Program Information

Feasibility of Real Time MRI-Guidance in Proton Therapy

M Moteabbed

M Moteabbed*, J Schuemann, H Paganetti, Massachusetts General Hospital, Boston, MA

TH-E-BRA-6 Thursday 1:00:00 PM - 2:50:00 PM Room: Ballroom A

Purpose: To investigate the feasibility of in-vivo real-time MRI guidance as a potential treatment monitoring technique in proton therapy if such a system would be installed in a treatment room.

Methods: The effect of MRI magnetic field on the proton dose distribution inside the patient anatomy was studied using the TOPAS (Tool for Particle Simulation) Monte Carlo (MC) tool. The right and left lateral fields for a prostate patient with 50 Gy prescribed dose (excluding the boost) were simulated based on the existing treatment plans using 0, 0.5 and 1.5 T uniform magnetic field in the superior-inferior direction. Dose Volume Histograms were compared for the CTV and several organs at risk (OARs) such as bladder, rectum and femoral heads.

Results: Similar for both beams, lateral deflection of 2.5 and 7.3 cm was observed for 0.5 and 1.5 T fields at the end of range, respectively. It was found that an additional gantry rotation of 10 and 30 degrees could correct for the curved path of the proton beam. Therefore, the beams were re-simulated in the magnetic field, applying an anterior-posterior shift in the beam position. Using a beam position shift of 2.5 cm in the planning/delivery process could very well compensate for the magnetic field deflection in 0.5 T setting. The D95 varied by only 0.3 Gy. Also the OARs dose was maintained at the same level compared with the original treatment. However, the beams in 1.5 T field could not be well approximated by a simple shift of the field and the CTV and OAR doses were higher than prescribed.

Conclusions: Since most existing open-MRI systems operate at or less than 0.5 T, proton-MRI treatments can be potentially planned by revising planned beam angles and considering MC-determined beam position shifts requiring only subsequent fine-tuning of the treatment plan optimization.

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