Abstract Book

S284

ESTRO 37

4 University of Wollongong, Centre for Medical Radiation Physics, Wollongong, Australia Purpose or Objective Investigations of MRI-linac systems for clinical implementation for real-time image guided radiotherapy are increasing. The bespoke magnet design of the Australian MRI-linac prototype allows for an open configuration with 2 imaging orientations and imaging gradients designed to work across this gap. Hence the magnet has a reduced uniformity and gradient linearity compared to clinical systems so the need to assess geometric distortion is an important part of the development of this technology. This work quantifies the geometric distortion within the defined imaging volume on the Australian MRI-linac system with 2 techniques: 1. Distortion assessment based comparing MRI- linac to images acquired on a clinical MRI scanner (MRI-sim) Phantom based sequence dependent distortion assessment and correction Material and Methods The distortion assessment methods were as follows: 1. Volunteer brain images were acquired with the MRI-linac and a 3T MRI-sim, the latter with known negligible systematic distortion within the imaging ROI. The MRI-linac images were deformably registered to the MRI-sim. This produced a corrected MRI-linac image and quantified the distortion observed within the defined anatomical DSV relative to routine clinical MRI scans. 2.

Conclusion Two techniques for distortion assessment have been shown and an offline geometric distortion correction method implemented. Ongoing work is to provide a sequence independent on-line correction for gradient non linearity. PV-0534 Multi-Resolution radial MRI to Reduce IDLE time in pre-beam imaging on an MR-Linac (MR-RIDDLE) T. Bruijnen 1 , B. Stemkens 1 , J.J.W. Lagendijk 1 , C.A.T. Van den Berg 1 , R.H.N. Tijssen 1 1 University Medical Center Utrecht, Radiotherapy, Utrecht, The Netherlands Purpose or Objective The exquisite soft-tissue contrast of MRI makes MR-Linac (MRL) systems the ultimate tool for online adaptive radiation treatments. The acquisition time of a conventional 3D pre-beam imaging sequence is several minutes, which results in long idle times before the first clinical actions can be performed. An additional 4D-MRI to characterize motion and obtain a representative (mid- position) motion state, further increases the pre-beam imaging time up to 10 minutes. To overcome these problems we have developed a single, multi-resolution, multi-purpose, radial MR sequence that allows image reconstruction to commence during data acquisition. The resolution and dimensionality (3D or 4D) are flexible and optimized with respect to the amount of data acquired at Fig 1 illustrates the general concept of the proposed pre- beam imaging protocol. Imaging data are continuously acquired during free-breathing using a 3D golden angle stack-of-stars readout [1]. Radially sampled sequences are robust to motion-induced artefacts and inherently portray the time-averaged (blurred) position of the anatomy [2]. After limited acquisition time we utilize the multi-resolution feature of golden angle radial sampling to interchange temporal and spatial resolution to obtain a first low resolution blurred image (3x3x4mm). This volume can rapidly be reconstructed and initially used for contour propagation. Data collection is continued and a second reconstruction is performed with increased spatial resolution (1.5x1.5x4mm). Next, the inherent self-gating is exploited to perform a motion-weighted image reconstruction (soft-gating) [3] to reduce respiratory- induced blurring of the mid-position. After completing the acquisition, a full 4D-MRI with 10 respiratory phases is reconstructed. each instant in time. Material and Methods

2.

A 3D large distortion phantom was scanned on both the MRI-linac with the current test sequence and a CT scanner, with the images deformably registered to the corresponding phantom CT to obtain a sequence specific correction deformation field. The deformation volume was calculated for a cylindrical volume of 300 mm diameter and 210 mm in length. A smaller QA phantom was also scanned on the MRI-linac and the deformation field obtained from the larger phantom was applied to this image and a ‘corrected’ QA phantom obtained. This was compared to the corresponding CT to assess the correction accuracy. Phantom scans were perpendicular to volunteer acquisitions (figure a).

A b-spline registration algorithm (NiftyReg Open source software) was utilised for the deformable image registrations. Results Linac-sim comparison: No noticeable distortion was evident in rigidly registered images over a 13x17x15 cm 3 (x,y,z) volume (Figure b) around the brain. Analysis of the deformation field showed the maximum distortion was 5.2 mm (mean: 2.6±1.7 mm) between the MRI- simulator and MRI-linac images. Sequence dependent assessment and correction: Distortion values within cylindrical ROIs as measured with the large 3D distortion phantom are shown in the table below. When the correction deformation field was applied to the secondary QA phantom the resulting imaged matched the corresponding CT within 2 mm accuracy. Figure c shows an overlay of distorted (yellow) and corrected (green) QA phantom images.