ArticlePhysics in medicine and biology2015
Radiotherapy planning using MRI.
Article in Physics in medicine and biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05786742 (ULTRA-HYPO Fractionated), which is not on this map. Cited by 154 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
ULTRA-HYPO Fractionated (UHF) Compared to Moderate-HYPO Fractionated (MHF) Prostate IGRT With HDR Brachytherapy BOOST : A Phase 1-2 Study.
Who cites it
154 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Quality requirements for MRI simulation in cranial stereotactic radiotherapy: a guideline from the German Taskforce "Imaging in Stereotactic Radiotherapy".Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2024Guideline
- Guidance on the use of MRI for treatment planning in radiotherapy clinical trials.The British journal of radiology · 2020Guideline
- Standardisation of Target Volume Delineation for Carotid-sparing Intensity-modulated Radiotherapy in Early Glottis Cancer.Clinical oncology (Royal College of Radiologists (Great Britain)) · 2017Pooled it
- MR-PROTECT: Clinical feasibility of a prostate MRI-only radiotherapy treatment workflow and investigation of acceptance criteria.Radiation oncology (London, England) · 2020Trial
- Dosimetric evaluation of synthetic CT for magnetic resonance-only based radiotherapy planning of lung cancer.Radiation oncology (London, England) · 2017Trial
- Evaluation-design effects and reference-CT-defined HU-class errors in brain MRI-to-CT synthesis on SynthRAD2023: a technical note.Radiological physics and technology · 2026Article
- Metal artifact reduction for 3 T MRI-only prostate radiotherapy in patients with hip prostheses: impact on target definition, synthetic CT generation, dose calculation, and fiducial marker identification.Radiation oncology (London, England) · 2026Article
- S2V-DREME: a time-resolved slice-to-volume MR image reconstruction framework with dynamic reconstruction and motion estimation.Physics in medicine and biology · 2026Article
- A comparison of contrast-to-noise ratio of liver tumors between dynamic contrast-enhanced CT and respiration-tracked 4D-CT for radiotherapy targeting.The British journal of radiology · 2026Article
- 3D analysis and evolution of prostate and tumor oxygenation using MRI-derived relative oxygen extraction fraction during MR-guided stereotactic body radiotherapy.Physics and imaging in radiation oncology · 2026Article
- Impact of dose calculation algorithm on magnetic resonance imaging-only radiotherapy for prostate and glioma.Physics and imaging in radiation oncology · 2026Article
- Importance of the Quality of Annotation: Impact of Simulated Inter-Observer Variability on Deep Neural Network Automated Segmentation Model Performance.Bioengineering (Basel, Switzerland) · 2026Article
- Synthetic CT imaging for pelvic and abdominal MR-only radiotherapy: Clinical validation on a 1.5T MR-Linac.Journal of applied clinical medical physics · 2026Article
- Deep Learning (nnU-Net)-Based Segmentation of Primary HPV-Positive OPSCC: Contrast-Enhanced T1-Weighted Fat-Suppressed Versus Non-Contrast-Enhanced T2-Weighted Fat-Suppressed MRI (Paired Single-Center Study).Diagnostics (Basel, Switzerland) · 2026Article
- cMeta-INR: cohort-informed meta-learning-based implicit neural representation for deformable registration-driven real-time volumetric MRI estimation.Physics in medicine and biology · 2025Article
- Deep learning-based synthetic-CT-free photon dose calculation in MR-guided radiotherapy: A proof-of-concept study.Medical physics · 2025Article
- Improving Spatial Accuracy of MRI in the Presence of Metal-induced Geometric Distortions.Investigative radiology · 2025Article
- Emerging Technologies in Radiation Therapy: Replacing Traditional Isotope-based Modalities.Health physics · 2025Review
- Universal mapping and patient-specific prior implicit neural representation for enhanced high-resolution MRI in MRI-guided radiotherapy.Medical physics · 2025Article
- SynthRAD2025 Grand Challenge dataset: Generating synthetic CTs for radiotherapy from head to abdomen.Medical physics · 2025Article
94 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The use of magnetic resonance imaging (MRI) in radiotherapy (RT) planning is rapidly expanding. We review the wide range of image contrast mechanisms available to MRI and the way they are exploited for RT planning. However a number of challenges are also considered: the requirements that MR images are acquired in the RT treatment position, that they are geometrically accurate, that effects of patient motion during the scan are minimized, that tissue markers are clearly demonstrated, that an estimate of electron density can be obtained. These issues are discussed in detail, prior to the consideration of a number of specific clinical applications. This is followed by a brief discussion on the development of real-time MRI-guided RT.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.