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MRIgRT real-time target tracking: TrackRAD2025 challenge report.

May 23, 2026pubmed logopapers

Authors

Blöcker TJ,Görts PAW,Wang Y,Lombardo E,Thummerer A,Fan Y,Zhao Y,Papadopoulou CI,Hurkmans C,Tijssen RHN,Cusumano D,Intven MP,Borman P,Riboldi M,Dudáš D,Byrne HL,Placidi L,Fusella M,Jameson M,Palacios MA,Cobussen P,Finazzi T,Tetar SU,Haasbeek CJA,Keall P,Maspero M,Kurz C,Tarifa ASB,He K,Zhu S,Song Y,Li G,Hu J,Knispel F,Gatidis S,Chu H,Guo J,Nielsen M,Sentker T,Boussot V,Hémon C,Ni J,Georgas K,Vagenas TP,Matsopoulos GK,Landry G

Affiliations (28)

  • Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany.
  • Department of Radiation Oncology, Catharina Hospital, Eindhoven, The Netherlands; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
  • Department of Radiation Oncology, Radiation Oncology Key Laboratory of Sichuan Province, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
  • Department of Radiation Oncology, Catharina Hospital, Eindhoven, The Netherlands; Department of Electrical Engineering, Technical university Eindhoven, The Netherlands; Department of Applied Physics and Science education, Technical university Eindhoven, The Netherlands.
  • Department of Radiation Oncology, Catharina Hospital, Eindhoven, The Netherlands.
  • Medical Physics Unit, Mater Olbia Hospital, Olbia, Italy.
  • Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Department of Medical Physics, Ludwig-Maximilians-Universität München, Garching, Germany.
  • Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany; Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, Prague, Czechia.
  • GenesisCare, St Vincent's Hospital, Sydney, Australia; Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Australia.
  • Fondazione Policlinico Universitario Agostino Gemelli, IRCCS, Department of Diagnostic Imaging, Oncological Radiotherapy and Hematology, Rome, Italy.
  • Department of Radiation Oncology, Abano Terme Hospital, Abano Terme, Veneto, Italy.
  • GenesisCare, St Vincent's Hospital, Sydney, Australia.
  • Department of Radiation Oncology, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
  • Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Australia.
  • Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands; Computational Imaging Group for MR Diagnostics & Therapy, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, The Netherlands; Diagnostic Image Analysis Group, Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
  • Machine Intelligence Laboratory College of Computer Science, Sichuan University, Chengdu 610065, PR China.
  • Department of Radiation Oncology, West China Hospital, Sichuan University, Chengdu 610041, PR China.
  • RWTH Aachen University, Aachen, Germany; Stanford University, Stanford, CA, USA.
  • Stanford University, Stanford, CA, USA.
  • Donald Smits Center for Information and Technology, University of Groningen, Groningen, NL 9700AB, The Netherlands.
  • Bernoulli Institute of Mathematics, Computer Science and Artificial Intelligence, University of Groningen, Nijenborg 9, Groningen, 9747AG, NL, The Netherlands.
  • Institute of Applied Medical Informatics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Univ Rennes 1, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, F-35000 Rennes, France.
  • Shanghai United Imaging Healthcare Co., Ltd., Shanghai 201815, China; School of Biomedical Engineering, ShanghaiTech University, Shanghai, China.
  • Biomedical Engineering Lab (BEL), School of Electrical and Computer Engineering, National Technical University of Athens, 15780, Greece.
  • Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany; Bavarian Cancer Research Center (BZKF), Munich, Germany; German Cancer Consortium (DKTK), partner site Munich, a partnership between DKFZ and LMU University Hospital Munich, Germany. Electronic address: [email protected].

Abstract

Magnetic resonance imaging (MRI)-guided radiotherapy (MRIgRT) integrates MRI with linear accelerators (MRI-linacs), enabling real-time motion management based on temporally resolved 2D MRI (cine-MRI). Current systems rely on template matching or deformable image registration for radiotherapy target (typically the gross tumor volume) localization, which allows beam gating. Further advances in localization could support more precise and efficient delivery methods. https://trackrad2025.grand-challenge.org/ was organized to provide a common dataset to benchmark algorithms for MRIgRT target tracking in 2D+t cine-MRI. Participants propagated target segmentation masks from an initialization frame across subsequent frames. The dataset comprised sagittal cine-MRI scans of 585 cancer patients undergoing radiotherapy at 0.35 T and 1.5 T MRI-linacs at six different institutions, with expert-annotated targets in 108 sequences. Target sites included the thorax (179 cases), abdomen (266 cases), and pelvis (140 cases). A total of 477 unlabeled and 50 labeled cases were provided for training purposes, 58 cases were kept private for preliminary testing (8) and final evaluation (50). The algorithms submitted by participants were executed on the challenge platform and assessed using metrics in three categories: geometric accuracy, surrogate dose accuracy and execution speed. Rankings were derived via a Rank-Then-Mean scheme. TrackRAD2025 attracted 148 registrations from 28 countries, 100 preliminary submissions and 24 final submissions from 14 teams. The top five methods achieved mean Dice similarity coefficients >0.87 and Euclidean center distances <2.1 mm, comparable to interobserver variability. Leading top five solutions featured foundation models with (4) or without (1) finetuning. Field strength had minimal effect on performance and tracking worked better for the pelvis with reduced motion amplitude compared to the thorax and abdomen cases, which achieved equivalent performance. TrackRAD2025 established a benchmark for MRIgRT tracking on multi-institutional cine-MRI data, highlighting foundation models as promising for clinical translation.

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