Evidence map›Paper›PMID 41663318›Full record

ArticleJournal of applied clinical medical physics2026

Development and implementation of an MRI-only simulation, planning, and treatment workflow for prostate radiotherapy using synthetic CT on MR-linac.

Reza Reiazi, Yao Ding, Sarath Vijayan, Jinzhong Yang, Ergys Subashi, Yao Zhao, Belinda M Lee, Hunter L Emory, Vi T Dinh, Greg L Swiedom and 9 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of applied clinical medical physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Reza ReiaziDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID https://orcid.org/0000-0003-1323-8942
Yao DingDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Sarath VijayanDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Jinzhong YangDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID https://orcid.org/0000-0002-9254-4501
Ergys SubashiDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Yao ZhaoDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Belinda M LeeDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Hunter L EmoryDepartment of Radiation Oncology Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Vi T DinhDepartment of Radiation Oncology Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Greg L SwiedomDepartment of Radiation Oncology Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Jie DengDepartment of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, Texas, USA.ORCID https://orcid.org/0000-0002-2518-7989
Mu-Han LinDepartment of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Peter BalterDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Rajat J KudchadkerDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Elaine E ChaDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Seungtaek ChoiDepartment of Genitourinary Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Yusung KimDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Eun Young HanDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Surendra PrajapatiDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID https://orcid.org/0000-0003-3531-8054

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeWe evaluated the feasibility of a magnetic resonance (MR)-only simulation, planning, and treatment (MROSPT) workflow for prostate cancer patients using synthetic computed tomography (sCT) generated from magnetic resonance imaging (MRI) data. By validating sCT-based dose calculations, we aimed to streamline radiotherapy workflows, eliminate the need for CT simulation, and enable reliable clinical implementation of MR-based radiotherapy for MR-linac (MRL).

methodsWe developed a comprehensive workflow encompassing the entire process from initial consultation to treatment delivery. After developing the workflow, a retrospective dosimetric validation study was performed on nine men with prostate cancer. They underwent CT and MRI simulations, and sCTs were generated from the MRI data. Contours and intensity-modulated radiation therapy treatment plans were created on the reference simulation CT (rCT) and transferred to sCTs for dose-calculation comparisons. Dosimetric accuracy was evaluated using gamma analysis (dose/distance; 2%/2mm). Bulk density sCTs (bCTs) were created by overriding organ density values with their mean (bulk) sCT-determined densities. bCT based on sCT allows treatment planning directly on MRI for MRL workflow efficiency.

resultsMinimal non-bone Hounsfield units (HU)-value differences between rCT and sCT (5.5 ± 2.9 HU for prostate) demonstrated the reliability of the sCT generation process. Dosimetric comparisons between treatment plans (rCT vs. sCT, rCT vs. bCT) showed agreement within ± 2% in gamma analysis, confirming robust accuracy. The gamma index pass rate for rCT versus sCT and rCT versus bCT were consistently > 95% using 2%/2 mm criteria. A dry run of the entire simulation-to-treatment workflow was successfully completed.

conclusionThe MROSPT workflow using sCT is clinically feasible and dosimetrically accurate for prostate cancer patients. Dose calculations based on sCT demonstrated high dosimetric agreement with simulation CT, with no statistically significant differences across all evaluated metrics. These findings support the adoption of sCT‑based planning for prostate cancer radiotherapy and suggest its potential applicability in other anatomical regions especially in the pelvis. Integration of robust quality‑assurance processes and treatment‑delivery flexibility will further enhance its clinical utility.

Indexed as

Image Processing, Computer-AssistedMagnetic Resonance ImagingParticle AcceleratorsProstatic NeoplasmsRadiotherapy Planning, Computer-AssistedTomography, X-Ray ComputedWorkflowComputer SimulationFeasibility StudiesHumansMaleOrgans at RiskRadiotherapy DosageRadiotherapy, Image-GuidedRadiotherapy, Intensity-ModulatedRetrospective StudiesMR‐only simulationprostateradiotherapysynthetic CT

Identifiers

PMID41663318
PMCPMC12885750

What Socratic holds

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LicenceCC BY
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Registered trials

None linked

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 Socratic graph.