A simulation-enhanced intraoperative planning tool for robotic-assisted total knee arthroplasty

The purpose of the present study was to investigate current methods of surgical planning used in conjunction with robotics-assisted total knee arthroplasty (raTKA) to determine if improvements could be made using advanced computational techniques. Thus, through the use of musculoskeletal multi-body dynamic simulations, an enhanced surgical planning tool was developed, which provides insight on active postoperative joint mechanics. Development of the tool relied on patient-specific simulations using single-leg and full-body models. These simulations were constructed using two publicly-available datasets (Orthoload and SimTK); in particular, joint loading data obtained from subjects during various activities. Simulation parameters were optimized using a design-of experiments (DOE) methodology and validation of each of the models was conducted by calculating the root mean square error (RMSE) between joint loading calculated using the model and the corresponding results given in the appropriate dataset. Optimized and validated variants of each of the models were used in conjunction with the results of DOE studies that characterized the influence of a number of surgical planning variables on various biomechanical responses and linear regression analysis to derive knee performance equations (KPEs). In literature studies, some of the aforementioned responses have been strongly correlated with two outcomes commonly reported by dissatisfied TKA patients, namely, anterior knee pain and poor proprioception. In a proof-of-concept study, KPEs were used to calculate optimal positions and orientations of the femoral and tibial components in the case of one subject featured in the SimTK dataset. These results differed from corresponding ones reportedly achieved for the implant components in the subject. This trend suggests there is potential to improve robotic surgical planning for current-generation raTKA systems through the use of musculoskeletal simulation. Use of the proposed surgical planning tool does not require computational resources beyond what are used with a specified current-generation raTKA system (Navio Surgical System). Furthermore, there are only minimal differences between the workflow involving the proposed planning tool and that when Navio Surgical System is used. A number of recommendations for future studies are made, such as larger scale simulation validation work and use of more complex regression techniques when deriving the KPEs

Patient Specific Alignment, Anatomy, Recovery and Outcome in Total Knee Arthroplasty

Total knee arthroplasty (TKA), despite being an otherwise highly successful medical operation, has a recurrent problem of dissatisfaction and recurrent pain rates in the 15-20% range. A variety of factors contribute to this incidence of dissatisfaction which can broadly be considered to fall into one of three groups: factors driven by the surgical outcome, pre-existing factors relating to the patients psychology, appropriateness for surgery or expectation level, and factors driven by the patient’s recovery and their management during that recovery process. With consideration to the extensive variation between patients, it is reasonable to posit that addressing patient specific factors in selection for surgery, alignment of components during surgery and post-operative management may reduce the instance of post-operative dissatisfaction. The first goal of this thesis was to understand the variation of patient anatomy as it relates to standard practice in TKA. Following the finding of extensive variation, a bio-mechanical rigid body dynamics simulation of the knee joint was developed to determine the degree to which this variation was reflected in the kinematic behaviour of the implanted knees. Later studies showed extensive kinematic variation that was responsive to variation in the alignment of the components as well as well as significantly related to patient reported outcome. Later studies further investigated how outcome related to patient selection for surgery and recovery of the patient as measured with simple activity monitoring. From this work, a pre-operative simulation assessment tool has been developed, the Dynamic Knee Score (DKS), and paired with selection and recovery management tools forms the basis of 360 Knee Systems surgical planning and patient management, which has been used in over 3,000 primary TKA’s to date

The Association Between Soft Tissue Releases and Bony Resections Performed During Total Knee Arthroplasty and Patients\u27 Pain and Satisfaction Postoperatively

Total knee arthroplasty (TKA) is a surgical treatment of degenerative knee conditions such as osteoarthritis to reduce pain and increase function. Intraoperative soft tissue releases (STRs) and bony resections (BRs) are necessary for a balanced and aligned TKA. It is possible that the degree of STRs and BRs is related to final outcome following TKA and thus there may be implications for patient rehabilitation, patient expectations, pain medications, and timelines for recovery. Thus, our primary objective was to examine the association between the number of STRs and BRs performed intraoperatively and patients’ satisfaction and pain at three months. We performed an interim analysis on 100 patients who had undergone a TKA. Using multiple regression models, we showed no association between degree of releases and satisfaction or pain. These results were limited by sample size such that we are unable to make definitive conclusions about the relationship between STRs and BRs and outcome following TKA

A Novel Free Form Femoral Cutting Guide

Knee arthoplasty is a common procedure that requires the removal of damaged bone and cartilage from the distal femur so that a reconstructive implant may be installed. Traditionally, a five planar resection has been accomplished with a universal cutting box and navigated with either metal jigs or optically tracked computer navigation systems. Free form, or curved, resections have been made possible with surgical robots which control the resection pathway and serve as the navigation system. The free form femoral cutting guide serves as a non powered framework to guide a standard surgical drill along an anatomically defined pathway, resulting in the removal of distal femoral cartilage. It is fixed via attachment to a bone mounted base component, which is positioned with a patient specific jig. To operate, the surgeon slides the surgical drill along a pair of interlocked tracks. One track controls motion in the anteroposterior (AP) direction and one track controls motion in the mediolateral (ML) direction. Combining both motions results in the removal of cartilage from the area of the distal femur for unilateral or total knee arthoplasty

Master of Science

thesisTotal knee arthroplasty (TKA) is the gold-standard treatment for degenerative and arthritic knee diseases. TKA replaces the damaged knee articular surfaces with a prosthetic knee joint composed of a metal femoral component and polyethylene tibial insert. In 2013, approximately 650,000 primary TKA procedures were performed in the U.S., with approximately 10% requiring revision surgery necessitated by the 10 - 15 years limited lifetime of the prosthetic knee joint. A major limiting factor to the longevity of a prosthetic knee joint is fatigue crack damage of the tibial insert. The objective of this work is to address the problem of fatigue crack damage through: (1) experimentally quantifying fatigue crack damage in polyethylene tibial inserts and (2) predicting fatigue crack damage through finite element modeling. We have developed a novel subsurface fatigue crack damage measurement method based on specimen transillumination and used this method to measure fatigue crack damage in two tibial inserts. We have also developed a dynamic finite element simulation of the stress in the tibial insert under knee simulator wear test conditions, for an entire gait cycle. Two polyethylene material models, linear elastic and linear viscoelastic, were compared. It was observed that choice of material model has a substantial effect on the maximum von Mises stress. The location of maximum von Mises, principal, and shear stress in the tibial insert were compared to the experimentally measured fatigue crack damage to determine whether the simulation accurately predicts fatigue crack damage in the tibial insert. It was observed that the von Mises stress alone is a poor predictor of fatigue crack damage, while the locations of maximum tensile principal stress and shear stress correspond closely to the locations where fatigue crack damage occurred

AN AUTOMATED, DEEP LEARNING APPROACH TO SYSTEMATICALLY & SEQUENTIALLY DERIVE THREE-DIMENSIONAL KNEE KINEMATICS DIRECTLY FROM TWO-DIMENSIONAL FLUOROSCOPIC VIDEO

Total knee arthroplasty (TKA), also known as total knee replacement, is a surgical procedure to replace damaged parts of the knee joint with artificial components. It aims to relieve pain and improve knee function. TKA can improve knee kinematics and reduce pain, but it may also cause altered joint mechanics and complications. Proper patient selection, implant design, and surgical technique are important for successful outcomes. Kinematics analysis plays a vital role in TKA by evaluating knee joint movement and mechanics. It helps assess surgery success, guides implant and technique selection, informs implant design improvements, detects problems early, and improves patient outcomes. However, evaluating the kinematics of patients using conventional approaches presents significant challenges. The reliance on 3D CAD models limits applicability, as not all patients have access to such models. Moreover, the manual and time-consuming nature of the process makes it impractical for timely evaluations. Furthermore, the evaluation is confined to laboratory settings, limiting its feasibility in various locations. This study aims to address these limitations by introducing a new methodology for analyzing in vivo 3D kinematics using an automated deep learning approach. The proposed methodology involves several steps, starting with image segmentation of the femur and tibia using a robust deep learning approach. Subsequently, 3D reconstruction of the implants is performed, followed by automated registration. Finally, efficient knee kinematics modeling is conducted. The final kinematics results showed potential for reducing workload and increasing efficiency. The algorithms demonstrated high speed and accuracy, which could enable real-time TKA kinematics analysis in the operating room or clinical settings. Unlike previous studies that relied on sponsorships and limited patient samples, this algorithm allows the analysis of any patient, anywhere, and at any time, accommodating larger subject populations and complete fluoroscopic sequences. Although further improvements can be made, the study showcases the potential of machine learning to expand access to TKA analysis tools and advance biomedical engineering applications

On the quantification and objective classification of instability in the healthy, osteoarthritic and prosthetic knee

Knee instability is a common complaint in osteoarthritis (OA), and a common reason for revision following total knee arthroplasty (TKA). Despite this, assessment of instability is hampered by the lack of a validated method of objective classification or quantification, with most research relying upon patient reports of frequency of symptoms. The aim of this thesis is to define a theoretical framework for instability in the knee, and to develop a protocol for the classification and quantification of instability in the native and prosthetic knee. Instability of the knee in this thesis is understood as the failure of the joint to return to a zero-state following perturbation using all the available active and passive mechanisms available to it, resulting in system collapse. Symptomatic instability is the awareness of reaching the boundary between the stable and unstable state. The prevalence of subjective instability in the end stage OA knee was measured from a publicly available database of pre-operative knee scores from TKA patients, while the prevalence of instability as a cause of revision was assessed from case note review of TKA revision patients from a tertiary referral orthopaedic unit. A single channel, tibia mounted accelerometer was selected for assessment of frontal plane knee movement during normal walking and a protocol developed its use. This was assessed for its repeatability and compared with standard gait analysis in healthy volunteers, and subjectively stable and unstable post-operative TKA patients. Found to be repeatable with differentiation of output between subjectively stable and unstable TKA, the protocol was adapted and used to compare subjectively stable and unstable OA knees prior to TKA. Using patient subjective assessment as classifier, wavelet transforms, Principal Component Analysis and linear regression was used to produce a classification model from the accelerometer data. The single accelerometer was found to produce classification with an accuracy of 84.6%, sensitivity of 93.3% and specificity of 72.7%, with area under the curve (AUC) of 0.797. This classification model for instability produces the basis from which the protocol can be adapted and developed to improve performance and ultimate quantify instability in the knee for use in clinical and research settings.Knee instability is a common complaint in osteoarthritis (OA), and a common reason for revision following total knee arthroplasty (TKA). Despite this, assessment of instability is hampered by the lack of a validated method of objective classification or quantification, with most research relying upon patient reports of frequency of symptoms. The aim of this thesis is to define a theoretical framework for instability in the knee, and to develop a protocol for the classification and quantification of instability in the native and prosthetic knee. Instability of the knee in this thesis is understood as the failure of the joint to return to a zero-state following perturbation using all the available active and passive mechanisms available to it, resulting in system collapse. Symptomatic instability is the awareness of reaching the boundary between the stable and unstable state. The prevalence of subjective instability in the end stage OA knee was measured from a publicly available database of pre-operative knee scores from TKA patients, while the prevalence of instability as a cause of revision was assessed from case note review of TKA revision patients from a tertiary referral orthopaedic unit. A single channel, tibia mounted accelerometer was selected for assessment of frontal plane knee movement during normal walking and a protocol developed its use. This was assessed for its repeatability and compared with standard gait analysis in healthy volunteers, and subjectively stable and unstable post-operative TKA patients. Found to be repeatable with differentiation of output between subjectively stable and unstable TKA, the protocol was adapted and used to compare subjectively stable and unstable OA knees prior to TKA. Using patient subjective assessment as classifier, wavelet transforms, Principal Component Analysis and linear regression was used to produce a classification model from the accelerometer data. The single accelerometer was found to produce classification with an accuracy of 84.6%, sensitivity of 93.3% and specificity of 72.7%, with area under the curve (AUC) of 0.797. This classification model for instability produces the basis from which the protocol can be adapted and developed to improve performance and ultimate quantify instability in the knee for use in clinical and research settings

Patient-Specific Implants in Musculoskeletal (Orthopedic) Surgery

Most of the treatments in medicine are patient specific, aren’t they? So why should we bother with individualizing implants if we adapt our therapy to patients anyway? Looking at the neighboring field of oncologic treatment, you would not question the fact that individualization of tumor therapy with personalized antibodies has led to the thriving of this field in terms of success in patient survival and positive responses to alternatives for conventional treatments. Regarding the latest cutting-edge developments in orthopedic surgery and biotechnology, including new imaging techniques and 3D-printing of bone substitutes as well as implants, we do have an armamentarium available to stimulate the race for innovation in medicine. This Special Issue of Journal of Personalized Medicine will gather all relevant new and developed techniques already in clinical practice. Examples include the developments in revision arthroplasty and tumor (pelvic replacement) surgery to recreate individual defects, individualized implants for primary arthroplasty to establish physiological joint kinematics, and personalized implants in fracture treatment, to name but a few

The Effect of Robotic Technology on Perioperative Outcomes in Total Knee Arthroplasty

Introduction Robotic technology has recently regained momentum in total knee arthroplasty (TKA) but the effects of this technology on accuracy of implant positioning, intraoperative soft tissue injury and postoperative functional rehabilitation remain unknown. The objectives of this research thesis were to compare a comprehensive range of radiological objectives and perioperative outcomes in conventional jig-based TKA versus robotic-arm assisted TKA, and use optical motion capture technology to quantify the effects of anterior cruciate ligament (ACL) and posterior cruciate ligament (PCL) resection on knee biomechanics. Methods A series of prospective cohort studies were undertaken in patients with established knee osteoarthritis undergoing primary conventional jig-based TKA versus robotic-arm assisted TKA. Predefined radiological and perioperative study outcomes were recorded by independent observers. Optical motion capture technology during robotic TKA was used to quantify the effects of ACL and PCL resection on knee biomechanics. Results Robotic-arm assisted TKA was associated with improved accuracy of implant positioning, reduced periarticular soft tissue injury, decreased bone trauma, improved postoperative functional rehabilitation, and reduced early systemic inflammatory response compared to conventional jig-based TKA. The Macroscopic Soft Tissue Injury (MASTI) classification system was developed and validated for grading intraoperative periarticular soft tissue injury and bone trauma during TKA. ACL resection created flexion-extension mismatch by increasing the extension gap more than the flexion gap, whilst PCL resection increased the flexion gap proportionally more than the extension gap and created mediolateral laxity in knee flexion but not in extension. Conclusion Robotic-arm assisted TKA was associated with increased accuracy of implant positioning, reduced iatrogenic soft tissue injury, and improved functional rehabilitation compared to conventional jig-based TKA. ACL and PCL resections created unique changes in knee biomechanics that affected flexion-extension gaps and mediolateral soft tissue tension during TKA. On the basis of this thesis, further clinical trials have been established to determine the long-term clinical significance of these findings