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SU‐E‐J‐237: Real‐Time 3D Anatomy Estimation From Undersampled MR Acquisitions
Author(s) -
Glitzner M,
de Senneville B Denis,
Lagendijk J,
Raaymakers B,
Crijns S
Publication year - 2015
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4924323
Subject(s) - undersampling , image registration , artificial intelligence , voxel , computer vision , computer science , image quality , displacement (psychology) , data acquisition , image resolution , reproducibility , process (computing) , nuclear medicine , medicine , mathematics , image (mathematics) , psychology , statistics , psychotherapist , operating system
Recent developments made MRI guided radiotherapy feasible. Performing simultaneous imaging during fractions can provide information about changing anatomy by means of deformable image registration for either immediate plan adaptations or accurate dose accumulation on the changing anatomy. In 3D MRI, however, acquisition time is considerable and scales with resolution. Furthermore, intra‐scan motion degrades image quality.In this work, we investigate the sensitivity of registration quality on imageresolution: potentially, by employing spatial undersampling, the acquisition timeof MR images for the purpose of deformable image registration can be reducedsignificantly.On a volunteer, 3D‐MR imaging data was sampled in a navigator‐gated manner, acquiring one axial volume (360×260×100mm 3 ) per 3s during exhale phase. A T1‐weighted FFE sequence was used with an acquired voxel size of (2.5mm 3 ) for a duration of 17min. Deformation vector fields were evaluated for 100 imaging cycles with respect to the initial anatomy using deformable image registration based on optical flow. Subsequently, the imaging data was downsampled by a factor of 2, simulating a fourfold acquisition speed. Displacements of the downsampled volumes were then calculated by the same process.In kidneyliver boundaries and the region around stomach/duodenum, prominent organ drifts could be observed in both the original and the downsampled imaging data. An increasing displacement of approximately 2mm was observed for the kidney, while an area around the stomach showed sudden displacements of 4mm. Comparison of the motile points over time showed high reproducibility between the displacements of high‐resolution and downsampled volumes: over a 17min acquisition, the componentwise RMS error was not more than 0.38mm.Based on the synthetic experiments, 3D nonrigid image registration shows little sensitivity to image resolution and the displacement information is preserved even when halving the resolution. This can be employed to greatly reduce image acquisition times for interventional applications in real‐time. This work was funded by the SoRTS consortium, which includes the industry partners Elekta, Philips and Technolution