CUED Publications database

An exploratory study into measuring the cortical bone thickness from CT in the presence of metal implants.

Whitmarsh, T and Treece, GM and Gee, AH and Poole, KES (2017) An exploratory study into measuring the cortical bone thickness from CT in the presence of metal implants. Int J Comput Assist Radiol Surg.

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Abstract

PURPOSE: The aim of this study was to develop and evaluate a method for measuring the cortical bone thickness from computed tomography (CT) scans with metallic implants and to assess the benefits of metal artefact removal software. METHODS: A previously validated technique based on the fitting of a cortical model was modified to also model metal structures when required. Cortical thickness measurements were taken over intact bone segments and compared with the corresponding contralateral bone segment. The evaluation dataset includes post-operative CT scans of a unipolar hemi-arthroplasty, a dynamic hip screw fixation, a bipolar hemi-arthroplasty, a fixation with cannulated screws and a total hip arthroplasty. All CT scans were analysed before and after processing with metal artefact removal software. RESULTS: Cortical thickness validity and accuracy were improved through the use of a modified metalwork-optimised model and metal artefact removal software. For the proximal femoral segments of the aforementioned cases, the cortical thickness was measured with a mean absolute error of 0.55, 0.39, 0.46, 0.53 and 0.69 mm. The hemi-pelvis produced thickness errors of 0.51, 0.52, 0.52, 0.47 and 0.67 mm, respectively. CONCLUSIONS: The proposed method was shown to measure cortical bone thickness in the presence of metalwork at a sub-millimetre accuracy. This new technique might be helpful in assessing fracture healing near implants or fixation devices, and improve the evaluation of periprosthetic bone after hip replacement surgery.

Item Type: Article
Uncontrolled Keywords: Computed tomography Cortical thickness Hip implants Metal artefact removal
Subjects: UNSPECIFIED
Divisions: Div F > Machine Intelligence
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:08
Last Modified: 29 Aug 2017 01:16
DOI: