PATIENT-SPECIFIC FINITE ELEMENT MODELS OF THE TOTAL HIP FOR COMPUTER-ASSISTED SURGERY AND BONE DENSITOMETRY WITH REDUCED COMPUTED TOMOGRAPHY RADIATION EXPOSURE

Abstract

In recent years, some attempts have been made to develop a method that generates finite element (FE) models of the femur and pelvis using CT. However, due to the complex bone geometry, most of these methods require an excessive amount of CT radiation dosage. Here we describe a method for generating accurate patient-specific FE models of the total hip using a small number of CT scans in order to reduce radiation exposure.

A previously reported method for autogenerating patient-specific FE models of the femur was extended to include the pelvis. CT osteodensitometry was performed on 3 patients who had hip replacement surgery and patient-specific FE models of the total hip were generated. The pelvis was generated with a new technique that incorporated a mesh morphing method called ‘host mesh fitting’. It used an existing generic mesh and then morphed it to reflect the patient specific geometry. This can be used to morph the whole pelvis, but our patient dataset was limited to the acetabulum. An algorithm was developed that automated all the procedures involved in the fitting process.

Average error between the fitted mesh and patient specific data sets for the femur was less than 1mm. The error for the pelvis was about 2.5mm. This was when a total 18 CT scans with 10mm gap were used – 12 of the femur, and 6 of the pelvis. There was no element distortion and a smooth element surface was achieved.

Previously, we reported a new method for automatically generating a FE model of the femur with as few CT scans as possible. Here we describe a technique that customizes a generic pelvis mesh to patient-specific data sets. Thus we have developed a novel hybrid technique which can generate an accurate FE model of the total hip using significantly less CT scans.

An automated method of generating FE models for the total hip with reduced CT radiation exposure will be a valuable clinical tool for surgeons.