Kyle Joseph Edmunds

Quantitative Computed Tomography and image analysis for advanced muscle assessment

Medical imaging is of particular interest in the field of translational myology, as extant literature describes the utilization of a wide variety of techniques to non-invasively recapitulate and quantity various internal and external tissue morphologies. In the clinical context, medical imaging remains a vital tool for diagnostics and investigative assessment. This review outlines the results from several investigations on the use of computed tomography (CT) and image analysis techniques to assess muscle conditions and degenerative process due to aging or pathological conditions. Herein, we detail the acquisition of spiral CT images and the use of advanced image analysis tools to characterize muscles in 2D and 3D. Results from these studies recapitulate changes in tissue composition within muscles, as visualized by the association of tissue types to specified Hounsfield Unit (HU) values for fat, loose connective tissue or atrophic muscle, and normal muscle, including fascia and tendon. We show how results from these analyses can be presented as both average HU values and compositions with respect to total muscle volumes, demonstrating the reliability of these tools to monitor, assess and characterize muscle degeneration.

Imaging approaches in functional assessment of implantable myogenic biomaterials and engineered muscle tissue

The fields of tissue engineering and regenerative medicine utilize implantable biomaterials and engineered tissues to regenerate damaged cells or replace lost tissues. There are distinct challenges in all facets of this research, but functional assessments and monitoring of such complex environments as muscle tissues present the current strategic priority. Many extant methods for addressing these questions result in the destruction or alteration of tissues or cell populations under investigation. Modern advances in non-invasive imaging modalities present opportunities to rethink some of the anachronistic methods, however, their standard employment may not be optimal when considering advancements in myology. New image analysis protocols and/or combinations of established modalities need to be addressed. This review focuses on efficacies and limitations of available imaging modalities to the functional assessment of implantable myogenic biomaterials and engineered muscle tissues.

Bone Mineral Density and Fracture Risk Assessment to Optimize Prosthesis Selection in Total Hip Replacement

The variability in patient outcome and propensity for surgical complications in total hip replacement (THR) necessitates the development of a comprehensive, quantitative methodology for prescribing the optimal type of prosthetic stem: cemented or cementless. The objective of the research presented herein was to describe a novel approach to this problem as a first step towards creating a patient-specific, presurgical application for determining the optimal prosthesis procedure. Finite element analysis (FEA) and bone mineral density (BMD) calculations were performed with ten voluntary primary THR patients to estimate the status of their operative femurs before surgery. A compilation model of the press-fitting procedure was generated to define a fracture risk index (FRI) from incurred forces on the periprosthetic femoral head. Comparing these values to patient age, sex, and gender elicited a high degree of variability between patients grouped by implant procedure, reinforcing the notion that age and gender alone are poor indicators for prescribing prosthesis type. Additionally, correlating FRI and BMD measurements indicated that at least two of the ten patients may have received nonideal implants. This investigation highlights the utility of our model as a foundation for presurgical software applications to assist orthopedic surgeons with selecting THR prostheses.

Improving planning and post-operative assessment for Total Hip Arthroplasty

Total Hip Arthroplasty (THA) remains the gold standard of treatment for patients who suffer with a variety of hip-related pathological degeneration or trauma. These patients often exhibit significantly less post-operative pain and an increase in the range of motion of the joint, but there are still relatively common instances of debilitating periprosthetic complications that call into question the method for pre-surgical implant choice. Currently, there are two principal options for THA prostheses: cemented or non cemented. Utilizing the cemented procedure ensures a faster acquisition of adequate implant stability than with the non cemented procedure, but can eventually lead to an increased periprosthetic fracture risk. Non cemented prosthetic stems are more frequently revised within the first few years following THA due to periprosthetic fracture, but non cemented revision surgeries generally result in fewer complications than those of cemented implants. Surgeons typically rely on experience or simple patient metrics such as age and sex to prescribe which implant procedure is optimal, and while this may work for most patients, there is a clear need to analyze more rigoriously patient conditions that correlate to optimal post-THA outcomes. The results from the investigation reported herein indicate that an understanding of how the percent composition and quality of a patients quadriceps muscle in both healthy and operated legs may be a better indicator for prosthetic choice. Additionally, these data emphasize that the traditional metrics of age and sex inadequately predict changes in quadriceps composition and quality and thereby have comparatively minor utility in determining the patient-appropriate prosthetic type. Key Words: Total Hip Arthroplasty, Prosthetic selection, Muscle size and quality, Anatomical modeling, Surgical planning.

New Directions in 3D Medical Modeling: 3D-Printing Anatomy and Functions in Neurosurgical Planning

This paper illustrates the feasibility and utility of combining cranial anatomy and brain function on the same 3D-printed model, as evidenced by a neurosurgical planning case study of a 29-year-old female patient with a low-grade frontal-lobe glioma. We herein report the rapid prototyping methodology utilized in conjunction with surgical navigation to prepare and plan a complex neurosurgery. The method introduced here combines CT and MRI images with DTI tractography, while using various image segmentation protocols to 3D model the skull base, tumor, and five eloquent fiber tracts. This 3D model is rapid-prototyped and coregistered with patient images and a reported surgical navigation system, establishing a clear link between the printed model and surgical navigation. This methodology highlights the potential for advanced neurosurgical preparation, which can begin before the patient enters the operation theatre. Moreover, the work presented here demonstrates the workflow developed at the National University Hospital of Iceland, Landspitali, focusing on the processes of anatomy segmentation, fiber tract extrapolation, MRI/CT registration, and 3D printing. Furthermore, we present a qualitative and quantitative assessment for fiber tract generation in a case study where these processes are applied in the preparation of brain tumor resection surgery.This paper illustrates the feasibility and utility of combining cranial anatomy and brain function on the same 3D-printed model, as evidenced by a neurosurgical planning case study of a 29-year-old female patient with a low-grade frontal-lobe glioma. We herein report the rapid prototyping methodology utilized in conjunction with surgical navigation to prepare and plan a complex neurosurgery. The method introduced here combines CT and MRI images with DTI tractography, while using various image segmentation protocols to 3D model the skull base, tumor, and five eloquent fiber tracts. This 3D model is rapid-prototyped and coregistered with patient images and a reported surgical navigation system, establishing a clear link between the printed model and surgical navigation. This methodology highlights the potential for advanced neurosurgical preparation, which can begin before the patient enters the operation theatre. Moreover, the work presented here demonstrates the workflow developed at the National University Hospital of Iceland, Landspitali, focusing on the processes of anatomy segmentation, fiber tract extrapolation, MRI/CT registration, and 3D printing. Furthermore, we present a qualitative and quantitative assessment for fiber tract generation in a case study where these processes are applied in the preparation of brain tumor resection surgery.

Low-amplitude craniofacial EMG power spectral density and 3D muscle reconstruction from MRI

Improving EEG signal interpretation, specificity, and sensitivity is a primary focus of many current investigations, and the successful application of EEG signal processing methods requires a detailed knowledge of both the topography and frequency spectra of low-amplitude, high-frequency craniofacial EMG. This information remains limited in clinical research, and as such, there is no known reliable technique for the removal of these artifacts from EEG data. The results presented herein outline a preliminary investigation of craniofacial EMG high-frequency spectra and 3D MRI segmentation that offers insight into the development of an anatomically-realistic model for characterizing these effects. The data presented highlights the potential for confounding signal contribution from around 60 to 200 Hz, when observed in frequency space, from both low and high-amplitude EMG signals. This range directly overlaps that of both low γ (30-50 Hz) and high γ (50-80 Hz) waves, as defined traditionally in standatrd EEG measurements, and mainly with waves presented in dense-array EEG recordings. Likewise, average EMG amplitude comparisons from each condition highlights the similarities in signal contribution of low-activity muscular movements and resting, control conditions. In addition to the FFT analysis performed, 3D segmentation and reconstruction of the craniofacial muscles whose EMG signals were measured was successful. This recapitulation of the relevant EMG morphology is a crucial first step in developing an anatomical model for the isolation and removal of confounding low-amplitude craniofacial EMG signals from EEG data. Such a model may be eventually applied in a clinical setting to ultimately help to extend the use of EEG in various clinical roles.

Advanced quantitative methods in correlating sarcopenic muscle degeneration with lower extremity function biometrics and comorbidities

Sarcopenic muscular degeneration has been consistently identified as an independent risk factor for mortality in aging populations. Recent investigations have realized the quantitative potential of computed tomography (CT) image analysis to describe skeletal muscle volume and composition; however, the optimum approach to assessing these data remains debated. Current literature reports average Hounsfield unit (HU) values and/or segmented soft tissue cross-sectional areas to investigate muscle quality. However, standardized methods for CT analyses and their utility as a comorbidity index remain undefined, and no existing studies compare these methods to the assessment of entire radiodensitometric distributions. The primary aim of this study was to present a comparison of nonlinear trimodal regression analysis (NTRA) parameters of entire radiodensitometric muscle distributions against extant CT metrics and their correlation with lower extremity function (LEF) biometrics (normal/fast gait speed, timed up-and-go, and isometric leg strength) and biochemical and nutritional parameters, such as total solubilized cholesterol (SCHOL) and body mass index (BMI). Data were obtained from 3,162 subjects, aged 66–96 years, from the population-based AGES-Reykjavik Study. 1-D k-means clustering was employed to discretize each biometric and comorbidity dataset into twelve subpopulations, in accordance with Sturges’ Formula for Class Selection. Dataset linear regressions were performed against eleven NTRA distribution parameters and standard CT analyses (fat/muscle cross-sectional area and average HU value). Parameters from NTRA and CT standards were analogously assembled by age and sex. Analysis of specific NTRA parameters with standard CT results showed linear correlation coefficients greater than 0.85, but multiple regression analysis of correlative NTRA parameters yielded a correlation coefficient of 0.99 (P<0.005). These results highlight the specificities of each muscle quality metric to LEF biometrics, SCHOL, and BMI, and particularly highlight the value of the connective tissue regime in this regard.

Multimodal Quantitative Assessment for Pre-operative Prosthesis Selection in Total Hip Arthroplasty

Total Hip Arthroplasty (THA) is one of the most utilized and successful orthopedic surgical procedures, and with increasing life expectancies in many populations worldwide, THA rates are projected to continue to rise accordingly. Despite the procedure’s rising prevalence, many periprosthetic fracture and unloading events are still reported. While many investigations have recently focused on potential assessment modalities and metrics to observe and characterize periprosthetic pathophysiology in THA patients, there is no extant, reliable method for the quantitative assessment of patients prior to THA. In most cases, respective opinions of the physicians involved dictate this decision, and procedures are therefore founded upon both the surgeon’s own experiences and qualitative generalizations based on suggested indicators of bone quality (gender, age, and qualitative assessment of CT images). There is therefore a great need for a quantitative, multimodal gold standard to securely choose the appropriate implant on a patient-specific basis. The objective of the re- search presented herein was to describe a novel assembly of such data from a 72-patient cohort as a first step towards eventually creating a patient-specific, presurgical application that orthopedic surgeons can utilize for determining the optimal THA prosthesis procedure. Here, we report the use of 3D soft tissue segmentation of the Rectus femoris, Vastus lateralis, and the Vastus medialis muscles, the use of 3D FEA to compute Fracture Risk Indices (FRI), the pre-operative measurement and user-friendly assembly of 11 gait parameters, and the measurement and analyses of EMG activation data – all of which are presented herein as a comprehensive patient report for a representative 60 year-old female patient.

Nonlinear Trimodal Regression Analysis of Radiodensitometric Distributions to Quantify Sarcopenic and Sequelae Muscle Degeneration.

Muscle degeneration has been consistently identified as an independent risk factor for high mortality in both aging populations and individuals suffering from neuromuscular pathology or injury. While there is much extant literature on its quantification and correlation to comorbidities, a quantitative gold standard for analyses in this regard remains undefined. Herein, we hypothesize that rigorously quantifying entire radiodensitometric distributions elicits more muscle quality information than average values reported in extant methods. This study reports the development and utility of a nonlinear trimodal regression analysis method utilized on radiodensitometric distributions of upper leg muscles from CT scans of a healthy young adult, a healthy elderly subject, and a spinal cord injury patient. The method was then employed with a THA cohort to assess pre- and postsurgical differences in their healthy and operative legs. Results from the initial representative models elicited high degrees of correlation to HU distributions, and regression parameters highlighted physiologically evident differences between subjects. Furthermore, results from the THA cohort echoed physiological justification and indicated significant improvements in muscle quality in both legs following surgery. Altogether, these results highlight the utility of novel parameters from entire HU distributions that could provide insight into the optimal quantification of muscle degeneration.

Patient-specific mobility assessment to monitor recovery after total hip arthroplasty

Total hip arthroplasty is a ubiquitously successful orthopedic surgical procedure, whose prevalence is rising worldwide. While many investigations focus on characterizing periprosthetic pathophysiology, the objective of our research is to develop and describe multi-metric assemblies as a first step toward creating a patient-specific mobility index that rehabilitators and orthopedic surgeons can utilize for prescribing their respective procedures. In total, 48 total hip arthroplasty patients (both cemented and uncemented) undergoing unilateral, primary surgery went through computed tomographic scans and gait analysis measurements both before and 1 year following their surgery. Altogether, the reported quantitative metrics include 11 spatial and temporal gait parameters, muscle density, and electromyography signals from the rectus femoris, vastus lateralis, and vastus medialis, and bone mineral density values from bioimage analysis around the implant stem. We found that measured parameters from a subgroup were sensitive to changes observed during patient recovery, implicating the predictive sensitivity of these patient conditions. Most post-operative gait parameters changed significantly, while electromyography data indicated few significant differences. Moreover, results from bioimage analyses indicate a general reduction of periprosthetic bone mineral density after 1 year, in association with increasing density of the quadriceps muscles. Furthermore, this work identifies which quantitative metrics undergo the greatest variation after total hip arthroplasty and demonstrates the clinical feasibility of a multimodal approach to mobility assessment that may ultimately support decision-making for post-surgical rehabilitation protocols.