteria to select accurate TCPEs for pose estimation (4.8/7.3 deg, 5.8/12.3 mm), was compared with RBLS (4.3/6.6 deg, 6.9/16.6 mm) and HDLS (4.6/7.6 deg, 6.7/12.5 mm). Accounting for homogeneous deformation, using HDLS or selected TCPEs, yielded more accurate position estimations than RBLS method, which, conversely, yielded more accurate orientation estimations. Further investigation is required to devise effective criteria for cluster selection that could represent a significant improvement in bone pose estimation accuracy.     

Proximal placement of lateral thigh skin markers reduces soft tissue artefact during normal gait using the Conventional Gait Model

A primary source of measurement error in gait analysis is soft-tissue artefact. Hip and knee angle measurements, regularly used in clinical decision-making, are particularly prone to pervasive soft tissue on the femur. However, despite several studies of thigh marker artefact it remains unclear how lateral thigh marker height affects results using variants of the Conventional Gait Model. We compared Vicon Plug-in Gait hip and knee angle estimates during gait using a proximal and distal thigh marker placement for ten healthy subjects. Knee axes were estimated by optimizing thigh rotation offsets to minimize knee varus-valgus range during gait. Relative to the distal marker, the proximal marker produced 37% less varus-valgus range and 50% less hip rotation range (p < 0.001), suggesting that it produced less soft-tissue artefact in knee axis estimates. The thigh markers also produced different secondary effects on the knee centre estimate. Using whole gait cycle optimization, the distal marker showed greater minimum and maximum knee flexion (by 6° and 2° respectively) resulting in a 4° reduction in range. Mid-stance optimization reduced distal marker knee flexion by 5° throughout, but proximal marker results were negligibly affected. Based on an analysis of the Plug-in Gait knee axis definition, we show that the proximal marker reduced sensitivity to soft-tissue artefact by decreasing collinearity between the points defining the femoral frontal plane and reducing anteroposterior movement between the knee and thigh markers. This study suggests that a proximal thigh marker may be preferable when performing gait analysis using the Plug-in Gait model.     

Adaptive radiotherapy in patients receiving neoadjuvant radiation for soft tissue sarcoma

AimThe aim of this study is to evaluate tumor volume changes during preoperative radiotherapy and to assess the role of adaptive radiation.BackgroundContemporary neoadjuvant radiotherapy utilizes image guidance for precise treatment delivery. Moreover, it may depict changes in tumor size and shape.Materials and methodsBetween 2016 and 2018, 23 patients aged ≥18 years with soft tissue sarcoma were treated with neoadjuvant radiation followed by surgical resection. The tumor volumes (cc) were measured using the Pinnacle planning system prior to starting radiotherapy and during treatment, the changes in volume and absolute differences were estimated. Moreover, patient's position on the machine was evaluated to assess setup offsets. The triggers for plan adaptation were >1 cm expansion or unacceptable setup offsets.ResultsThe mean tumors volume at presentation was 810 cc (range, 55–4000). At last cone beam CT the tumor volume had changed in 14 patients (61%); it was stable in nine patients (39%). Disease regression was documented in eight patients (35%), with median shrinkage of −20.5% (range, −2 to −29%), while tumor progression was observed in six cases (26%), the median change was 12.5% (range, +10 to +25%).Adaptive radiation was required in four patients (17%). For the remaining 19 cases (83%), the dose distribution was adequate to cover target volumes.ConclusionsChange in soft tissue sarcoma volume during radiation is not uncommon. Image guidance should be used to reduce setup errors and to detect differences in tumor volume. Image guidance and adaptive radiation are paramount to ensure optimal radiation delivery.     

Regional variations of in vivo surface stiffness of soft tissue layers of musculoskeletal extremities

Surface stiffness of bulk soft tissue in musculoskeletal extremities is important to consider in the design of prosthetics, exoskeletons, and protective gear. This knowledge is also foundational for surgical simulation and clinical interventions leveraging manipulation of the musculoskeletal surfaces. Injuries to musculoskeletal extremities are common and surgical and preventive interventions require interactions between various objects such as surgical tools and support surfaces with tissue boundaries. While a handful of investigations examined the variations in indentation mechanics due to pathology or injury specific sites, a comprehensive analysis across the surfaces of musculoskeletal extremities has not been completed. In this study we examine variations of surface stiffness across 8 sites of the upper and lower arms and legs for 95 subjects using an instrumented ultrasound device. Differences in surface stiffness were observed between gender, activity level, and indentation location groups. The lower arm posterior location had the highest average stiffness (3.89 × 10⁻³ MPa/mm), while the lowest stiffness was observed at the upper leg posterior location (0.98 × 10⁻³ MPa/mm). The differences between indentation sites were larger in magnitude when compared to differences due to demographics (gender and activity level). However the large ranges of the 95% confidence intervals suggest that an aggregated metric based on population or sub-group may not capture individual variations. This study implicates the motivation to explore tissue composition variations within the indentation sites as well as the potential importance to include variations in surface stiffness during surgical simulations.     

Identification of rheological properties of human body surface tissue

According to World Health Organization obesity is one of the greatest public health challenges of the 21st century. It has tripled since the 1980s and the numbers of those affected continue to rise at an alarming rate, especially among children. There are number of devices that act as a prevention measure to boost person?s motivation for physical activity and its levels. The placement of these devices is not restricted thus the measurement errors that appear because of the body rheology, clothes, etc. cannot be eliminated. The main objective of this work is to introduce a tool that can be applied directly to process measured accelerations so human body surface tissue induced errors can be reduced. Both the modeling and experimental techniques are proposed to identify body tissue rheological properties and prelate them to body mass index. Multi-level computational model composed from measurement device model and human body surface tissue rheological model is developed. Human body surface tissue induced inaccuracies can increase the magnitude of measured accelerations up to 34% when accelerations of the magnitude of up to 27 m/s² are measured. Although the timeframe of those disruptions are short – up to 0.2 s – they still result in increased overall measurement error.     

Bayesian inverse kinematics vs. least-squares inverse kinematics in estimates of planar postures and rotations in the absence of soft tissue artifact

A variety of inverse kinematics (IK) algorithms exist for estimating postures and displacements from a set of noisy marker positions, typically aiming to minimize IK errors by distributing errors amongst all markers in a least-squares (LS) sense. This paper describes how Bayesian inference can contrastingly be used to maximize the probability that a given stochastic kinematic model would produce the observed marker positions. We developed Bayesian IK for two planar IK applications: (1) kinematic chain posture estimates using an explicit forward kinematics model, and (2) rigid body rotation estimates using implicit kinematic modeling through marker displacements. We then tested and compared Bayesian IK results to LS results in Monte Carlo simulations in which random marker error was introduced using Gaussian noise amplitudes ranging uniformly between 0.2 mm and 2.0 mm. Results showed that Bayesian IK was more accurate than LS-IK in over 92% of simulations, with the exception of one center-of-rotation coordinate planar rotation, for which Bayesian IK was more accurate in only 68% of simulations. Moreover, while LS errors increased with marker noise, Bayesian errors were comparatively unaffected by noise amplitude. Nevertheless, whereas the LS solutions required average computational durations of less than 0.5 s, average Bayesian IK durations ranged from 11.6 s for planar rotation to over 2000 s for kinematic chain postures. These results suggest that Bayesian IK can yield order-of-magnitude IK improvements for simple planar IK, but also that its computational demands may make it impractical for some applications.     

Surgical resection,intraoperative radiotherapy and immediate plastic reconstruction: A good option for the treatment of distal extremity soft tissue sarcomas

AimTo show three patients with soft tissue sarcomas of distal extremities conservatively treated after tumor-board discussion, involving margin-free surgery, exclusive intraoperative radiotherapy, and immediate reconstruction.BackgroundCurrent guidelines show clear and robust recommendations regarding the composition of the treatment of sarcomas of extremities. However, little evidence exists regarding the application of these treatments depending on the location of the primary neoplasia. Tumors that affect the distal extremities present different challenges and make multidisciplinary discussions desirable.Methods/ResultsWe reported 3 patients who were approached with a conservative intention, after tumor board recomendation. The goals from the treatment performed were aesthetic and functional preservation, while enruring locoregional control. We had wound healing complications in 2 of the cases, requiring additional reconstruction measures. Patients are followed up for 24, 20 and 10 months; local control is 100%, and functional preservation is 100%.ConclusionsDespite being a small series, it was sufficient to illustrate successful multidisciplinary planning, generating a therapeutic result with improved quality of life for patients who had an initial indication for extremity amputation.     

Evaluation of missing data imputation methods for human osteometric measurements

It is not uncommon for biological anthropologists to analyze incomplete bioarcheological or forensic skeleton specimens. As many quantitative multivariate analyses cannot handle incomplete data, missing data imputation or estimation is a common preprocessing practice for such data. Using William W. Howells' Craniometric Data Set and the Goldman Osteometric Data Set, we evaluated the performance of multiple popular statistical methods for imputing missing metric measurements. Results indicated that multiple imputation methods outperformed single imputation methods, such as Bayesian principal component analysis (BPCA). Multiple imputation with Bayesian linear regression implemented in the R package norm2, the Expectation–Maximization (EM) with Bootstrapping algorithm implemented in Amelia, and the Predictive Mean Matching (PMM) method and several of the derivative linear regression models implemented in mice, perform well regarding accuracy, robustness, and speed. Based on the findings of this study, we suggest a practical procedure for choosing appropriate imputation methods.     

背阔肌肌皮瓣修复肩背部软组织肉瘤术后缺损研究

目的:分析背阔肌肌皮瓣在肩背部软组织肉瘤扩大切除术后缺损修复中的方便性及优越性。方法:选取临床确诊肩背部软组织肉瘤患者8例,行肩背部病灶扩大切除术后,依据背阔肌肌皮瓣解剖学特点,选择合适的背阔肌肌皮瓣转移修复肩背部缺损。结果:皮瓣全部存活,随访6月至28月,肩背部外形满意,日常活动无明显影响。结论:应用背阔肌肌皮瓣修复肩背部软组织肉瘤扩大术后缺损是一种行之有效的方法。该方法简单易行,临床效果明显。