The effect of a neck-specific exercise program on cervical kinesthesia for patients with chronic whiplash-associated disorders: a case-control study.

INTRODUCTION: Cervical kinesthesia is an important part of movement control and of great importance for daily function. Previous research on kinesthesia in whiplash-associated disorders (WAD) has focused on grades I-II. More research is needed on WAD grade III. The aim of this study was to investigate cervical kinesthesia in individuals with WAD grades II-III before and after a neck-specific exercise intervention and compare them to healthy controls. METHODS: A prospective, case-control study with a treatment arm (n = 30) and a healthy control arm (n = 30) was conducted in Sweden. The WAD group received a neck-specific exercise program for 12 weeks. The primary outcome to evaluate kinesthesia was neck movement control (the Fly test). Secondary outcomes were neck disability, dizziness and neck pain intensity before and after the Fly test. Outcomes were measured at baseline and post-treatment. The control arm underwent measurements at baseline except for the dizziness questionnaire. A linear mixed model was used to evaluate difference between groups (WAD and control) and over time, with difficulty level in the Fly test and gender as factors. RESULTS: Between-group analysis showed statistically significant differences in three out of five kinesthetic metrics (p = 0.002 to 0.008), but not for the WAD-group follow-up versus healthy control baseline measurements. Results showed significant improvements for the WAD-group over time for three out of five kinaesthesia metrics (p < 0.001 to 0.008) and for neck disability (p < 0.001) and pain (p = 0.005), but not for dizziness (p = 0.70). CONCLUSIONS: The exercise program shows promising results in improving kinesthesia and reducing neck pain and disability in the chronic WAD phase. Future research might benefit from focusing on adding kinesthetic exercises to the exercise protocol and evaluating its beneficial effects on dizziness or further improvement in kinesthesia. IMPACT STATEMENT: Kinesthesia can be improved in chronic WAD patients without the use of specific kinesthetic exercises. TRIAL REGISTRATION: ClinicalTrials.gov (NCT03664934), first registration approved 11/09/2018.

Quadriceps and Hamstrings Activation Peaks Earlier as Athletes Repeatedly Hop, but There are Differences Depending on ACL Reconstruction Technique.

Background: After Anterior Cruciate Ligament Reconstruction (ACLR) athletes face the challenge of regaining their previous competitive level while avoiding re-injury and early knee joint cartilage degeneration. Quadriceps and hamstrings strength reductions and neuromuscular alterations potentially related to risk of re-injury are present after ACLR and relate to deficits in muscle activation. Design: Cross-sectional laboratory study. Purpose: To examine quadriceps and hamstrings muscle activation during repeated hops in healthy pivoting-sport athletes and those who had undergone ACLR (bone-tendon-bone and semitendinosus graft) who had met functional criteria allowing return to training. Methods: Surface electromyography (SEMG) was recorded from vastus medialis and lateralis and medial and lateral hamstrings bilaterally during 30 seconds' repeated hopping in male athletes on average eight months after ACLR surgery (5-12 months). All patients underwent hamstring (HS) (n=24) or bone-tendon-bone (BTB) reconstruction (n=20) and were compared to healthy controls (n=31). The SEMG signals were normalized to those obtained during maximal voluntary isometric contraction. Results: A significant time shift in peak muscle activation (earlier) was seen for: vastus medialis and vastus lateralis activation in the control group, in the BTB group's healthy (but not injured) leg and both legs of the HS group. A significant time shift in peak muscle activation was seen for lateral hamstrings (earlier) in all but the BTB group's injured leg and the medial hamstrings in the control group only. Lower peak activation levels of the vastus lateralis (p\<0.001) and vastus medialis (p\<0.001) were observed in the injured compared to healthy legs and lower peak lateral hamstrings activity (p\<0.009) in the injured leg compared to control leg. Decline in medial hamstring peak activation (p\<0.022) was observed between 1st and 3rd phase of the hop cycle in all groups. Conclusion: Repeated hop testing revealed quadriceps and hamstring activation differences within ACLR athletes, and compared to healthy controls, that would be missed with single hop tests. Level of evidence: 3.

BloodSpot 3.0: a database of gene and protein expression data in normal and malignant haematopoiesis.

BloodSpot is a specialised database integrating gene expression data from acute myeloid leukaemia (AML) patients related to blood cell development and maturation. The database and interface has helped numerous researchers and clinicians to quickly get an overview of gene expression patterns in healthy and malignant haematopoiesis. Here, we present an update to our framework that includes protein expression data of sorted single cells. With this update we also introduce datasets broadly spanning age groups, which many users have requested, with particular interest for researchers studying paediatric leukaemias. The backend of the database has been rewritten and migrated to a cloud-based environment to accommodate the growth, and provide a better user-experience for our many international users. Users can now enjoy faster transfer speeds and a more responsive interface. In conclusion, the continuing popularity of the database and emergence of new data modalities has prompted us to rewrite and futureproof the back-end, including paediatric centric views, as well as single cell protein data, allowing us to keep the database updated and relevant for the years to come. The database is freely available at www.bloodspot.eu.

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

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

GraphPart: homology partitioning for biological sequence analysis.

When splitting biological sequence data for the development and testing of predictive models, it is necessary to avoid too-closely related pairs of sequences ending up in different partitions. If this is ignored, performance of prediction methods will tend to be overestimated. Several algorithms have been proposed for homology reduction, where sequences are removed until no too-closely related pairs remain. We present GraphPart, an algorithm for homology partitioning that divides the data such that closely related sequences always end up in the same partition, while keeping as many sequences as possible in the dataset. Evaluation of GraphPart on Protein, DNA and RNA datasets shows that it is capable of retaining a larger number of sequences per dataset, while providing homology separation on a par with reduction approaches.

Toward New Assessment of Knee Cartilage Degeneration.

OBJECTIVE: Assessment of human joint cartilage is a crucial tool to detect and diagnose pathological conditions. This exploratory study developed a workflow for 3D modeling of cartilage and bone based on multimodal imaging. New evaluation metrics were created and, a unique set of data was gathered from healthy controls and patients with clinically evaluated degeneration or trauma. DESIGN: We present a novel methodology to evaluate knee bone and cartilage based on features extracted from magnetic resonance imaging (MRI) and computed tomography (CT) data. We developed patient specific 3D models of the tibial, femoral, and patellar bones and cartilages. Forty-seven subjects with a history of degenerative disease, traumatic events, or no symptoms or trauma (control group) were recruited in this study. Ninety-six different measurements were extracted from each knee, 78 2D and 18 3D measurements. We compare the sensitivity of different metrics to classify the cartilage condition and evaluate degeneration. RESULTS: Selected features extracted show significant difference between the 3 groups. We created a cumulative index of bone properties that demonstrated the importance of bone condition to assess cartilage quality, obtaining the greatest sensitivity on femur within medial and femoropatellar compartments. We were able to classify degeneration with a maximum recall value of 95.9 where feature importance analysis showed a significant contribution of the 3D parameters. CONCLUSION: The present work demonstrates the potential for improving sensitivity in cartilage assessment. Indeed, current trends in cartilage research point toward improving treatments and therefore our contribution is a first step toward sensitive and personalized evaluation of cartilage condition.

SignalP 6.0 predicts all five types of signal peptides using protein language models.

Signal peptides (SPs) are short amino acid sequences that control protein secretion and translocation in all living organisms. SPs can be predicted from sequence data, but existing algorithms are unable to detect all known types of SPs. We introduce SignalP 6.0, a machine learning model that detects all five SP types and is applicable to metagenomic data.

Lower medial hamstring activity after ACL reconstruction during running: a cross-sectional study.

OBJECTIVE: Anterior cruciate ligament reconstruction (ACLR) predisposes footballers for subsequent ACL and hamstring (HS) injury. This case series examines HS muscle activation patterns during the running in ACLR patients (bone-patellar tendon-bone (BTB) and (HS) graft) after completion of functional criteria allowing return to training. METHODS: Electromyography (EMG) recorded from medial and lateral HS bilaterally during treadmill running (12, 14 and 16 km/hour) from 21 male ACLR patients on average 7 months from surgery (5-9) that underwent (HS) (n=12) or BTB reconstruction (n=9) were compared with 19 healthy runners. Main outcome measures: EMG signal was normalised to peak during the running. Pairwise comparisons were made for each muscle group examining stance and swing activation for mean and peak EMG for each patient group and leg. RESULTS: Significantly lower relative peak activation in stance (not swing) phase for medial HS was seen for all conditions with effect sizes ranging from -0.63 (controls, BTB non-injured leg) to -1.09 (HS injured). For lateral HS only BTB injured were significantly lower in stance phase (-1.05). CONCLUSION: ACLR patients show neuromuscular alterations during different phases of running. The finding of reduced medial HS activity in stance phase might have implications for knee instability and HS muscle injury on resumption of sport.

Healthy Aging Within an Image: Using Muscle Radiodensitometry and Lifestyle Factors to Predict Diabetes and Hypertension.

The strong age dependency of many deleterious health outcomes likely reflects the cumulative effects from a variety of risk and protective factors that occur over one's life course. This notion has become increasingly explored in the etiology of chronic disease and associated comorbidities in aging. Our recent work has shown the robust classification of individuals at risk for cardiovascular pathophysiology using CT-based soft tissue radiodensity parameters obtained from nonlinear trimodal regression analysis (NTRA). Past and present lifestyle influences the incidence of comorbidities like hypertension (HTN), diabetes (DM) and cardiac diseases. 2,943 elderly subjects from the AGES-Reykjavik study were sorted into a three-level binary-tree structure defined by: 1) lifestyle factors (smoking and self-reported physical activity level), 2) comorbid HTN or DM, and 3) cardiac pathophysiology. NTRA parameters were extracted from mid-thigh CT cross-sections to quantify radiodensitometric changes in three tissue types: lean muscle, fat, and loose-connective tissue. Between-group differences were assessed at each binary-tree level, which were then used in tree-based machine learning (ML) models to classify subjects with DM or HTN. Classification scores for detecting HTN or DM based on lifestyle factors were excellent (AUCROC: 0.978 and 0.990, respectively). Finally, tissue importance analysis underlined the comparatively-high significance of connective tissue parameters in ML classification, while predictive models of DM onset from five-year longitudinal data gave a classification accuracy of 94.9%. Altogether, this work serves as an important milestone toward the construction of predictive tools for assessing the impact of lifestyle factors and healthy aging based on a single image.

Improving Prosthetic Selection and Predicting BMD from Biometric Measurements in Patients Receiving Total Hip Arthroplasty.

There are two surgical approaches to performing total hip arthroplasty (THA): a cemented or uncemented type of prosthesis. The choice is usually based on the experience of the orthopaedic surgeon and on parameters such as the age and gender of the patient. Using machine learning (ML) techniques on quantitative biomechanical and bone quality data extracted from computed tomography, electromyography and gait analysis, the aim of this paper was, firstly, to help clinicians use patient-specific biomarkers from diagnostic exams in the prosthetic decision-making process. The second aim was to evaluate patient long-term outcomes by predicting the bone mineral density (BMD) of the proximal and distal parts of the femur using advanced image processing analysis techniques and ML. The ML analyses were performed on diagnostic patient data extracted from a national database of 51 THA patients using the Knime analytics platform. The classification analysis achieved 93% accuracy in choosing the type of prosthesis; the regression analysis on the BMD data showed a coefficient of determination of about 0.6. The start and stop of the electromyographic signals were identified as the best predictors. This study shows a patient-specific approach could be helpful in the decision-making process and provide clinicians with information regarding the follow up of patients.

Three dimensional bone mineral density changes in the femur over 1 year in primary total hip arthroplasty patients.

BACKGROUND: The aim of the study was to compare the bone mineral density changes between unmatched patients undergoing total hip arthroplasty receiving uncemented and cemented type of implants. Previous studies have used DEXA or a two dimensional analysis to estimate the bone quality following total joint replacement, whereas this study presents the changes in three dimensions. METHODS: Fifty subjects both male and females receiving both cemented and uncemented type of implant were recruited. Two CT scans were taken of each subject, the first at 24 h post surgery and the second one 1 year after surgery. The scans were calibrated using a phantom converting the Hounsfield units to bone mineral density values in g/cm3. The two scans were registered together using anatomical landmarks and resliced to compare the two femurs in the identical frame of reference. The bone density gain and loss was calculated by comparing density values between the two sets of scans. FINDINGS: The results showed that most of the bone loss was located around the Lesser Trochanter and some bone density gain at the distal tip of the implant. The three dimensional density changes occur differently between individuals and the study showed no correlation of bone loss with age. INTERPRETATION: The bone loss occurred mostly at the proximal femur, which is in agreement with previously presented studies. By carrying out three dimensional analysis on the bone gain and loss on the femur, it is possible to identify the patients that are showing high degree of bone loss.

Machine learning predictive system based upon radiodensitometric distributions from mid-thigh CT images.

The nonlinear trimodal regression analysis (NTRA) method based on radiodensitometric CT images distributions was developed for the quantitative characterization of soft tissue changes according to the lower extremity function of elderly subjects. In this regard, the NTRA method defines 11 subject-specific soft tissue parameters and has illustrated high sensitivity to changes in skeletal muscle form and function. The present work further explores the use of these 11 NTRA parameters in the construction of a machine learning (ML) system to predict body mass index and isometric leg strength using tree-based regression algorithms. Results obtained from these models demonstrate that when using an ML approach, these soft tissue features have a significant predictive value for these physiological parameters. These results further support the use of NTRA-based ML predictive assessment and support the future investigation of other physiological parameters and comorbidities.

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.

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.

Women with late whiplash syndrome have greatly reduced load-bearing of the cervical spine. In-vivo biomechanical, cross-sectional, lateral radiographic study.

BACKGROUND: No study has been conducted to ascertain whether the load-bearing capacity of the cervical spine is reduced in vivo in late whiplash syndrome (LWS). AIM: To compare the segmental cervical angular values across C0-C6, between two conditions: without versus with external axial load upon the head in three groups of women. DESIGN: A single-blind, age-Body Mass Index (BMI) matched, radiographic, cross-sectional study. SETTING: Radiographic Department at a University Hospital. POPULATION: One hundred eighty-two women, aged between 18-50 years were enrolled. METHODS: Participants were divided into 3 groups: a group with LWS (N.=62) and two control groups: a chronic insidious neck pain (IONP) group (N.=60) and an asymptomatic group (N.=60). Prior to and on the same day as the radiographic examination took place, BMI in kg/m2 was recorded and all participants answered the Neck Disability Index (NDI). The two symptomatic groups answered also three other pain and disability questionnaires. RESULTS: Analysis of variance (mixed-model ANOVA) for repeated measures was used for comparison. Significant differences between groups, and the two conditions tested was revealed, but only within the asymptomatic and the IONP groups (P<0.0001), but not within the LWS group (P=0.9433). Unexpectedly the women with LWS adopted a rigid horizontal translation strategy when external load was applied upon their head. The inter-rater and intra-rater segmental measurements were highly reliable. Women with LWS scored significantly higher on all questionnaires. CONCLUSIONS: The results of this study strongly indicate that the load-bearing capacity of the cervical spine is reduced in vivo in women with LWS. The study shows, for the first time, that the cervical spine in women with LWS predominately functions such as a rigid cylinder when loaded. CLINICAL REHABILITATION IMPACT: The study implies that the cervical column is extremely weak in the LWS and that the superficial neck muscles, which are designed to move the head-neck, must compensate and act as rigid stabilizers. This causes great joint reaction forces through the cervical spine and its injured inert structures maintaining the pain and disability, as the results of the questionnaires show.

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.

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.

Patient-specific bone mineral density distribution in the tibia of individuals with chronic spinal cord injury, derived from multi-slice peripheral Quantitative Computed Tomography (pQCT) - A cross-sectional study.

BACKGROUND: The high risk of fracture associated with chronic spinal cord injury (SCI) is attributed to extensive disuse-related bone loss in previously weight-bearing long bones. Changes in bone mineral density (BMD) after SCI have been documented extensively for the epiphyses of the tibia and femur, fracture-prone sites in this patient group. Less attention has been given to patterns of cortical bone loss in the diaphyses, but variability in BMD distributions throughout the long bones may contribute to some patients' increased susceptibility to shaft fractures in chronic SCI. AIM: A cross-sectional study was carried out to determine whether BMD distributions along the tibia differ between individuals with chronic SCI and healthy able-bodied (AB) controls, in both the trabecular and cortical bone compartments. The effects of time post-injury and gender on BMD distribution were also explored. METHODS: Individuals with chronic (≥6months post-injury) motor-complete SCI were recruited from the Queen Elizabeth National Spinal Injuries Unit (Glasgow, UK). AB control subjects were recruited to achieve similar age and gender profiles for the SCI and control groups. Multi-slice pQCT (XCT3000, Stratec) was performed along the length of the tibia (2mm thickness, 0.5mm voxel size), at 1% intervals in the epiphyses and 5% intervals in the diaphysis (34 slices in total). These were used to reconstruct full 3-D subject-specific models (Mimics, Materialise) of BMD distribution, by interpolating between slices. Subjects with chronic SCI were subdivided into 'early' (<4years post-injury) and 'established' SCI (≥4years post-injury). Subject-specific BMD distribution was described according to new parameters determined from the 3-D patient-specific models, quantifying descriptors of the trabecular and cortical BMD regions separately (volume, peak BMD, half-peak width, area under the curve). These were compared between sub-groups (using independent-samples t-tests or Mann-Whitney tests, significance level of 5%). RESULTS: 11 men (age range 17-59years old; mean 35.7±10.6) and 3 post-menopausal women (age range 56-58years old; mean 56.7±1.2years) with motor-complete SCI (ranging from 6months to 27years post-injury) were recruited; 6 men (age range 20-56years old; 33.0±12.7years) and 1 post-menopausal woman (56years) formed the AB control group. Overall, SCI resulted in lower BMD at both trabecular and cortical regions of the tibia. In men, longer time since injury resulted in greater BMD differences when compared to AB, throughout the tibia. For the post-menopausal women, differences in BMD between SCI and AB were greater in cortical bone than in trabecular bone. From the models, individual BMD distribution curves showed healthy double-peaks in AB subjects: one trabecular peak (around 200-300mg/cm3) and the other cortical (around 1000-1100mg/cm3). In most subjects with established SCI, trabecular peaks were exaggerated whilst the cortical peaks were barely discernible, with crucially some individuals already exhibiting a diminishing cortical BMD peak even <4years post-injury. CONCLUSIONS: These findings may have implications for determining the fracture susceptibility of the long bones in individual patients with SCI. Epiphyseal fractures associated with low trabecular BMD are well characterised, but our data show that some individuals with SCI may also be at higher risk of shaft fractures. The proposed BMD distribution description parameters, determined from patient-specific models, could be used to identify patients with a weakened diaphysis who may be susceptible to fractures of the tibial shaft, but this requires validation.

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.

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.