Journal Article

DKFZ-2025-01384

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png TrackRAD2025 challenge dataset: real-time tumor tracking for MRI-guided radiotherapy.

Wang, Y. ; Lombardo, E. ; Thummerer, A. ; Blöcker, T. ; Fan, Y. ; Zhao, Y. ; Papadopoulou, C. I. ; Hurkmans, C. ; Tijssen, R. H. N. ; Görts, P. A. W. ; Tetar, S. U. ; Cusumano, D. ; Intven, M. P. ; Borman, P. ; Riboldi, M. ; Dudáš, D. ; Byrne, H. ; Placidi, L. ; Fusella, M. ; Jameson, M. ; Palacios, M. ; Cobussen, P. ; Finazzi, T. ; Haasbeek, C. J. A. ; Keall, P. ; Kurz, C. ; Landry, G.DKFZ* ; Maspero, M.

2025
Wiley Hoboken, NJ

Abstract: Magnetic resonance imaging (MRI) to visualize anatomical motion is becoming increasingly important when treating cancer patients with radiotherapy. Hybrid MRI-linear accelerator (MRI-linac) systems allow real-time motion management during irradiation. This paper presents a multi-institutional real-time MRI time series dataset from different MRI-linac vendors. The dataset is designed to support developing and evaluating real-time tumor localization (tracking) algorithms for MRI-guided radiotherapy within the TrackRAD2025 challenge ( https://trackrad2025.grand-challenge.org/).The dataset consists of sagittal 2D cine MRIs (20-20543 frames per scan) in 585 patients from six centers (3 Dutch, 1 German, 1 Australian, and 1 Chinese). Tumors in the thorax, abdomen, and pelvis acquired on two commercially available MRI-linacs (0.35 T and 1.5 T) were included. For 108 cases, irradiation targets or tracking surrogates were manually segmented on each temporal frame. The dataset was randomly split into a public training set of 527 cases (477 unlabeled and 50 labeled) and a private testing set of 58 cases (all labeled).The data is publicly available under the TrackRAD2025 collection: https://doi.org/10.57967/hf/4539. Both the images and segmentations for each patient are available in metadata format.This novel clinical dataset will enable the development and evaluation of real-time tumor localization algorithms for MRI-guided radiotherapy. By enabling more accurate motion management and adaptive treatment strategies, this dataset has the potential to advance the field of radiotherapy significantly.

Keyword(s): Radiotherapy, Image-Guided: methods (MeSH) ; Humans (MeSH) ; Magnetic Resonance Imaging (MeSH) ; Neoplasms: diagnostic imaging (MeSH) ; Neoplasms: radiotherapy (MeSH) ; Time Factors (MeSH) ; Databases, Factual (MeSH) ; Image Processing, Computer-Assisted (MeSH) ; MRI‐guided radiotherapy ; Real‐time tumor localization ; TrackRAD2025

---

Contributing Institute(s):

1. DKTK Koordinierungsstelle München (MU01)

Research Program(s):

1. 899 - ohne Topic (POF4-899) (POF4-899)

Appears in the scientific report 2025

---

Database coverage:
; Clarivate Analytics Master Journal List ; Current Contents - Clinical Medicine ; Current Contents - Life Sciences ; DEAL Wiley ; Ebsco Academic Search ; Essential Science Indicators ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

---