1
Return

MRI-enhanced online adaptive radiotherapy by virtual integration of a standalone MRI simulator and CBCT-based treatment delivery

delete2026-07-06
delete0
delete
OA
AI
S
Silvia Fabiano *
K
Klara Kefer
M
Michael Baumgartl
H
Hubert Gabrys
R
Riccardo Dal Bello
E
Elizabeth Denney
M
Michael Mayinger
J
Jens von der Grün
L
Lotte Wilke
M
Matthias Guckenberger
S
Stephanie Tanadini-Lang
S
Sebastian M. Christ
DOI:10.1186/s13014-026-02887-wdelete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
MR-guided radiotherapy (MRgRT) offers superior soft-tissue contrast and enables adaptive treatments which improve tumor targeting and organ-at-risk sparing. However, integrated MR-Linac systems remain financially and logistically inaccessible for many hospitals. To address this gap, we implemented a modular MRgRT workflow — termed the “Virtual MR-Linac”— which decouples MR imaging and treatment delivery, enabling daily adaptive radiotherapy (ART) using diagnostic-quality MRI. Between November 2023 and January 2025, 31 male patients with pelvic lymph node metastases were treated using this workflow. Daily MR scans were acquired in treatment position using a 1.5T MR scanner. Contours were adapted on 2D T2 turbo-spin-echo images, while synthetic CTs generated from T1 DIXON sequences were used for dose calculation. Adapted plans were delivered on a C-arm Linac using CBCT imaging for positioning. Quality assurance included independent Monte Carlo dose recalculations, automated plan parameters verification and a plan complexity check using in-house scripting. Across 99 adapted fractions, plan adaptation improved dosimetric outcomes, with a median 14% increase in Planning Target Volume (PTV) coverage and a 7% reduction in bowel D1cc (dose to 1 cc). Median times for MR imaging, contouring, and planning were 12, 12, and 20 min, respectively. The Virtual MR-Linac approach enables high-quality ART to compensate for inter-fractional motion without the costs and complexity of integrated systems. It improves resource utilization, maintains patient comfort, and offers a flexible, scalable solution for clinical implementation.
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Radiation Oncology cover
Radiation Oncology
IF:
3.2
Papers:
3.9K
Citations:
9.1K

Organization

D
department of radiation oncology
Scholars:
823
Papers: 267
Citations: 0
Cited Papers

Cited Papers

Citing Papers

Citing Papers