Abstract
Abstract
Objective. Virtual imaging trials enable efficient assessment and optimization of medical image devices and techniques via simulation rather than physical studies. These studies require realistic, detailed ground-truth models or phantoms of the relevant anatomy or physiology. Anatomical structures within computational phantoms are typically based on medical imaging data; however, for small and intricate structures (e.g. trabecular bone), it is not reasonable to use existing clinical data as the spatial resolution of the scans is insufficient. In this study, we develop a mathematical method to generate arbitrary-resolution bone structures within virtual patient models (XCAT phantoms) to model the appearance of CT-imaged trabecular bone. Approach. Given surface definitions of a bone, an algorithm was implemented to generate stochastic bicontinuous microstructures to form a network to define the trabecular bone structure with geometric and topological properties indicative of the bone. For an example adult male XCAT phantom (50th percentile in height and weight), the method was used to generate the trabecular structure of 46 chest bones. The produced models were validated in comparison with published properties of bones. The utility of the method was demonstrated with pilot CT and photon-counting CT simulations performed using the accurate DukeSim CT simulator on the XCAT phantom containing the detailed bone models. Main results. The method successfully generated the inner trabecular structure for the different bones of the chest, having quantiative measures similar to published values. The pilot simulations showed the ability of photon-counting CT to better resolve the trabecular detail emphasizing the necessity for high-resolution bone models. Significance. As demonstrated, the developed tools have great potential to provide ground truth simulations to access the ability of existing and emerging CT imaging technology to provide quantitative information about bone structures.
Funder
National Institute of Biomedical Imaging and Bioengineering
Subject
Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology
Reference76 articles.
1. DukeSim: a realistic, rapid, and scanner-specific simulation framework in computed tomography;Abadi;IEEE Trans. Med. Imaging,2018a
2. COPD quantifications via CT imaging: ascertaining the effects of acquisition protocol using virtual imaging trial;Abadi,2021
3. Optimization of energy thresholds in photon-counting CT via a virtual clinical trial;Abadi,2020
4. Trade-off between spatial details and motion artifact in multi-detector CT: a virtual clinical trial with 4D textured human models;Abadi,2019a
5. Modeling ‘Textured’ bones in virtual human phantoms;Abadi;IEEE Trans. Radiat. Plasma Med. Sci.,2019b