The aim of this study was to compare the clinical outcomes of robotic arm-assisted bi-unicompartmental knee arthroplasty (bi-UKA) with conventional mechanically aligned total knee arthroplasty (TKA) during the first six weeks and at one year postoperatively. A per protocol analysis of 76 patients, 43 of whom underwent TKA and 34 of whom underwent bi-UKA, was performed from a prospective, single-centre, randomized controlled trial. Diaries kept by the patients recorded pain, function, and the use of analgesics daily throughout the first week and weekly between the second and sixth weeks. Patient-reported outcome measures (PROMs) were compared preoperatively, and at three months and one year postoperatively. Data were also compared longitudinally and a subgroup analysis was conducted, stratified by preoperative PROM status.Aims
Methods
The aim of this study was to compare robotic arm-assisted bi-unicompartmental knee arthroplasty (bi-UKA) with conventional mechanically aligned total knee arthroplasty (TKA) in order to determine the changes in the anatomy of the knee and alignment of the lower limb following surgery. An analysis of 38 patients who underwent TKA and 32 who underwent bi-UKA was performed as a secondary study from a prospective, single-centre, randomized controlled trial. CT imaging was used to measure coronal, sagittal, and axial alignment of the knee preoperatively and at three months postoperatively to determine changes in anatomy that had occurred as a result of the surgery. The hip-knee-ankle angle (HKAA) was also measured to identify any differences between the two groups.Aims
Methods
The objective of this study was to compare differences in alignment following robotic arm-assisted bi-unicompartmental knee arthroplasty (Bi-UKA) and conventional total knee arthroplasty (TKA). This was a prospective, randomised controlled trial of 70 patients. 39 TKAs were implanted manually, as per standard protocol at our institution, and 31 Bi-UKA patients simultaneously received fixed-bearing medial and lateral UKAs, implanted using robotic arm-assistance. Preoperative and 3-month postoperative CT scans were analysed to determine hip knee ankle angle (HKAA), medial distal femoral angle (MDFA), and medial proximal tibial angle (MPTA). Analysis was repeated for 10 patients by a second rater to validate measurement reliability by calculating the intra-class correlation coefficient (ICC). Mean change in HKAA towards neutral was 2.7° in TKA patients and 2.3° in Bi-UKA patients (P=0.6). Mean change in MDFA was 2.5° for TKA and 1.0° for Bi-UKA (P<0.01). Mean change in MPTA was 3.7° for TKA and 0.8° for Bi-UKA (P<0.01). Mean postoperative MDFA and MPTA for TKAs were 89.8° and 89.6° respectively, indicating orientation of femoral and tibial components perpendicular to the mechanical axis. Mean postoperative MDFA and MPTA for Bi-UKAs were 91.0° and 86.9° respectively, indicating a more oblique joint line orientation. Inter-rater agreement was excellent (ICC>0.99). Early functional activities, according to the new Knee Society Scoring System, favoured Bi-UKAs (P<0.05). Robotic arm-assisted, cruciate-sparing Bi-UKA better maintains the natural anatomy of the knee in the coronal plane and may therefore preserve normal joint kinematics, compared to a mechanically aligned TKA. This has been achieved without significantly altering overall HKAA.
Over the last decade Computer Assisted Orthopaedic Surgery (CAOS) has emerged particularly in the area of minimally invasive Unicompartmental Knee Replacement (UKR) surgery. Image registration is an important aspect in all computer assisted surgeries which is a process of developing a spatial relationship between pre-operative data, such as Computerised Tomography (CT) scans or Magnetic Resonance Imaging (MRI) scans and the physical patient in the operation theatre. It allows the surgeon to visualise the 3D pre-operative scan data in-relation to the patient's anatomy in the operating theatre. Current image registration techniques for CAOS in minimally invasive UKR are achieved by digitising points on the articulating surface of the knee joint using a navigated probe. By using these digitised points a rigid body is formed which is then fitted to the pre-operative scan data using a best fit type minimisation. However, this manual digitisation approach is time consuming and often takes 15–20 minutes and is therefore costly. The rationale for this study was to develop a new, quick, cost effective, contactless shape acquisition technique which could produce an accurate rigid body model in theatre from the ends of the exposed bones using 3D scans taken intra-operatively by a Laser Displacement Sensor. Bespoke and automated 3D laser scanning techniques based on DAVID-Laserscanner have been developed and were used to scan surface geometry of the knee joint in 10 cadaveric legs. The Medial compartments of 9 joints had undergone a UKR procedure post donation but the lateral compartments were unaffected. The 9 legs were CT scanned and then segmented using Mimics 12.01 to generate 3D models of the medial compartments. The 10 legs were also MRI scanned using a 3D FLASH technique to produce 3D models of the lateral articular cartilage. All the samples were then 3D Laser scanned using a tailored plane-less technique and customised positioner assemblies. The CT and MRI generated 3D models were then registered with the corresponding 3D Laser scans in the Geomagic Qualify® package using manual surface registration. This is a type of surface (point based registration or free-form surface matching) registration which works closely on Iterative closest point (ICP) algorithm. Once the models were registered, a best fit alignment was performed between two datasets. Results indicate average best fit alignment errors and standard deviations ranging from 0.2 mm to 0.9 mm with errors normally distributed. Most of the errors could be attributed to calibration errors, segmentation errors and post-processing systematic errors. We have demonstrated the feasibility of using a novel laser scanning technique where by acquiring multiple scans of the tibio-femoral joint in theatre, complete 3D models of the geometry and surface texture can be developed which can be registered with the pre-operative scan. The overall time for scanning, post-processing and the registration requires less than 5 minutes and is a non-invasive, cost-efficient approach. This study has provided proof of concept for a new automated registration technique with the potential for providing a quantitative assessment of the articular cartilage integrity during lower limb arthroplasty.
