%0 Journal Article %T Analyzing bone remodeling patterns after total hip arthroplasty using quantitative computed tomography and patient-specific 3D computational models %A Arachchi, Shanika %A Pitto, Rocco P. %A Anderson, Iain A. %A Shim, Vickie B. %J Quantitative Imaging in Medicine and Surgery %D 2015 %B 2015 %9 %! Analyzing bone remodeling patterns after total hip arthroplasty using quantitative computed tomography and patient-specific 3D computational models %K %X Background: Computational models in the form of finite element analysis technique that incorporates bone remodeling theories along with DEXA scans has been extensively used in predicting bone remodeling patterns around the implant. However, majority of such studies used generic models. Therefore, the aim of this study is to develop patient-specific finite element models of total hip replacement patients using their quantitative computed tomography (QCT) scans and accurately analyse bone remodelling patterns after total hip arthroplasty (THA). Methods: Patient-specific finite element models have been generated using the patients’ QCT scans from a previous clinical follow-up study. The femur was divided into five regions in proximal-distal direction and then further divided into four quadrants for detailed analysis of bone remodeling patterns. Two types of analysis were performed—inter-patient and intra patient to compare them and then the resulting bone remodeling patterns were quantitatively analyzed. Results: Our results show that cortical bone density decrease is higher in diaphyseal region over time and the cancellous bone density decreases significantly in metaphyseal region over time. In metaphyseal region, posterior-medial (P-M) quadrant showed high bone loss while diaphyseal regions show high bone loss in anterior-lateral (A-L) quadrant. Conclusions: Our study demonstrated that combining QCT with 3D patient-specific models has the ability of monitoring bone density change patterns after THA in much finer details. Future studies include using these findings for the development of a bone remodelling algorithm capable of predicting surgical outcomes for THA patients. %U https://qims.amegroups.org/article/view/7220 %V 5 %N 4 %P 575-582 %@ 2223-4306