Feasibility of interactive magnetic resonance imaging of moving anatomy for clinical practice

Magnetic Resonance Imaging only Workflow for Radiotherapy Simulation and Planning in Prostate Cancer

Magnetic resonance imaging (MRI) is often combined with computed tomography (CT) in prostate radiotherapy to optimise delineation of the target and organs-at-risk (OAR) while maintaining accurate dose calculation. Such a dual-modality workflow requires two separate imaging sessions, and it has some fundamental and logistical drawbacks. Due to the availability of new MRI hardware and software solutions, CT examinations can be omitted for prostate radiotherapy simulations. All information for treatment planning, including electron density maps and bony anatomy, can nowadays be obtained with MRI. Such an MRI-only simulation workflow reduces delineation ambiguities, eases planning logistics, and improves patient comfort; however, careful validation of the complete MRI-only workflow is warranted. The first institutes are now adopting this MRI-only workflow for prostate radiotherapy. In this article, we will review technology and workflow requirements for an MRI-only prostate simulation workflow.

Dose evaluation of fast synthetic-CT generation using a generative adversarial network for general pelvis MR-only radiotherapy

To enable magnetic resonance (MR)-only radiotherapy and facilitate modelling of radiation attenuation in humans, synthetic CT (sCT) images need to be generated. Considering the application of MR-guided radiotherapy and online adaptive replanning, sCT generation should occur within minutes. This work aims at assessing whether an existing deep learning network can rapidly generate sCT images for accurate MR-based dose calculations in the entire pelvis. A study was conducted on data of 91 patients with prostate (59), rectal (18) and cervical (14) cancer who underwent external beam radiotherapy acquiring both CT and MRI for patients' simulation. Dixon reconstructed water, fat and in-phase images obtained from a conventional dual gradient-recalled echo sequence were used to generate sCT images. A conditional generative adversarial network (cGAN) was trained in a paired fashion on 2D transverse slices of 32 prostate cancer patients. The trained network was tested on the remaining patients to generate sCT images. For 30 patients in the test set, dose recalculations of the clinical plan were performed on sCT images. Dose distributions were evaluated comparing voxel-based dose differences, gamma and dose-volume histogram (DVH) analysis. The sCT generation required 5.6 s and 21 s for a single patient volume on a GPU and CPU, respectively. On average, sCT images resulted in a higher dose to the target of maximum 0.3%. The average gamma pass rates using the 3%, 3 mm and 2%, 2 mm criteria were above 97 and 91%, respectively, for all volumes of interests considered. All DVH points calculated on sCT differed less than  ±2.5% from the corresponding points on CT. Results suggest that accurate MR-based dose calculation using sCT images generated with a cGAN trained on prostate cancer patients is feasible for the entire pelvis. The sCT generation was sufficiently fast for integration in an MR-guided radiotherapy workflow.

Three-dimensional liver motion tracking using real-time two-dimensional MRI

PURPOSE

Combined magnetic resonance imaging (MRI) systems and linear accelerators for radiotherapy (MR-Linacs) are currently under development. MRI is noninvasive and nonionizing and can produce images with high soft tissue contrast. However, new tracking methods are required to obtain fast real-time spatial target localization. This study develops and evaluates a method for tracking three-dimensional (3D) respiratory liver motion in two-dimensional (2D) real-time MRI image series with high temporal and spatial resolution.

METHODS

The proposed method for 3D tracking in 2D real-time MRI series has three steps: (1) Recording of a 3D MRI scan and selection of a blood vessel (or tumor) structure to be tracked in subsequent 2D MRI series. (2) Generation of a library of 2D image templates oriented parallel to the 2D MRI image series by reslicing and resampling the 3D MRI scan. (3) 3D tracking of the selected structure in each real-time 2D image by finding the template and template position that yield the highest normalized cross correlation coefficient with the image. Since the tracked structure has a known 3D position relative to each template, the selection and 2D localization of a specific template translates into quantification of both the through-plane and in-plane position of the structure. As a proof of principle, 3D tracking of liver blood vessel structures was performed in five healthy volunteers in two 5.4 Hz axial, sagittal, and coronal real-time 2D MRI series of 30 s duration. In each 2D MRI series, the 3D localization was carried out twice, using nonoverlapping template libraries, which resulted in a total of 12 estimated 3D trajectories per volunteer. Validation tests carried out to support the tracking algorithm included quantification of the breathing induced 3D liver motion and liver motion directionality for the volunteers, and comparison of 2D MRI estimated positions of a structure in a watermelon with the actual positions.

RESULTS

Axial, sagittal, and coronal 2D MRI series yielded 3D respiratory motion curves for all volunteers. The motion directionality and amplitude were very similar when measured directly as in-plane motion or estimated indirectly as through-plane motion. The mean peak-to-peak breathing amplitude was 1.6 mm (left-right), 11.0 mm (craniocaudal), and 2.5 mm (anterior-posterior). The position of the watermelon structure was estimated in 2D MRI images with a root-mean-square error of 0.52 mm (in-plane) and 0.87 mm (through-plane).

CONCLUSIONS

A method for 3D tracking in 2D MRI series was developed and demonstrated for liver tracking in volunteers. The method would allow real-time 3D localization with integrated MR-Linac systems.