ArticleRadiation oncology (London, England)2020
Accuracy of automatic deformable structure propagation for high-field MRI guided prostate radiotherapy.
Article in Radiation oncology (London, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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18 citing papers in PubMed.
- Contrastive adversarial mix-up learning for unsupervised cross-modality image segmentation.Quantitative imaging in medicine and surgery · 2026Article
- Conditional organs-of-interest segmentation with plausible inter-fraction variation simulation for pancreatic magnetic resonance-guided radiotherapy in limited-data settings.Physics and imaging in radiation oncology · 2026Article
- Evaluation of hybrid DIR performance using controlling structures and points of interest in MR-guided adaptive radiotherapy for prostate cancer patients.Journal of applied clinical medical physics · 2026Article
- Volume change of the prostate during moderately hypo-fractionated radiotherapy assessed by artificial intelligence.Physics and imaging in radiation oncology · 2025Article
- Feasibility of creating a daily adaptive plan using automatic DIR-created target and OARs contours in patients with prostate cancer magnetic-resonance-guided adaptive radiotherapy.Journal of radiation research · 2024Article
- Automatic AI-based contouring of prostate MRI for online adaptive radiotherapy.Zeitschrift fur medizinische Physik · 2024Article
- Investigation of autosegmentation techniques on T2-weighted MRI for off-line dose reconstruction in MR-linac workflow for head and neck cancers.Medical physics · 2024Article
- The Use of MR-Guided Radiation Therapy for Head and Neck Cancer and Recommended Reporting Guidance.Seminars in radiation oncology · 2024Review
- Review and recommendations on deformable image registration uncertainties for radiotherapy applications.Physics in medicine and biology · 2023Review
- Prostate volume analysis in image registration for prostate cancer care: a verification study.Physical and engineering sciences in medicine · 2023Article
- An integrated and fast imaging quality assurance phantom for a 0.35 T magnetic resonance imaging linear accelerator.Physics and imaging in radiation oncology · 2023Article
- An open-source nnU-net algorithm for automatic segmentation of MRI scans in the male pelvis for adaptive radiotherapy.Frontiers in oncology · 2023Article
- Dosimetric comparison of automatically propagated prostate contours with manually drawn contours in MRI-guided radiotherapy: A step towards a contouring free workflow?Clinical and translational radiation oncology · 2022Article
- Clinical rationale forPhysics and imaging in radiation oncology · 2022Article
- Inter- and intrafraction motion assessment and accumulated dose quantification of upper gastrointestinal organs during magnetic resonance-guided ablative radiation therapy of pancreas patients.Physics and imaging in radiation oncology · 2022Article
- Dose accumulation for MR-guided adaptive radiotherapy: From practical considerations to state-of-the-art clinical implementation.Frontiers in oncology · 2022Review
- Online adaptive planning for prostate stereotactic body radiotherapy using a 1.5 Tesla magnetic resonance imaging-guided linear accelerator.Physics and imaging in radiation oncology · 2021Article
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6 authors.
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Abstract
backgroundIn this study we have evaluated the accuracy of automatic, deformable structure propagation from planning CT and MR scans for daily online plan adaptation for MR linac (MRL) treatment, which is an important element to minimize re-planning time and reduce the risk of misrepresenting the target due to this time pressure.
methodsFor 12 high-risk prostate cancer patients treated to the prostate and pelvic lymph nodes, target structures and organs at risk were delineated on both planning MR and CT scans and propagated using deformable registration to three T2 weighted MR scans acquired during the treatment course. Generated structures were evaluated against manual delineations on the repeated scans using intra-observer variation obtained on the planning MR as ground truth.
resultsMR-to-MR propagated structures had significant less median surface distance and larger Dice similarity index compared to CT-MR propagation. The MR-MR propagation uncertainty was similar in magnitude to the intra-observer variation. Visual inspection of the deformed structures revealed that small anatomical differences between organs in source and destination image sets were generally well accounted for while large differences were not.
conclusionBoth CT and MR based propagations require manual editing, but the current results show that MR-to-MR propagated structures require fewer corrections for high risk prostate cancer patients treated at a high-field MRL.
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