Search

Purpose: To quickly and automatically propagate organ contours from pretreatment to fraction images in magnetic resonance (MR)‐guided prostate external‐beam radiotherapy. Methods: Five prostate cancer patients underwent 20 fractions of image‐guided external‐beam radiotherapy on a 1.5 T MR‐Linac system. For each patient, a pretreatment T2‐weighted three‐dimensional (3D) MR imaging (MRI) scan was used to delineate the clinical target volume (CTV) contours. The same scan was repeated during each fraction, with the CTV contour being manually adapted if necessary. A convolutional neural network (CNN) was trained for combined image registration and contour propagation. The network estimated the propagated contour and a deformation field between the two input images. The training set consisted of a synthetically generated ground truth of randomly deformed images and prostate segmentations. We performed a leave‐one‐out cross‐validation on the five patients and propagated the prostate segmentations from the pretreatment to the fraction scans. Three variants of the CNN, aimed at investigating supervision based on optimizing segmentation overlap, optimizing the registration, and a combination of the two were compared to results of the open‐source deformable registration software package Elastix. Results: The neural networks trained on segmentation overlap or the combined objective achieved significantly better Hausdorff distances between predicted and ground truth contours than Elastix, at the much faster registration speed of 0.5 s. The CNN variant trained to optimize both the prostate overlap and deformation field, and the variant trained to only maximize the prostate overlap, produced the best propagation results. Conclusions: A CNN trained on maximizing prostate overlap and minimizing registration errors provides a fast and accurate method for deformable contour propagation for prostate MR‐guided radiotherapy. [ABSTRACT FROM AUTHOR]

• First study of seminal vesicle intrafraction motion during MR-Linac RT sessions. • High quality 3D cine-MRI and seminal vesicle tracking is feasible during RT beam-on. • Seminal vesicles show larger intrafraction rotational spread than prostate. • 5 mm isometric expansion provides seminal vesicle coverage probability of 99%. To evaluate seminal vesicle (SV) intrafraction motion using cinematic magnetic resonance imaging (cine-MR) during the delivery of online adaptive MR-Linac radiotherapy fractions, in preparation of MR-guided extremely hypofractionated radiotherapy for intermediate to high-risk prostate cancer patients. Fifty prostate cancer patients were treated with 5 × 7.25 Gy on a 1.5 Tesla MR-Linac. 3D Cine-MR imaging was started simultaneously and acquired over the full beam-on period. Intrafraction motion in this cine-MR was determined for each SV separately with a previously validated soft-tissue contrast-based tracking algorithm. Motion statistics and coverage probability for the SVs and prostate were determined based on the obtained results. SV motion was automatically determined during the beam-on period (approx. 10 min) for 247 fractions. SV intrafraction motion shows larger spread than prostate intrafraction motion and increases over time. This difference is especially evident in the anterior and cranial translation directions. Significant difference in rotation about the left–right axis was found, with larger rotation for the SVs than the prostate. Intra-fraction coverage probability of 99% can be achieved when using 5 mm isometric expansion for the left and right SV and 3 mm for the prostate. This is the first study to investigate SV intrafraction motion during MR-guided RT sessions on an MR-Linac. We have shown that high quality 3D cine-MR imaging and SV tracking during RT is feasible with beam-on. The tracking method as described may be used as input for a fast replanning algorithm, which allows for intrafraction plan adaptation. [ABSTRACT FROM AUTHOR]

Radiation therapy (RT) is an essential component of effective cancer care and is used across nearly all cancer types. The delivery of RT is becoming more precise through rapid advances in both computing and imaging. The direct integration of magnetic resonance imaging (MRI) with linear accelerators represents an exciting development with the potential to dramatically impact cancer research and treatment. These impacts extend beyond improved imaging and dose deposition. Real-time MRI-guided RT is actively transforming the work flows and capabilities of virtually every aspect of RT. It has the opportunity to change entirely the delivery methods and response assessments of numerous malignancies. This review intends to approach the topic of MRI-based RT guidance from a vendor neutral and international perspective. It also aims to provide an introduction to this topic targeted towards oncologists without a speciality focus in RT. Speciality implications, areas for physician education and research opportunities are identified as they are associated with MRI-guided RT. The uniquely disruptive implications of MRI-guided RT are discussed and placed in context. We further aim to describe and outline important future changes to the speciality of radiation oncology that will occur with MRI-guided RT. The impacts on RT caused by MRI guidance include target identification, RT planning, quality assurance, treatment delivery, training, clinical workflow, tumour response assessment and treatment scheduling. In addition, entirely novel research areas that may be enabled by MRI guidance are identified for future investigation. • We present a review on the current state of MR-guided RT (RT). • Speciality implications, areas for physician education and research opportunities are identified. • Some impacts include target identification, quality assurance and tumour response assessment. [ABSTRACT FROM AUTHOR]