µCT images are commonly analysed to assess changes in bone density and architecture in preclinical murine models. Several platforms provide automated analysis of bone architecture parameters from volumetric regions of interest (ROI). However, segmentation of the regions of subchondral bone to create the volumetric ROIs remains a manual and time-consuming task. This study aimed to develop and evaluate automated pipelines for trabecular bone architecture analysis of mouse proximal tibia subchondral bone. A segmented dataset involving 62 knees (healthy and arthritic) from 10-week male C57BL/6 mice were used to train a U-Net type architecture, with µCT scans (downsampled) input that output segmentation and bone volume density (BV/TV) of the subchondral trabecular bone. Segmentations were upsampled and used in tandem with the original scans (10µ) as input for architecture analysis along with the thresholded trabecular bone. The analysis considered the manually and U-Net segmented ROIs using two available pipelines: the ITKBoneMorphometry library and CTan (SKYSCAN). The analyses included: bone volume (BV), total volume (TV), BV/TV, trabecular number (TbN), trabecular thickness (TbTh), trabecular separation (TbSp), and bone surface density (BSBV). There was good agreement for bone measures between the manual and U-Net pipelines utilizing ITK (R=0.88-0.98) and CTan (R=0.91-0.98). ITK and CTan showed good agreement for BV, TV, BV/TV, TbTh and BSBV (R=0.9-0.98). However, a limited agreement was seen between TbN (R=0.73) and TbSb (R=0.59) due to methodological differences in how spacing is evaluated. This U-Net/ITK pipeline seamlessly automated both segmentation and quantification of the proximal tibia subchondral bone. This automated pipeline allows the analysis of large volumes of data, and its open-source nature may enable the standardization of stereologic analysis of trabecular bone across different research groups.
Total knee and hip arthroplasty (TKA and THA) are the most commonly performed surgical procedures, the costs of which constitute a significant healthcare burden. Improving access to care for THA/TKA requires better efficiency. It is hypothesized that this may be possible through a two-stage approach that utilizes prediction of surgical time to enable optimization of operating room (OR) schedules. Data from 499,432 elective unilateral arthroplasty procedures, including 302,490 TKAs, and 196,942 THAs, performed from 2014-2019 was extracted from the American College of Surgeons (ACS) National Surgical and Quality Improvement (NSQIP) database. A deep multilayer perceptron model was trained to predict duration of surgery (DOS) based on pre-operative clinical and biochemical patient factors. A two-stage approach, utilizing predicted DOS from a held out “test” dataset, was utilized to inform the daily OR schedule. The objective function of the optimization was the total OR utilization, with a penalty for overtime. The scheduling problem and constraints were simulated based on a high-volume elective arthroplasty centre in Canada. This approach was compared to current patient scheduling based on mean procedure DOS. Approaches were compared by performing 1000 simulated OR schedules. The predict then optimize approach achieved an 18% increase in OR utilization over the mean regressor. The two-stage approach reduced overtime by 25-minutes per OR day, however it created a 7-minute increase in underutilization. Better objective value was seen in 85.1% of the simulations. With deep learning prediction and mathematical optimization of patient scheduling it is possible to improve overall OR utilization compared to typical scheduling practices. Maximizing utilization of existing healthcare resources can, in limited resource environments, improve patient's access to arthritis care by increasing patient throughput, reducing surgical wait times and in the immediate future, help clear the backlog associated with the COVID-19 pandemic.
Physiotherapy is a critical element in successful conservative management of low back pain (LBP). The aim of this study was to develop and evaluate a system with wearable inertial sensors to objectively detect sitting postures and performance of unsupervised exercises containing movement in multiple planes (flexion, extension, rotation). A set of 8 inertial sensors were placed on 19 healthy adult subjects. Data was acquired as they performed 7 McKenzie low-back exercises and 3 sitting posture positions. This data was used to train two models (Random Forest (RF) and XGBoost (XGB)) using engineered time series features. In addition, a convolutional neural network (CNN) was trained directly on the time series data. A feature importance analysis was performed to identify sensor locations and channels that contributed most to the models. Finally, a subset of sensor locations and channels was included in a hyperparameter grid search to identify the optimal sensor configuration and the best performing algorithm(s) for exercise classification. Models were evaluated using F1-score in a 10-fold cross validation approach. The optimal hardware configuration was identified as a 3-sensor setup using lower back, left thigh, and right ankle sensors with acceleration, gyroscope, and magnetometer channels. The XBG model achieved the highest exercise (F1=0.94±0.03) and posture (F1=0.90±0.11) classification scores. The CNN achieved similar results with the same sensor locations, using only the accelerometer and gyroscope channels for exercise classification (F1=0.94±0.02) and the accelerometer channel alone for posture classification (F1=0.91±0.03). This study demonstrates the potential of a 3-sensor lower body wearable solution (e.g. smart pants) that can identify proper sitting postures and exercises in multiple planes, suitable for low back pain. This technology has the potential to improve the effectiveness of LBP rehabilitation by facilitating quantitative feedback, early problem diagnosis, and possible remote monitoring.
Bone turnover and microdamage are impacted by skeletal metastases which can contribute to increased fracture risk. Treatments for metastatic disease may further impact bone quality. This study aimed to establish an understanding of microdamage accumulation and load to failure in healthy and osteolytic vertebrae following cancer treatment (stereotactic body radiotherapy (SBRT), zoledronic acid (ZA), or docetaxel (DTX)). Forty-two 6-week old athymic female rats (Hsd:RH-Foxn1rnu, Envigo) were studied; 22 were inoculated with HeLa cervical cancer cells through intracardiac injection (day 0). Animals were randomly assigned to four groups: untreated (healthy=5, osteolytic=6), SBRT on day 14 (healthy=6, osteolytic=6), ZA on day 7 (healthy=4, osteolytic=5), and DTX on day 14 (healthy=5, osteolytic=5). Animals were euthanized on day 21. L1-L3 motion segments were compression loaded to failure and force-displacement data recorded. T13 vertebrae were stained with BaSO4 and µCT imaged (90kVp, 44uA, 4.9µm) to visualize microdamage location and volume. Damage volume fraction (DV/BV) was calculated as the ratio of BaSO4 to bone volume. Differences in mean load-to-failure were compared using three-way ANOVA (disease status, treatment, cells injected). Differences in mean DV/BV between treatment groups were compared using one-way ANOVA. Treatment had a significant effect on load-to-failure (p=0.004) with ZA strengthening the healthy and osteolytic vertebrae. Reduced strength post SBRT seen in the metastatic (but not the healthy) group may be explained by greater tumor involvement secondary to higher cell injection concentrations. Untreated metastatic samples had higher DV/BV (16.25±2.54%) compared to all treatment groups (p<0.05) suggesting a benefit of treatment to bone quality. Focal and systemic cancer treatments were shown to effect load-to-failure and microdamage accumulation in healthy and osteolytic vertebrae. Developing a better understanding of how treatments effect bone quality and mechanical stability is critical for effective management of patients with spinal metastases.
Access to health care, 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 low back physiotherapy exercise participation without the direct supervision of a medical professional. The aim of this study was to develop and evaluate the potential for performing automatic, unsupervised video-based monitoring of at-home low back physiotherapy exercises using a single mobile phone camera. 24 healthy adult subjects performed seven exercises based on the McKenzie low back physiotherapy program while being filmed with two smartphone cameras. Joint locations were automatically extracted using an open-source pose estimation framework. Engineered features were extracted from the joint location time series and used to train a support vector machine classifier (SVC). A convolutional neural network (CNN) was trained directly on the joint location time series data to classify exercises based on a recording from a single camera. The models were evaluated using a 5-fold cross validation approach, stratified by subject, with the class-balanced accuracy used as the performance metric. Optimal performance was achieved when using a total of 12 pose estimation landmarks from the upper and lower body, with the SVC model achieving a classification accuracy of 96±4% and the CNN model an accuracy of 97±2%. This study demonstrates the feasibility of using a smartphone camera and a supervised machine learning model to effectively assess at-home low back physiotherapy adherence. This approach could provide a low-cost, scalable method for tracking adherence to physical therapy exercise programs in a variety of settings.
An objective technological solution for tracking adherence to at-home shoulder physiotherapy is important for improving patient engagement and rehabilitation outcomes, but remains a significant challenge. The aim of this research was to evaluate performance of machine-learning (ML) methodologies for detecting and classifying inertial data collected during in-clinic and at-home shoulder physiotherapy exercise. A smartwatch was used to collect inertial data from 42 patients performing shoulder physiotherapy exercises for rotator cuff injuries in both in-clinic and at-home settings. A two-stage ML approach was used to detect out-of-distribution (OOD) data (to remove non-exercise data) and subsequently for classification of exercises. We evaluated the performance impact of grouping exercises by motion type, inclusion of non-exercise data for algorithm training, and a patient-specific approach to exercise classification. Algorithm performance was evaluated using both in-clinic and at-home data.Aims
Methods
Excessive resident duty hours (RDH) are a recognized issue with implications for physician well-being and patient safety. A major component of the RDH concern is on-call duty. While considerable work has been done to reduce resident call workload, there is a paucity of research in optimizing resident call scheduling. Call coverage is scheduled manually rather than demand-based, which generally leads to over-scheduling to prevent a service gap. Machine learning (ML) has been widely applied in other industries to prevent such issues of a supply-demand mismatch. However, the healthcare field has been slow to adopt these innovations. As such, the aim of this study was to use ML models to 1) predict demand on orthopaedic surgery residents at a level I trauma centre and 2) identify variables key to demand prediction. Daily surgical handover emails over an eight year (2012-2019) period at a level I trauma centre were collected. The following data was used to calculate demand: spine call coverage, date, and number of operating rooms (ORs), traumas, admissions and consults completed. Various ML models (linear, tree-based and neural networks) were trained to predict the workload, with their results compared to the current scheduling approach. Quality of models was determined by using the area under the receiver operator curve (AUC) and accuracy of the predictions. The top ten most important variables were extracted from the most successful model. During training, the model with the highest AUC and accuracy was the multivariate adaptive regression splines (MARS) model, with an AUC of 0.78±0.03 and accuracy of 71.7%±3.1%. During testing, the model with the highest AUC and accuracy was the neural network model, with an AUC of 0.81 and accuracy of 73.7%. All models were better than the current approach, which had an AUC of 0.50 and accuracy of 50.1%. Key variables used by the neural network model were (descending order): spine call duty, year, weekday/weekend, month, and day of the week. This was the first study attempting to use ML to predict the service demand on orthopaedic surgery residents at a major level I trauma centre. Multiple ML models were shown to be more appropriate and accurate at predicting the demand on surgical residents as compared to the current scheduling approach. Future work should look to incorporate predictive models with optimization strategies to match scheduling with demand in order to improve resident well being and patient care.
Single level discectomy (SLD) is one of the most commonly performed spinal surgery procedures. Two key drivers of their cost-of-care are duration of surgery (DOS) and postoperative length of stay (LOS). Therefore, the ability to preoperatively predict SLD DOS and LOS has substantial implications for both hospital and healthcare system finances, scheduling and resource allocation. As such, the goal of this study was to predict DOS and LOS for SLD using machine learning models (MLMs) constructed on preoperative factors using a large North American database. The American College of Surgeons (ACS) National Surgical and Quality Improvement (NSQIP) database was queried for SLD procedures from 2014-2019. The dataset was split in a 60/20/20 ratio of training/validation/testing based on year. Various MLMs (traditional regression models, tree-based models, and multilayer perceptron neural networks) were used and evaluated according to 1) mean squared error (MSE), 2) buffer accuracy (the number of times the predicted target was within a predesignated buffer), and 3) classification accuracy (the number of times the correct class was predicted by the models). To ensure real world applicability, the results of the models were compared to a mean regressor model. A total of 11,525 patients were included in this study. During validation, the neural network model (NNM) had the best MSEs for DOS (0.99) and LOS (0.67). During testing, the NNM had the best MSEs for DOS (0.89) and LOS (0.65). The NNM yielded the best 30-minute buffer accuracy for DOS (70.9%) and ≤120 min, >120 min classification accuracy (86.8%). The NNM had the best 1-day buffer accuracy for LOS (84.5%) and ≤2 days, >2 days classification accuracy (94.6%). All models were more accurate than the mean regressors for both DOS and LOS predictions. We successfully demonstrated that MLMs can be used to accurately predict the DOS and LOS of SLD based on preoperative factors. This big-data application has significant practical implications with respect to surgical scheduling and inpatient bedflow, as well as major implications for both private and publicly funded healthcare systems. Incorporating this artificial intelligence technique in real-time hospital operations would be enhanced by including institution-specific operational factors such as surgical team and operating room workflow.
Bone turnover and the accumulation of microdamage are impacted by the presence of skeletal metastases which can contribute to increased fracture risk. Treatments for metastatic disease may further impact bone quality. The present study aims to establish a preliminary understanding of microdamage accumulation and load to failure in osteolytic vertebrae following stereotactic body radiotherapy (SBRT), zoledronic acid (ZA), or docetaxel (DTX) treatment. Twenty-two six-week old athymic female rats (Hsd:RH-Foxn1rnu, Envigo, USA) were inoculated with HeLa cervical cancer cells through intracardiac injection (day 0). Institutional approval was obtained for this work and the ARRIVE guidelines were followed. Animals were randomly assigned to four groups: untreated (n=6), spine stereotactic body radiotherapy (SBRT) administered on day 14 (n=6), zoledronic acid (ZA) administered on day 7 (n=5), and docetaxel (DTX) administered on day 14 (n=5). Animals were euthanized on day 21. T13-L3 vertebral segments were collected immediately after sacrifice and stored in −20°C wrapped in saline soaked gauze until testing. µCT scans (µCT100, Scanco, Switzerland) of the T13-L3 segment confirmed tumour burden in all T13 and L2 vertebrae prior to testing. T13 was stained with BaSO4 to label microdamage. High resolution µCT scans were obtained (90kVp, 44uA, 4W, 4.9µm voxel size) to visualize stain location and volume. Segmentations of bone and BaSO4 were created using intensity thresholding at 3000HU (~736mgHA/cm3) and 10000HU (~2420mgHA/cm3), respectively. Non-specific BaSO4 was removed from the outer edge of the cortical shell by shrinking the segmentation by 105mm in 3D. Stain volume fraction was calculated as the ratio of BaSO4 volume to the sum of BaSO4 and bone volume. The L1-L3 motion segments were loaded under axial compression to failure using a µCT compatible loading device (Scanco) and force-displacement data was recorded. µCT scans were acquired unloaded, at 1500µm displacement and post-failure. Stereological analysis was performed on the L2 vertebrae in the unloaded µCT scans. Differences in mean stain volume fraction, mean load to failure, and mean bone volume/total volume (BV/TV) were compared between treatment groups using one-way ANOVAs. Pearson's correlation between stain volume fraction and load to failure by treatment was calculated using an adjusted load to failure divided by BV/TV. Stained damage fraction was significantly different between treatment groups (p=0.0029). Tukey post-hoc analysis showed untreated samples to have higher stain volume fraction ( Focal and systemic cancer treatments effect microdamage accumulation and load to failure in osteolytic vertebrae. Current testing of healthy controls will help to further separate the effects of the tumour and cancer treatments on bone quality.
Bone turnover and the accumulation of microdamage are impacted by the presence of skeletal metastases which can contribute to increased fracture risk. Treatments for metastatic disease may further impact bone quality. The present study aims to establish a preliminary understanding of microdamage accumulation and load to failure in osteolytic vertebrae following stereotactic body radiotherapy (SBRT), zoledronic acid (ZA), or docetaxel (DTX) treatment. Twenty-two six-week old athymic female rats (Hsd:RH-Foxn1rnu, Envigo, USA) were inoculated with HeLa cervical cancer cells through intracardiac injection (day 0). Institutional approval was obtained for this work and the ARRIVE guidelines were followed. Animals were randomly assigned to four groups: untreated (n=6), spine stereotactic body radiotherapy (SBRT) administered on day 14 (n=6), zoledronic acid (ZA) administered on day 7 (n=5), and docetaxel (DTX) administered on day 14 (n=5). Animals were euthanized on day 21. T13-L3 vertebral segments were collected immediately after sacrifice and stored in −20°C wrapped in saline soaked gauze until testing. µCT scans (µCT100, Scanco, Switzerland) of the T13-L3 segment confirmed tumour burden in all T13 and L2 vertebrae prior to testing. T13 was stained with BaSO4 to label microdamage. High resolution µCT scans were obtained (90kVp, 44uA, 4W, 4.9µm voxel size) to visualize stain location and volume. Segmentations of bone and BaSO4 were created using intensity thresholding at 3000HU (~736mgHA/cm3) and 10000HU (~2420mgHA/cm3), respectively. Non-specific BaSO4 was removed from the outer edge of the cortical shell by shrinking the segmentation by 105mm in 3D. Stain volume fraction was calculated as the ratio of BaSO4 volume to the sum of BaSO4 and bone volume. The L1-L3 motion segments were loaded under axial compression to failure using a µCT compatible loading device (Scanco) and force-displacement data was recorded. µCT scans were acquired unloaded, at 1500µm displacement and post-failure. Stereological analysis was performed on the L2 vertebrae in the unloaded µCT scans. Differences in mean stain volume fraction, mean load to failure, and mean bone volume/total volume (BV/TV) were compared between treatment groups using one-way ANOVAs. Pearson's correlation between stain volume fraction and load to failure by treatment was calculated using an adjusted load to failure divided by BV/TV. Stained damage fraction was significantly different between treatment groups (p=0.0029). Tukey post-hoc analysis showed untreated samples to have higher stain volume fraction ( Focal and systemic cancer treatments effect microdamage accumulation and load to failure in osteolytic vertebrae. Current testing of healthy controls will help to further separate the effects of the tumour and cancer treatments on bone quality.
Total knee and hip arthroplasty (TKA and THA) are two of the highest volume and resource intensive surgical procedures. Key drivers of the cost of surgical care are duration of surgery (DOS) and postoperative inpatient length of stay (LOS). The ability to predict TKA and THA DOS and LOS has substantial implications for hospital finances, scheduling and resource allocation. The goal of this study was to predict DOS and LOS for elective unilateral TKAs and THAs using machine learning models (MLMs) constructed on preoperative patient factors using a large North American database. The American College of Surgeons (ACS) National Surgical and Quality Improvement (NSQIP) database was queried for elective unilateral TKA and THA procedures from 2014-2019. The dataset was split into training, validation and testing based on year. Multiple conventional and deep MLMs such as linear, tree-based and multilayer perceptrons (MLPs) were constructed. The models with best performance on the validation set were evaluated on the testing set. Models were evaluated according to 1) mean squared error (MSE), 2) buffer accuracy (the number of times the predicted target was within a predesignated buffer of the actual target), and 3) classification accuracy (the number of times the correct class was predicted by the models). To ensure useful predictions, the results of the models were compared to a mean regressor. A total of 499,432 patients (TKA 302,490; THA 196,942) were included. The MLP models had the best MSEs and accuracy across both TKA and THA patients. During testing, the TKA MSEs for DOS and LOS were 0.893 and 0.688 while the THA MSEs for DOS and LOS were 0.895 and 0.691. The TKA DOS 30-minute buffer accuracy and ≤120 min, >120 min classification accuracy were 78.8% and 88.3%, while the TKA LOS 1-day buffer accuracy and ≤2 days, >2 days classification accuracy were 75.2% and 76.1%. The THA DOS 30-minute buffer accuracy and ≤120 min, >120 min classification accuracy were 81.6% and 91.4%, while the THA LOS 1-day buffer accuracy and ≤2 days, >2 days classification accuracy were 78.3% and 80.4%. All models across both TKA and THA patients were more accurate than the mean regressors for both DOS and LOS predictions across both buffer and classification accuracies. Conventional and deep MLMs have been effectively implemented to predict the DOS and LOS of elective unilateral TKA and THA patients based on preoperative patient factors using a large North American database with a high level of accuracy. Future work should include using operational factors to further refine these models and improve predictive accuracy. Results of this work will allow institutions to optimize their resource allocation, reduce costs and improve surgical scheduling. The American College of Surgeons National Surgical Quality Improvement Program and the hospitals participating in the ACS NSQIP are the source of the data used herein; they have not verified and are not responsible for the statistical validity of the data analysis or the conclusions derived by the authors.Acknowledgements:
The spine is a common site of metastasis. Complications include pathologic fracture, spinal cord compression, and neurological deficits. Vertebroplasty (VP) and Balloon Kyphoplasty (KP) are minimally invasive stabilization procedures used as a palliative treatment to improve mechanical stability, quality of life, and reduce pain. Photodynamic therapy (PDT) is a tumour-ablative modality that may complement mechanical stability afforded by VP/KP. This first-in-human study evaluates PDT safety when applied in conjunction with VP/KP. This dose escalation trial involved one light only control group and four light-drug doses (50,100,150,200J;n=6) delivered at 150mW from a 690nm diode laser by 800-micron optical fibers prior to KP/VP. Patients eligible for VP/KP in treating pathologic fracture or at-risk lesions at a single level were recruited. Exclusion criteria included spinal canal compromise or neurologic impairment. PDT is a two-step binary therapy of systemic drug followed by intravertebral light activation. Light was applied via bone trochar prior to cementation. This study used a benzoporphyrin derivative monoacid (BPD-MA), Verteporfin (VisudyneTm), as the photosensitizer drug in the therapy. Drug/light safety, neurologic safety, generic (SF-36), and disease-specific outcomes (VAS, EORTC-QLQ-BM22, EORTC-QLQ-C15-PAL) were recorded through six weeks. Phototoxicity and the side effects of the BPD-MA were also examined following PDT use. Thirty (10 male, 20 female) patients were treated (13 KP, 17 VP). The average age was 61 and significantly different between genders (Male 70yrs vs. Female 57yrs: p 0.05), and tumour status (lytic vs. mixed blastic/lytic: p>0.05). In most cases, fluence rates were similar throughout PDT treatment time, indicating a relatively stable treatment. Twelve (40%) of patients experienced complications during the study, none of which were attributed to PDT therapy. This included two kyphoplasty failures due to progression of disease, one case of shingles, one ankle fracture, one prominent suture, one case of constipation due to a lung lesion, one case of fatigue, and five patients experienced pain that was surgically related or preceded therapy. Vertebral PDT appears safe from pharmaceutical and neurologic perspectives. KP/VP failure rate is broadly in line with reported values and PDT did not compromise efficacy. The 50J group demonstrated an improved response. Ongoing study determining safe dose range and subsequent efficacy studies are necessary.
Rotator cuff tears are the most common cause of shoulder disability, affecting 10% of the population under 60 and 40% of those aged 70 and above. Massive irreparable rotator cuff tears account for 30% of all tears and their management continues to be an orthopaedic challenge. Traditional surgical techniques, that is, tendon transfers are performed to restore shoulder motion, however, they result in varying outcomes of stability and complications. Superior capsular reconstruction (SCR) is a novel technique that has shown promise in restoring shoulder function, albeit in limited studies. To date, there has been no biomechanical comparison between these techniques. This study aims to compare three surgical techniques (SCR, latissimus dorsi tendon transfer and lower trapezius tendon transfer) for irreparable rotator cuff tears with respect to intact cuff control using a clinically relevant biomechanical outcome of rotational motion. Eight fresh-frozen shoulder specimens with intact rotator cuffs were tested. After dissection of subcutaneous tissue and muscles, each specimen was mounted on a custom shoulder testing apparatus and physiologic loads were applied using a pulley setup. Under 2.2 Nm torque loading maximum internal and external rotation was measured at 0 and 60 degrees of glenohumeral abduction. Repeat testing was conducted after the creation of the cuff tear and subsequent to the three repair techniques. Repeated measures analysis with paired t-test comparisons using Sidak correction was performed to compare the rotational range of motion following each repair technique with respect to each specimen's intact control. P-values of 0.05 were considered significant. At 0° abduction, internal rotation increased after the tear (intact: 39.6 ± 13.6° vs. tear: 80.5 ± 47.7°, p=0.019). Internal rotation was higher following SCR (52.7 ± 12.9°, intact - SCR 95% CI: −25.28°,-0.95°, p=0.034), trapezius transfer (74.2 ± 25.3°, intact – trapezius transfer: 95% CI: −71.1°, 1.81°, p=0.064), and latissimus transfer (83.5 ± 52.1°, intact – latissimus transfer: 95% CI: −118.3°, 30.5°, p=0.400) than in intact controls. However, internal rotation post SCR yielded the narrowest estimate range close to intact controls. At 60° abduction, internal rotation increased after the tear (intact: 38.7 ± 14.4° vs. tear: 49.5 ± 13°, p=0.005). Internal rotation post SCR did not differ significantly from intact controls (SCR: 49.3 ± 10.1°, intact – SCR: 95% CI: −28°, 6.91°, p=0.38). Trapezius transfer showed a trend toward significantly higher internal rotation (65.7 ± 21.1°, intact – trapezius transfer: 95% CI: −55.7°, 1.7°, p=0.067), while latissimus transfer yielded widely variable rotation angle (65.7 ± 38°, intact – latissimus transfer: 95% CI: −85.9°, 31.9°, p=0.68). There were no significant differences in external rotation for any technique at 0° or 60° abduction. Preliminary evaluation in this cadaveric biomechanical study provides positive evidence in support of use of SCR as a less morbid surgical option than tendon transfers. The cadaveric nature of this study limits the understanding of the motion to post-operative timepoint and the results herein are relevant for otherwise normal shoulders only. Further clinical evaluation is warranted to understand the long-term outcomes related to shoulder function and stability post SCR.
Spinal stenosis is a condition resulting in the compression of the neural elements due to narrowing of the spinal canal. Anatomical factors including enlargement of the facet joints, thickening of the ligaments, and bulging or collapse of the intervertebral discs contribute to the compression. Decompression surgery alleviates spinal stenosis through a laminectomy involving the resection of bone and ligament. Spinal decompression surgery requires appropriate planning and variable strategies depending on the specific situation. Given the potential for neural complications, there exist significant barriers to residents and fellows obtaining adequate experience performing spinal decompression in the operating room. Virtual teaching tools exist for learning instrumentation which can enhance the quality of orthopaedic training, building competency and procedural understanding. However, virtual simulation tools are lacking for decompression surgery. The aim of this work was to develop an open-source 3D virtual simulator as a teaching tool to improve orthopaedic training in spinal decompression. A custom step-wise spinal decompression simulator workflow was built using 3D Slicer, an open-source software development platform for medical image visualization and processing. The procedural steps include multimodal patient-specific loading and fusion of Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) data, bone threshold-based segmentation, soft tissue segmentation, surgical planning, and a laminectomy and spinal decompression simulation. Fusion of CT and MRI elements was achieved using Fiducial-Based Registration which aligned the scans based on manually placed points allowing for the identification of the relative position of soft and hard tissues. Soft tissue segmentation of the spinal cord, the cerebrospinal fluid, the cauda equina, and the ligamentum flavum was performed using Simple Region Growing Segmentation (with manual adjustment allowed) involving the selection of structures on T1 and/or T2-weighted scans. A high-fidelity 3D model of the bony and soft tissue anatomy was generated with the resulting surgical exposure defined by labeled vertebrae simulating the central surgical incision. Bone and soft tissue resecting tools were developed by customizing manual 3D segmentation tools. Simulating a laminectomy was enabled through bone and ligamentum flavum resection at the site of compression. Elimination of the stenosis enabled decompression of the neural elements simulated by interpolation of the undeformed anatomy above and below the site of compression using Fill Between Slices to reestablish pre-compression neural tissue anatomy. The completed workflow allows patient specific simulation of decompression procedures by staff surgeons, fellows and residents. Qualitatively, good visualization was achieved of merged soft tissue and bony anatomy. Procedural accuracy, the design of resecting tools, and modeling of the impact of bone and ligament removal was found to adequately encompass important challenges in decompression surgery. This software development project has resulted in a well-characterized freely accessible tool for simulating spinal decompression surgery. Future work will integrate and evaluate the simulator within existing orthopaedic resident competency-based curriculum and fellowship training instruction. Best practices for effectively teaching decompression in tight areas of spinal stenosis using virtual simulation will also be investigated in future work.
Quantitative assessment of metastatic involvement of the bony spine is important for assessing disease progression and treatment response. Quantification of metastatic involvement is challenging as tumours may appear as osteolytic (bone resorbing), osteoblastic (bone forming) or mixed. This investigation aimed to develop an automated method to accurately segment osteoblastic lesions in a animal model of metastatically involved vertebrae, imaged with micro computed tomography (μCT). Radiomics seeks to apply standardized features extracted from medical images for the purpose of decision-support as well as diagnosis and treatment planning. Here we investigate the application of radiomic-based features for the delineation of osteoblastic vertebral metastases. Osteoblastic lesions affect bone deposition and bone quality, resulting in a change in the texture of bony material physically seen through μCT imaging. We hypothesize that radiomics based features will be sensitive to changes in osteoblastic lesion bone texture and that these changes will be useful for automating segmentation. Osteoblastic metastases were generated via intracardiac injection of human ZR-75-1 breast cancer cells into a preclinical athymic rat model (n=3). Four months post inoculation, ex-vivo μCT images (µCT100, Scanco) were acquired of each rodent spine focused on the metastatically involved third lumbar vertebra (L3) at 7µm/voxel and resampled to 34µm/voxel. The trabecular bone within each vertebra was isolated using an atlas and level-set based segmentation approach previously developed by our group. Pyradiomics, an open source Radiomics library written in python, was used to calculate 3D image features at each voxel location within the vertebral bone. Thresholding of each radiomic feature map was used to isolate the osteoblastic lesions. The utility of radiomic feature-based segmentation of osteoblastic bone tissue was evaluated on randomly selected 2D sagittal and axial slices of the μCT volume. Feature segmentations were compared to ground truth osteoblastic lesion segmentations by calculating the Dice Similarity Coefficient (DSC). Manually defined ground truth osteoblastic tumor segmentations on the μCT slices were informed by histological confirmation of the lesions. The radiomic based features that best segmented osteoblastic tissue while optimizing computational time were derived from the Neighbouring Gray Tone Difference Matrix (NGTDM). Measures of coarseness yielded the best agreement with the manual segmentations (DSC=707%) followed by contrast, strength and complexity (DSC=6513%, 5428%, and 4826%, respectively). This pilot study using a radiomic based approach demonstrates the utility of the NGTDM features for segmentation of vertebral osteoblastic lesions. This investigation looked at the utility of isolated features to segment osteoblastic lesions and found modest performance in isolation. In future work we will explore combining these features using machine learning based classifiers (i.e. decision forests, support vector machines, etc.) to improve segmentation performance.
Anatomic studies have demonstrated that bipolar glenoid and humeral bone loss have a cumulative impact on shoulder instability, and that these defects may engage in functional positions depending on their size, location, and orientation, potentially resulting in failure of stabilisation procedures. Determining which lesions pose a risk for engagement remains a challenge, with Itoi's 3DCT based glenoid track method and arthroscopic assessment being the accepted approaches at this time. The purpose of this study was to investigate the interaction of humeral and glenoid bone defects on shoulder engagement in a cadaveric model. Two alternative approaches to predicting engagement were evaluated; 1) CT scanning the shoulder in abduction and external rotation 2) measurement of Bankart lesion width and a novel parameter, the intact anterior articular angle (IAAA), on conventional 2D multi-plane reformats. Hill-Sachs and Bony Bankart defects of varying size were created in 12 cadaveric upper limbs, producing 45 bipolar defect combinations. The shoulders were assessed for engagement using cone beam CT in various positions of function, from 30 to 90 degrees of both abduction and external rotation. The humeral and glenoid defects were characterised by measurement of their size, location, and orientation. The abduction external rotation scan and 2D IAAA approaches were compared to the glenoid track method for predicting engagement. Engagement was predicted by Itoi's glenoid track method in 24 of 45 specimens (53%). The abduction external rotation CT scan performed at 60 degrees of glenohumeral abduction (corresponding to 90 degrees of abduction relative to the trunk) and 90 degrees of external rotation predicted engagement accurately in 43 of 45 specimens (96%), with sensitivity and specificity of 92% and 100% respectively. A logistic model based on Bankart width and IAAA provided a prediction accuracy of 89% with sensitivity and specificity of 91% and 87%. Inter-rater agreement was excellent (Kappa = 1) for classification of engagement on the abduction external rotation CT, and good (intraclass correlation = 0.73) for measurement of IAAA. Bipolar lesions at risk for engagement can be identified using an abduction external rotation CT scan at 60 degrees of glenohumeral abduction and 90 degrees of external rotation, or by performing 2D measurements of Bankart width and IAAA on conventional CT multi-plane reformats. This information will be useful for peri-operative decision making around surgical techniques for shoulder stabilisation in the setting of bipolar bone defects.
Predictable fracture healing fails to occur in 5–10% of cases. This is particularly concerning among individuals with osteoporosis. With an increasing aging population, one in three women and one in five men above the age of 50 experience fragility fractures. As such, there is a critical need for an effective treatment option that could enhance fracture healing in osteoporotic bone. Lithium, the standard treatment for bipolar disorder, has been previously shown to improve fracture healing through modulation of the Wnt/beta-catenin pathway. We optimised the precise oral lithium administration parameters to improve mechanical strength and enhance healing of femoral fractures in healthy rats. A low dose of Lithium (20 mg/kg) administered seven days post fracture for a two week duration improved torsional strength by 46% at four weeks post fracture compared to non-treated animals. Application of lithium to enhance fracture healing in osteoporotic bone would have a significant healthcare impact and requires further study. Aim: To evaluate the efficacy of optimal lithium administration post fracture on quality of fracture healing in a rat osteoporotic model. Hypothesis: Lithium treatment in osteoporotic rats will improve the structural and mechanical properties of the healing bone despite the impaired nature of bone tissue. Sprague Dawley female rats (∼350 g, age ∼3 months) were bilaterally ovariectomised and maintained for 3 months to establish the osteoporotic phenotype. A unilateral, closed mid-shaft femoral fracture was created using a weight-drop apparatus. At seven days post fracture, the treatment group received 20 mg/kg-wt lithium chloride via oral gavage daily for 14 days. The control group received an equivalent dose of saline. All animals were sacrificed at day 28 and the femurs harvested bilaterally. Treatment efficacy was evaluated based on torsional loading and stereologic analysis. Lithium treatment positively impacted the healing femurs, with an average yield torque ∼1.25-fold higher than in the saline group (200±36 vs. 163±31 N-mm, p=0.15). Radiographically, the lithium-treated rats had a high level of restored periosteal continuity, larger bridging and intercortical callus at the fracture site. These hallmarks of healing were generally absent in the saline group. The Lithium group had significantly higher total volume (624±32 vs. 568±95 mm3), lower bone volume fraction (41±4 vs. 50±5%) and higher theoretical torsional rigidity (477±50 vs. 357±93 kN-mm2) compared to the saline group. Torsional strength and stereology values were similar for the contralateral femurs of the two groups. Lithium was found to enhance fracture healing in osteoporotic bone under the dosing regimen optimised in healthy femora. This is promising data as treatment represents an easily translatable pharmacological intervention for fracture healing that may ultimately reduce the healthcare burden of osteoporotic fractures.
Strain is a robust indicator of bone failure initiation. Previous work has demonstrated the measurement of vertebral trabecular bone strain by Digital Volume Correlation (DVC) of µCT scan in both a loaded and an unloaded configuration. This project aims to improve previous strain measurement methods relying on image registration, improving resolution to resolve trabecula level strain and to improve accuracy by applying feature based registration algorithms to µCT images of vertebral trabecular bone to quantify strain. It is hypothesised that extracting reliable corresponding feature points from loaded and unloaded µCT scans can be used to produce higher resolution strain fields compared to DVC techniques. The feature based strain calculation algorithm has two steps: 1) a displacement field is calculated by finding corresponding feature points identified in both the loaded and unloaded µCT scans 2) strain fields are calculated from the displacement fields. Two methods of feature point extraction, Scale Invariant Feature Transform (SIFT) and Skeletonisation, were applied to unloaded (fixed) and loaded (moving) µCT images of a rat tail vertebra. Spatially non-uniform displacement fields were generated by automatically matching corresponding feature points in the unloaded and loaded scans. The Thin Plate Spline method and a Moving Least Squares Meshless Method were both tested for calculating strain from the displacement fields. Verification of the algorithms was performed by testing against known artificial strain/displacement fields. A uniform and a linearly varying 2% compressive strain field were applied separately to an unloaded 2D sagittal µCT slice to simulate the moving image. SIFT was unable to reliably match identified feature points leading to large errors in displacement. Skeletonisation generated a more accurate and precise displacement field. TPS was not tolerant to small displacement field errors, which resulted in inaccurate strain fields. The Meshless Methods proved much more resilient to displacement field errors. The combination of Skeletonisation with the Meshless Method resulted in best performance with an accuracy of −405µstrain and a detection limit of 1210µstrain at a strain resolution of 221.5µm. The DVC algorithm verified using the same validation test yielded a similar detection limit (1190µstrain), but with a lower accuracy for the same test (2370µstrain) for a lower resolution strain field (770µm) (Hardisty, 2009). The Skeletonisation algorithm combined with the Meshless Method calculated strain at a higher resolution, but with a similar detection limit, to that of traditional DVC methods. Future improvements to this method include the implementation of subpixel feature point identification and adapting this method of strain measurement into a 3D domain. Ultimately, a hybrid DVC/feature registration algorithm may further improve the ability to measure trabecular bone strain using µCT based image registration.
Simulation is an effective adjunct to the traditional surgical curriculum, though access to these technologies is often limited and costly. The objectives of this work were to develop a freely accessible virtual pedicle screw simulator and to improve the clinical authenticity of the simulator through integration of low-cost motion tracking. The open-source medical imaging and visualisation software, 3D Slicer, was used as the development platform for the virtual simulation. 3D Slicer contains many features for quickly rendering and transforming 3D models of the bony spine anatomy from patient-specific CT scans. A step-wise pedicle screw insertion workflow module was developed which emulated typical pre-operative planning steps. This included taking anatomic measurements, identifying insertion landmarks, and choosing appropriate screw sizes. Monitoring of the surgeon's simulated tool was assessed with a low-cost motion tracking sensor in real-time. This allowed for the surgeon's physical motions to be tracked as they defined the virtual screw's insertion point and trajectory on the rendered anatomy. Screw insertion was evaluated based on bone density contact and cortical breaches. Initial surgeon feedback of the virtual simulator with integrated motion tracking was positive, with no noticeable lag and high accuracy between the real-world and virtual environments. The software yields high fidelity 3D visualisation of the complex geometry and the tracking enabled coordination of motion to small changes in both translational and angular positioning. Future work will evaluate the benefit of this simulation platform with use over the course of resident spine rotations to improve planning and surgical competency.
A novel bipolar cooled radiofrequency ablation probe, optimised for bone metastases applications, is shown in two preclinical models to offer a safe and minimally invasive treatment option that can ablate large tissue volumes and preserve the regenerative ability of bone. Use of radiofrequency ablation (RFA) in treating of skeletal metastases has been rising, yet its impact on bone tissue is poorly understood. 2–11 RF treatment induces frictional heating and effectively necrotises tissue in a local and minimally invasive manner.1 Bipolar cooled RF (BCRF) is a significant improvement to conventional RF whereby larger regions can be safely treated, protecting sensitive neighbouring tissues from thermal effects. This study aimed to evaluate the safety and feasibility of a novel bipolar RFA probe to create large contained lesions within healthy pig vertebrae and its determine its effects on bone and tumour cells in a rabbit long bone tumour model.Summary
Introduction
Fractures of the clavicle are relatively common, occurring mostly in younger patients and have historically been managed non-operatively. Recent studies have shown an advantage to surgical reduction and stabilisation of clavicle fractures with significant displacement. Currently, fracture displacement is measured using simple anterior-posterior two-dimensional x-rays of the clavicle. Since displacement can occur in all three-dimensions, however, evaluation of the amount displacement can be difficult and inaccurate. The purpose of this study was to determine the view that provides the most accurate assessment. Nine CT scans of acute displaced clavicle fractures were analysed with AmiraDEV5.2.2 Imaging software. Measurements for degrees of shortening and fracture displacement of the fracture clavicle were taken. Using a segmentation and manipulation module (ITK toolkit), five digitally reconstructed radiographs (DRRs) mimicking antero-posterior x-rays were created for every CT, with each differing by projection angle (ranging from 20° upwards tilt to 20° downwards tilt). Measurements were taken on each DRR using landmarks of entire clavicle length, distance from vertebrae to fracture (medial fragment length), distance from fracture to acromium (lateral fragment length), and horizontal shortening, and then compared to the true measurement obtained from the original CT. For all 9 samples, after comparing the measurements of clavicle fracture displacement in each 2D image, we found that an AP view with a 20° downward tilt yielded displacement measurements closest to the 3D (“gold standard”) measurements. The results agree with previous data collected from cadaveric specimens using physical X-ray film images. DDRs enable creation of multiple standard AP radiographs from which accurate tilt can be measured. The large deviation in measurements on different DRR projections motivates consideration of standardising X-ray projections. A uniform procedure would allow one to correctly evaluate the displacement of clavicular fractures if fracture displacement information is to be utilized in motivating surgical decision-making.
Bone is the preferred site of metastases in women with breast cancer, which can cause skeletal-related events (SRE¡¦s) such as pathologic fractures. Bisphosphonates are the current standard of care for treatment of meta-static bone disease by preventing further bone destruction. Photodynamic therapy (PDT) has been applied successfully as a non-radiative treatment for malignancies. In PDT, light is delivered to a tumour after the administration of a photosensitiser. Earlier pre-clinical studies in a metastatic rat model have shown that PDT reduced the tumour burden in the vertebrae. The goal of this investigation was to study the effect of PDT on bisphosphonate pre-treated cancer in-vitro. Human breast cancer cells, MT-1, were cultured until confluent. The following groups were formed: no treatment; incubation with zoledronic acid (24h; 10 ƒÝmol) only; PDT treatment only and incubation with zoledronic acid and PDT treatment. Prior to light application 1 microg/ml of the photosensitiser BPD-MA was added. PDT was performed with a light dose of 1J and 10 J. The cells were stained with a live/dead stain and analyzed by fluorescence microscope and flowcytometry. Incubation of the MT-1 carcinoma cells with bisphosphonate zoledronic acid resulted in a significantly higher number of dying cells following PDT treatment when compared cells that were not treated by zoledronic acid (p<
0.05). When comparing cell groups that did not undergo PDT treatment the incubation with zoledronic acid alone did not have a statistically significant effect on cell survival twenty-four hours following zoledronic acid administration. In-vitro, breast cancer cells appear more susceptible to PDT after they have been incubated with the zoledronic acid. Zoledronic acid, a potent bisphosphonate, inhibits farsenylpyrophosphate (FPP) which is involved in farsenylation of cell membrane proteins. The inhibition of FPP may cause a reduced effect of PDT on cell rescue. The treatment with bisphosphonates seems to have a synergistic effect with PDT treatment. As such, light dosimetry in PDT treatment may need to take into account potential therapeutic interactions between PDT and current medical therapies in the treatment of skeletal metastatic burden.
The importance of mechanism of injury was initially introduced by Holdsworth who made the supposition that all fractures are created when the spine is subject to one of 5 types of violence. It has been our experience that similar injury mechanisms can lead to variable fracture patterns. Alternatively, different injury mechanisms can lead to the same fracture pattern.
The impact of cement leakage during percutaneous vertebroplasty has not been well characterized. This study aimed to quantify and compare cement leakage and its clinical significance in osteoporotic and metastatic vertebrae treated with vertebroplasty. Cement leakage was quantified using semi-automated thresholding of digital CT scans for fouteen metastatic and nineteen osteoporotic vertebrae and compared to pain scores. Cement leakage was present in 90.9% of vertebrae. Cement leaked predominantly into the disc in the osteoporotic vertebrae but yielded more diffuse leakage patterns in the metastatic cases. Despite cement leakage, there was significant improvement in pain immediately following vertebroplasty for all patients. This study aimed to quantify cement leakage in osteoporotic and metastatic vertebrae post-vertebroplasty and to determine whether leakage has clinical significance at follow-up. Despite high incidences of cement leakage, both osteoporotic and metastatic patients experienced significant immediate pain relief post-vertebroplasty. Cement leakage is investigated as a possible rationale for the higher rates of pain relief seen in osteoporotic vs metastatic patients undergoing percutaneous vertebroplasty. Cement leakage was present in 90.9% of the vertebrae treated. The percent volume of cement leakage was 11.6±10.6 in the osteoporotic vertebrae and 19.4±19.1 in the metastatic vertebrae (p=0.144). Cement leaked predominantly into the disc in the osteoporotic vertebrae whereas leakage was more diffuse in the metastatic vertebrae. Pain scores were high prior to vertebroplasty and decreased significantly following the procedure in both groups irrespective of leakage (p<
0.05). Digital CT scans were retrieved for osteoporotic (n=19) and metastatic (n=14) patients treated with percutaneous vertebroplasty. Volume of cement injected directly into the vertebral body and location of cement leakage (pedicle, disc, periphery, canal) was quantified using semi-automated thresholding techniques. Pain scores were collected at four stages of treatment (pre, immediately post, one day post, one week post-vertebroplasty). Disruption of the endplate in the osteoporotic spine provides an easily accessible pathway for the leakage of cement into the disc. Elevated pressurization during cement injection into metastatically involved vertebrae may account for the more diffuse cement leakage seen in the metastatic group. Clinically, pain scores improved irrespective of leakage.
Photodynamic therapy is a promising cancer treatment that employs wavelength-specific light in combination with a photosensitizing agent to induce local tumor destruction by photochemical generation of cytotoxic singlet oxygen. Clinical PDT has been evaluated for a variety of primary tumors, however, its use in spinal metastases to our knowledge has not been previously evaluated. A practical consideration is the ability to deliver light to bone. The investigators are evaluating a novel method of applying light to targeted spinal lesions using a minimally invasive technique similar to percutaneous vertebroplasty. This preliminary preclinical study evaluates the feasibility and efficacy of spinal PDT. To evaluate the feasibility and efficacy of spinal meta-static photodynamic therapy (PDT) using a percutaneous minimally invasive surgical approach similar to that of vertebroplasty in a preclinical model of bone metastases. A bioluminescent metastatic model was developed (intracardiac injection 2x106 MT-1Luc human breast cancer cells; Spinal PDT caused a reduction in bioluminescence of targeted lesions (66% to 87% in three hour drug-light group using light fluence rates of 25J and 150J, respectively; p<
0.05). The most selective drug-light interval was twenty-four hours where PDT induced tumor cell apoptosis/necrosis occurred, however, no spinal cord injury was observed. The greatest anti-tumor effect was observed at the three hour drug-light interval but observations of neurologic sequalae (9/22 animals) highlight the importance of ongoing study to closely define the therapeutic window of PDT. Drug dosimetry and the drug-light interval are critical in establishing an efficacious and safe treatment range for spinal PDT. Bioluminescent reporter imaging provides an
Vertebroplasty (VP) is currently used to improve spinal stability in patients with vertebral metastases. This study assessed the effects of Laser Induced Thermo Therapy (LITT), a minimally invasive technique used to ablate tumor tissue prior to vertebroplasty. Load-induced canal narrowing (LICN) was measured pre and post-vertebroplasty in twelve paired spinal motion segments with simulated lytic metastases. LICN improved post-vertebroplasty for all specimens treated with LITT. In all specimens, cement location was an important factor in post-vertebroplasty stability. Reduction of the tumor volume pre-vertebroplasty resulted in more reliable defect filling. To investigate the effect of tumor ablation using Laser Induced Thermo Therapy (LITT) prior to vertebroplasty (VP) on cement distribution and vertebral stability. Tumor volume reduction using LITT prior to cement injection improves defect filling and consistently reduces Load Induced Canal Narrowing (LICN). A simple, minimally invasive procedure providing accurate tissue destruction pre-vertebroplasty may result in more reliable cement fill, reduce cement extravasation and improve post-vertebroplasty stability. Following verebroplasty, LICN improved in all specimens treated with LITT and in those VP alone specimens with cement located posterior to the tumor tissue (33%). LITT treated vertebrae exhibited a trend toward reduced posterior wall motion post-vertebroplasty (LICN=29.7±27.1%) versus specimens treated with VP alone (LICN=248.7±253%). In the LITT+VP group, cement was fully contained within the vertebral body while cement extravasation into the canal was noted in 33% of the specimens treated without LITT. Twelve paired cadaveric thoracolumbar spinal motion segments with simulated lytic metastases were randomized for treatment with VP alone or LITT+VP. In the LITT+VP group, a laser fibre inserted through a transpedicular approach was used to ablate the tumor tissue prior to cement injection. The specimens were axially loaded to 800N pre and post-treatment. LICN was used as a measure of vertebral stability. Cement location was assessed post-testing through axial sectioning. Location of cement is an important factor in determining post-VP stability. Vertebroplasty is effective in decreasing LICN if the tumor is ablated or surrounded posteriorly with cement.
In percutaneous vertebroplasty, clinically significant complications occur predominantly in patients with spinal metastases. This higher rate of complication may be associated with increased pressurization that has been reported due to the presence of lytic tissue during vertebroplasty. To date, there has been no research investigating techniques aimed at reducing this pressurization. This study investigated the potential of tumour volume reduction using laser induced thermo therapy ablation within the metastatic spine. This novel technique proved to be capable of efficient tissue shrinkage (average 60%) with little or no pressurization (average 1.3mmHg) and moderate levels of temperature elevation (average increase of 15.1°C). This study aims to investigate the potential of minimally invasive tumour volume reduction using laser induced thermo therapy ablation within the metastatic spine. Volume reduction of tumour tissue prior to cement injection may provide a method to reduce pressurization, reduce the likelihood of tumour extravasation and improve cement fill during percutaneous vertebroplasty. In percutaneous vertebroplasty, clinically significant complications occur predominantly in patients with spinal metastases (10%). Laser-induced thermo therapy condensed and coagulated the simulated tumour. Volume shrinkage of the tumour tissue averaged 60%. Pressures generated within the vertebral body only rose an average of 1.3mmHg during the procedure. Maximum temperatures on the posterior body wall increased by 15.1°C, with average temperatures 6.8°C above the baseline. A simulated lytic defect created using breast tissue was introduced into the vertebral body of a calf spine to model a metastatically involved vertebra. A pre-charred surgical fibre coupled to a diode laser delivering 1750J of energy was inserted through an eleven-guage needle into the centre of the tumour using an intrapedicular technique. During treatment, the temperature at the posterior body wall and intravertebral pressure were measured. Following ablation, the volume of the remaining tissue was measured. The results suggest that this novel technique is capable of reproducible, uniform, and effective tissue destruction with little to no pressurization and moderate levels of temperature elevation. Both pressures and temperatures generated during our study were lower than reported values during percutaneous vertebroplasty and suggest little risk of complications.
Intramedullary nailed high proximal tibial fractures rely on the proximal screw-bone interface to provide stability, which can be insufficient in low-density bones. This study investigated the biomechanics of proximal screw cement augmentation in intramedullary nailing of high proximal tibial fractures. Mechanical stability in flexion/extension, varus/valgus and torsion was tested on six pairs of cadaveric proximal tibiae, with/without cement augmentation. Cement augmentation significantly increased construct stability in torsion and demonstrated a trend towards improved varus/valgus stabilization. Surprisingly, cement augmentation significantly decreased stability in flexion/extension, suggesting the potential benefits of cement augmentation may be limited in intramedullary nailed high proximal tibial fractures. This study assessed the biomechanical effects of augmenting proximal screws with cement in intramedullary nailing of high proximal third tibial fractures. While increased biomechanical stability was seen in torsion and varus/valgus, the reduction in stability in flexion/extension suggests that there may be limited benefit in cement augmentation in the nailing of high proximal tibia fractures. High proximal tibial fractures fixed with intramedullary nailing rely primarily on proximal screw fixation to provide stability. Cement augmentation of the proximal screws may provide needed increased construct stability in low-density tibiae. Cement augmentation provided a significant increase in construct stability in torsion (37.5% ± 8.0%, p<
0.05), with a trend toward increased stability in varus/valgus (25.5% ± 36.2%, p=0.08). Conversely, stability in flex-ion/extension was significantly decreased with the use of cement (25.9% ± 13.0%, p<
0.05). Reamed intramedullary nails (Zimmer, MDN) were implanted into six pairs of elderly cadaveric fresh-frozen proximal tibiae and secured using four proximal screws (two transverse, two oblique, 4.5mm diameter). Bone cement was injected into the screw holes just prior to screw insertion to augment the bone-screw interface in one tibia from each pair. Specimen stability was tested in flexion/extension and varus/valgus loading to 12Nm and in torsion to 7Nm. Displacement data was generated and analyzed using a repeated measures design. We hypothesized that intramedullary nail-bone construct stability would be increased with cement augmentation, particularly in low-density specimens. While construct stability was improved in torsion and varus/valgus, surprisingly stability consistently decreased in flexion/extension.
Spinal metastatic disease can result in burst fracture and neurologic compromise. This study aims to examine the effects of tumour location, shape and surface texture on burst fracture risk in the metastatic spine using a parametric poroelastic finite element model. Tumours were found to be most hazardous in the posterior region of the vertebral body, whereas the multiple tumour scenarios reduced risk. Tumour shape may affect the mechanism of burst fracture. Serrated and smooth outer tumour surfaces yielded similar trends. These results can be used to improve guidelines for burst fracture risk assessment in patients with spinal metastases. This study aims to examine the effects of tumour location, shape and surface texture on burst fracture risk in the metastatic spine. Both tumour location and shape are important factors in assessing the risk of burst fracture in the meta-static spine. Improving risk prediction may reduce burst fracture in patients with spinal metastases. Vertebral bulge increased over 30% when the tumour was moved posteriorly. Conversely, for the multi-tumour scenarios, vertebral bulge and axial displacement decreased by 41% and 35% in comparison to a single central tumour. Anterior and lateral movement demonstrated only small effects. Vertebral bulge increased proportionally to mediolateral tumour length and axial displacement increased proportionally to superior-inferior tumour length. Similar trends were seen with smoothed and serrated tumour surfaces. Using a parametric poroelastic finite element model of a metastaticaly involved T7 spinal motion segment, fourteen single and two multi-tumour scenarios were analyzed, each comprising approximately 24% tumour volume. Ellispoidal tumours were positioned in central, anterior, posterior and lateral locations. Tumour shape was altered by adjusting tumour radii for a centrally located tumour. Tumours were modeled using smoothed and serrated outer surface configurations. Burst fracture risk was assessed by measuring maximum vertebral bulge and axial displacement under load. Tumours were found to be most hazardous in the posterior region of the vertebral body, whereas the multi-tumour scenarios reduced risk. Modeling of tumour surface texture did not impact shape or location effects. Tumour shape may affect the mechanism of burst fracture.
Using serial CT scans, this project aims to develop a clinical research tool that analyzes changes in vertebral density in spines involved with metastatic disease. Tracking of total vertebral body and tumor volume alone was investigated. A program was developed to semi-automate the segmentation of the region of interest followed by image registration to superimpose the segmentation onto spatially aligned serial scans. Based on analysis of a simulated metastatic vertebra, generating a voxel distribution histogram from the vertebral body best quantified density in serial scans. This quantification method may improve clinical decision-making and treatment options for patients with vertebral metastases. To develop a clinical research tool to serially track tumor involvement in vertebrae with metastatic disease by quantifying changes in CT attenuation. Segmentation of the vertebral body and analysis of the voxel distribution within the region provides the most accurate method of quantifying changes in tumor involvement for the metastatic spine. A quantitative method to assess the progression or regression of disease may improve clinical decision–making and treatment options for patients with spinal metastases. The vertebral body segmentation was more accurate at tracking tumor involvement (voxel distribution histogram: 96.8% +/− 0.75% accuracy, mean density error: 4.7% +/− 0.8%) than segmenting the tumor volume alone (voxel distribution histogram: 86.1% +/− 3.6% accuracy, mean density error: 14.1% +/− 4.8%). A program was developed to semi-automatically segment the total vertebral body and tumor volume alone from CT scans of metastatically involved vertebrae. Image registration through user-defined landmarks and surface matching was used to spatially align serial scans, and the initial segmentation was superimposed with the aligned scans. Changes within the segmentation between CT scans were tracked using mean density and a voxel distribution histogram. A cadaveric vertebra with a simulated tumor was scanned at five orientations with 20° offsets to determine the accuracy of the methods. Error primarily resulted from unavoidable re-sampling during alignment of the scans.
Photodynamic therapy (PDT) is a promising new treatment for spinal metastases; however, the effects of PDT on bone are largely unknown. This study assessed the impact of PDT on spinal stability in rats at high (non-therapeutic) drug and LASER light doses. Spinal stability was assessed using stereological measures attained from in vitro μCT scans. High doses of PDT were shown to cause a reduction in vertebral density. Postoperative paralysis was also noted in a subset of animals treated. Tumour-involved vertebrae are already mechanically weakened; as such it is essential to establish a safe and efficacious therapeutic window for vertebral PDT. This study assessed the effect of high doses of photodynamic therapy (PDT) on biomechanical stability and bone density of lumbar vertebrae. PDT can cause damage to the vertebral bone and induce paralysis when treatment is applied at very high doses in the rat spine. PDT is a promising new treatment for spinal metastases however, it is important to understand its effect on vertebral bone in order to closely define the therapeutic window for safety and efficacy. Trabecular bone density decreased from L1–L3 in normal, untreated rats. The L2 vertebra when treated with high dose PDT was shown to have decreased bone density as compared to both L1 and L3. As expected, tumour-bearing rats had lower vertebral densities than normals. Rnu/Rnu rats were separated into normal controls, normals treated with PDT and tumour-bearing rats. Rats treated with PDT received an intercardiac injection of 2.5mg/Kg BPD-MA. The drug was activated through administration of 500J (300mA) of a non-thermal 690nm LASER adjacent to the L2 vertebral body. After one week, in vitro μCT scans were taken of L1–L3 and stereological quantities measured. The demonstrated reduction of bone density as quantified one week following treatment is important when considering spinal stability in the potential use of PDT to treat vertebral metastases. We have observed that the therapy can induce paralysis when treatment is applied at high doses in the rat spine. The intermediate and long-term effects of PDT on bone remain unknown and require ongoing study.