# Improvement of deep learning-based dose conversion accuracy to a Monte Carlo algorithm in proton beam therapy for head and neck cancers

## TL;DR

This study shows that using image rotation and zooming improves deep learning accuracy in converting proton beam doses for cancer treatment.

## Contribution

The study introduces image-rotation and zooming augmentation to enhance deep learning dose conversion accuracy in proton beam therapy.

## Key findings

- Image-rotation and zooming augmentation improved γ-passing rates to 93.0% and reduced range differences to -0.5%.
- The data-augmentation model outperformed baseline models in dose conversion accuracy.
- These techniques significantly improved DL-based dose calculation accuracy in proton beam therapy.

## Abstract

This study is aimed to clarify the effectiveness of the image-rotation technique and zooming augmentation to improve the accuracy of the deep learning (DL)-based dose conversion from pencil beam (PB) to Monte Carlo (MC) in proton beam therapy (PBT). We adapted 85 patients with head and neck cancers. The patient dataset was randomly divided into 101 plans (334 beams) for training/validation and 11 plans (34 beams) for testing. Further, we trained a DL model that inputs a computed tomography (CT) image and the PB dose in a single-proton field and outputs the MC dose, applying the image-rotation technique and zooming augmentation. We evaluated the DL-based dose conversion accuracy in a single-proton field. The average γ-passing rates (a criterion of 3%/3 mm) were 80.6 ± 6.6% for the PB dose, 87.6 ± 6.0% for the baseline model, 92.1 ± 4.7% for the image-rotation model, and 93.0 ± 5.2% for the data-augmentation model, respectively. Moreover, the average range differences for R90 were − 1.5 ± 3.6% in the PB dose, 0.2 ± 2.3% in the baseline model, −0.5 ± 1.2% in the image-rotation model, and − 0.5 ± 1.1% in the data-augmentation model, respectively. The doses as well as ranges were improved by the image-rotation technique and zooming augmentation. The image-rotation technique and zooming augmentation greatly improved the DL-based dose conversion accuracy from the PB to the MC. These techniques can be powerful tools for improving the DL-based dose calculation accuracy in PBT.