This project's goal is to demonstrate a new Monte Carlo radiation simulation software package, for a low-cost desktop high-performance computer, that will significantly reduce the turn-around time for computed tomography (CT) imaging dose calculations. X-ray is the oldest and most widely used diagnostic imaging modality. However, controversy about the potential risk of radiation-induced carcinogenic effects has always surrounded the clinical use of 3D volumetric CT body imaging. However, experiences suggest that existing patient CT dose computational tools are insufficient for patient- specific risk assessment, scanner optimization, protocol comparison, and accident investigation. We propose an innovative approach which takes advantage of general-purpose graphics processing units (GPGPUs) that harvest the enormous power from massively parallel processors at unprecedented low prices. We have assembled this multidisciplinary team of experts from nuclear engineering, Monte Carlo radiation transport theory, medical physics, computer science, clinical radiology, and CT scanner design to achieve the following Specific Aims: 1. To develop a new Monte Carlo software package that is specifically designed and optimized for the emerging hybrid CPU/GPU parallel computing platforms and to validate the software. 2. To integrate the software with GE LightSpeed CT scanner models and a library of deformable patient phantoms. 3. To demonstrate and evaluate clinical benefits of the new Monte Carlo computing tool for typical diagnostic CT scanning protocols. 4. To establish a national resource center of Monte Carlo parallel-computing for the clinical radiological community
A new Monte Carlo radiation simulation software package for a low-cost CPU/GPU desktop high- performance computer is developed to significantly reduce the turn-around time for computed tomography (CT) imaging dose calculations.
|Zhang, Da; Padole, Atul; Li, Xinhua et al. (2014) In vitro dose measurements in a human cadaver with abdomen/pelvis CT scans. Med Phys 41:091911|
|Su, Lin; Yang, Youming; Bednarz, Bryan et al. (2014) ARCHERRT - a GPU-based and photon-electron coupled Monte Carlo dose computing engine for radiation therapy: software development and application to helical tomotherapy. Med Phys 41:071709|
|Xu, X George (2014) An exponential growth of computational phantom research in radiation protection, imaging, and radiotherapy: a review of the fifty-year history. Phys Med Biol 59:R233-302|
|Zhang, Da; Li, Xinhua; Gao, Yiming et al. (2013) A method to acquire CT organ dose map using OSL dosimeters and ATOM anthropomorphic phantoms. Med Phys 40:081918|