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

## TL;DR

This paper introduces a faster and accurate method for calculating radiation doses in liver cancer treatment using physics-inspired patch-based simulations.

## Contribution

A physics-inspired cropping layout for patch-based Monte Carlo simulations is proposed to reduce computation time while maintaining accuracy.

## Key findings

- The patch-based Monte Carlo approach produced results closest to whole-body simulations.
- The physics-inspired layout achieved <2% voxel-wise error in soft tissue with 10% of the computation time.
- The method was validated in five patients undergoing Yttrium-90 liver SIRT.

## Abstract

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.

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 \documentclass[12pt]{minimal}
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This work demonstrates the feasibility and accuracy of physics-inspired cropping layouts for patch-based Monte Carlo simulations.