A comparison of proton stopping power measured with proton CT and x-ray CT in fresh postmortem porcine structures

Proton CT on biological phantoms for x-ray CT calibration in proton treatment planning

Objective.To present and characterize a novel method for x-ray computed tomography (xCT) calibration in proton treatment planning, based on proton CT (pCT) measurements on biological phantoms.Approach.A pCT apparatus was used to perform direct measurements of 3D stopping power relative to water (SPR) maps on stabilized, biological phantoms. Two single-energy xCT calibration curves-i.e. tissue substitutes and stoichiometric-were compared to pCT data. Moreover, a new calibration method based on these data was proposed, and verified against intra- and inter-species variability, dependence on stabilization, beam-hardening conditions, and analysis procedures.Main results.Biological phantoms were verified to be stable in time, with a dependence on temperature conditions, especially in the fat region: (-2.5 0.5) HU °C-1. The pCT measurements were compared with standard xCT calibrations, revealing an average SPR discrepancy within ±1.60% for both fat and muscle regions. In the bone region the xCT calibrations overestimated the pCT-measured SPR of the phantom, with a maximum discrepancy of about +3%. As a result, a new cross-calibration curve was directly extracted from the pCT data. Overall, the SPR uncertainty margin associated with this curve was below 3%; fluctuations in the uncertainty values were observed across the HU range. Cross-calibration curves obtained with phantoms made of different animal species and anatomical parts were reproducible with SPR discrepancies within 3%. Moreover, the stabilization procedure did not affect the resulting curve within a 2.2% SPR deviation. Finally, the cross-calibration curve was affected by the beam-hardening conditions on xCTs, especially in the bone region, while dependencies below 2% resulted from the image registration procedure.Significance.Our results showed that pCT measurements on biological phantoms may provide an accurate method for the verification of current xCT calibrations and may represent a tool for the implementation of a new calibration method for proton treatment planning.

Meeting the detector challenges for pre-clinical proton and ion computed tomography

Six decades after its conception, proton computed tomography (pCT) and proton radiography have yet to be used in medical clinics. However, good progress has been made on relevant detector technologies in the past two decades, and a few prototype pCT systems now exist that approach the performance needed for a clinical device. The tracking and energy-measurement technologies in common use are described, as are the few pCT scanners that are in routine operation at this time. Most of these devices still look like detector R&D efforts as opposed to medical devices, are difficult to use, are at least a factor of five slower than desired for clinical use, and are too small to image many parts of the human body. Recommendations are made for what to consider when engineering a pre-clinical pCT scanner that is designed to meet clinical needs in terms of performance, cost, and ease of use.

Focus stacking single-event particle radiography for high spatial resolution images and 3D feature localization

Objective.We demonstrate a novel focus stacking technique to improve spatial resolution of single-event particle radiography (pRad), and exploit its potential for 3D feature detection.Approach.Focus stacking, used typically in optical photography and microscopy, is a technique to combine multiple images with different focal depths into a single super-resolution image. Each pixel in the final image is chosen from the image with the largest gradient at that pixel's position. pRad data can be reconstructed at different depths in the patient based on an estimate of each particle's trajectory (called distance-driven binning; DDB). For a given feature, there is a depth of reconstruction for which the spatial resolution of DDB is maximal. Focus stacking can hence be applied to a series of DDB images reconstructed from a single pRad acquisition for different depths, yielding both a high-resolution projection and information on the features' radiological depth at the same time. We demonstrate this technique with Geant4 simulated pRads of a water phantom (20 cm thick) with five bone cube inserts at different depths (1 × 1 × 1 cm3) and a lung cancer patient.Main results.For proton radiography of the cube phantom, focus stacking achieved a median resolution improvement of 136% compared to a state-of-the-art maximum likelihood pRad reconstruction algorithm and a median of 28% compared to DDB where the reconstruction depth was the center of each cube. For the lung patient, resolution was visually improved, without loss in accuracy. The focus stacking method also enabled to estimate the depth of the cubes within few millimeters accuracy, except for one shallow cube, where the depth was underestimated by 2.5 cm.Significance.Focus stacking utilizes the inherent 3D information encoded in pRad by the particle's scattering, overcoming current spatial resolution limits. It further opens possibilities for 3D feature localization. Therefore, focus stacking holds great potential for future pRad applications.

A review of the clinical introduction of 4D particle therapy research concepts

Background and purpose

Many 4D particle therapy research concepts have been recently translated into clinics, however, remaining substantial differences depend on the indication and institute-related aspects. This work aims to summarise current state-of-the-art 4D particle therapy technology and outline a roadmap for future research and developments.

Material and methods

This review focused on the clinical implementation of 4D approaches for imaging, treatment planning, delivery and evaluation based on the 2021 and 2022 4D Treatment Workshops for Particle Therapy as well as a review of the most recent surveys, guidelines and scientific papers dedicated to this topic.

Results

Available technological capabilities for motion surveillance and compensation determined the course of each 4D particle treatment. 4D motion management, delivery techniques and strategies including imaging were diverse and depended on many factors. These included aspects of motion amplitude, tumour location, as well as accelerator technology driving the necessity of centre-specific dosimetric validation. Novel methodologies for X-ray based image processing and MRI for real-time tumour tracking and motion management were shown to have a large potential for online and offline adaptation schemes compensating for potential anatomical changes over the treatment course. The latest research developments were dominated by particle imaging, artificial intelligence methods and FLASH adding another level of complexity but also opportunities in the context of 4D treatments.

Conclusion

This review showed that the rapid technological advances in radiation oncology together with the available intrafractional motion management and adaptive strategies paved the way towards clinical implementation.

Effect of extended field-of-view approaches on the accuracy of stopping power ratio estimation for single-energy computed tomography simulators

BACKGROUND

Extended field-of-view (eFOV) methods have been proposed to generate larger demonstration FOVs for computed tomography (CT) simulators with a limited scanning FOV (sFOV) size in order to ensure accurate dose calculation and patient collision avoidance. Although the efficacy of these strategies has been evaluated for photon applications, the effect of stopping power ratio (SPR) estimation on proton therapy has not been studied. This study investigated the effect of an eFOV approach on the accuracy of SPR to water estimation in homogeneous and heterogeneous phantoms.

MATERIALS AND METHODS

To simulate patient geometries, tissue-equivalent material (TEM) and customized extension phantoms were used. The TEM phantom supported various rod arrangements through predefined holes. Images were reconstructed to three FOV sizes using a commercial eFOV technique. A single-energy CT stoichiometric method was used to generate Hounsfield unit (HU) to SPR (HU-to-SPR) conversion curves for each FOV. To investigate the effect of rod location in the sFOV and eFOV regions, eight TEM rods were placed at off-center distances in the homogeneous phantom and scanned individually. Similarly, 16 TEM rods were placed in the heterogeneous TEM phantom and scanned simultaneously.

RESULTS

The conversion curves derived from the sFOV and eFOV data were identical. The average SPR differences of soft-tissue, bone, and lung materials for rods placed at various off-center locations were 3.3%, 4.8%, and 39.6%, respectively. In the heterogeneous phantom, the difference was within 1.0% in the absence of extension. However, in the presence of extension, the difference increased to 2.8% for all rods, except for lung materials, whose difference was 4.8%.

CONCLUSIONS

When an eFOV method is used, the SPR variation in phantoms considerably increases for all TEM rods, especially for lung TEM rods. This phenomenon may substantially increase the uncertainty of HU-to-SPR conversion. Therefore, image reconstruction with a standard FOV size is recommended.

A stopping criterion for iterative proton CT image reconstruction based on correlated noise properties

BACKGROUND

Whereas filtered back projection algorithms for voxel-based CT image reconstruction have noise properties defined by the filter, iterative algorithms must stop at some point in their convergence and do not necessarily produce consistent noise properties for images with different degrees of heterogeneity.

PURPOSE

A least-squares iterative algorithm for proton CT (pCT) image reconstruction converges toward a unique solution for relative stopping power (RSP) that optimally fits the protons. We present a stopping criterion that delivers solutions with the property that correlations of RSP noise between voxels are relatively low. This provides a method to produce pCT images with consistent noise properties useful for proton therapy treatment planning, which relies on summing RSP along lines of voxels. Consistent noise properties will also be useful for future studies of image quality using metrics such as contrast to noise ratio, and to compare RSP noise and dose of pCT with other modalities such as dual-energy CT.

METHODS

With simulated and real images with varying heterogeneity from a prototype clinical proton imaging system, we calculate average RSP correlations between voxel pairs in uniform regions-of-interest versus distance between voxels. We define a parameter r, the remaining distance to the unique solution relative to estimated RSP noise, and our stopping criterion is based on r falling below a chosen value.

RESULTS

We find large correlations between voxels for larger values of r, and anticorrelations for smaller values. For r in the range of 0.5-1, voxels are relatively uncorrelated, and compared to smaller values of r have lower noise with only slight loss of spatial resolution.

CONCLUSIONS

Iterative algorithms not using a specific metric or rationale for stopping iterations may produce images with an unknown and arbitrary level of convergence or smoothing. We resolve this issue by stopping iterations of a least-squares iterative algorithm when r reaches the range of 0.5-1. This defines a pCT image reconstruction method with consistent statistical properties optimal for clinical use, including for treatment planning with pCT images.

A systematic review of volumetric image guidance in proton therapy

In recent years, proton therapy centres have begun to shift from conventional 2D-kV imaging to volumetric imaging systems for image guided proton therapy (IGPT). This is likely due to the increased commercial interest and availability of volumetric imaging systems, as well as the shift from passively scattered proton therapy to intensity modulated proton therapy. Currently, there is no standard modality for volumetric IGPT, leading to variation between different proton therapy centres. This article reviews the reported clinical use of volumetric IGPT, as available in published literature, and summarises their utilisation and workflow where possible. In addition, novel volumetric imaging systems are also briefly summarised highlighting their potential benefits for IGPT and the challenges that need to be overcome before they can be used clinically.

Validation of an MR-based multimodal method for molecular composition and proton stopping power ratio determination using ex vivo animal tissues and tissue-mimicking phantoms

Objective. Range uncertainty in proton therapy is an important factor limiting clinical effectiveness. Magnetic resonance imaging (MRI) can measure voxel-wise molecular composition and, when combined with kilovoltage CT (kVCT), accurately determine mean ionization potential (Im), electron density, and stopping power ratio (SPR). We aimed to develop a novel MR-based multimodal method to accurately determine SPR and molecular compositions. This method was evaluated in tissue-mimicking andex vivoporcine phantoms, and in a brain radiotherapy patient.Approach. Four tissue-mimicking phantoms with known compositions, two porcine tissue phantoms, and a brain cancer patient were imaged with kVCT and MRI. Three imaging-based values were determined: SPRCM(CT-based Multimodal), SPRMM(MR-based Multimodal), and SPRstoich(stoichiometric calibration). MRI was used to determine two tissue-specific quantities of the Bethe Bloch equation (Im, electron density) to compute SPRCMand SPRMM. Imaging-based SPRs were compared to measurements for phantoms in a proton beam using a multilayer ionization chamber (SPRMLIC).Main results. Root mean square errors relative to SPRMLICwere 0.0104(0.86%), 0.0046(0.45%), and 0.0142(1.31%) for SPRCM, SPRMM, and SPRstoich, respectively. The largest errors were in bony phantoms, while soft tissue and porcine tissue phantoms had <1% errors across all SPR values. Relative to known physical molecular compositions, imaging-determined compositions differed by approximately ≤10%. In the brain case, the largest differences between SPRstoichand SPRMMwere in bone and high lipids/fat tissue. The magnitudes and trends of these differences matched phantom results.Significance. Our MR-based multimodal method determined molecular compositions and SPR in various tissue-mimicking phantoms with high accuracy, as confirmed with proton beam measurements. This method also revealed significant SPR differences compared to stoichiometric kVCT-only calculation in a clinical case, with the largest differences in bone. These findings support that including MRI in proton therapy treatment planning can improve the accuracy of calculated SPR values and reduce range uncertainties.

Image-Guided Proton Therapy: A Comprehensive Review

Image guidance for radiation therapy can improve the accuracy of the delivery of radiation, leading to an improved therapeutic ratio. Proton radiation is able to deliver a highly conformal dose to a target due to its advantageous dosimetric properties, including the Bragg peak. Proton therapy established the standard for daily image guidance as a means of minimizing uncertainties associated with proton treatment. With the increasing adoption of the use of proton therapy over time, image guidance systems for this modality have been changing. The unique properties of proton radiation present a number of differences in image guidance from photon therapy. This paper describes CT and MRI-based simulation and methods of daily image guidance. Developments in dose-guided radiation, upright treatment, and FLASH RT are discussed as well.

An inception network for positron emission tomography based dose estimation in carbon ion therapy

Objective. We aim to evaluate a method for estimating 1D physical dose deposition profiles in carbon ion therapy via analysis of dynamic PET images using a deep residual learning convolutional neural network (CNN). The method is validated using Monte Carlo simulations of 12C ion spread-out Bragg peak (SOBP) profiles, and demonstrated with an experimental PET image. Approach. A set of dose deposition and positron annihilation profiles for monoenergetic 12C ion pencil beams in PMMA are first generated using Monte Carlo simulations. From these, a set of random polyenergetic dose and positron annihilation profiles are synthesised and used to train the CNN. Performance is evaluated by generating a second set of simulated 12C ion SOBP profiles (one 116 mm SOBP profile and ten 60 mm SOBP profiles), and using the trained neural network to estimate the dose profile deposited by each beam and the position of the distal edge of the SOBP. Next, the same methods are used to evaluate the network using an experimental PET image, obtained after irradiating a PMMA phantom with a 12C ion beam at QST’s Heavy Ion Medical Accelerator in Chiba facility in Chiba, Japan. The performance of the CNN is compared to that of a recently published iterative technique using the same simulated and experimental 12C SOBP profiles. Main results. The CNN estimated the simulated dose profiles with a mean relative error (MRE) of 0.7% ± 1.0% and the distal edge position with an accuracy of 0.1 mm ± 0.2 mm, and estimate the dose delivered by the experimental 12C ion beam with a MRE of 3.7%, and the distal edge with an accuracy of 1.7 mm. Significance. The CNN was able to produce estimates of the dose distribution with comparable or improved accuracy and computational efficiency compared to the iterative method and other similar PET-based direct dose quantification techniques.

Radiation shielding assessment of high energy proton imaging at a proton therapy facility

Background

Proton imaging makes use of high‐energy, low‐intensity proton beams that fully traverse the patient and has been suggested to reduce range uncertainty in proton therapy. Upright patient positioning with proton imaging is being considered for a fixed beam room of a new proton therapy facility currently under construction. Considering that the yield and energy spectrum of secondary radiation from high‐energy proton beams is proton beam energy dependent, an assessment of radiation shielding at the energies required for proton imaging should be performed prior to use. Furthermore, NCRP 144 recommends that pion production be considered for proton energies greater than 300 MeV, which are not typically utilized for proton therapy but may be required for proton imaging.

Purpose

The purpose of this work was to determine whether proton treatment and imaging with an upright patient positioning system on a fixed beamline were acceptable from a radiation shielding perspective. This is the first report on radiation shielding assessment of proton imaging applications and includes consideration of pion production at the proton beam energy of 330 MeV.

Methods

The Geant4 Monte Carlo toolkit was used for the radiation shielding assessment. The calculations consisted of the generation of secondary particle phase‐space files by simulating the passage of high‐energy proton beams in two target materials, and subsequent simulation of the secondary particles in the proton therapy facility geometry. Particle fluence was converted to operational and protection radiation safety quantities with a custom python script for assessment of instantaneous and annual doses, respectively.

Results

The total yields of pions from a 330‐MeV proton beam were many orders of magnitude less than that of neutrons and photons. Three‐dimensional maps of ambient dose rate for a 330‐MeV proton beam showed doses arising from secondary neutrons and photons far exceed those arising from pion production. Incorporating representative annual workloads into the calculation demonstrated that proton imaging doses outside the shielded area were negligible compared to those arising from proton therapy.

Conclusions

Pion production has a negligible impact on the radiation shielding of proton imaging at 330 MeV relative to neutron and photon production. Radiation shielding designed for proton therapy is adequate for high‐energy proton imaging applications.

Comparative accuracy and resolution assessment of two prototype proton computed tomography scanners

BACKGROUND

Improving the accuracy of relative stopping power (RSP) in proton therapy may allow reducing range margins. Proton computed tomography (pCT) has been shown to provide state-of-the-art RSP accuracy estimation, and various scanner prototypes have recently been built. The different approaches used in scanner design are expected to impact spatial resolution and RSP accuracy.

PURPOSE

The goal of this study was to perform the first direct comparison, in terms of spatial resolution and RSP accuracy, of two pCT prototype scanners installed at the same facility and by using the same image reconstruction algorithm.

METHODS

A phantom containing cylindrical inserts of known RSP was scanned at the phase-II pCT prototype of the U.S. pCT collaboration and at the commercially oriented ProtonVDA scanner. Following distance-driven binning filtered backprojection reconstruction, the radial edge spread function of high-density inserts was used to estimate the spatial resolution. RSP accuracy was evaluated by the mean absolute percent error (MAPE) over the inserts. No direct imaging dose estimation was possible, which prevented a comparison of the two scanners in terms of RSP noise.

RESULTS

In terms of RSP accuracy, both scanners achieved the same MAPE of 0.72% when excluding the porous sinus insert from the evaluation. The ProtonVDA scanner reached a better overall MAPE when all inserts and the body of the phantom were accounted for (0.81%), compared to the phase-II scanner (1.14%). The spatial resolution with the phase-II scanner was found to be 0.61 lp/mm, while for the ProtonVDA scanner somewhat lower at 0.46 lp/mm.

CONCLUSIONS

The comparison between two prototype pCT scanners operated in the same clinical facility showed that they both fulfill the requirement of an RSP accuracy of about 1%. Their spatial resolution performance reflects the different design choices of either a scanner with full tracking capabilities (phase-II) or of a more compact tracker system which only provides the positions of protons but not their directions (ProtonVDA). This article is protected by copyright. All rights reserved.