Biomechanical Comparison of 3 Medial Patellofemoral Complex Reconstruction Techniques Shows Medial Overconstraint but No Significant Difference in Patella Lateralization and Contact Pressure.

PURPOSE: The purpose of this study was to investigate biomechanical differences of medial patellofemoral ligament (MPFL) reconstruction, medial quadriceps tendon femoral ligament (MQTFL) reconstruction, and a combination of these techniques to restore lateral patellar constraint and contact pressures. METHODS: Eight fresh frozen cadaver knees were mounted to a custom jig with physiological quadriceps tendon loading. Flexion angles and contact pressure (CP) were dynamically measured using Tekscan® pressure sensors and Polhemus® Liberty 6 degree of freedom (6DOF) positioning sensors in the following conditions: 1) intact 2) MPFL and MQTFL deficient, 3) MPFL reconstructed, 4) Combined MPFL + MQTFL reconstructed, and 5) MQTFL reconstructed. Lateral patellar translation was tested using horizontally directed 30 N force applied at 30° of knee flexion. The knees were flexed in dynamic fashion, and CP values were recorded for 10°, 20°, 30°, 50°, 70°, and 90° degrees of flexion. Group differences were assessed with ANOVA's followed by pairwise comparisons with Bonferroni correction. RESULTS: MPFL (P = .002) and combined MPFL/MQTFL (P = .034) reconstruction significantly reduced patellar lateralization from +19.28% (9.78%, 28.78%) in the deficient condition to -17.57% (-27.84%, -7.29%) and -15.56% (-33.61%, 2.30%), respectively. MPFL reconstruction was most restrictive and MQTFL reconstruction the least -7.29% (-22.01%, 7.45%). No significant differences were found between the three reconstruction techniques. Differences in CP between the three reconstruction techniques were not significant (<.02 MPa) at all flexion angles. CONCLUSION: The present study found no significant difference for patellar lateralization and patellofemoral CP between MPFL, combined MPFL/MQTFL, and MQTFL reconstruction. All 3 techniques resulted in stronger lateral patellar constraint compared to the native state, while the MQTFL reconstruction emulated the intact state the closest. CLINICAL RELEVANCE: Various surgical techniques for medial patellofemoral complex reconstruction can restore patellar stability with similar patellofemoral articular pressures.

Artificial Intelligence-Based Modeling Can Predict Face Shape Based on Underlying Craniomaxillofacial Bone.

Reconstructing facial deformities is often challenging due to the complex 3-dimensional (3D) anatomy of the craniomaxillofacial skeleton and overlying soft tissue structures. Bilateral injuries cannot benefit from mirroring techniques and as such preinjury information (eg, 2D pictures or 3D imaging) may be utilized to determine or estimate the desired 3D face shape. When patient-specific information is not available, other options such as statistical shape models may be employed; however, these models require registration to a consistent orientation which may be challenging. Artificial intelligence (AI) has been used to identify facial features and generate highly realistic simulated faces. As such, it was hypothesized that AI can be used to predict 3D face shape by learning its relationship with the underlying bone surface anatomy in a subject-specific manner. An automated image processing and AI modeling workflow using a modified 3D UNet was generated to estimate 3D face shape using the underlying bone geometry and additional metadata (eg, body mass index and age) obtained from 5 publicly available computed tomography imaging datasets. Visually, the trained models provided a reasonable prediction of the contour and geometry of the facial tissues. The pipeline achieved a validation dice=0.89 when trained on the combined 5 datasets, with the highest dice=0.925 achieved with the single HNSCC dataset. Estimated predefect facial geometry may ultimately be used to aid preoperative craniomaxillofacial surgical planning, providing geometries for intraoperative templates, guides, navigation, molds, and forming tools. Automated face shape prediction may additionally be useful in forensic studies to aid in the identification of unknown skull remains.

Assessing the Nasal Midline in Rhinoplasty: How Good Are We?

BACKGROUND: The challenge of assessing nasal alignment and asymmetry can contribute to high revision rates in rhinoplasty. Comparing to a validated computer algorithm for nasal alignment, the accuracy with which plastic surgeons can assess deviation of the nasal midline from the facial midline was measured. METHODS: Using 20 faces from the Binghamton University 3-dimensional face database, deviation was evaluated from facial midline of the middorsal line for the upper, middle, and lower thirds of the nose. Surgeons were asked to assess extent of deviation from facial midline for each third of the nose using a linear analog scale. Spearman correlations were performed comparing the surgeons' results to the algorithm measurements. Eleven residents and 9 consultant surgeons were tested. RESULTS: Surgeons' assessment of deviation correlated poorly with the algorithm in the upper third ( r =0.32, P <0.0001) and moderately in the middle third ( r =0.49, P <0.0001) and lower third ( r =0.41, P <0.0001) of the nose. No difference in accuracy was found between trainee and consultant surgeons ( P =0.51), and greater experience (>10 y performing nasal surgery) did not significantly affect performance ( P =0.15). The effect of fatigue on the accuracy of assessment was found to be significant ( P =0.0009). CONCLUSIONS: Surgeons have difficulty in visually assessing the 3-dimensional nasal midline irrespective of experience, and surgeon fatigue was found to be adversely affect the accuracy of assessments.

Accuracy of Orbital Shape Reconstruction-Comparative Analysis of Errors in Implant Shape Versus Implant Positioning: A Cadaveric Study.

INTRODUCTION: Orbital blowout fractures are commonly reconstructed with implants shaped to repair orbital cavity defects, restore ocular position and projection, and correct diplopia. Orbital implant shaping has traditionally been performed manually by surgeons, with more recent use of computer-assisted design (CAD). Accuracy of implant placement is also key to reconstruction. This study compares the placement accuracy of orbital implants, testing the hypothesis that CAD-shaped implants indexed to patient anatomy will better restore orbit geometry compared with manually shaped implants and manually placed implants. METHODS: The placement accuracy of orbital implants was assessed within a cadaveric blowout fracture model (3 skulls, 6 orbits) via 3-dimensional CT analysis. Defects were repaired with 4 different techniques: manually placed-manually shaped composite (titanium-reinforced porous polyethylene), manually placed CAD composite, indexed placed CAD composite, and indexed placed CAD titanium mesh. RESULTS: Implant placement accuracy differed significantly with the implant preparation method ( P =0.01). Indexing significantly improved the placement accuracy ( P =0.002). Indexed placed titanium mesh CAD implants (1.42±0.33 mm) were positioned significantly closer to the intact surface versus manually placed-manually shaped composite implants (2.12±0.39 mm). DISCUSSION: Computer-assisted design implants indexed to patient geometry yielded average errors below the acceptable threshold (2 mm) for enophthalmos and diplopia. This study highlights the importance of adequately indexing CAD-designed implants to patient geometry to ensure accurate orbital reconstructions.

Key Stakeholder Perceptions of Standard vs. Total Cost of Ownership: A Procurement Analysis for Orthopaedic-Powered Instruments.

This study compares standard procurement methodology (SPM) with total cost of ownership (TCO) methodology for the procurement of orthopaedic-powered instruments. The authors conducted semi-structured standardized interviews with key hospital procurement stakeholders following consolidated criteria for reporting qualitative research. Of the 33 hospital procurement stakeholders interviewed, all (100%) reported that SPM would be easier to use than TCO. However, only six (18%) preferred SPM over TCO. Barriers to the adoption of TCO emerged as a theme. Creating TCO frameworks can help to simplify the process for procurement agents and facilitate its adoption in the healthcare sector.

Forehead Flap Templates for Nasal Reconstruction Digitally Developed From 2D and 3D Images.

ABSTRACT: The forehead flap is the gold standard procedure for nasal reconstruction to address a partial or complete rhinectomy. Traditionally, the three-dimensional (3D) nasal defect is manually templated intraoperatively to design the two-dimensional (2D) flap shape on intact morphology. In this clinical study, digital preoperative planning is used to template with computer-assisted design and manufacturing. Preoperative digital templates were implemented for 3 representative patients (1 in Supplementary Digital Content, http://links.lww.com/SCS/D60). This includes designs for a hemi-rhinectomy case from 3D mirroring, a partial total rhinectomy case generated from a 3D scan, and a total rhinectomy case generated from a 3D morphable model based on a prepathology 2D photo. Digital unwrapping flattened the patient's 3D nasal geometry designs to 2D skin flap shapes. Finally, the 2D designs were printed as traceable intraoperative templates at a 1:1 scale. This clinical study demonstrates the application of digital 3D preoperative templating to improve workflow for nasal reconstruction.

Personalized Activity Recognition with Deep Triplet Embeddings.

A significant challenge for a supervised learning approach to inertial human activity recognition is the heterogeneity of data generated by individual users, resulting in very poor performance for some subjects. We present an approach to personalized activity recognition based on deep feature representation derived from a convolutional neural network (CNN). We experiment with both categorical cross-entropy loss and triplet loss for training, and describe a novel loss function based on subject triplets. We evaluate these methods on three publicly available inertial human activity recognition datasets (MHEALTH, WISDM, and SPAR) comparing classification accuracy, out-of-distribution activity detection, and generalization to new activity classes. The proposed triplet algorithm achieved an average 96.7% classification accuracy across tested datasets versus the 87.5% achieved by the baseline CNN algorithm. We demonstrate that personalized algorithms, and, in particular, the proposed novel triplet loss algorithms, are more robust to inter-subject variability and thus exhibit better performance on classification and out-of-distribution detection tasks.

Physiotherapy Exercise Classification with Single-Camera Pose Detection and Machine Learning.

Access to healthcare, including physiotherapy, is increasingly occurring through virtual formats. At-home adherence to physical therapy programs is often poor and few tools exist to objectively measure participation. The aim of this study was to develop and evaluate the potential for performing automatic, unsupervised video-based monitoring of at-home low-back and shoulder physiotherapy exercises using a mobile phone camera. Joint locations were extracted from the videos of healthy subjects performing low-back and shoulder physiotherapy exercises using an open source pose detection framework. A convolutional neural network was trained to classify physiotherapy exercises based on the segments of keypoint time series data. The model's performance as a function of input keypoint combinations was studied in addition to its robustness to variation in the camera angle. The CNN model achieved optimal performance using a total of 12 pose estimation landmarks from the upper and lower body (low-back exercise classification: 0.995 ± 0.009; shoulder exercise classification: 0.963 ± 0.020). Training the CNN on a variety of angles was found to be effective in making the model robust to variations in video filming angle. This study demonstrates the feasibility of using a smartphone camera and a supervised machine learning model to effectively classify at-home physiotherapy participation and could provide a low-cost, scalable method for tracking adherence to physical therapy exercise programs in a variety of settings.

Multi-Modal Deep Learning for Assessing Surgeon Technical Skill.

This paper introduces a new dataset of a surgical knot-tying task, and a multi-modal deep learning model that achieves comparable performance to expert human raters on this skill assessment task. Seventy-two surgical trainees and faculty were recruited for the knot-tying task, and were recorded using video, kinematic, and image data. Three expert human raters conducted the skills assessment using the Objective Structured Assessment of Technical Skill (OSATS) Global Rating Scale (GRS). We also designed and developed three deep learning models: a ResNet-based image model, a ResNet-LSTM kinematic model, and a multi-modal model leveraging the image and time-series kinematic data. All three models demonstrate performance comparable to the expert human raters on most GRS domains. The multi-modal model demonstrates the best overall performance, as measured using the mean squared error (MSE) and intraclass correlation coefficient (ICC). This work is significant since it demonstrates that multi-modal deep learning has the potential to replicate human raters on a challenging human-performed knot-tying task. The study demonstrates an algorithm with state-of-the-art performance in surgical skill assessment. As objective assessment of technical skill continues to be a growing, but resource-heavy, element of surgical education, this study is an important step towards automated surgical skill assessment, ultimately leading to reduced burden on training faculty and institutes.

Spatial correspondence of spinal cord white matter tracts using diffusion tensor imaging, fibre tractography, and atlas-based segmentation.

PURPOSE: Neuroimaging provides great utility in complex spinal surgeries, particularly when anatomical geometry is distorted by pathology (tumour, degeneration, etc.). Spinal cord MRI diffusion tractography can be used to generate streamlines; however, it is unclear how well they correspond with white matter tract locations along the cord microstructure. The goal of this work was to evaluate the spatial correspondence of DTI tractography with anatomical MRI in healthy anatomy (where anatomical locations can be well defined in T1-weighted images). METHODS: Ten healthy volunteers were scanned on a 3T system. T1-weighted (1 × 1 × 1 mm) and diffusion-weighted images (EPI readout, 2 × 2 × 2 mm, 30 gradient directions) were acquired and subsequently registered (Spinal Cord Toolbox (SCT)). Atlas-based (SCT) anatomic label maps of the left and right lateral corticospinal tracts were identified for each vertebral region (C2-C6) from T1 images. Tractography streamlines were generated with a customized approach, enabling seeding of specific spinal tract regions corresponding to individual vertebral levels. Spatial correspondence of generated fibre streamlines with anatomic tract segmentations was compared in unseeded regions of interest (ROIs). RESULTS: Spatial correspondence of the lateral corticospinal tract streamlines was good over a single vertebral ROI (Dice's similarity coefficient (DSC) = 0.75 ± 0.08, Hausdorff distance = 1.08 ± 0.17 mm). Over larger ROI, fair agreement between tractography and anatomical labels was achieved (two levels: DSC = 0.67 ± 0.13, three levels: DSC = 0.52 ± 0.19). CONCLUSION: DTI tractography produced good spatial correspondence with anatomic white matter tracts, superior to the agreement between multiple manual tract segmentations (DSC ~ 0.5). This supports further development of spinal cord tractography for computer-assisted neurosurgery.

The Impact of an Open-Book Pelvic Ring Injury on Bone Strain: Validation of a Finite Element Model and Analysis Within the Gait Cycle.

The threshold for surgical stabilization for an open-book pelvic fracture is not well defined. The purpose of this research was to validate the biomechanical behavior of a specimen-specific pelvic finite element (FE) model with an open-book fracture with the biomechanical behavior of a cadaveric pelvis in double leg stance configuration under physiologic loading, and to utilize the validated model to compare open book versus intact strain patterns during gait. A cadaveric pelvis was experimentally tested under compressive loading in double leg stance, intact, and with a simulated open-book fracture. An intact FE model of this specimen was reanalyzed with an equivalent simulated open-book fracture. Comparison of the FE generated and experimentally measured strains yielded an R2 value of 0.92 for the open-book fracture configuration. Strain patterns in the intact and fractured models were compared throughout the gait cycle. In double leg stance and heel-strike/heel-off models, tensile strains decreased, especially in the pubic ramus contralateral to the injury, and compressive strains increased in the sacroiliac region of the injured side. In the midstance/midswing gait configuration, higher tensile and compressive FE strains were observed on the midstance side of the fractured versus intact model and decreased along the superior and inferior pubic rami and ischium, with midswing side strains reduced almost to zero in the fractured model. Identified in silico patterns align with clinical understanding of open-book fracture pathology suggesting future potential of FE models to quantify instability and optimize fixation strategies.

Out-of-Distribution Detection of Human Activity Recognition with Smartwatch Inertial Sensors.

Out-of-distribution (OOD) in the context of Human Activity Recognition (HAR) refers to data from activity classes that are not represented in the training data of a Machine Learning (ML) algorithm. OOD data are a challenge to classify accurately for most ML algorithms, especially deep learning models that are prone to overconfident predictions based on in-distribution (IIN) classes. To simulate the OOD problem in physiotherapy, our team collected a new dataset (SPARS9x) consisting of inertial data captured by smartwatches worn by 20 healthy subjects as they performed supervised physiotherapy exercises (IIN), followed by a minimum 3 h of data captured for each subject as they engaged in unrelated and unstructured activities (OOD). In this paper, we experiment with three traditional algorithms for OOD-detection using engineered statistical features, deep learning-generated features, and several popular deep learning approaches on SPARS9x and two other publicly-available human activity datasets (MHEALTH and SPARS). We demonstrate that, while deep learning algorithms perform better than simple traditional algorithms such as KNN with engineered features for in-distribution classification, traditional algorithms outperform deep learning approaches for OOD detection for these HAR time series datasets.

Biomechanical Properties of Metastatically Involved Osteolytic Bone.

PURPOSE OF REVIEW: Skeletal metastasis involves the uncoupling of physiologic bone remodeling resulting in abnormal bone turnover and radical changes in bony architecture, density, and quality. Bone strength assessment and fracture risk prediction are critical in clinical treatment decision-making. This review focuses on bone tissue and structural mechanisms altered by osteolytic metastasis and the resulting changes to its material and mechanical behavior. RECENT FINDINGS: Both organic and mineral phases of bone tissue are altered by osteolytic metastatic disease, with diminished bone quality evident at multiple length-scales. The mechanical performance of bone with osteolytic lesions is influenced by a combination of tissue-level and structural changes. This review considers the effects of osteolytic metastasis on bone biomechanics demonstrating its negative impact at tissue and structural levels. Future studies need to assess the cumulative impact of cancer treatments on metastatically involved bone quality, and its utility in directing multimodal treatment planning.

Perceptions of using lithium in fracture management: a survey of orthopaedic surgeons, fracture patients and the general public.

BACKGROUND: Lithium, an established psychiatric medication, has recently been shown to enhance new bone formation in preclinical fracture models. Current research is focused on evaluating the efficacy of low-dose, short-term lithium treatment to improve long bone fracture healing through a Phase II randomized clinical trial (LiFT NCT02999022). In working towards future applications of lithium for fracture management, this study aimed to understand the current perceptions of lithium as a psychiatric drug and the potential barriers to its orthopaedic adoption. METHODS: Three questionnaires, evaluating knowledge about lithium and willingness to embrace its use in fracture healing were disseminated among the general population, fracture patients eligible for the LiFT (Lithium for Fracture Treatment) trial and orthopaedic surgeons across Canada. RESULTS: Of the 768 public respondents, 84% were willing to take a medication that would aid fracture healing but only 62.6% if the medication was lithium. Willingness dropped to 44.6% among the 168 respondents who knew about the psychiatric use of lithium. Lack of sufficient knowledge (n = 50) and concerns about side effects including effects on the brain (n = 74) were the main reasons cited by those who were unwilling to use lithium. Of the 29 fracture patients, only 20 patients had previously heard of lithium. Of these, 40% were willing to take lithium for fracture healing with an additional 10% if the dose was low or if the intake duration was short. Only 50% knew that lithium has side effects. Of the 43 orthopaedic surgeons, 38 surgeons knew about clinical use of lithium. Of these, 68% knew that lithium has side effects and 29% knew that it interacts with other drugs. While most agreed that new strategies are needed to improve fracture management, only 68% were willing to prescribe lithium for fractures with an additional 16% if there is scientific evidence and/or a standard dosing protocol. CONCLUSIONS: This study identified a lack of knowledge about uses and side effects of lithium among all three cohorts. A robust educational framework for orthopaedic surgeons, their patients and the members of their clinical care teams will be essential to widespread repurposing of lithium for fracture care.

Diffusion-Tensor Imaging Versus Digitization in Reconstructing the Masseter Architecture.

Accurate characterization of the craniomaxillofacial (CMF) skeleton using finite element (FE) modeling requires representation of complex geometries, heterogeneous material distributions, and physiological loading. Musculature in CMF FE models are often modeled with simple link elements that do not account for fiber bundles (FBs) and their differential activation. Magnetic resonance (MR) diffusion-tensor imaging (DTI) enables reconstruction of the three-dimensional (3D) FB arrangement within a muscle. However, 3D quantitative validation of DTI-generated FBs is limited. This study compares 3D FB arrangement in terms of pennation angle (PA) and fiber bundle length (FBL) generated through DTI in a human masseter to manual digitization. CT, MR-proton density, and MR-DTI images were acquired from a single cadaveric specimen. Bone and masseter surfaces were reconstructed from CT and MR-proton density images, respectively. PA and FBL were estimated from FBs reconstructed from MR-DTI images using a streamline tracking (STT) algorithm (n = 193) and FBs identified through manual digitization (n = 181) and compared using the Mann-Whitney test. DTI-derived PAs did not differ from the digitized data (p = 0.411), suggesting that MR-DTI can be used to simulate FB orientation and the directionality of transmitted forces. Conversely, a significant difference was observed in FBL (p < 0.01) which may have resulted due to the tractography stopping criterion leading to early tract termination and greater length variability. Overall, this study demonstrated that DTI can yield muscle FB orientation data suitable to representative directionality of physiologic muscle loading in patient-specific CMF FE modeling.

The impact of thermal cycling on Staphylococcus aureus biofilm growth on stainless steel and titanium orthopaedic plates.

BACKGROUND: Orthopaedic implant infections are difficult to eradicate because bacteria adhering to implant surfaces inhibit the ability of the immune system and antibiotics to combat these infections. Thermal cycling is a temperature modulation process that improves performance and longevity of materials through molecular structural reorientation, thereby increasing surface uniformity. Thermal cycling may change material surface properties that reduce the ability for bacteria to adhere to the surface of orthopaedic implants. This study aims to determine whether thermal cycling of orthopaedic implants can reduce bacterial growth. METHODS: In a randomized, blinded in-vitro study, titanium and stainless steel plates treated with thermal cycling were compared to controls. Twenty-seven treated and twenty-seven untreated plates were covered with 10 ml tryptic soy broth containing ~ 105 colony forming units (CFU)/ml of bioluminescent Staphylococcus aureus (S. aureus)Xen29 and incubated at 37 °C for 14d. Quantity and viability of bacteria were characterized using bioluminescence imaging, live/dead staining and determination of CFUs. RESULTS: Significantly fewer CFUs grow on treated stainless steel plates compared to controls (p = 0.0088). Similar findings were seen in titanium plates (p = 0.0048) following removal of an outlier. No differences were evident in live/dead staining using confocal microscopy, or in metabolic activity determined using bioluminescence imaging (stainless steel plates: p = 0.70; titanium plates: p = 0.26). CONCLUSION: This study shows a reduction in CFUs formation on thermal cycled plates in-vitro. Further in-vivo studies are necessary to investigate the influence of thermal cycling on bacterial adhesion during bone healing. Thermal cycling has demonstrated improved wear and strength, with reductions in fatigue and load to failure. The added ability to reduce bacterial adhesions demonstrates another potential benefit of thermal cycling in orthopaedics, representing an opportunity to reduce complications following fracture fixation or arthroplasty.

Dynamically tensioned ACL functional knee braces reduce ACL and meniscal strain.

PURPOSE: The effectiveness of ACL functional knee braces to reduce meniscal and ACL strain after ACL injury or reconstruction is not well understood. A new dynamic knee tensioning brace system has been designed to apply an active stabilizing force to the knee. The ability of this system to reduce tissue strains is unknown. The purpose of this study was to test the ability of the dynamically tensioned brace to reduce strain in both the ACL and meniscus during rehabilitation activities. METHODS: A combined in vivo/in silico/in vitro method was used to study three activities: gait, double leg squat, and single leg squat. Muscle forces and kinematics for each activity were derived through in vivo motion capture and applied to seven cadaveric knee specimens fitted with custom braces. Medial meniscal strain and ACL strain were measured in ACL intact, deficient and reconstructed conditions. RESULTS: The brace lowered peak and average meniscal strain in ACL deficient knees (P < 0.05) by an average of 1.7%. The brace was also found to lower meniscal strain in reconstructed knees (1.1%) and lower ACL strain in ACL intact (1.3%) and reconstructed knees (1.4%) (P < 0.05). CONCLUSIONS: This study supports the use of a brace equipped with a dynamic tensioning system to lower meniscal strain in ACL-deficient knees. Its use may help decrease the risk of subsequent meniscal tears in chronic ACL deficiency or delayed reconstruction. In ACL-intact and reconstructed knees, the brace may be beneficial in injury prophylaxis or in protecting the ACL graft following reconstruction. These results will aid clinicians make informed recommendations for functional brace use in patients with unstable knees. LEVEL OF EVIDENCE: II.

Collagen fibril organization within rat vertebral bone modified with metastatic involvement.

Metastatic involvement diminishes the mechanical integrity of vertebral bone, however its specific impact on the structural characteristics of a primary constituent of bone tissue, the collagen-I fibril matrix, has not been adequately characterized. Female athymic rats were inoculated with HeLa or Ace-1 cancer cells lines producing osteolytic or mixed (osteolytic & osteoblastic) metastases respectively. A maximum of 21days was allowed between inoculation and rat sacrifice for vertebrae extraction. Linear polarization-in, polarization-out (PIPO) second harmonic generation (SHG) and transmission electron microscopy (TEM) imaging was utilized to assess the impact of metastatic involvement on collagen fibril organization. Increased observations of deviations in the typical plywood motif or a parallel packing structure and an increased average measured susceptibility ratio (related to relative degree of in-plane vs. out-plane fibrils in the analyzed tissue area) in bone adjacent to metastatic involvement was indicative of change in fibrilar organization compared to healthy controls. In particular, collagen-I fibrils in tumour-induced osteoblastic bone growth showed no adherence to the plywood motif or parallel packing structure seen in healthy lamellar bone, exhibiting a much higher susceptibility ratio and degree of fibril disorder. Negative correlations were established between measured susceptibility ratios and the hardness and modulus of metastatic bone tissue assessed in a previous study. Characterizing modifications in tissue level properties is key in defining bone quality in the presence of metastatic disease and their potential impact on material behaviour.

Comparison of the effect of two different bone-targeted radiofrequency ablation (RFA) systems alone and in combination with percutaneous vertebroplasty (PVP) on the biomechanical stability of the metastatic spine.

INTRODUCTION: Radiofrequency ablation (RFA) and percutaneous vertebroplasty (PVP) are used independently and in combination to treat metastatically involved vertebrae with the aim of relieving pain, reducing tumour burden and providing bony mechanical stabilization. PURPOSE: The aim of this work was to characterize the effect of two bone-targeted RFA devices, alone and in combination with PVP, to improve strength and mechanical stability in vertebrae with osteolytic metastatic disease. METHODS: Simulated spinal metastases (n = 12) were treated with one of two bone-targeted RFA devices (bipolar cooled or bone coil RF electrodes), followed by PVP. Under axial compressive loading, spinal canal narrowing was measured in the intact specimen, after tumour simulation, post-RFA and post-PVP. RESULTS: RFA alone resulted in successful tumour shrinkage and cavitation, but further increased canal narrowing under loading. RFA combined with PVP significantly reduced posterior wall stability in samples where sufficient tumour shrinkage and cavitation were coupled with a pattern of cement deposition which extended to posterior vertebral body. CONCLUSIONS: RFA combined with cement deposition in the posterior vertebral body demonstrates significantly more stable vertebrae under axial loading.

Quantitative MRI in a non-surgical model of cervical spinal cord injury.

Quantitative T2 (qT2), diffusion tensor imaging (DTI), and histology were used to investigate a cervical model of spinal cord injury (SCI) in the rat. While quantitative MRI can significantly increase the specificity in the presence of pathology, it must be validated for each type of injury or disease. In the case of traumatic SCI most models are difficult to image, either due to the location of the injury, or as a result of damage to surrounding tissues resulting from invasive surgical procedures. In this study a non-surgical cervical model of SCI, produced using a combination of focused ultrasound and microbubbles, was used to produce pathology similar to that seen in models of contusive and compressive injuries. qT2 and DTI were performed at 24 h and 1 and 2 weeks following injury, and compared with H&E and luxol fast blue histology. In the injured spinal cord, in addition to intra/extracellular (I/E) water and myelin water in white matter, qT2 revealed a large component with very short T2 of about 3 ms, which was highly correlated with the presence of hemorrhage in both gray and white matter at 24 h, and with the presence of hemosiderin in gray matter at 2 weeks following injury. The T2 of the I/E water peak was also elevated at 24 h in both gray and white matter, which was correlated with the presence of vacuolation/edema on histology. Cystic cavities were only seen at the 1 or 2 week timepoints, and were correlated with the presence of a water peak with T2 > 250 ms. No significant changes in diffusivity parameters were observed. Pathologies were often co-occurring, with opposite effects on the average T2 in a given voxel, reducing the visibility of injured tissue on standard T2 -weighted MR images.