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.
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.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
OTHER
Masking
NONE
Enrollment
brain radiotherapy planned on synthetic CTs
Erlangen, Universitätsklinikum Strahlenklinik
Erlangen, Germany
Proportion of patients that can successfully be treated in an MRI-only workflow
All criteria have to be met for the MRI-only workflow to be classified as successful: Verification criteria that will be assessed: 1. Can the sCT be generated and is the sCT clinically utilizable? 2. Are the three rotations needed for CT-MRI registration each ≤ 3°? 3. Can a treatment plan be generated and verified using the sCT? 4. Is the dosimetric difference between sCT and CT based treatment plan in the planning target volume ≤ 3%? 5. Is the dosimetric difference between the sCT and CT based treatment plan in affected organs at risk (receiving \> 10% of prescribed dose) ≤ 3%? 6. Are the couch correction parameters during patient positioning in the rotational degrees of freedom ≤ 3°?
Time frame: 12 month
Reasons that lead to unfeasibility of an MRI-only workflow
Presence (Yes/No) of individual reasons responsible for the unfeasibility of the MRI-only workflow, as assessed with a predefined checklist.
Time frame: 12 month
Dosimetric differences between MRI-only and standard workflow for radiotherapy treatment planning
Paired difference in Dose-volume-histogram parameters (Target coverage, mean, median, near maximum and minimum dose) between MRI-only and standard radiotherapy treatment workflow.
Time frame: 12 month
Measurement of intra-MRI patient positional changes
Patient shift (vector magnitude) and rotational errors occuring during the course of MRI acquisition due to patient movement, as assessed by rigid registration of the last acquired MRI sequence in reference to the first sequence.
Time frame: 12 month
Organ at risk contouring accuracy on MRI data
Similarity of organ at risk segmentations defined in MRI compared to reference segmentations defined in CT as assessed by the volumetric and surface Dice score, as well as mean surface and Hausdorff distances.
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.
54
Time frame: 12 month