Vienna, Austria

ESTRO 2023

Session Item

Saturday
May 13
15:15 - 16:15
Stolz 2
Image processing and treatment evaluation
Eliana Maria Vasquez Osorio, United Kingdom;
Lando Bosma, The Netherlands
1430
Mini-Oral
Physics
Evaluation and correction of geometric accuracy in diffusion-weighted imaging on a 0.35T MR-LINAC
Bertrand Pouymayou, Switzerland
MO-0228

Abstract

Evaluation and correction of geometric accuracy in diffusion-weighted imaging on a 0.35T MR-LINAC
Authors:

Bertrand Pouymayou1, Philipp Wallimann1, Marco Piccirelli2, Sylwia Nowakowska3, Michael Mayinger1, Matthias Guckenberger1, Stephanie Tanadini-Lang1, Andreas Boss3, Nicolaus Andratschke1, Andrea Bink2

1University Hospital Zürich, Department of Radiation Oncology, Zürich, Switzerland; 2University Hospital Zürich, Department of Neuroradiology, Zürich, Switzerland; 3University Hospital Zürich, Department of Radiology, Zürich, Switzerland

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Purpose or Objective

Diffusion weighted (DW) MRI is a promising tool to assess early tumor response in radiotherapy. Apparent diffusion coefficient (ADC) maps conventionally rely on echo planar imaging (EPI). These sequences are sensitive to static magnetic field inhomogeneities especially in the phase encoding direction and are usually implemented with lower resolution. This makes their use in a low field MR-Linac context challenging. We designed a method to quantify the 3D-spatial integrity of such sequences and report potential improvements using the reversed phase-encode correction method.

Material and Methods

We evaluated the vendor single shot DW-EPI sequence on a 0.35T MRIdian (ViewRay) with the following standard parameters: TR=3200ms, TE=120ms, flip angle=90°, voxel 3x3x5mm3, FOV=30x30x15cm3, three orthogonal diffusion directions and five b-values (0, 200, 300, 500, 800 s.mm-2), gantry angle (GA) at 330°. We used a 10-channel head and neck coil and additionally tested a prototype head coil (4 channels). To evaluate the geometric accuracy of low-resolution sequences we printed a 3D grid (6mm thickness, 25mm spacing, PLA) defining 5^3 markers over a 10cm3 FOV. We evaluated the 3D-printing accuracy with a CT scan (Siemens, SOMATOM, 0.78x0.78x0.6mm3). The structure was immersed in water (Figure 1b-d). The marker detection was performed using a template matching approach implemented in Matlab. The distortion is defined as the Euclidean distance to the theoretical marker position after rigid registration (Procrustes method on the 27 central markers). We investigated the influence of GA, phase encoding directions, slice orientation and receiver bandwidth on the geometric accuracy. We further evaluated the performance of reversed phase-encode correction (Anderson et al., 2003, FSL implementation). The impact of this correction on ADC values was evaluated by estimating the free water ADC (expected value=1.77x10^-3mm2.s-1 at 20°C, Krynicki et al., 1978) in the phantom using the DTIFIT module of FSL.

Results

We report a mean manufacturing accuracy of 0.22±0.09mm (maximum 0.51mm) applying our marker detection method on the CT scan. The mean distortion over the different settings was 0.83±0.09mm accounting for the geometric stability of the sequence (Table 1). The distortions increase in average by 0.1mm with higher b-values (Figure 1e). The correction strategy reduced the distortion for all settings (on average by -40%) at the cost of doubling the acquisition time as it combines AP and PA images. ADC accuracy is difficult to evaluate without calibrated values, however the correction method reduced the ADCs variability and is on average closer to the expected value.


Conclusion

The 3D-spatial integrity after correction of the low resolution DW-EPI (mean distortion 0.49mm, maximum 1.24mm at 8.6cm from the isocenter) is close to our planning criteria (<1mm within 10cm radius). Further developments aim at reaching a higher resolution while preserving the spatial integrity to get closer to diagnostic standards.