Quantifying intrafractional gastric motion using auto-segmentation on MRI: Deformation and respiratory-induced displacement compared.

Abstract

For accurate pre-operative gastric radiotherapy, intrafractional changes must be taken into account. The aim of this study is to quantify local gastric deformations and compare these deformations with respiratory-induced displacement. Coronal 2D MRI scans (15-16min; 120 repetitions of 25-27 interleaved slices) were obtained for 18 healthy volunteers. A deep-learning network was used to auto-segment the stomach. To separate out respiratory-induced displacements, auto-segmentations were rigidly shifted in superior-inferior (SI) direction to align the centre of mass (CoM) within every slice. From these shifted auto-segmentations, 3D iso-probability surfaces (isosurfaces) were established: a reference surface for POcc =0.50 and 50 other isosurfaces (from POcc =0.01 to 0.99), with POcc indicating the probability of occupation by the stomach. For each point on the reference surface, distances to all isosurfaces were determined and a cumulative Gaussian was fitted to this probability-distance dataset to obtain a standard deviation (SDdeform ) expressing local deformation. For each volunteer, we determined median and 98th percentile of SDdeform over the reference surface and compared these with the respiratory-induced displacement SDresp , that is, the SD of all CoM shifts (paired Wilcoxon signed-rank, α=0.05). Larger deformations were mostly seen in the antrum and pyloric region. Median SDdeform (range, 2.0-2.9mm) was smaller than SDresp (2.7-8.8mm) for each volunteer (p<0.00001); 98th percentile of SDdeform (3.2-7.3mm) did not significantly differ from SDresp (p=0.13). Locally, gastric deformations can be large. Overall, however, these deformations are limited compared to respiratory-induced displacement. Therefore, unless respiratory motion is considerably reduced, the need to separately include these deformation uncertainties in the treatment margins may be limited.