Blake Schultze

A Fast Experimental Scanner for Proton CT: Technical Performance and First Experience With Phantom Scans

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.

Reconstructing highly accurate relative stopping powers in proton computed tomography

PROTON computed tomography (pCT) is an evolving tomographic imaging modality with applications in proton and ion therapy. The method allows direct reconstruction of relative stopping power of patient tissues in a 3D-fashion. The pCT collaboration has built first experimental prototypes of pCT scanning systems [1] and has developed approaches to reconstruct proton CT images based on registering the coordinates and water equivalent path length (WEPL) of individual protons traversing the scanned volume. From these data one reconstructs the object boundary (hull) and initial image based on filtered back projection (FBP), calculates a most likely path (MLP) for each proton, and improves the initial image iteratively by solving a large linear system of equations of the form Ax = b using an iterative projection algorithm [2].

Space carving and filtered back-projection as preconditioners for proton computed tomography reconstruction

This paper considers how to determine the boundary of an object by comparing two methods: space carving (SC) and filtered back-projection (FBP). Determination of the boundary is an important first step in proton CT. The boundary is used to set up the large sparse linear system of equations, which are then solved to determine the relative stopping power of each element (voxel) in the object. For instance, to find the path of the proton through the object, the entry and exit points on the boundary must first be found. The boundary also becomes important in the iterative reconstruction, as only voxels inside the object are updated, to reduce computational complexity and prevent external artifacts from forming. SC and FBP are compared on speed and boundary results for four cases: (1) noiseless simulated data, (2) noisy simulated data, (3) a real pediatric head phantom, and (4) a real rat. The usefulness and potential of both methods are discussed and future directions are outlined.

A proton simulator for testing implementations of proton CT reconstruction algorithms on GPGPU clusters

Proton computed tomography (pCT) is an image modality that will improve treatment planning for patients receiving proton radiation therapy compared with the current treatment techniques, which are based on X-ray CT. Reconstruction of a pCT image requires solving a large and sparse system of linear equations, which should be accomplished within a few minutes in order to be clinically practical. Analyzing the efficiency of potentially clinical reconstruction implementations requires multiple quality pCT data sets. The purpose of this paper is to describe the simulator that was developed to generate realistic pCT data sets to be used in testing the efficiency of reconstruction algorithms, in particular string-averaging and block-iterative projection algorithms using sparse matrix formats on General Purpose Graphics Processing Units (GPGPU)s.

Results from a pre-clinical head scanner for proton CT

We report on the first beam test results with our pre-clinical (Phase-II) head scanner developed for proton computed tomography (pCT). After extensive preclinical testing, pCT will be employed in support of proton therapy treatment planning and pre-treatment verification in patients undergoing treatment with particle beam therapy. The Phase-II pCT system consists of two silicon-strip telescopes that track individual protons before and after the phantom or patient, 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 associated paths of protons passing through the object over a 360° angular scan is 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 beam tests with 200 MeV protons from the synchrotron of the Loma Linda University Medical Center. The first objective was the 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.

Incorporating robustness in diagonally-relaxed orthogonal projections method for proton computed tomography

Iterative algorithms such as ART, DROP, and CARP are commonly used in reconstructing computed tomography images, but only account for errors in the measurements. Errors in the predicted path and intersection lengths, or even blocks of missing measurements can result in degraded image quality. Robust techniques allow for errors in other areas of the model and produce good images that show less sensitivity. In this paper we introduce a robust version of DROP and compare its performance advantages to the standard DROP algorithm on on real data.