Soft-tissue prostate intrafraction motion tracking in 3D cine-MR for MR-guided radiotherapy

PURPOSE To develop a method to automatically determine intrafraction motion of the prostate based on soft tissue contrast on 3D cine-magnetic resonance (MR) images with high spatial and temporal resolution. METHODS Twenty-nine patients who underwent prostate stereotactic body radiotherapy (SBRT), with four implanted cylindrical gold fiducial markers (FMs), had cine-MR imaging sessions after each of five weekly fractions. Each cine-MR session consisted of 55 sequentially obtained 3D data sets ('dynamics') and was acquired over a 11 second period, covering a total of 10 minutes. The prostate was delineated on the first dynamic of every dataset and this delineation was used as the starting position for the soft tissue tracking. Each subsequent dynamic was rigidly aligned to the first dynamic, based on the contrast of the prostate. The obtained translation and rotation describes the intrafraction motion of the prostate. The algorithm was applied to 6270 dynamics over 114 scans of 29 patients and the results were validated by comparing to previously obtained fiducial marker tracking data of the same dataset. Our proposed tracking method was also retro-perspectively applied to cine-MR images acquired during MR-guided radiotherapy of our first prostate patient treated on the MR-Linac. RESULTS The difference in the 3D translation results between the soft tissue and marker tracking was below 1 mm for 98.2% of the time. The mean translation at 10 minutes were X: 0.0±0.8 mm, Y: 1.0±1.8 mm and Z: -1.0±1.8 mm. The mean rotation results at 10 minutes were X: -0.3±2.1° , Y: 0.1±0.6° and Z: 0.0±0.7°. CONCLUSION A fast, robust and accurate soft tissue tracking algorithm was developed which obviates the need for fiducial markers during MR-guided prostate radiotherapy. To our knowledge, this is the first data using full 3D cine-MR images for real-time soft-tissue prostate tracking, which is validated against previously obtained marker tracking data.

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