# Evaluation of hybrid DIR performance using controlling structures and points of interest in MR‐guided adaptive radiotherapy for prostate cancer patients

## TL;DR

This study evaluates how adding controlling structures and points of interest improves deformable image registration accuracy in prostate cancer radiotherapy, enhancing dose accumulation and treatment planning.

## Contribution

The study introduces a novel hybrid DIR approach using controlling structures and points of interest to improve geometric and dosimetric accuracy in prostate cancer ART.

## Key findings

- CS and CS+P improved geometric agreement compared to intensity-only DIR, especially for bladder contours.
- Dosimetric accuracy improved with CS and CS+P, reducing dose discrepancies in CTV, bladder, and rectum.
- CS+P showed the best performance, particularly for bladder, but automated contouring is still needed for session images.

## Abstract

MR‐guided adaptive radiotherapy (ART) allows for daily plan optimization based on patient‐specific anatomy. Accumulated doses, driven by deformable image registration (DIR), of daily fractions can provide cumulative dose metrics and insights into toxicity and tumor control. In prostate ART, inter‐ and intra‐factional deformations, particularly due to bladder and rectum, pose a challenge to accurate DIR generation.

To quantify geometric and dosimetric accuracy of a proposed prostate MR‐to‐MR DIR approach to support MR‐guided ART dose accumulation.

We evaluated DIR accuracy in 25 patients treated with 30 Gy in five fractions on a 1.5 T MR‐linac using an adaptive workflow. For all patients, a reference MR was used for planning, with three images collected at each fraction: adapt MR for adaptive planning, verify MR for pretreatment position verification and beam‐on for capturing anatomy during radiation delivery. We assessed three DIR approaches: intensity‐based, intensity‐based with controlling structures (CS), and intensity‐based with controlling structures and points of interest (CS + P). DIRs were performed between the reference and fraction images and within fractions (adapt‐to‐verify and adapt‐to‐beam‐on). For the evaluation, we propagated CTV, bladder, and rectum contours using the DIRs and compared each to manually delineated contours using Dice similarity coefficient, mean distance to agreement, and dose–volume metrics.

CS and CS + P improved geometric agreement between manual and propagated contours over intensity‐only DIR. For example, mean distance to agreement (DTAmean) for reference‐to‐beam‐on intensity‐only DIR was 0.131 ± 0.009 cm (CTV), 0.46 ± 0.08 cm (bladder), and 0.154 ± 0.013 cm (rectum). For the CS, the DTAmean values were 0.018 ± 0.002, 0.388 ± 0.14, and 0.036 ± 0.013 cm. Finally, for CS + P, these values were 0.015 ± 0.001, 0.025 ± 0.004, and 0.021 ± 0.002 cm. Dosimetrically, comparing CS and CS + P for reference to beam‐on DIRs resulted in a change of CTV D98% from [−29 cGy, 19 cGy] to [−18 cGy, 26 cGy], bladder D5cc from [−51 cGy, 544 cGy] to [−79 cGy, 36 cGy], and rectum D1cc from [−106 cGy, 72 cGy] to [−52 cGy, 74 cGy].

CS improved geometric and dosimetric accuracy over intensity‐only DIR, with CS + P providing further performance improvement, particularly for bladder. However, session image segmentation remains a challenge, which may be addressed with automated contouring.