# The 2024 Brain Tumor Segmentation Challenge Meningioma Radiotherapy (BraTS-MEN-RT) dataset

## TL;DR

This paper introduces a large dataset of annotated MRIs for meningioma radiotherapy planning to improve automated segmentation methods.

## Contribution

The BraTS-MEN-RT dataset is the largest multi-institutional collection of annotated MRIs for meningioma radiotherapy planning.

## Key findings

- The dataset includes 570 MRIs with 500 expert-annotated gross tumor volumes.
- It supports both intact and postoperative meningioma cases, enhancing clinical relevance.
- Contributions from seven medical centers improve the dataset's generalizability.

## Abstract

Meningiomas are the most common primary intracranial tumors, frequently requiring radiotherapy as a part of management. Effective radiotherapy planning for meningiomas necessitates accurate and consistent segmentation of target volumes on MRI, a process that is complex, labor-intensive, and dependent on expert expertise. The 2024 Brain Tumor Segmentation Challenge Meningioma Radiotherapy (BraTS-MEN-RT) Dataset addresses this problem by providing the largest multi-institutional collection of systematically annotated radiotherapy planning MRIs for meningiomas. Publicly accessible, this dataset comprises 570 radiotherapy planning 3D T1-weighted post-contrast MRIs at native resolutions, with 500 cases featuring expert-annotated gross tumor volumes (GTV). Annotations follow standardized radiotherapy planning protocols and include both intact and postoperative meningioma cases, ensuring wide clinical relevance. Contributions from seven diverse medical centers across the United States and the United Kingdom enhance the dataset’s generalizability. The dataset aims to accelerate the development of automated segmentation methods for radiotherapy planning, improving workflow efficiency, reducing interobserver variability, and ultimately enhancing patient outcomes.