AI Beam Angle Prediction in Proton Therapy for Brain Patients.

Abstract

Patients receiving brain Intensity-modulated Proton Therapy (IMPT) are treated with 1-3 fields. Typically, beam angles must be selected manually, requiring substantial planner time and experience. The choice of beam angles has a major impact on the treatment plan quality. An AI model was developed to automate this process aiming to improve efficiency and potentially plan quality. AI performance was tested by comparing predicted beam angles to the human ground truth angles and evaluating plans resulting from each set of beam angles. Previously treated IMPT brain patients were divided into a training (n = 40) and validation set (n = 10) for the AI. Beam-angle selection in the AI was cast as a multi-label classification problem, training the convolution neural network with a Circular Earth Mover's Distance based regularization and multi-label circular-smooth label technique. An analytical post-processing algorithm is employed to minimize distance to the target and avoid organs-at-risk. Finalized gantry angle predictions are discretized in steps of 5°. For an independent test set of n = 10 patients beam angles were predicted by the AI and compared to those chosen by human planners. Both sets of angles were used to create treatment plans with an automated knowledge-based planning (KBP) tool for brain IMPT utilizing single-field optimization and robust optimization. Plan differences are therefore solely due to the choice of beam angles as automated KBP removes human optimization variability. Resulting plan quality was compared by standard clinical dosimetric parameters to the CTV, brain, brainstem, cochlea, cord, eye, lens, optic chiasm, optic nerves, pituitary, and temporal lobes. All Human and AI selected beam angles are shown in the table. For cases 1-6, AI and Human selected beam angles were within ±15° and resulting plans showed minimal dosimetric differences. In cases 7-9 AI beam angles reduced max dose while keeping organ-at-risk dose within ±2 Gy. In case 10 the AI chosen beam angles reduced cord Dmax by 9.1 Gy but increased left eye Dmax by 4.9 Gy, other organs-at-risk showed minimal differences. Gantry beam angle selection was automated by a newly developed AI model and tested on 10 brain IMPT patients. The comparison showed that the AI often chooses similar beam angles to the human planners. When there are differences, dosimetric analysis demonstrated that plans created from AI beam angles have at least the same quality as the human ones. Results motivate further research into this approach showing the AI being a promising tool to fill a current gap in the strive for automating proton treatment planning, increasing planning efficiency and potentially quality.