MArkerless lung target Tracking CHallenge (MATCH) dataset - Part A

Abstract

The MATCH challenge stands for Markerless Lung Target Tracking Challenge. The aim is to systematically investigate and benchmark the accuracy of various approaches for lung tumour motion tracking during radiation therapy in both a retrospective simulation study (Part A) and a prospective phantom experiment (Part B).

What is the Rationale? The goal of the MATCH challenge is to explore the possibility of tracking lung tumour motion without the cost and risk of surgically inserted fiducial markers at the time that is needed most – in real-time during the radiation treatment.

Lung cancer stereotactic ablative body radiation therapy (SABR) is one of the cancer treatment success stories. The American Association of Physicists in Medicine (AAPM) Task Groups 76 1 (respiratory motion management) and 1012 (stereotactic body radiation therapy) have highlighted the need for accurate target tracking during radiation therapy. To further improve patient safety for SABR, reduce margins and account for the breath-to-breath and day-to-day variation in lung tumour motion several commercial and academic markerless lung target tracking algorithms have been developed. These algorithms have yet to be benchmarked using a common prospective measurement methodology. This knowledge gap motivated the Markerless Lung Target Tracking Challenge.

The Challenge The MATCH challenge consists of two parts: (Part A) in-silico study based on images with unknown motion and (Part B) experimental phantom measurements with patient-measured motion. The challenge is open to any participant, and participants can complete either one or both parts of the challenge. This data set is for Part A of the Challenge.

Any study that makes use of the MATCH Challenge dataset should cite the following reference: https://doi.org/10.1002/mp.15418