Spots Global Cancer Trial Database for Clinical Feasibility of Brain Radiotherapy Using Synthetic CTs in an MRI-only Workflow

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Trial Identification

Brief Title: Clinical Feasibility of Brain Radiotherapy Using Synthetic CTs in an MRI-only Workflow

Official Title: Feasibility Study of an MRI-only Workflow: Use of Synthetic CTs Generated From MRI Data for MRI-based Radiotherapy

Study ID: NCT06106997

Conditions

Brain Tumor, Primary

Brain Tumor - Metastatic

Interventions

brain radiotherapy

Study Description

Brief Summary: The goal of this observational study is to show the feasibility of an MRI-only workflow in brain radiotherapy. The main question it aims to answer is: * Is an MRI-only workflow based on deep learning sCTs feasible in clinical routine? Participants will be treated as in clinical routine, but treatment planning will be based on sCTs, that are generated from MRI images. The dosimetrical equivalence to the standard CT based workflow will be tested at several points in the study.

Detailed Description: The purpose of this clinical study is to investigate the clinical feasibility of a deep learning-based MRI-only workflow for brain radiotherapy, that eliminates the registration uncertainty through calculation of a synthetic CT (sCT) from MRI data. A total of 54 patients with an indication for radiation treatment of the brain and stereotactic mask immobilization will be recruited. All study patients will receive standard therapy and imaging including both CT and MRI. All patients will receive dedicated RT-MRI scans in treatment position. An sCT will be reconstructed from an acquired MRI DIXON-sequence using a commercially available deep learning solution on which subsequent radiotherapy planning will be performed. Through multiple quality assurance (QA) measures and reviews during the course of the study, the feasibility of an MRI-only workflow and comparative parameters between sCT and standard CT workflow will be investigated holistically. These QA measures include feasibility and quality of image guidance (IGRT) at the linear accelerator using sCT derived digitally reconstructed radiographs in addition to potential dosimetric deviations between the CT and sCT plan. The aim of this clinical study is to establish a brain MRI-only workflow as well as to identify risks and QA mechanisms to ensure a safe integration of deep learning-based sCT into radiotherapy planning and delivery.