Proton radiography and tomography have long promised benefit for proton therapy. Their first suggestion was in the early 1960s and the first published proton radiographs and CT images appeared in the late 1960s and 1970s, respectively. More than just providing anatomical images, proton transmission imaging provides the potential for the more accurate estimation of stopping-power ratio inside a patient and hence improved treatment planning and verification. With the recent explosion in growth of clinical proton therapy facilities, the time is perhaps ripe for the imaging modality to come to the fore. Yet many technical challenges remain to be solved before proton CT scanners become commonplace in the clinic. Research and development in this field is currently more active than at any time with several prototype designs emerging. This review introduces the principles of proton radiography and tomography, their historical developments, the raft of modern prototype systems and the primary design issues.

Proton radiography and tomography with application to proton therapy

This article reviews Proton Therapy Physics by H Paganetti , Boca Raton, FL, 2012 704 pp Price: $12995 ISBN: 9781439836446 (hardcover)

Proton Therapy Physics.

Purpose: Iterative projection reconstruction algorithms are currently the preferred reconstruction method in proton computed tomography (pCT). However, due to inconsistencies in the measured data arising from proton energy straggling and multiple Coulomb scattering, the noise in the reconstructed image increases with successive iterations. In the current work, the authors investigated the use of total variation superiorization (TVS) schemes that can be applied as an algorithmic add-on to perturbation-resilient iterative projection algorithms for pCT image reconstruction.

Methods: The block-iterative diagonally relaxed orthogonal projections (DROP) algorithm was used for reconstructing GEANT4 Monte Carlo simulated pCT data sets. Two TVS schemes added on to DROP were investigated; the first carried out the superiorization steps once per cycle and the second once per block. Simplifications of these schemes, involving the elimination of the computationally expensive feasibility proximity checking step of the TVS framework, were also investigated. The modulation transfer function and contrast discrimination function were used to quantify spatial and density resolution, respectively.

Results: With both TVS schemes, superior spatial and density resolution was achieved compared to the standard DROP algorithm. Eliminating the feasibility proximity check improved the image quality, in particular image noise, in the once-per-block superiorization, while also halving image reconstruction time. Overall, the greatest image quality was observed when carrying out the superiorization once per block and eliminating the feasibility proximity check.

Conclusions: The low-contrast imaging made possible with TVS holds a promise for its incorporation into future pCT studies.

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Total variation superiorization schemes in proton computed tomography image reconstruction

The use of hadron beams, especially proton beams, in cancer radiotherapy has expanded rapidly in the past two decades. To fully realize the advantages of hadron therapy over traditional x-ray and gamma-ray therapy requires accurate positioning of the Bragg peak throughout the tumor being treated. A half century ago, suggestions had already been made to use protons themselves to develop images of tumors and surrounding tissue, to be used for treatment planning. The recent global expansion of hadron therapy, coupled with modern advances in computation and particle detection, has led several collaborations around the world to develop prototype detector systems and associated reconstruction codes for proton computed tomography (pCT), as well as more simple proton radiography, with the ultimate intent to use such systems in clinical treatment planning and verification. Recent imaging results of phantoms in hospital proton beams are encouraging, but many technical and programmatic challenges remain to be overcome before pCT scanners will be introduced into clinics. This review introduces hadron therapy and the perceived advantages of pCT and proton radiography for treatment planning, reviews its historical development, and discusses the physics related to proton imaging, the associated experimental and computation issues, the technologies used to attack the problem, contemporary efforts in detector and computational development, and the current status and outlook.

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Review of medical radiography and tomography with proton beams

Purpose: Proton CT (pCT) has the potential to accurately measure the electron density map of tissues at low doses but the spatial resolution is prohibitive if the curved paths of protons in matter is not accounted for. The authors propose to account for an estimate of the most likely path of protons in a filtered backprojection (FBP) reconstruction algorithm. Methods: The energy loss of protons is first binned in several proton radiographs at different distances to the proton source to exploit the depth-dependency of the estimate of the most likely path. This process is named the distance-driven binning. A voxel-specific backprojection is then used to select the adequate radiograph in the distance-driven binning in order to propagate in the pCT image the best achievable spatial resolution in proton radiographs. The improvement in spatial resolution is demonstrated using Monte Carlo simulations of resolution phantoms. Results: The spatial resolution in the distance-driven binning depended on the distance of the objects from the source and was optimal in the binned radiograph corresponding to that distance. The spatial resolution in the reconstructed pCT images decreased with the depth in the scanned object but it was always better than previous FBP algorithms assuming straight line paths. In a water cylinder with 20 cm diameter, the observed range of spatial resolutions was 0.7 − 1.6 mm compared to 1.0 − 2.4 mm at best with a straight line path assumption. The improvement was strongly enhanced in shorter 200° scans. Conclusions: Improved spatial resolution was obtained in pCT images with filtered backprojection reconstruction using most likely path estimates of protons. The improvement in spatial resolution combined with the practicality of FBP algorithms compared to iterative reconstruction algorithms makes this new algorithm a candidate of choice for clinical pCT.

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Filtered backprojection proton CT reconstruction along most likely paths

The limited spatial resolution in proton computed tomography (pCT) in comparison to x-ray CT is related to multiple Coulomb scattering (MCS) within the imaged object The current generation pCT design utilizes silicon detectors that measure the position and direction of individual protons prior to and post-traversing the patient to maximize the knowledge of the path of the proton within the imaged object For efficient reconstruction with the proposed pCT system, one needs to develop compact and flexible mathematical formalisms that model the effects of MCS as the proton traverses the imaged object In this article, a compact, matrix-based most likely path (MLP) formalism is presented employing Bayesian statistics and a Gaussian approximation of MCS Using GEANT4 simulations in a homogeneous 20 cm water cube, the MLP expression was found to be able to predict the Monte Carlo tracks of 200 MeV protons to within 06 mm on average when employing 3sigma cuts on the relative exit angle and exit energy These cuts were found to eliminate the majority of events not conforming to the Gaussian model of MCS used in the MLP derivation M riszwana Banu

John Tafas

Papers

A maximum likelihood proton path formalism for application in proton computed tomography