Real-time dose reconstruction in proton therapy from in-beam PET measurements

Abstract

Objective. Clinical implementation of in-beam positron emission tomography (PET) monitoring in proton therapy (PT) requires the integration of an online fast and reliable dose calculation engine. This manuscript reports on the achievement of real-time reconstruction of 3D dose and activity maps with proton range verification from experimental in-beam PET measurements. Approach. Several cylindrical homogeneous PMMA phantoms were irradiated with a monoenergetic 70 MeV proton beam in a clinical facility. Additionally, PMMA range-shifting foils of varying thicknesses were placed at the proximal surface of the phantom to investigate range shift prediction capabilities. PET activity was measured using a state-of-the-art in-house developed six-module PET scanner equipped with online PET reconstruction capabilities. For real-time dose estimation, we integrated this system with an in-beam dose estimation algorithm, which combines a graphical processing unit-based 3D reconstruction algorithm with a dictionary-based software, capable of estimating deposited doses from the 3D PET activity images. The range shift prediction performance has been quantitatively studied in terms of the minimum dose to be delivered and the maximum acquisition time. Main results. With this framework, 3D dose maps were accurately reconstructed and displayed with a delay as short as one second. For a dose fraction of 8.4 Gy at the Bragg peak maximum, range shifts as small as 1 mm could be detected. The quantitative analysis shows that accumulating 20 s of statistics from the start of the irradiation, doses down to 1 Gy could be estimated online with total uncertainties smaller than 2 mm. Significance. The hardware and software combination employed in this work can deliver dose maps and accurately predict range shifts after short acquisition times and small doses, suggesting that real-time monitoring and dose reconstruction during PT are within reach. Future work will focus on testing the methodology in more complex clinical scenarios and on upgrading the PET prototype for increased sensitivity.