Advertisement for orthosearch.org.uk
Results 1 - 3 of 3
Results per page:
Applied filters
General Orthopaedics

Include Proceedings
Dates
Year From

Year To
Orthopaedic Proceedings
Vol. 99-B, Issue SUPP_4 | Pages 80 - 80
1 Feb 2017
Van Haver A Kolk S DeBoodt S Valkering K Verdonk P
Full Access

Introduction

Accurate placement of total knee arthroplasty (TKA) components is critical for obtaining good long-term clinical outcome. Several contemporary CT- or MRI-based technologies allow surgeons to pre-plan TKA and translate that planning into the operating room. To evaluate TKA component placement, post-operative CT or MRI scans allow comprehensive 3D measurements. However, these are expensive and difficult to obtain in large numbers, and yield an additional radiation dose to the patient (in case of CT). A potential solution to overcome these hurdles exists in using 2D/3D registration techniques. In this technique, a new tool (the X-ray Module, Mimics®, Materialise NV) is used to align one or more post-operative X-rays with the preoperative CT- or MRI-based 3D planning (Figure 1). The aim of this study was to determine the accuracy of this 2D/3D registration technique for determining 3D position of TKA implant components postoperatively.

Materials and Methods

A TKA was performed in six human cadaver legs. A CT scan was acquired preoperatively and the bones were segmented using Mimics® to obtain 3D bone models. Post-operatively, a high-resolution CT scan with minimization of metal scatters was acquired and bones and implant components were segmented in Mimics® to obtain the ground truth for their relative position. To apply the novel X-ray based post-op analysis, conventional anteroposterior and lateral radiographs were obtained. The accuracy of the X-ray tool was determined by calculating the angles (varus/valgus, flexion/extension, external/internal rotations) and the distances (anterior/posterior, proximal/distal, medial/lateral) between the centers of gravity of the implants from the X-ray based method and the CT-based ground truth in the anatomical coordinate system of the bone. X-ray based alignment was assessed by an orthopedic surgeon (3 repetitions) and Bland-Altman plots were created to visualize the differences between the ground truth and the X-ray based assessment of the implant position.


Orthopaedic Proceedings
Vol. 98-B, Issue SUPP_2 | Pages 101 - 101
1 Jan 2016
Vigneron L Delport H Khairul A Kobayashi T DeBoodt S
Full Access

Introduction

A full 3D postoperative analysis, i.e. a quantitative comparison between planned and postoperative positions of bone(s) and implant(s) in 3D, is necessary for a thorough assessment of the outcome of the surgery, as well as to provide information that could be used to optimize similar procedures in the future. In this work, we present a method of postoperative analysis based on a pair of X-ray images only, which reaches a level of accuracy that is comparable with the results obtained with a 3D postoperative image.

Methods

The method consists in using 3D models of bones, segmented from 3D preoperative image (e.g. CT or MRI scans), and 3D models of implant, and aligning them independently to X-rays by matching contours manually drawn on the X-rays and projected contours. The result gives the relative postoperative position of bone and implant. The method was tested on a phantom consisting of commonly available femoral knee implant on a physical model of a femur (Sawbones®). Result was compared to the optical scan, considered as ground truth, of the implanted saw bone. Two studies were performed: inter-operator (six operators), and intra-operator (5 tests). In addition, the inter-operator study was repeated while asking all the operators to use the same pre-drawn contours. The results are presented by calculating the distance (anterior/posterior, proximal/distal, medial/lateral) between the centers of gravity, and the angles (varus/valgus, flexion/extension, external/internal rotations) of the implants from the X-ray based method and the ground truth.

Results were also compared with the relative position of bone and implant extracted from a 3D CT postoperative image. Saw bone and implant were first segmented from this image. In order to determine the position of the implant, despite the metal artefacts in the CT images, the 3D model of the implant was registered on the segmented implant.

All processing, including segmentation, registration of X-rays, and measurements, was performed using Mimics Innovation Suite 17.0 ®.


Orthopaedic Proceedings
Vol. 95-B, Issue SUPP_34 | Pages 116 - 116
1 Dec 2013
Lawrenchuk M Vigneron L DeBoodt S
Full Access

With the increasing use of 3D medical imaging, it is possible to analyze 3D patient anatomy to extract features, trends and population specific shape information. This is applied to the development of ‘standard implants’ targeted to specific population groups.

INTRODUCTION

Human beings are diverse in their physical makeup while implants are often designed based on some key measurements taken from the literature or a limited sampling of patient data. The different implant sizes are often scaled versions of the ‘average’ implant, although in reality, the shape of anatomy changes as a function of the size of patient. The implant designs are often developed based on a certain demographic and ethnicity and then, simply applied to others, which can result in poor design fitment [1]. Today, with the increasing use of 3D medical imaging (e.g. CT or MRI), it is possible to analyze 3D patient anatomy to extract features, trends and population specific shape information. This can be applied to the development of new ‘standard implants’ targeted to a specific population group [2].

PATIENTS & METHODS

Our population analysis was performed by creating a Statistical Shape Model (SSM) [3] of the dataset. In this study, 40 full Chinese cadaver femurs and 100 full Caucasian cadaver femurs were segmented from CT scans using Mimics®. Two different SSMs, specific to each population, were built using in-house software tools. These SSMs were validated using leave-one-out experiments, and then analyzed and compared in order to enhance the two population shape differences.