Computational study of estimating 3D trabecular bone microstructure for the volume of interest from CT scan data

• Published in: International journal for numerical methods in biomedical engineering Vol. 34; no. 4; pp. e2950 - n/a
• Main Authors: Kim, Jung Jin, Nam, Jimin, Jang, In Gwun
• Format: Journal Article
• Language: English
• Published: England Wiley Subscription Services, Inc 01.04.2018
• Subjects: Bone Density; Bone mineral density; bone remodeling; Cancellous bone; Cancellous Bone - anatomy & histology; Cancellous Bone - diagnostic imaging; Computational efficiency; Computed tomography; Computer applications; Computer Simulation; Computing time; Deviation; Feasibility studies; Female; Femur; Femur Head - diagnostic imaging; finite element analysis; Finite element method; Humans; Image reconstruction; Imaging, Three-Dimensional; Inventory management; Iron; Localization; Medical imaging; Microstructure; Middle Aged; Spatial distribution; Supermarkets; Tomography; Tomography, X-Ray Computed; Topology; Topology optimization; trabecular bone; computed tomography; bone remodeling; topology optimization; finite element analysis; trabecular bone
• ISSN: 2040-7939; 2040-7947
• DOI: 10.1002/cnm.2950

Inspired by the self‐optimizing capabilities of bone, a new concept of bone microstructure reconstruction has been recently introduced by using 2D synthetic skeletal images. As a preliminary clinical study, this paper proposes a topology optimization‐based method that can estimate 3D trabecular bone microstructure for the volume of interest (VOI) from 3D computed tomography (CT) scan data with enhanced computational efficiency and phenomenological accuracy. For this purpose, a localized finite element (FE) model is constructed by segmenting a target bone from CT scan data and determining the physiological local loads for the VOI. Then, topology optimization is conducted with multiresolution bone mineral density (BMD) deviation constraints to preserve the patient‐specific spatial bone distribution obtained from the CT scan data. For the first time, to our knowledge, this study has demonstrated that 60‐μm resolution trabecular bone images can be reconstructed from 600‐μm resolution CT scan data (a 62‐year‐old woman with no metabolic bone disorder) for the 4 VOIs in the proximal femur. The reconstructed trabecular bone includes the characteristic trabecular patterns and has morphometric indices that are in good agreement with the anatomical data in the literature. As for computational efficiency, the localization for the VOI reduces the number of FEs by 99%, compared with that of the full FE model. Compared with the previous single‐resolution BMD deviation constraint, the proposed multiresolution BMD deviation constraints enable at least 65% and 47% reductions in the number of iterations and computing time, respectively. These results demonstrate the clinical feasibility and potential of the proposed method. This paper presents a topology optimization‐based method estimating trabecular bone microstructure for the volume of interest from CT scan data. For enhanced computational efficiency and phenomenological accuracy, a 3D localized finite element model for the volume of interest is constructed, then topology optimization with multiresolution bone mineral density deviation constraints and a black‐and‐white filtering constraint is conducted. The estimated microstructure shows the characteristic trabecular patterns and morphometric indices that are in good agreement with the anatomical data in the literature.