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Clinical monitoring of metastatic disease to the brain can be a laborious andtime-consuming process, especially in cases involving multiple metastases whenthe assessment is performed manually. The Response Assessment in Neuro-OncologyBrain Metastases (RANO-BM) guideline, which utilizes the unidimensional longestdiameter, is commonly used in clinical and research settings to evaluateresponse to therapy in patients with brain metastases. However, accuratevolumetric assessment of the lesion and surrounding peri-lesional edema holdssignificant importance in clinical decision-making and can greatly enhanceoutcome prediction. The unique challenge in performing segmentations of brainmetastases lies in their common occurrence as small lesions. Detection andsegmentation of lesions that are smaller than 10 mm in size has notdemonstrated high accuracy in prior publications. The brain metastaseschallenge sets itself apart from previously conducted MICCAI challenges onglioma segmentation due to the significant variability in lesion size. Unlikegliomas, which tend to be larger on presentation scans, brain metastasesexhibit a wide range of sizes and tend to include small lesions. We hope thatthe BraTS-METS dataset and challenge will advance the field of automated brainmetastasis detection and segmentation.

The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI