PURPOSE

To validate the efficacy and accuracy of a novel patient specific guide (PSG) and instrumentation system that enables minimally invasive (MI) short stemmed total shoulder arthroplasty (TSA).

Patient Specific Instruments (PSIs) are becoming increasingly common in arthroplasty but have only been used with highly invasive surgical approaches that can result in significant complications. We have previously described a novel PSI for minimally invasive total shoulder arthroplasty and shown that it can accurately guide the creation of guide holes in the humerus and scapula. However, conducting shoulder replacement in a minimally invasive environment precludes the use of traditional instruments. In this work, we describe and evaluate the efficacy of a set of novel instruments that, in conjunction with our PSIs, enable accurate minimally invasive total shoulder arthroplasty to be achieved for the first time.

The key components of this surgical procedure are: 1) a new minimally invasive posterior surgical approach that avoids the need for muscle transection; 2) a novel PSI that enables accurate guide tunnels to be simultaneously created in the humerus and scapula using a c- shaped drill guide that mates to the PSI; 3) a custom humeral head resection guide that uses the humeral guide tunnel; 4) a novel reamer and 3D metal printed gear mechanism for radial displaced drilling both powered by a central driver placed through the humeral head; and 5) custom impactors for glenoid and humeral implantation – the latter is achieved using a modular slap hammer that is guided by the central humeral drill hole. Accuracy of this system was assessed at each surgical step using an optical tracking camera and an iterative closest point registration method to map measurements to the pre-operative plan.

The accuracy results for the physical PSI registration and guide hole drilling were found to be in line with our previously reported results: the intra-articular guide hole locations were 2.2mm and 3.9mm for the humerus and glenoid with angular errors of 2.8° and 8°, respectively. After humeral resection, the humeral cut plane had an angular error of 10.1°. The final humeral implant location had an error of 12.1° and 1.9mm. For the glenoid implant, the positional error was 3.8mm with angular errors of 3.3° ante-retroversion and 8.6° supero- inferior inclination.

We believe that these initial results demonstrate that this minimally invasive PSI and instrumentation system can accurately guide total shoulder replacement while avoiding the complications of open surgery. A full cadaveric testing series is currently being completed.

In robot-assisted orthopaedic surgery, registration is a key step, which defines the position of the patient in the robot frame so that the preoperative plan can be performed. Current registration methods have their limitations, such as the requirement of immobilisation of the limbs or the line of sight (LOS) issues. These issues cause inconvenience for the surgeons and interrupt the surgical workflow in the operating room.

Targetting these issues of current registration methods, we propose a camera-robot registration system for joint replacement. The bone geometry, which is measured directly by a depth camera, is aligned to a preoperatively obtained bone model to calculate the pose of the target. Simultaneously, in order to avoid registration failure caused by LOS interruptions, the depth camera tracks objects that may occlude the target bone, and a robot manipulator is used to move the camera away from the nearest obstacle. The optimal camera motion is calculated based on the position and velocity of the obstacle, which avoids the occlusion efficiently without changing the target position in the camera frame. Inverse kinematics of the robot is used to project the Cartesian velocity of the end-effector into the joint space, with kinematic singularities considered for stable robotic control. An admittance controller is designed as the human-robot interface so that the surgeon can directly set the robot configuration by hand according to the actual environment.

Simulations and experiments were conducted to test the performance. The results show that the proposed obstacle avoidance method can effectively increase the distance between the obstacle and the LOS, which lowers the risk of registration failure due to obstacle occlusion. This pilot study is promising in reducing distractions to the surgeon and can help achieve a fluent and surgeon-centred workflow.

Introduction

There is little information available to surgeons regarding how the lateral soft-tissue structures prevent instability in knees implanted with total knee arthroplasty (TKA). The aim of this study was to quantify the lateral soft-tissue contributions to stability following cruciate retaining (CR) TKA.

Introduction

We report 10-year clinical outcomes of a prospective randomised controlled study on uni-compartmental knee arthroplasty using an active constraint robot.

Measuring the clinical impact of CAOS systems has generally been based around surrogate radiological measures with currently few long-term functional follow-up studies reported. We present 10 year clinical follow up results of robotic vs conventional surgery in UKA.

Background

Total Shoulder Arthroplasty (TSA) has been shown to improve the function and pain of patients with severe degeneration. Recently, TSA has been of interest for younger patients with higher post-operative expectations; however, they are treated using traditional surgical approaches and techniques, which, although amenable to the elderly population, may not achieve acceptable results with this new demographic. Specifically, to achieve sufficient visualization, traditional TSA uses the highly invasive deltopectoral approach that detaches the subscapularis, which can significantly limit post-operative healing and function. To address these concerns, we have developed a novel surgical approach, and guidance and instrumentation system (for short-stemmed/stemless TSA) that minimize muscle disruption and aim to optimize implantation accuracy.

In computer assisted orthopaedic surgery, intraoperative registration is commonly performed by fitting features acquired from the exposed bone surface to a preoperative virtual model of the bone geometry. In cases where the acquired spatial measurements are unreliable or have been inappropriately chosen, the registration result can degenerate. Current performance indicators, such as the root mean squared (RMS) error and the spatial distribution of the registered feature errors may not be sufficient to warn the surgeon of such a case.

In this study, statistical analysis is applied to the registration outcomes of perturbed variants of a collected point set. In this way, it is possible to assess the ability of the original set to represent the underlying surface, taking into account the distribution of the points as well as errors introduced during the acquisition process. Confidence measures are calculated to predict the reliability of the original registration result and therefore the robustness of the point set itself.

For proof of concept, this method has been tested in simulation with a CT-generated tibia model. The algorithm was used to identify the 10 best performing of a population of 1000 randomly generated point sets. All registration outcomes produced by these point sets were found to be superior to those resulting from sets of the same size produced manually using an optimised point-acquisition protocol. Preliminary results suggest that this method, alongside the standard RMS and residual point error distribution, may be used to provide the surgeon with a reliable indication of registration outcome in the operating room.