We report on the design, fabrication, and first tests of a tomographic scanner developed for proton computed tomography (pCT) of head-sized objects. After extensive preclinical testing, pCT is intended to be employed in support of proton therapy treatment planning and pre-treatment verification in patients undergoing particle-beam therapy. The scanner consists of two silicon-strip telescopes that track individual protons before and after the phantom, and a novel multistage scintillation detector that measures a combination of the residual energy and range of the proton, from which we derive the water equivalent path length (WEPL) of the protons in the scanned object. The set of WEPL values and the associated paths of protons passing through the object over a 360 ^° angular scan are processed by an iterative, parallelizable reconstruction algorithm that runs on modern GP-GPU hardware. In order to assess the performance of the scanner, we have performed tests with 200 MeV protons from the synchrotron of the Loma Linda University Medical Center and the IBA cyclotron of the Northwestern Medicine Chicago Proton Center. Our first objective was calibration of the instrument, including tracker channel maps and alignment as well as the WEPL calibration. Then we performed the first CT scans on a series of phantoms. The very high sustained rate of data acquisition, exceeding one million protons per second, allowed a full 360 ^° scan to be completed in less than 10 minutes, and reconstruction of a CATPHAN 404 phantom verified accurate reconstruction of the proton relative stopping power in a variety of materials.

Proton radiography has applications in patient alignment and verification procedures for proton beam radiation therapy. In this paper, we report an experiment which used 200 MeV protons to generate proton energy-loss and scattering radiographs of a hand phantom. The experiment used the first-generation proton computed tomography (CT) scanner prototype, which was installed on the research beam line of the clinical proton synchrotron at Loma Linda University Medical Center. It was found that while both radiographs displayed anatomical details of the hand phantom, the energy-loss radiograph had a noticeably higher resolution. Nonetheless, scattering radiography may yield more contrast between soft and bone tissue than energy-loss radiography, however, this requires further study. This study contributes to the optimization of the performance of the next-generation of clinical proton CT scanners. Furthermore, it demonstrates the potential of proton imaging (proton radiography and CT), which is now within reach of becoming available as a new, potentially low-dose medical imaging modality.

Objective . To propose a mathematical model for applying ionization detail (ID), the detailed spatial distribution of ionization along a particle track, to proton and ion beam radiotherapy treatment planning (RTP). Approach . Our model provides for selection of preferred ID parameters ( I _p ) for RTP, that associate closest to biological effects. Cluster dose is proposed to bridge the large gap between nanoscopic I _p and macroscopic RTP. Selection of I _p is demonstrated using published cell survival measurements for protons through argon, comparing results for nineteen I _p : N _k , k = 2, 3, …, 10, the number of ionizations in clusters of k or more per particle, and F _k , k = 1, 2, …, 10, the number of clusters of k or more per particle. We then describe application of the model to ID-based RTP and propose a path to clinical translation. Main results . The preferred I _p were N ₄ and F ₅ for aerobic cells, N ₅ and F ₇ for hypoxic cells. Significant differences were found in cell survival for beams having the same LET or the preferred N _k . Conversely, there was no significant difference for F ₅ for aerobic cells and F ₇ for hypoxic cells, regardless of ion beam atomic number or energy. Further, cells irradiated with the same cluster dose for these I _p had the same cell survival. Based on these preliminary results and other compelling results in nanodosimetry, it is reasonable to assert that I _p exist that are more closely associated with biological effects than current LET-based approaches and microdosimetric RBE-based models used in particle RTP. However, more biological variables such as cell line and cycle phase, as well as ion beam pulse structure and rate still need investigation. Significance . Our model provides a practical means to select preferred I _p from radiobiological data, and to convert I _p to the macroscopic cluster dose for particle RTP.

Previous work has shown that total variation superiorization (TVS) improves reconstructed image quality in proton computed tomography (pCT). The structure of the TVS algorithm has evolved since then and this paper investigated if this new algorithmic structure provides additional benefits to pCT image quality. Structural and parametric changes introduced to the original TVS algorithm included: (1) inclusion or exclusion of TV reduction requirement, (2) a variable number, N, of TV perturbation steps per feasibility-seeking iteration, and (3) introduction of a perturbation kernel 0 <; α <; 1. The structural change of excluding the TV reduction requirement check tended to have a beneficial effect for 3 ≤ N ≤ 6 and allows full parallelization of the TVS algorithm. Repeated perturbations per feasibility-seeking iterations reduced total variation (TV) and material dependent standard deviations for 3 ≤ N ≤ 6. The perturbation kernel α, effectively equal to α = 0.5 in the original TVS algorithm, reduced TV and standard deviations as α was increased beyond α = 0.5, but negatively impacted reconstructed relative stopping power (RSP) values for α > 0.75. The reductions in TV and standard deviations allowed feasibility-seeking with a larger relaxation parameter λ than previously used, without the corresponding increases in standard deviations experienced with the original TVS algorithm. This paper demonstrates that the modifications related to the evolution of the original TVS algorithm provide benefits in terms of both pCT image quality and computational efficiency for appropriately chosen parameter values.