# Semi‐automated hippocampal avoidance whole‐brain radiotherapy planning

**Authors:** Dong Joo Rhee, Subha Perni, Kelly J. Perrin, Kevin E. Casey, Alexandra O. Leone, Callistus M. Nguyen, Laurence E. Court, He Wang, Xin Wang, Eun Young Han

PMC · DOI: 10.1002/acm2.70076 · Journal of Applied Clinical Medical Physics · 2025-03-18

## TL;DR

This paper introduces an automated method for hippocampal avoidance whole-brain radiotherapy planning that improves efficiency and plan quality compared to manual methods.

## Contribution

A rule-based autoplanning algorithm for hippocampal avoidance radiotherapy that reduces planning time and improves dosimetric outcomes.

## Key findings

- Autoplans achieved better target coverage and lower maximum doses compared to manual plans.
- Autoplans reduced the minimum hippocampal dose by 5% and scored higher in qualitative reviews.
- IMRT QA results showed higher gamma pass rates for autoplans than manual plans.

## Abstract

Hippocampal avoidance whole‐brain radiotherapy (HA‐WBRT) is designed to spare cognitive function by reducing radiation dose to the hippocampus during the treatment of brain metastases. Current manual planning methods can be time‐consuming and may vary in quality, necessitating the development of automated approaches to streamline the process and ensure consistency.

To automate hippocampal avoidance whole‐brain radiotherapy (HA‐WBRT) planning.

Our algorithm automatically contours organs‐at‐risk (OARs) and the hippocampal‐avoidance brain target. The algorithm generates planning structures from given contours, utilizing preset beam parameters and dose constraints for optimization. If the dose constraints are unmet, “hotspot” contours will be created to improve dosimetry. The algorithm was written with RayStation's scripting feature and was compared with clinically approved manual HA‐WBRT plans for 20 retrospective patients using target and OAR dose metrics, with statistical analysis performed using the Student's t‐test. In the qualitative review, an experienced radiation oncologist blindly scored both the manual plans and autoplans for qualitative review. Lastly, IMRT QA was performed to determine the plans’ deliverability.

The autoplans demonstrated a better target coverage with a more uniform dose. With a prescription dose of 3000 cGy, autoplans achieved higher D
95% (3026 cGy vs. 2998 cGy, p = 0.02) and lower D
max (3337 cGy vs. 3533 cGy, p < 0.01) for the target. The maximum OAR doses were substantially lower in the eyes of autoplans (1727 cGy vs. 2176 cGy, p < 0.01), while the other OARs had similar maximum doses to those of the manual plans. The autoplans met all of the in‐house dose constraints, and the minimum dose to the hippocampus was reduced by 5% compared to the manual plans; the average MU was 1376 ± 329 MU for the manual plans and 1141 ± 64 MU for the autoplans. Autoplan generation took an average of 100.2 ± 16.3 minutes (range 62.9–127.9 min). In the qualitative review, the average scores were 4.9 ± 0.4 for the autoplans and 3.4 ± 1.0 for the manual plans. The gamma criteria results for IMRT QA were 96.4 ± 2.1% for the autoplans and 91.6 ± 5.3% for the manual plans.

Our rule‐based autoplanning algorithm produces high‐quality plans that are comparable to those of manual planning, demonstrating autoplanning's potential to reduce HA‐WBRT planning time while ensuring consistent plan quality.

## Full-text entities

- **Diseases:** metastases (MESH:D009362)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

3 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12256275/full.md

## References

19 references — full list in the complete paper: https://tomesphere.com/paper/PMC12256275/full.md

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Source: https://tomesphere.com/paper/PMC12256275