ArticleJournal of applied clinical medical physics2025
Technical development and In Silico implementation of SyntheticMR in head and neck adaptive radiation therapy: A prospective R-IDEAL stage 0/1 technology development report.
Article in Journal of applied clinical medical physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Characterizing electronic noise interference from the external laser positioning system on a radiation therapy MRI simulation scanner.Journal of applied clinical medical physics · 2026Article
- Feasibility of longitudinal relaxation rate mapping with non-Cartesian sampling and compressed sensing on a 1.5 T magnetic resonance linear accelerator.Physics and imaging in radiation oncology · 2026Article
- Technical Development and Implementation of 3D-QALAS on a 1.5T MR-Linac for the Brain: A Prospective R-IDEAL Stage 0/1 Technology Development Report.medRxiv : the preprint server for health sciences · 2026Article
- Article
- A method for sensitivity analysis of automatic contouring algorithms across different contrast weightings using synthetic magnetic resonance imaging.Physics and imaging in radiation oncology · 2025Article
- Technical development and In Silico implementation of SyntheticMR in head and neck adaptive radiation therapy: A prospective R-IDEAL stage 0/1 technology development report.Journal of applied clinical medical physics · 2025Article
- Technical Optimization of SyntheticMR for the Head and Neck on a 3T MR-Simulator and 1.5T MR-Linac: A Prospective R-IDEAL Stage 2a Technology Innovation Report.medRxiv : the preprint server for health sciences · 2025Article
- A Method for Sensitivity Analysis of Automatic Contouring Algorithms Across Different MRI Contrast Weightings Using SyntheticMR.medRxiv : the preprint server for health sciences · 2025Article
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14 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundSyntheticMR has the capability of generating quantitative relaxometry maps and synthetic contrast-weighted MRI images in rapid acquisition times. Recently, it has gained attention in the diagnostic community, however, no studies have investigated its feasibility on the MR-Simulation or MR-Linac systems, especially as part of the head and neck adaptive radiation oncology workflow. PURPOSE: Demonstrating its feasibility will facilitate rapid quantitative biomarker extraction, which can be leveraged to guide adaptive radiation therapy decision making.
methodsTwo phantoms, two healthy volunteers, and one patient were scanned using SyntheticMR on the MR-Simulation and MR-Linac devices with scan times between 4 to 6 min. The correlation between measured and reference quantitative T1, T2, and PD values were determined across clinical ranges in the phantom. Distortion was also studied. Contours of head and neck organs-at-risk (OAR) were drawn and applied to extract T1, T2, and PD. These values were plotted against each other, clusters were computed, and their separability significance was determined to evaluate SyntheticMR for differentiating tumor and normal tissue.
resultsThe Lin's Concordance Correlation Coefficient between the measured and phantom reference values was above 0.97 for both the MR-Sim and MR-Linac. No significant levels of distortion were measured. The mean bias between the measured and phantom reference values across repeated scans was below 6% for T1, 11% for T2, and 6% for PD for both the MR-Sim and MR-Linac. For T1 versus T2 and T1 versus PD, the GTV contour exhibited perfect purity against neighboring OARs, while being 0.7 for T2 versus PD. All cluster significance levels between the GTV and the nearest OAR, the tongue, using the SigClust method was p < 0.001.
conclusionsThe technical feasibility of SyntheticMR was confirmed. Application of this technique to the head and neck adaptive radiation therapy workflow can enrich the current quantitative biomarker landscape.
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