DosePatch: physics-inspired cropping layout for patch-based Monte Carlo simulations to provide fast and accurate internal dosimetry

• Published in: EJNMMI physics Vol. 11; no. 1; pp. 51 - 16
• Main Authors: De Benetti, Francesca, Brosch-Lenz, Julia, Guerra González, Jorge Mario, Uribe, Carlos, Eiber, Matthias, Navab, Nassir, Wendler, Thomas
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 26.06.2024; Springer Nature B.V; SpringerOpen
• Subjects: Applied and Technical Physics; Computation; Computational Mathematics and Numerical Analysis; Dose kernels; Dosimeters; Dosimetry; Engineering; Imaging; Imaging and dosimetry for radionuclide based therapy; Layouts; Liver; Medicine; Medicine & Public Health; Monte Carlo simulation; Monte Carlo simulations; Nuclear Medicine; Organ-S-values; Original Research; Physics; Radiation therapy; Radiology; Simulation; SIRT; Soft tissues; Yttrium; Yttrium isotopes; Dose kernels; Organ-S-values; Monte Carlo simulations; Dosimetry; SIRT
• ISSN: 2197-7364; 2197-7364
• DOI: 10.1186/s40658-024-00646-y

Background Dosimetry-based personalized therapy was shown to have clinical benefits e.g. in liver selective internal radiation therapy (SIRT). Yet, there is no consensus about its introduction into clinical practice, mainly as Monte Carlo simulations (gold standard for dosimetry) involve massive computation time. We addressed the problem of computation time and tested a patch-based approach for Monte Carlo simulations for internal dosimetry to improve parallelization. We introduce a physics-inspired cropping layout for patch-based MC dosimetry, and compare it to cropping layouts of the literature as well as dosimetry using organ-S-values, and dose kernels, taking whole-body Monte Carlo simulations as ground truth. This was evaluated in five patients receiving Yttrium-90 liver SIRT. Results The patch-based Monte Carlo approach yielded the closest results to the ground truth, making it a valid alternative to the conventional approach. Our physics-inspired cropping layout and mosaicking scheme yielded a voxel-wise error of < 2% compared to whole-body Monte Carlo in soft tissue, while requiring only ≈  10% of the time. Conclusions This work demonstrates the feasibility and accuracy of physics-inspired cropping layouts for patch-based Monte Carlo simulations.