Introduction

The current methods for measuring femoral torsion have limitations, including variability and inaccuracies. Existing 3D methods are not reliable for abnormal femoral anteversion measurement. A new 3D method is needed for accurate measurement and planning of proximal femoral osteotomies. Currently available software for viewing and modelling CT data lacks measurement capabilities. The MSK Hip planner aims to address these limitations by combining measurement, planning, and analysis functionalities into one tool. We aim to answer 5 key questions: Is there a difference between 2D measurement methods? Is there a difference between 3D measurement methods? Is there a difference between 2D and 3D measurement methods? Are any of the measurement methods affected by the presence of osteoarthritis or a CAM deformity?

Introduction

Bernese periacetabular osteotomy (PAO) repositions the acetabulum to increase femoral head coverage (FHC) in hip dysplasia. Currently, there is a paucity of objective peri-operative metrics to plan for optimal acetabular fragment repositioning. The MSk Lab Hip 3D Planner (MSkL-HP) measures acetabular morphology and simulates PAO cuts to achieve optimal FHC. We evaluated how adjusting location and orientation of cutting planes can alter FHC.

Tibial bone density may affect implant stability and functional outcomes following total knee replacement (TKR). Our aim was to characterise the bone density profile at the implant-tibia interface following TKR in mechanical versus kinematic alignment. Pre-operative computed tomography scans for 10 patients were obtained. Using surgical planning software, tibial cuts were made for TKR either neutral (mechanical) or 3 degrees varus (kinematic) alignment. Signal intensity, in Hounsfield Units (HU), was measured at 25,600 points throughout an axial slice at the implant-tibia interface and density profiles compared along defined radial axes from the centre of the tibia towards the cortices. From the tibial centre towards the lateral cortex, trabecular bone density for kinematic and mechanical TKR are similar in the inner 50% but differ significantly beyond this (p= 0.012). There were two distinct density peaks, with peak trabecular bone density being higher in kinematic TKR (p<0.001) and peak cortical bone density being higher in mechanical TKR (p<0.01). The difference in peak cortical to peak trabecular signal was 43 HU and 185 HU respectively (p<0.001). On the medial side there was no significant difference in density profile and a linear increase from centre to cortex. In the lateral proximal tibia, peak cortical and peak trabecular bone densities differ between kinematic TKR and mechanical TKR. Laterally, mechanical TKR may be more dependent upon cortical bone for support compared to kinematic TKR, where trabecular bone density is higher. This may have implications for surgical planning and implant design.

Trochlear geometry of modern femoral implants is designed for mechanical alignment (MA) technique for TKA. The biomechanical goal is to create a proximalised and more valgus trochlea to better capture the patella and optimize tracking. In contrast, Kinematic alignment (KA) technique for TKA respects the integrity of the soft tissue envelope and therefore aims to restore native articular surfaces, either femoro-tibial or femoro-patellar. Consequently, it is possible that current implant designs are not suitable for restoring patient specific trochlea anatomy when they are implanted using the kinematic technique, this could cause patellar complications, either anterior knee pain, instability or accelerated wear or loosening. The aim of our study is therefore to explore the extent to which native trochlear geometry is restored when the Persona^®implant (Zimmer, Warsaw, USA) is kinematically aligned.

A retrospective study of a cohort of 15 patients with KA-TKA was performed with the Persona^®prosthesis (Zimmer, Warsaw, USA). Preoperative knee MRIs and postoperative knee CTs were segmented to create 3D femoral models. MRI and CT segmentation used Materialise Mimics and Acrobot Modeller software, respectively. Persona^®implants were laser scanned to generate 3D implant models. Those implant models have been overlaid on the 3D femoral implant model (generated via segmentation of postoperative CTs) to replicate, in silico, the alignment of the implant on the post-operative bone and to reproduce in the computer models the features of the implant lost due to CT metal artefacts. 3D models generated from post-operative CT and pre-operative MRI were registered to the same coordinate geometry. A custom written planner was used to align the implant, as located on the CT, onto the pre-operative MRI based model. In house software enabled a comparison of trochlea parameters between the native trochlea and the performed prosthetic trochlea. Parameters assessed included 3D trochlear axis and anteroposterior offset from medial facet, central groove, and lateral facet. Sulcus angle at 30% and 40% flexion was also measured. Inter and intra observer measurement variabilities have been assessed.

Varus-valgus rotation between the native and prosthetic trochleae was significantly different (p<0.001), with the prosthetic trochlear groove being on average 7.9 degrees more valgus. Medial and lateral facets and trochlear groove were significantly understuffed (3 to 6mm) postoperatively in the proximal two thirds of the trochlear, with greatest understuffing for the lateral facet (p<0.05). The mean medio-lateral translation and internal-external rotation of the groove and the sulcus angle showed no statistical differences, pre and postoperatively.

Kinematic alignment of Persona^®implants poorly restores native trochlear geometry. Its clinical impact remains to be defined.

Conventional TKA surgery attempts to restore patients to a neutral alignment, and devices are designed with this in mind. Neutral alignment may not be natural for many patients, and may cause dissatisfaction. To solve this, kinematical alignment (KA) attempts to restore the native pre-arthritic joint-line of the knee, with the goal of improving knee kinematics and therefore patient's function and satisfaction.

Proper prosthetic trochlea alignment is important to prevent patella complications such as instability or loosening. However, available TKA components have been designed for mechanical implantation, and concerns remain relating the orientation of the prosthetic trochlea when implants are kinematically positioned. The goal of this study is to investigate how a currently available femoral component restores the native trochlear geometry of healthy knees when virtually placed in kinematic alignment.

The healthy knee OAI (Osteoarthritis Initiative) MRI dataset was used. 36 MRI scans of healthy knees were segmented to produce models of the bone and cartilage surfaces of the distal femur. A set of commercially available femoral components was laser scanned. Custom 3D planning software aligned these components with the anatomical models: distal and posterior condyle surfaces of implants were coincident with distal and posterior condyle surfaces of the cartilage; the anterior flange of the implant sat on the anterior cortex; the largest implant that fitted with minimal overhang was used, performing ‘virtual surgery’ on healthy subjects.

Software developed in-house fitted circles to the deepest points in the trochlear grooves of the implant and the cartilage. The centre of the cartilage trochlear circle was found and planes, rotated from horizontal (0%, approximately cutting through the proximal trochlea) through to vertical (100%, cutting through the distal trochlea) rotated around this, with the axis of rotation parallel to the flexion facet axis. These planes cut through the trochlea allowing comparison of cartilage and implant surfaces at 1 degree increments. Trochlear groove geometry was quantified with (1) groove radial distance from centre of rotation cylinder (2) medial facet radial distance (3) lateral facet radial distance and (4) sulcus angle, along the length of the trochlea. Data were normalised to the mean trochlear radius. The orientation of the groove was measured in the coronal and axial plane relative to the flexion facet axis. Inter- and intra-observer reliability was measured.

In the coronal plane, the implant trochlear groove was oriented a mean of 8.7° more valgus (p<0.001) than the normal trochlea. The lateral facet was understuffed most at the proximal groove between 0–60% by a mean of 5.3 mm (p<0.001). The medial facet was understuffed by a mean of 4.4 mm between 0–60% (p<0.001).

Despite attempts to design femoral components with a more anatomical trochlea, there is significant understuffing of the trochlea, which could lead to reduced extensor moment of the quadriceps and contribute to patient dissatisfaction.

The accurate positioning of the total knee arthroplasty affects the survival of the implants(1). Alignment of the femoral component in relation to the native knee is best determined using pre- and post-operative 3D-CT reconstruction(2). Currently, the scans are visualised on separate displays. There is a high inter- and intra-observer variability in measurements of implant rotation and translation(3). Correct alignment is required to allow a direct comparison of the pre- and post-operative surfaces. This is prevented by the presence of the prostheses, the bone shape alteration around the implant, associated metal artefacts, and possibly a segmentation noise.

The aim is to create a novel method to automatically register pre- and post-operative femora for the direct comparison of the implant and the native bone.

The concept is to use post-operative femoral shaft segments free of metal noise and of surgical alteration for alignment with the pre-operative scan. It involves three steps. Firstly, using principal component analysis, the femoral shafts are re-oriented to match the X axis. Secondly, variants of the post-operative scan are created by subtracting 1mm increments from the distal femoral end. Thirdly, an iterative closest point algorithm is applied to align the variants with the pre-operative scan.

For exploratory validation, this algorithm was applied to a mesh representing the distal half of a 3D scanned femur. The mesh of a prosthesis was blended with the femur to create a post-operative model. To simulate a realistic environment, segmentation and metal artefact noise were added. For segmentation noise, each femoral vertex was translated randomly within +−1mm,+−2mm,+−3mm along its normal vector. To create metal artefact random noise was added within 50 mm of the implant points in the planes orthogonal to the shaft. The alignment error was considered as the average distance between corresponding points which are identical in pre- and post-operative femora.

These preliminary results obtained within a simulated environment show that by using only the native parts of the femur, the algorithm was able to automatically register the pre- and post-operative scans even in presence of the implant. Its application will allow visualisation of the scans on the same display for the direct comparison of the perioperative scans.

This method requires further validation with more realistic noise models and with patient data. Future studies will have to determine if correct alignment has any effect on inter- and intra-observer variability.