TY - JOUR
T1 - Virtual Clinical Trials in 2D and 3D X-ray Breast Imaging and Dosimetry
T2 - Comparison of CPU-Based and GPU-Based Monte Carlo Codes
AU - Mettivier, Giovanni
AU - Sarno, Antonio
AU - Lai, Youfang
AU - Golosio, Bruno
AU - Fanti, Viviana
AU - Italiano, Maria Elena
AU - Jia, Xun
AU - Russo, Paolo
N1 - Funding Information:
Funding: This research was funded by Istituto Nazionale di Fisica Nucleare (INFN), project names MC_INFN and AGATA.
Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2022/2/1
Y1 - 2022/2/1
N2 - Computational reproductions of medical imaging tests, a form of virtual clinical trials (VCTs), are increasingly being used, particularly in breast imaging research. The accuracy of the computational platform that is used for the imaging and dosimetry simulation processes is a funda-mental requirement. Moreover, for practical usage, the imaging simulation computation time should be compatible with the clinical workflow. We compared three different platforms for in-silico X-ray 3D breast imaging: the Agata (University & INFN Napoli) that was based on the Geant4 toolkit and running on a CPU-based server architecture; the XRMC Monte Carlo (University of Cagliari) that was based on the use of variance reduction techniques, running on a CPU hardware; and the Monte Carlo code gCTD (University of Texas Southwestern Medical Center) running on a single GPU platform with CUDA environment. The tests simulated the irradiation of cylindrical objects as well as anthropomorphic breast phantoms and produced 2D and 3D images and 3D maps of absorbed dose. All the codes showed compatible results in terms of simulated dose maps and imaging values within a maximum discrepancy of 3%. The GPU-based code produced a reduction of the computation time up to factor 104, and so permits real-time VCT studies for X-ray breast imaging.
AB - Computational reproductions of medical imaging tests, a form of virtual clinical trials (VCTs), are increasingly being used, particularly in breast imaging research. The accuracy of the computational platform that is used for the imaging and dosimetry simulation processes is a funda-mental requirement. Moreover, for practical usage, the imaging simulation computation time should be compatible with the clinical workflow. We compared three different platforms for in-silico X-ray 3D breast imaging: the Agata (University & INFN Napoli) that was based on the Geant4 toolkit and running on a CPU-based server architecture; the XRMC Monte Carlo (University of Cagliari) that was based on the use of variance reduction techniques, running on a CPU hardware; and the Monte Carlo code gCTD (University of Texas Southwestern Medical Center) running on a single GPU platform with CUDA environment. The tests simulated the irradiation of cylindrical objects as well as anthropomorphic breast phantoms and produced 2D and 3D images and 3D maps of absorbed dose. All the codes showed compatible results in terms of simulated dose maps and imaging values within a maximum discrepancy of 3%. The GPU-based code produced a reduction of the computation time up to factor 104, and so permits real-time VCT studies for X-ray breast imaging.
KW - Breast cancer
KW - Geant4
KW - GPU code
KW - Virtual clinical trials
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U2 - 10.3390/cancers14041027
DO - 10.3390/cancers14041027
M3 - Article
C2 - 35205775
AN - SCOPUS:85124976969
VL - 14
JO - Cancers
JF - Cancers
SN - 2072-6694
IS - 4
M1 - 1027
ER -