Orthopaedic Biomechanics

The orthopaedic biomechanics laboratory (OBL) is part of the Holland Bone and Joint Research Program and Physical Sciences Platform at Sunnybrook Research Institute (SRI). We work under the direction of Dr. Cari Whyne, who is also the director of the Holland Bone and Joint Program at Sunnybrook Health Sciences Centre and co-chair of orthopaedic research at the University of Toronto. OBL is part of the Spine Research Program and the Bone Metastases Site Group at the Odette Cancer Centre, and we are an important resource for the division of orthopaedics at the University of Toronto.

Our laboratory’s research focus is clinically translational bioengineering research aimed at maximizing function among those who develop musculoskeletal disease or disability. We conduct experimental and computational research related to testing and designing novel orthopaedic techniques and devices.

Our research areas include the following:

  1. skeletal metastases
  2. spinal tissue engineering and biomechanics
  3. thin bone structure biomechanics
  4. computer-assisted orthopaedic surgery

We are fully affiliated with the University of Toronto and we offer training positions for undergraduate, M.Sc. and PhD students and postdoctoral or post-health professional degree fellowships. Contact Dr. Whyne with any questions about her research activities and current opportunities in our group.

Areas of Research

Craniomaxillofacial research

Within the Orthopaedic Biomechanics Laboratory and the Division of Plastic and Reconstructive Surgeryat Sunnybrook, we have been exploring improved image processing and modeling techniques to better understand the biomechanics of the craniomaxillo facial skeleton (CMFS). Specifically, the lab has published new approaches for segmenting and deblurring head CT data to generate more accurate visualization and segmentation of thin bone structures. An improved pipeline for CMFSCT image analysis was developed and has been applied to experimentally validated finite element models which have changed our fundamental understanding of load transmission in the CMFS. This work has also yielded a drastically improved work flow for the generation of templates for intraoperative formation of CMF mesh implants, via custom software tools and pipelines implemented within an open source platform, 3D Slicer .Grant-funded work conducted in collaboration with Calavera Surgical Design (a Sunnybrook start-up company) has improved the efficacy of pre-operative planning for CMF skeletal reconstruction and is in clinical use today. Our (ongoing) work has been extended to the development of a computer-assisted pipeline for intra-operative CMF skeletal and soft tissue reconstruction. Our work has also led to novel CMF device design, including the development of “Bone Tape” (US patent 61/677,290).

Deblurring clinical CT scans to restore thin bone structures

In clinical CT imaging, there are severe errors in geometry and material properties in thin bone structures, which are in large part due to blurring. As such we aimed to restore sub-mm bone geometry and intensity information in clinical CT images by post-reconstruction image processing. Knowing what the non-blurred profile of cortical bone should look like, we can estimate it based on the observed profile in low-resolution CT images to restore the 3D anatomy of the craniomaxillofacial skeleton (CMFS).

Finite Element modelling of the CMFS

We created a new pipeline to generate accurate Finite Element (FE) models of the CMFS with heterogenous application of bone modulus values based on deblurred CT image intensity. Due to the very thin nature of the bone, this used nodal based assignments and algorithms to deal with partial volume effects at surfaces.

Mechanical testing is performed on specimens instrumented with strain gages to validate our modelling. Under more physiologic loading conditions, these models are able to show important pathways of load transmission occurring through the complex areas of the zygoma and orbital rim.

Understanding the sensitivity to load and boundary conditions, we are employing new methods to better represent muscle loading. MR-based diffusion tensor imaging (DTI), in combination with anatomical data, can elucidate the fibres and fibre bundles associated with the muscles of mastication. We are concurrently developing models focused on representing loading post-fracture reconstruction towards optimizing hardware requirements for stable fixation.

Computed tomography (CT) 3D geometrical reconstruction of the skull.
A) Masseter and skull volumes obtained from MRI and CT, B) Masseter fiber architecture obtained from DTI within the masseter volume, C) Mesh generation of the skull and masseter, D) Heterogeneous distribution of bone elastic modulus obtained using CT-based bone densities.
Load transmission through the zygoma and orbital rim.

A CAD-CAM pipeline for facial and skeletal reconstruction

In CMF reconstruction, the goal is to recreate the pre-traumatic appearance of the individual. Using pre-trauma 2D photographs, a pipeline of facial detection (finding faces in images), facial recognition (finding the same person’s face), facial landmarking (locating points of interest on the face) and face morph modelling (generating 3D face guided by landmarks) can be used to create a pre-trauma 3D face geometry. A ‘reverse-engineering’ of a forensics soft tissue model can then be used to determine the underlying skull shape from the 3D facial surface topography.

  1. Pre-trauma photos
  2. Patient provides reference photos to surgeon
  3. Surgeon provides photos for analysis
  4. Facial detection, facial recognition, 2D landmarking, 3D morph model
  5. Pre-trauma 3D face geometry
  6. Forensics’ soft-tissue thickness
  7. Inferred skull
  8. Nose skin & cartilage templates
  9. Surgery

The pipeline which goes from photo to face model to underlying craniomaxillofacial skeleton (CMFS) must consider age, sex, BMI, ethnicity, and facial expression. Application for this is in both form and function considering re-establishment of appearance, structure and facial reanimation.

A) A three-quarter side view 2D photos, B) Front view 2D photos, C) Corresponding 3D face shape surfaces, D) Basel face model 2017 3D facial estimate for the front 2D photos, E) Regional per-vertex Euclidean distance error between the estimate and the true scans (0-5 mm), F) Soft tissue depth map, G) Inferred skull.

An application of the CAD-CAM pipeline is shown in nasal reconstruction following trauma or tumour resection. A forehead flap graft can be preoperatively planned based on a 3D facial reconstruction. Flattening software transforms the 3D shape into a physical template for the graft to direct intraoperative cutting of a skin flap.

A) Patient photos with cancerous regions, B) Mirrored 3D scan with sculpted nostril, C) Nose labelled with aesthetic subunits, D) Flattened nose template with subunit boundaries (not to scale). E) Template traced in foil and test-fit into the defect, F) Template traced on the forehead, G) Forehead flap transferred and sutured.

Patient-specific CMFS implants made in the operating room

Calavera Surgical Design (a Sunnybrook start up company) has a process which creates unique patient-specific implants from standard commercial meshes that can be modified in the OR – enabling intraoperative sizing of the implants based on the actual resection. We have developed a new image analysis pipeline, including our deblurring algorithm, which has been integrated into Calavera’s clinical workflow, to reduce time and manual intervention in creating the designs.

Much like a shattered vase, reconstruction of the craniomaxillofacial skeleton (CMFS) requires the simultaneous alignment and stabilization of multiple articulated fragments for successful reconstruction. Fragments are accessed from different incisions and entry points that are not simultaneously visible, making perfect anatomic alignment in 3D technically challenging. Tape can facilitate temporary stabilization of multiple fragments with enough flexibility to adjust the alignment and perfect it prior to permanent rigid bonding. As a surface-bonding device, tape is less invasive than hardware and is not dependent on limited areas of dense bone. The flexibility of tape allows wrapping and bonding to complex bony contours yielding 3D matrix-type (vs. linear) stabilization.

In vivo study has demonstrated the healing of zygomatic fractures stabilized with Bone Tape without any adverse histologic reactions. Additional work is ongoing in optimizing the tape formulation and workflow leading to further in vivo preclinical testing. Commercialization of Bone Tape is being led by a new start-up company Cohesys .

Healed osteomy.

Skeletal metastases

Bone is the most common site for the distant spread of cancer. In particular, up to one third of all cancer patients develop tumours in the spine. Longer life expectancies for patients with cancer and metastatic disease makes quality of life an important issue and stresses the need for better diagnosis and treatment of skeletal metastases. The Orthopaedic Biomechanics Laboratory aims to understand and quantify the mechanics of bone metastases. This work is important in predicting fracture risk and developing new devices and methodologies for improved treatment. Maintaining the structural stability of metastatically involved bones is crucial in reducing morbidity and mortality associated with skeletal metastases.

Work conducted in collaboration with the Feldberg Chair in Spinal Research.

Bone quality is important from mechanics and material perspectives when considering vertebral structural integrity. Quality is dependent on mechanical (material and structural) properties, including mineralization, composition, remodelling, connectivity and architecture. To understand how metastatic disease (osteolytic and osteoblastic) affects bone quality we developed preclinical nude rat models of Osteolytic (HeLa), Mixed (ACE-1) and Osteoblastic (ZR-75) metastases. These models highlighted changes in the properties of both the mineral (hydroxyapatite) and organic (collagen) phases of the metastatic bone tissue, which correlated to tissue level material behaviour and whole vertebral mechanical properties. Computationally we have developed algorithms to directly measure deformation and strain via registration of loaded and unloaded µCT scans.

Unloaded, Subvoxel Interpolation 
Loaded, Subvoxel Interpolation
Multiresolution Deformable Registration 
Deformation field
Strain
Multiresolution Deformable Image Registration Pipeline.
  1. Unloaded, Subvoxel Interpolation
  2. Loaded, Subvoxel Interpolation
  3. Multiresolution Deformable Registration
  4. Deformation field
  5. Strain

Load and boundary conditions from this experimental imaging data have been applied to continuum and micro finite element (µFE) models of healthy and metastatically involved vertebrae. Microdamage present in healthy and metastatically involved vertebrae can be identified histologically through fuchsin staining, chelating agents and barium sulphate staining combined with µCT imaging. For higher resolution information, back scatter electron microscopy can be performed on BaSO4 stained sections. µFE models of these vertebrae were able to represent the load induced microdamage seen in these images. Microdamage was found to be spatially correlated with regions of high stress and strain in our µFE models with clear microdamage thresholds identified. Yet mechanically induced microdamage thresholds were different in healthy vs metastatic bone suggesting tissue level changes in bone quality.

Micro Finite Element Modelling, Backscatter Electron Imaging and µCT imaging of BaSO4 stained Osteolytic (top), Mixed (middle) and Control (bottom) vertebrae.

Recent work has gone beyond modelling of stress and strain, demonstrating the ability of non-linear FE models incorporating cohesive elements to represent post-yield modeling of crack initiation, propagation and failure. The impact of multimodal treatments on bone quality in the metastatic skeleton is an ongoing area of investigation.

Micro FE vertebral model generated from microCT data incorporating cohesive elements to enable the modelling of post yield behaviour/fracture.

Fracture risk prediction in the metastatic spine

Bone strength assessment and fracture risk prediction are critically important in guiding clinical treatment decisions aimed at preventing and/or lessening the burden of skeletal metastases. We developed medical image analysis algorithms that use an atlas-based segmentation approach, relying on demons deformable registration to quantify osteolytic and osteoblastic involvement within individual vertebrae over time to assess disease progression, and aid in clinical decision making.

Cancer treatment can also impact skeletal stability. High rates of vertebral compression fractures have been reported following spine stereotactic body radiotherapy (SBRT, 11-39 per cent). Application of the developed software pipeline successfully identified a pre-treatment osteolytic disease volume threshold of >11.6 predicted post-SBRT vertebral compression fractures (odds ratio 37.4). More recent work has identified that changes in vertebral volume over time are indicative of ongoing vertebral compression fracture progression post SBRT.

CT slice of a human Osteolytic vertebra.
Osteolytic volume automatically segmented within a vertebral body.
Greater change in vertebral body volume over time predicts ultimate spinal stability.

Vertebral compression fracture risk prediction: A deep learning approach

U net Convolutional Neural Network (CNN) architectures have been shown to be fast and highly accurate for image segmentation problems. A combination of segmentation and classification information (fractured/not fractured) will ultimately be used to train and develop a CNN based approach for fracture risk prediction in the metastatic spine. Deeper networks using additional training data and systematic hyper-parameter optimization may further improve initial segmentation results. We also aim to combine CT and MR images using a latent model to enable multimodal vertebral segmentation with an ultimate goal of integrating this approach into a clinical scoring system.

U net convolutional neural network architecture and sample results for vertebral body segmentation comparing manual and CNN-based methods. Vertebral body segmentation network trained (370 vertebrae) and tested (97 vertebrae).

Treatments of bone metastases are designed to decrease pain, increase structural stability, improve mobility and control tumour growth. Treatments include systemic drugs [Bisphosphonates (BPs), Rank-L inhibitors (i.e. Denosumab) and chemotherapeutic agents (e.g. docetaxel)], focal treatments (i.e. spine stereotactic body radiotherapy [SBRT] and radiofrequency ablation [RFA]) and structural stabilization (i.e. cement augmentation or instrumentation). Our research has primarily focused on focal minimally invasive treatment modalities, including consideration of these treatments within a more comprehensive multimodal approach to the treatment of skeletal metastases.

Photodynamic therapy

Used clinically in the treatment of macular degeneration and light accessible cancers such as melanoma, Photodynamic Therapy (PDT) involves systemic administration of a photosensitizer that accumulates preferentially in target tissue and becomes activated by non-thermal light at a specific wavelength.

Day 14 - Pre PDT
Day 16 - Post PDT
1. Administration of photosensitizer 2. Uptake of PS by tumour tissue 3. PS activated by external light source 4. Active PS ablates tumour

Activation of the photosensitizer in the presence of molecular oxygen leads to generation of highly reactive singlet oxygen, which causes tumor cell toxicity and tissue necrosis. A minimally invasive approach allows direct delivery of laser light to spinal lesions. Initial testing demonstrated the ability of PDT to ablate tumour tissue and augment the surrounding bone.

A reduction in bioluminescence demonstrates the impact of PDT on an osteolytic vertebral lesion.

A multimodal preclinical treatment study demonstrated the impact of PDT in conjunction with standard of care clinical treatments Bisphosphonates (BP) and Radiation therapy (RT). BP+PDT both destroyed the tumour and had the largest positive effect on bone, restoring bone volume fraction to non-tumour bearing control levels (with increased osteoid, woven bone, periosteal bone growth). An increase in bone volume was correlated to improved mechanical stability. Combined RT+PDT showed a similar effect on bone (lower magnitude).

1. Control
2. 1-week
3. 6-weeks
PDT leads to structural augmentation in the vertebrae, with increased bone deposition seen at one and six weeks post treatment.

Motivated by this promising preclinical work, a phase I clinical trial of PDT for spinal metastases has successfully been completed at Sunnybrook. Next steps will focus on treatment planning and running a Phase II clinical trial to quantify the direct impact of PDT on the vertebrae.

The clinical future of PDT.
The clinical future of PDT.

Radiofrequency Ablation (RFA)

Radiofrequency (RF) refers to the electromagnetic spectrum covering the frequencies from 3 Hz to 300 GHz. In the context of tumour destruction, RF ablation induces ionic modulation leading to controlled heat production & local ablation of targeted tissue.

In collaboration with Baylis Medical (Mississauga, ON) we developed a novel bipolar internally cooled RF probe for the ablation of spinal metastases. The probe was designed to overcome previous limitations with RF of small and incomplete ablated regions, charring, boiling, iatrogenic injury, and difficulty completing the RF circuit in bone. Large lesions were ablated with RFA without damage to the neighbouring critical structures. Osteoclasts and tumour cells were also shown to be very susceptible to RFA but destruction of osteocytes was more limited (desirable for bone health).

RFA of the spine: highlighted lesions are visualized on MR, optical and histology images.

The device was brought to first in human testing and ultimately became an FDA clinically approved device, Osteocool. With the sale of the Osteocool system to Medtronic, there is now worldwide clinical use of this device. We are currently developing a treatment planning and navigation system for RFA of spinal metastases with an integrated approach to enable multimodal treatment with SBRT.

Feldberg Chair in Spinal research

The Feldberg Chair in Spinal Research provides an enhanced opportunity for innovating, integrating and improving the diagnosis and treatment of spinal trauma and pathology. The following projects are supported by the Feldberg chair in spinal research; the first three are being carried out in conjunction with the Orthopaedic Biomechanics Laboratory.

Pedicle screw instrumentation is the dominant surgical approach to achieve immediate stability of the spine. Transcortical screw insertion is an emerging technique of posterior spinal instrumentation with promising biomechanical properties; it requires a more medialized start point and follows an “up and out” trajectory. The objective of this work is to validate a freehand technique for insertion of transcortical screws.

A custom surgical simulator was used to determine appropriate freehand techniques of cortical screw insertion in the thoracic and lumbar spine. Specifically, case-specific volume rendering of non-pathologic and degenerative/scoliotic thoracic and lumbar spine CTs were used.

The start point and trajectory determination were modified from previously published methods by assessing screw fixation and purchase virtually using CT density data. Once identifiable and reproducible anatomic landmarks (Transverse Process, Pars interarticularis, midline) of the posterior spine were selected based on simulation, these methods were translated to the operating room. The vertebral level specific approach and landmarks were then checked against a Stryker based navigation system. In all cases, the freehand technique was deemed to place cortical screws ideally or safely.

The usage of transcortical screw fixation in the lumbar and thoracic spine may be a reasonable and expeditious alternative to pedicle screw fixation with the distinct advantage of limiting further lateral dissection, simpler and reproducible screw insertion start points and trajectories, and decreased risk of undesired screw breaches. This project demonstrates the power of virtual 3D interaction with medical imaging for surgical planning and technique generation.

As residency programs move to competency-based curricula, more authentic and accessible teaching tools are required to train the next generation of orthopaedic and neurosurgeons. Given the potential for neural complications, there exist significant barriers to residents and fellows obtaining adequate experience performing spinal surgery in the operating room. Virtual simulation tools are lacking for spinal surgery. The aim of this work is to develop an open-source 3D virtual simulator as a teaching tool to improve training in spinal decompression and pedicle screw insertion.

A custom stepwise simulator workflow was built using 3D Slicer; an open-source software development platform for medical image visualization and processing.

The procedural steps include import of patient-specific imaging, fusion of CT and MRI data, bone threshold-based segmentation, soft tissue segmentation, vertebral level identification, surgical planning, surgical field simulation, laminectomy, pedicle screw placement (start point, screw size, and trajectory), spinal decompression simulation, and evaluation. Bone and soft tissue resecting tools were developed by customizing manual 3D segmentation tools. Laminectomy simulation was enabled through bone and ligamentum flavum resection at the site of compression.

The completed workflow allows patient specific simulation and visualization of spinal procedures. Procedural accuracy, the design of resecting tools, and modeling of the impact of bone and ligament removal adequately encompass important challenges in spinal surgery. Screw-bone contact area can be evaluated quantitatively. Visualization of contact, decompression, tissue resection and positioning can be evaluated.

This software development project has resulted in a well-characterized open source tool for simulating spinal surgery. Future work will integrate the simulator within existing orthopaedic resident competency-based curriculum and fellowship training instruction.

Virtual simulation tool for spinal surgery.

Computed Tomography (CT) based navigation is rapidly becoming the standard of care in spinal surgery. While CT provides excellent bony detail, it is quite limited in its ability to discern soft tissues. Intra-procedural ultrasound (US) can provide real-time soft tissue discrimination allowing the delineation of tumor tissue, discs and neural elements, which is particularly useful for minimally invasive surgery. Challenges exist with application of US in the spine with respect to spinal level and orientation determination.

We have developed a spine-focused surgical workflow allowing for interchangeable US probes and navigation systems. Our technology uses the 3D Slicer open source platform for rapid development of image visualization and navigation solutions. We tested our technology with both Phillips and Telmed US systems, and a Medtronic StealthStation S7 for optical tracking.

Virtual simulation tool for spinal surgery.

The interface shows in real-time: 3D view of US plane with a rendering of the anatomy, US Image, corresponding CT image plane and fused image. Accuracy (mm) of the system was established by identifying features on the vertebral body in both modalities.

Our spine surgery workflow allows US-CT fusion intra-operatively, simultaneously displaying hard and soft tissue information, using various combinations of US systems. Accurate localization enables the utilization of navigation to guide soft tissue resection in places that are difficult to visualize (i.e. in thoracic discectomy or assessing the adequacy of a dorsal decompression during a cervical laminectomy for myelopathy).

US Plane in 3D CT rendering.
US Plane in 3D CT rendering.
CT Plane.
CT Plane.
US Plane.
US Plane.
US – CT Fusion.
US – CT Fusion.

This project is a prospective longitudinal study investigating spine surgery (discectomies, decompressions and fusions) outcomes with a special focus on the presence of response shift in disease and generic functional outcome measures. Response shift refers to the idea that Patient Reported Outcome Measures (PROMs) change over time and are influenced by many factors – physical, subject and evaluative.

Change in rating of perceived QOL (observed)


Change explained by baseline and changes in health status (expected)


Discrepancy in QOL change (residual)

Response shift (measurement error)

The minimum important difference (MID) observed following spine surgery has varied drastically in the literature when considering PROMs. Here we are Investigating changes in patient’s MID over recovery from spinal surgery and how cognitive appraisal processes are implicated in the change trajectories.

Measures:

  • Rand-36 Physical and Mental Component Scores (PCS and MCS)
  • Oswestry Disability Index (ODI)
  • Pain Numeric Rating Scale Items (at rest, with activity, back and leg)
  • PROMIS pain impact
  • Global Assessment of Change (GAC) item
  • The QOL Appraisal Profile – Standards of comparison domain

Among patients with different trajectories after surgery, the relationship between PROM change and appraisal change differs by group. Better, Worse, and Bouncer patients are focusing on different standards of comparison over time.

Factors affecting minimal important difference:

  • Who you are asking (better or worse)
  • How disabled are they at baseline
  • When you are asking (time from surgery)
  • What the patient is comparing themselves to

By identifying whether and which appraisal processes influence PROM trajectories, the present work provides potential avenues for clinical intervention to improve spine surgery outcomes.

Upper and lower extremity research

Challenges in intramedullary (IM) nailing of long bone fractures arise during the entry point step in which 2D fluoroscopic imaging is used to guide 3D alignment of a guidewire safely into the IM canal. Specifically, the guidewire alignment achieved under fluoroscopy in one plane may be lost while adjusting the alignment in the orthogonal plane. This impedes the surgical workflow requiring unpredictable repetition of surgical activities (e.g. repeated fluoroscopic repositioning) and leads to frustration in the operating room. Such challenges are particularly evident in large (muscular and obese) patients.

FAST (Femoral Antegrade Starting Tool) is an innovative surgical tool that facilitates entry point selection and insertion for IM nailing. FAST enables maintenance of guidewire (Kirschner (K) wire) anteroposterior (AP) alignment during lateral imaging and K-wire positioning in the sagittal plane addressing both localization and orientation challenges that arise from the use of 2D imaging to achieve 3D alignment.

In use for femoral fracture stabilization, the initial FAST device entry point placement is conducted freehand at the greater trochanter under fluoroscopic image guidance. The device location and orientation are adjusted until satisfactory AP alignment is obtained. The device is fixed onto the greater trochanter, locking the AP alignment. Under lateral fluoroscopic imaging, the K-wire is inserted into a channel of the FAST device best aligned with the medullary canal. The FAST arm is rotated in plane to achieve optimal lateral alignment. With alignment optimized in both planes, the K-wire can be safely drilled into the bone. This workflow has been shown in preclinical study to minimize time and radiation exposure from fluoroscopic imaging in femoral IM nailing. A first-in-human trial of FAST was successfully completed in 2019.

Positioning of the glenoid component is one of the most challenging steps in total shoulder arthroplasty. Prosthetic longevity as well as functional outcomes are considered highly dependent on accurate positioning. Currently, there are no adequate means to verify the position of the glenoid component intra-operatively which is a significant impediment to accurate positioning. To address this clinical need we have developed Bullseye, a novel intra-operative imaging system that utilizes a hand-held structured light sensor and computer vision algorithms to verify the 3D position of the glenoid vault guide pin prior to preparation of the glenoid for component implantation.

a) Optical tracker on a sawbone scapula, b) structured light image of the scapula and optical tracker, c) registration of optical glenoid surface image to CT data, d) registration of optical fiducial image to its computer model, e) 3D model of registered fiducial and predicted guidepin position, f-h) predicted (green) and actual guidepin position for sagittal, axial, and coronal planes.

The canonical Wnt/β-Catenin pathway is a promising therapeutic target to stimulate bone growth. A molecular mechanism known to play a prominent role in skeletal development during embryogenesis, and believed to be recapitulated during fracture repair, the Wnt/β-Catenin pathway has been confirmed to influence the osteoblast lineage, stimulating mesenchymal progenitor precursors to differentiate into fully active, mature osteoblasts. Lithium is an integral component of psychotropic medicine but has also been linked to the Wnt/β-Catenin pathway and has been shown to positively influence bone biology acting as an anabolic agent to enhance fracture repair.

Through preclinical testing using a factorial design of experiments approach, we optimized the dose and duration of timing of lithium administration for fracture healing in healthy and osteoporotic femurs. It was found that the best treatment combination occurred at a low dose (20 mg/kgwt/day), late onset (7 days post-fracture) and a 2-week duration in healthy rats. Optimized lithium treatment yielded a 46 per cent increase in strength (maximum yield torque) at 4 weeks post-fracture over pooled controls. A similar 50 per cent increase in strength was seen with a further delayed administration of lithium (10 days post-fracture) in treating osteoporotic femurs at a six-week endpoint.

Impact of Li delivery on fracture healing.
Left: low dose, later onset, longer duration. Center: high dose, earlier onset, shorter duration. Right: intact contralateral control.
Impact of Li delivery on fracture healing. Left: low dose, later onset, longer duration. Center: high dose, earlier onset, shorter duration. Right: intact contralateral control.

A Phase II Clinical Trial in patients (LiFT) is currently underway at Sunnybrook to determine if lithium can improve clinical long bone fracture healing. This research is also considering potential barriers to the uptake of lithium therapy for fracture healing from the perspective of both patients and care providers.

Additional preclinical work is underway examining the impact of the microbiome on fracture healing.

Young athletes involved in pivoting and jumping sports are at high risk of tearing the anterior cruciate ligament (ACL) with 200,000/year occurring in the United States. ACL tears lead to short-term reduction in function and long-term morbidity, including post-traumatic knee arthritis. Injury prevention interventions have promising results, decreasing ACL injuries up to 60 per cent, however low (11 per cent) adherence is reported with efficacy strongly correlated with adherence. Readily deployable screening tools may provide objective injury risk estimates, potentially motivating improved adherence in intervention programs.

We developed a field-ready portable markerless computer vision-based system, Risk of Injury System based on Knee Kinematics (RISKK). RISKK uses a 3D camera for on court/field data acquisition and automatically analyzes functional tests (drop vertical jump, distance hop, timed hop) quickly (<5 minutes), without expert input, at low cost. Initial field testing produced promising results demonstrating measurement agreement with a gold standard multi-camera system (Vicon) and good reliability.

Once established, the ability to assess functional tests at low cost and at scale will have a paradigm shifting effect, from reactive to proactive. This will encourage early efforts in injury prevention and detection in young athletes, allowing routine screening, training assessment, and clinical decision support.

Screening tools used to assess a risk of injury on a knee.

Fractures of the pelvis occur due to high-energy impacts (traumatic fractures) and the application of physiologic loads to bone deficient in mineral or elastic resistance (insufficiency fractures). Displaced fractures can lead to disabling post-traumatic arthritis; some fracture patterns induce worse prognosis than others. However, clinical decision-making regarding patient management can be very complex. A better understanding of pelvic and acetabular mechanics and changes in the bone’s mechanical strength could lead to improved diagnosis and treatment of insufficiency and traumatic pelvic and acetabular fractures.

Specimen specific finite element model of the pelvis.
Specimen specific finite element model of the pelvis.

Finite element (FE) analysis is a powerful tool that has been successful in predicting the strength of healthy and pathologic bones. Patient-specific FE modeling is able to represent bones, which are highly heterogeneous in their presentation and are difficult to represent with other analytical or parametrically developed techniques. We have developed and experimentally validated specimen-specific 3D FE models of the pelvis and analyzed them under physiological loading. Using these models, we have examined the sensitivity of pelvic strain to bone material properties, shape difference and loading scenarios.

Physical therapy is essential for the successful rehabilitation of common shoulder injuries and following shoulder surgery. Patients may receive some training and supervision for shoulder physiotherapy through private pay or private insurance, but they are typically responsible for performing most of their physiotherapy independently at home. It is unknown to what degree patients perform their home exercises and if the exercises are done correctly without supervision. Our team has recently developed a Smart Physiotherapy Activity Recognition System (SPARS) for tracking home shoulder physiotherapy exercises using sensors in a commercial smart watch and artificial intelligence (AI). SPARS has been successfully shown to track shoulder exercises in healthy adults in the laboratory setting. Further inquiry is required to establish the clinical effectiveness of this technology and investigate the potential individual and societal impacts of its use. A clinical study focused on both implementation and implications of adherence monitoring with AI in patients with rotator cuff pathology is planned to be carried out within the Working Conditions Program at the Holland Centre.

Feature mapping:
1. 1D Convolution (Input 100 x 6)
2. Max Pooling (94 x 128)
3. 1D Convolution (47 x 128)
Sequence learning:
1. LSTM (20 x 128)
2. LSTM (20 x 100)
Classify:
1. Dense (1 x 100)
2. Output

Open source code available

Seglearn is a python package for machine learning time series or sequences which was developed for this project. It provides an integrated pipeline for segmentation, feature extraction, feature processing, and final estimator. Seglearn provides a flexible approach to multivariate time series and related contextual (meta) data for classification, regression, and forecasting problems. Support and examples are provided for learning time series with classical machine learning and deep learning models. It is compatible with scikit-learn.

Maximizing efficiency of surgical care

Waitlists for orthopaedic surgery, particularly hip and knee replacement are growing. Significant resources are required to run an operating room, making it one of the most valuable departments for hospitals and health care systems. Therefore, as resources – both physical and human – are limited across the public system in Canada, efficient management is crucial to the timely delivery of care. Assigning a specific date, time, operating room, surgeon, nurses, recovery bed and ward bed quickly becomes a daunting task for administrators due to the large volumes of cases. Our research challenges the tradition of tackling the highly complex orthopaedic surgery scheduling tasks using solely manual approaches based on surgeons’ estimates of operative time. Instead, we aim to design a comprehensive solution that leverages patient data, case volumes and patient-specific operative times to optimize the scheduling process in an automated way. Machine learning and mathematical optimization methods will be developed to enable both accurate predictions of operative time and optimal scheduling. In addition to financial benefits, optimized schedules would decrease patient waitlist times by facilitating more surgeries within the same amount of operating room time.

Facilities

Facilities within the Orthopaedic Biomechanics Laboratory include:

Sponsors

Members

Industry collaborators

Junior scientists

Research Engineers/Physicists

Clinical Fellows

  • Patrick Allison
  • Greg Berry
  • Allan Billig
  • Osama El-Badrawi
  • Tan Chen
  • Amal Khoury
  • Yves Laflamme
  • Martin Lesieur
  • Rafi Lotan
  • Omri Lubovsky
  • Ian McMurtray
  • Eran Regev
  • Declan Reidy
  • Chris Robertson
  • Shengi Yu

Postdoctoral Fellows

PhD students

  • Phil Boyer
  • Mikhail Burke
  • David Burns, SSTP
  • Meghan Crookshank
  • Hamid Ebrahimi
  • Cristina Falcinelli, visiting
  • Zachary Fishman
  • Parsa Hojjat
  • Asmaa Maloul
  • Michael Olsen
  • Zoryana Salo
  • Amir Pakdel Sefidgar
  • Padina Pezeshki
  • Elena Alacreu Samper, visiting
  • Devin Singh
  • Craig Tschirhart
  • Christian Wight

Undergraduate Students

  • Payal Agarwal
  • Prab Ajrawat
  • Iana Aranda
  • Daniel Axelrod
  • Simon Axelrod
  • Daniel Bartman
  • Mirza Beig
  • Lawrence Buchan
  • Daina Burnes
  • Katelyn Chan
  • Gary Chiang
  • Charlotte Curtis
  • Amanda DeVries
  • Hamid Ebrahimi
  • Aimee Gallant
  • Lyle Gordon
  • Daniela Heimlich
  • Ryan Herblum
  • Amanda Hope
  • Christine Huang​
  • Stephanie Huitema
  • Jeff Kasa
  • Kevin Kasa
  • Shawn Klein
  • Katlin Kreamer-Toni
  • Joey Kuang
  • Peggy Le
  • Natasha Lee Shee
  • Alexandra Leggett
  • Teri Leung
  • Jason Leung
  • Annie Leung
  • Bradley Lichtblau
  • Angela Lin
  • Andrew Liu
  • Jerry Luo
  • Fiona Macleod
  • Mohamed Gaith Majjani
  • Gen Mak
  • Amanda Manget
  • Taylor Martin
  • Michael Meguid
  • Payam Mousavi
  • Amik Nagpurkar
  • Sam Newhook
  • Matthew Ng
  • Meaghan O’Reilly
  • Andrea Pagotto
  • Chang Paik
  • Roy Park
  • Joshua Pope
  • Sohaib Qureshi
  • Shazia Rashid
  • Kazi Rahman
  • Mary Rebello
  • Raphael Rush
  • Hikmat Sahak
  • Austin Sawyer
  • Purav Shah
  • Caroline Shung
  • Vignesh Sivan
  • Kayley Ting
  • Earvin Tio
  • Teodora Vujovic
  • Yuan Wei
  • Andrew Welsh
  • Phoenix Wilkie
  • Edwin Wong
  • Tina Wu
  • Florence Wu
  • Jack Wunder
  • Celine Yeung
  • Yukun Netta Zhang
  • Stephanie Zhou

Masters students

  • Abdalrahman Alfakir
  • Joshua Bernick
  • Chetan Choudhari
  • Allison Clement
  • Dallis Ferguson
  • Soroush Ghomashchi
  • Deepthi Gorapalli
  • Michael Hardisty
  • Ryan Herblum
  • Amani Ibrahim
  • Deniz Jafari
  • Ashley Leckie
  • Diana Lee
  • Hui Tung Tony Lin
  • Victor Lo
  • Isaac Moss, SSTP
  • Sam Newhook
  • Brendan Polley
  • Justin Saddlemyer
  • Amir Samiezadeh
  • Hassan Syed
  • Thomas Szwedowski
  • Sebastian Tomescu, SSTP
  • Hoi-Ki Tong
  • Grace Underwood
  • Kathak Vachhani
  • Tessa Warmink
  • Emily Won
  • David Wright

Resident/medical students

  • Henry Ahn
  • Uosife Alfahd
  • Ali Belooshi
  • Megan Brenkel
  • Shane Burch
  • John de Almeida
  • Khal Elfala
  • Ryan Katchky
  • Jasjit Lochab
  • Allan Martin
  • Aaron Pellow
  • Dale Podolsky
  • Othman Ramadan
  • Caroline Scott
  • Ryan Sun
  • Stephen Szeto
  • John Townley
  • Teresa Ziegler

Medventions

  • Zaid Atto
  • Katelyn Chan
  • Joel Couture-Tremblay
  • Ginette Hartell
  • Annie Hollis
  • James Lee
  • Austen Lynds-Martin
  • Frank Lyons
  • Joel Moktar
  • Cameron Phillips
  • Austin Sawyer
  • Ian Whatley

College students

  • Timothy Cheng
  • Graham Rix

Highschool teachers (TSTOP)

  • Rosa Assalone

Scientists

Dr. Michael Hardisty