Improving single-event proton CT by removing nuclear interaction events within the energy/range detector

Energy painting: helium-beam radiography with thin detectors and multiple beam energies

Objective.Compact ion imaging systems based on thin detectors are a promising prospect for the clinical environment since they are easily integrated into the clinical workflow. Their measurement principle is based on energy deposition instead of the conventionally measured residual energy or range. Therefore, thin detectors are limited in the water-equivalent thickness range they can image with high precision. This article presents ourenergy paintingmethod, which has been developed to render high precision imaging with thin detectors feasible even for objects with larger, clinically relevant water-equivalent thickness (WET) ranges.Approach.A detection system exclusively based on pixelated silicon Timepix detectors was used at the Heidelberg ion-beam therapy center to track single helium ions and measure their energy deposition behind the imaged object. Calibration curves were established for five initial beam energies to relate the measured energy deposition to WET. They were evaluated regarding their accuracy, precision and temporal stability. Furthermore, a 60 mm × 12 mm region of a wedge phantom was imaged quantitatively exploiting the calibrated energies and five different mono-energetic images. These mono-energetic images were combined in a pixel-by-pixel manner by averaging the WET-data weighted according to their single-ion WET precision (SIWP) and the number of contributing ions.Main result.A quantitative helium-beam radiograph of the wedge phantom with an average SIWP of 1.82(5) % over the entire WET interval from 150 mm to 220 mm was obtained. Compared to the previously used methodology, the SIWP improved by a factor of 2.49 ± 0.16. The relative stopping power value of the wedge derived from the energy-painted image matches the result from range pullback measurements with a relative deviation of only 0.4 %.Significance.The proposed method overcomes the insufficient precision for wide WET ranges when employing detection systems with thin detectors. Applying this method is an important prerequisite for imaging of patients. Hence, it advances detection systems based on energy deposition measurements towards clinical implementation.

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 likelihood-based particle imaging filter using prior information

BACKGROUND

Particle imaging can increase precision in proton and ion therapy. Interactions with nuclei in the imaged object increase image noise and reduce image quality, especially for multinucleon ions that can fragment, such as helium.

PURPOSE

This work proposes a particle imaging filter, referred to as the Prior Filter, based on using prior information in the form of an estimated relative stopping power (RSP) map and the principles of electromagnetic interaction, to identify particles that have undergone nuclear interaction. The particles identified as having undergone nuclear interactions are then excluded from the image reconstruction, reducing the image noise.

METHODS

The Prior Filter uses Fermi-Eyges scattering and Tschalär straggling theories to determine the likelihood that a particle only interacts electromagnetically. A threshold is then set to reject those particles with a low likelihood. The filter was evaluated and compared with a filter that estimates this likelihood based on the measured distribution of energy and scattering angle within pixels, commonly implemented as the 3σ filter. Reconstructed radiographs from simulated data of a 20-cm water cylinder and an anthropomorphic chest phantom were generated with both protons and helium ions to assess the effect of the filters on noise reduction. The simulation also allowed assessment of secondary particle removal through the particle histories. Experimental data were acquired of the Catphan CTP 404 Sensitometry phantom using the U.S. proton CT (pCT) collaboration prototype scanner. The proton and helium images were filtered with both the prior filtering method and a state-of-the-art method including an implementation of the 3σ filter. For both cases, a dE-E telescope filter, designed for this type of detector, was also applied.

RESULTS

The proton radiographs showed a small reduction in noise (1 mm of water-equivalent thickness [WET]) but a larger reduction in helium radiographs (up to 5-6 mm of WET) due to better secondary filtering. The proton and helium CT images reflected this, with similar noise at the center of the phantom (0.02 RSP) for the proton images and an RSP noise of 0.03 for the proposed filter and 0.06 for the 3σ filter in the helium images. Images reconstructed from data with a dose reduction, up to a factor of 9, maintained a lower noise level using the Prior Filter over the state-of-the-art filtering method.

CONCLUSIONS

The proposed filter results in images with equal or reduced noise compared to those that have undergone a filtering method typical of current particle imaging studies. This work also demonstrates that the proposed filter maintains better performance against the state of the art with up to a nine-fold dose reduction.

Experimental helium-beam radiography with a high-energy beam: Water-equivalent thickness calibration and first image-quality results

PURPOSE

A clinical implementation of ion-beam radiography (iRad) is envisaged to provide a method for on-couch verification of ion-beam treatment plans. The aim of this work is to introduce and evaluate a method for quantitative water-equivalent thickness (WET) measurements for a specific helium-ion imaging system for WETs that are relevant for imaging thicker body parts in the future.

METHODS

Helium-beam radiographs (αRads) are measured at the Heidelberg Ion-beam Therapy Center (HIT) with an initial beam energy of 239.5 MeV/ u. An imaging system based on three pairs of thin silicon pixel detectors is used for ion path reconstruction and measuring the energy deposition (dE) of each particle behind the object to be imaged. The dE behind homogeneous plastic blocks is related to their well-known WETs between 280.6mm and 312.6 mm with a calibration curve that is created by fitting the measured data points. The quality of the quantitative WET measurements is determined by the uncertainty of the measured WET of a single ion (single-ion WET precision) and the deviation of a measured WET value to the well-known WET (WET accuracy). Subsequently, the fitted calibration curve is applied to an energy deposition radiograph of a phantom with a complex geometry. The spatial resolution (modulation transfer function at 10% (MTF_10% )) and WET accuracy (mean absolute percentage difference (MAPD)) of the WET map, are determined.

RESULTS

In the optimal imaging WET-range from ∼  280 mm to 300 mm, the fitted calibration curve reached a mean single-ion WET precision of 1.55 ± 0.00%. Applying the calibration to an ion radiograph (iRad) of a more complex WET distribution, the spatial resolution was determined to be MTF_10% = 0.49 ± 0.03 lp/mm and the WET accuracy was assessed as MAPD to 0.21%.

CONCLUSIONS

Using a beam energy of 239.5MeV/ u and the proposed calibration procedure, quantitative αRads of WETs between ∼  280mm to 300 mm can be measured and show high potential for clinical use. The proposed approach with the resulting image qualities encourages further investigation towards the clinical application of helium-beam radiography. This article is protected by copyright. All rights reserved.

Experimental comparison of photon versus particle computed tomography to predict tissue relative stopping powers

PURPOSE

Measurements comparing relative stopping power (RSP) accuracy of state-of-the-art systems representing single-energy and dual-energy computed tomography (SECT/DECT) with proton CT (pCT) and helium CT (HeCT) in biological tissue samples.

METHODS

We used 16 porcine and bovine samples of various tissue types and water, covering an RSP range from 0.90 ± 0.06 to 1.78 ± 0.05. Samples were packed and sealed into 3D-printed cylinders ( d = 2  cm, h = 5  cm) and inserted into an in-house designed cylindrical polymethyl methacrylate (PMMA) phantom ( d = 10  cm, h = 10  cm). We scanned the phantom in a commercial SECT and DECT (120 kV; 100  and 140 kV/Sn (tin-filtered)); and acquired pCT and HeCT ( E ∼ 200  MeV/u, 2 ∘ steps, ∼ 6.2 × 10 6 (p)/ ∼ 2.3 × 10 6 (He) particles/projection) with a particle imaging prototype. RSP maps were calculated from SECT/DECT using stoichiometric methods and from pCT/HeCT using the DROP-TVS algorithm. We estimated the average RSP of each tissue per modality in cylindrical volumes of interest and compared it to ground truth RSP taken from peak-detection measurements.

RESULTS

Throughout all samples, we observe the following root-mean-squared RSP prediction errors ± combined uncertainty from reference measurement and imaging: SECT 3.10 ± 2.88%, DECT 0.75 ± 2.80%, pCT 1.19 ± 2.81%, and HeCT 0.78 ± 2.81%. The largest mean errors ± combined uncertainty per modality are SECT 8.22 ± 2.79% in cortical bone, DECT 1.74 ± 2.00% in back fat, pCT 1.80 ± 4.27% in bone marrow, and HeCT 1.37 ± 4.25% in bone marrow. Ring artifacts were observed in both pCT and HeCT reconstructions, imposing a systematic shift to predicted RSPs.

CONCLUSION

Comparing state-of-the-art SECT/DECT technology and a pCT/HeCT prototype, DECT provided the most accurate RSP prediction, closely followed by particle imaging. The novel modalities pCT and HeCT have the potential to further improve on RSP accuracies with work focusing on the origin and correction of ring artifacts. Future work will study accuracy of proton treatment plans using RSP maps from investigated imaging modalities.

The accuracy of helium ion CT based particle therapy range prediction: an experimental study comparing different particle and x-ray CT modalities

This work provides a quantitative assessment of helium ion CT (HeCT) for particle therapy treatment planning. For the first time, HeCT based range prediction accuracy in a heterogeneous tissue phantom is presented and compared to single-energy x-ray CT (SECT), dual-energy x-ray CT (DECT) and proton CT (pCT). HeCT and pCT scans were acquired using the US pCT collaboration prototype particle CT scanner at the Heidelberg Ion-Beam Therapy Center. SECT and DECT scans were done with a Siemens Somatom Definition Flash and converted to RSP. A Catphan CTP404 module was used to study the RSP accuracy of HeCT. A custom phantom of 20 cm diameter containing several tissue equivalent plastic cubes was used to assess the spatial resolution of HeCT and compare it to DECT. A clinically realistic heterogeneous tissue phantom was constructed using cranial slices from a pig head placed inside a cylindrical phantom (ø150 mm). A proton beam (84.67 mm range) depth-dose measurement was acquired using a stack of GafchromicTM EBT-XD films in a central dosimetry insert in the phantom. CT scans of the phantom were acquired with each modality, and proton depth-dose estimates were simulated based on the reconstructions. The RSP accuracy of HeCT for the plastic phantom was found to be 0.3 ± 0.1%. The spatial resolution for HeCT of the cube phantom was 5.9 ± 0.4 lp cm-1for central, and 7.6 ± 0.8 lp cm-1for peripheral cubes, comparable to DECT spatial resolution (7.7 ± 0.3 lp cm-1and 7.4 ± 0.2 lp cm-1, respectively). For the pig head, HeCT, SECT, DECT and pCT predicted range accuracy was 0.25%, -1.40%, -0.45% and 0.39%, respectively. In this study, HeCT acquired with a prototype system showed potential for particle therapy treatment planning, offering RSP accuracy, spatial resolution, and range prediction accuracy comparable to that achieved with a commercial DECT scanner. Still, technical improvements of HeCT are needed to enable clinical implementation.

Investigating particle track topology for range telescopes in particle radiography using convolutional neural networks

BACKGROUND

Proton computed tomography (pCT) and radiography (pRad) are proposed modalities for improved treatment plan accuracy and in situ treatment validation in proton therapy. The pCT system of the Bergen pCT collaboration is able to handle very high particle intensities by means of track reconstruction. However, incorrectly reconstructed and secondary tracks degrade the image quality. We have investigated whether a convolutional neural network (CNN)-based filter is able to improve the image quality.

MATERIAL AND METHODS

The CNN was trained by simulation and reconstruction of tens of millions of proton and helium tracks. The CNN filter was then compared to simple energy loss threshold methods using the Area Under the Receiver Operating Characteristics curve (AUROC), and by comparing the image quality and Water Equivalent Path Length (WEPL) error of proton and helium radiographs filtered with the same methods.

RESULTS

The CNN method led to a considerable improvement of the AUROC, from 74.3% to 97.5% with protons and from 94.2% to 99.5% with helium. The CNN filtering reduced the WEPL error in the helium radiograph from 1.03 mm to 0.93 mm while no improvement was seen in the CNN filtered pRads.

CONCLUSION

The CNN improved the filtering of proton and helium tracks. Only in the helium radiograph did this lead to improved image quality.

Helium radiography with a digital tracking calorimeter-a Monte Carlo study for secondary track rejection

Radiation therapy using protons and heavier ions is a fast-growing therapeutic option for cancer patients. A clinical system for particle imaging in particle therapy would enable online patient position verification, estimation of the dose deposition through range monitoring and a reduction of uncertainties in the calculation of the relative stopping power of the patient. Several prototype imaging modalities offer radiography and computed tomography using protons and heavy ions. A Digital Tracking Calorimeter (DTC), currently under development, has been proposed as one such detector. In the DTC 43 longitudinal layers of laterally stacked ALPIDE CMOS monolithic active pixel sensor chips are able to reconstruct a large number of simultaneously recorded proton tracks. In this study, we explored the capability of the DTC for helium imaging which offers favorable spatial resolution over proton imaging. Helium ions exhibit a larger cross section for inelastic nuclear interactions, increasing the number of produced secondaries in the imaged object and in the detector itself. To that end, a filtering process able to remove a large fraction of the secondaries was identified, and the track reconstruction process was adapted for helium ions. By filtering on the energy loss along the tracks, on the incoming angle and on the particle ranges, 97.5% of the secondaries were removed. After passing through 16 cm water, 50.0% of the primary helium ions survived; after the proposed filtering 42.4% of the primaries remained; finally after subsequent image reconstruction 31% of the primaries remained. Helium track reconstruction leads to more track matching errors compared to protons due to the increased available focus strength of the helium beam. In a head phantom radiograph, the Water Equivalent Path Length error envelope was 1.0 mm for helium and 1.1 mm for protons. This accuracy is expected to be sufficient for helium imaging for pre-treatment verification purposes.

The 20th Gray lecture 2019: health and heavy ions

Objective

Particle radiobiology has contributed new understanding of radiation safety and underlying mechanisms of action to radiation oncology for the treatment of cancer, and to planning of radiation protection for space travel. This manuscript will highlight the significance of precise physical and biologically effective dosimetry to this translational research for the benefit of human health.

This review provides a brief snapshot of the evolving scientific basis for, and the complex current global status, and remaining challenges of hadron therapy for the treatment of cancer. The need for particle radiobiology for risk planning in return missions to the Moon, and exploratory deep-space missions to Mars and beyond are also discussed.

Methods

Key lessons learned are summarized from an impressive collective literature published by an international cadre of multidisciplinary experts in particle physics, radiation chemistry, medical physics of imaging and treatment planning, molecular, cellular, tissue radiobiology, biology of microgravity and other stressors, theoretical modeling of biophysical data, and clinical results with accelerator-produced particle beams.

Results

Research pioneers, many of whom were Nobel laureates, led the world in the discovery of ionizing radiations originating from the Earth and the Cosmos. Six radiation pioneers led the way to hadron therapy and the study of charged particles encountered in outer space travel. Worldwide about 250,000 patients have been treated for cancer, or other lesions such as arteriovenous malformations in the brain between 1954 and 2019 with charged particle radiotherapy, also known as hadron therapy. The majority of these patients (213,000) were treated with proton beams, but approximately 32,000 were treated with carbon ion radiotherapy. There are 3500 patients who have been treated with helium, pions, neon or other ions. There are currently 82 facilities operating to provide ion beam clinical treatments. Of these, only 13 facilities located in Asia and Europe are providing carbon ion beams for preclinical, clinical, and space research. There are also numerous particle physics accelerators worldwide capable of producing ion beams for research, but not currently focused on treating patients with ion beam therapy but are potentially available for preclinical and space research. Approximately, more than 550 individuals have traveled into Lower Earth Orbit (LEO) and beyond and returned to Earth.

Conclusion

Charged particle therapy with controlled beams of protons and carbon ions have significantly impacted targeted cancer therapy, eradicated tumors while sparing normal tissue toxicities, and reduced human suffering. These modalities still require further optimization and technical refinements to reduce cost but should be made available to everyone in need worldwide. The exploration of our Universe in space travel poses the potential risk of exposure to uncontrolled charged particles. However, approaches to shield and provide countermeasures to these potential radiation hazards in LEO have allowed an amazing number of discoveries currently without significant life-threatening medical consequences. More basic research with components of the Galactic Cosmic Radiation field are still required to assure safety involving space radiations and combined stressors with microgravity for exploratory deep space travel.

Advances in knowledge

The collective knowledge garnered from the wealth of available published evidence obtained prior to particle radiation therapy, or to space flight, and the additional data gleaned from implementing both endeavors has provided many opportunities for heavy ions to promote human health.

The role of Monte Carlo simulation in understanding the performance of proton computed tomography

Proton computed tomography (pCT) is a promising tomographic imaging modality allowing direct reconstruction of proton relative stopping power (RSP) required for proton therapy dose calculation. In this review article, we aim at highlighting the role of Monte Carlo (MC) simulation in pCT studies. After describing the requirements for performing proton computed tomography and the various pCT scanners actively used in recent research projects, we present an overview of available MC simulation platforms. The use of MC simulations in the scope of investigations of image reconstruction, and for the evaluation of optimal RSP accuracy, precision and spatial resolution omitting detector effects is then described. In the final sections of the review article, we present specific applications of realistic MC simulations of an existing pCT scanner prototype, which we describe in detail.

The TOPAS tool for particle simulation, a Monte Carlo simulation tool for physics, biology and clinical research

PURPOSE

This paper covers recent developments and applications of the TOPAS TOol for PArticle Simulation and presents the approaches used to disseminate TOPAS.

MATERIALS AND METHODS

Fundamental understanding of radiotherapy and imaging is greatly facilitated through accurate and detailed simulation of the passage of ionizing radiation through apparatus and into a patient using Monte Carlo (MC). TOPAS brings Geant4, a reliable, experimentally validated MC tool mainly developed for high energy physics, within easy reach of medical physicists, radiobiologists and clinicians. Requiring no programming knowledge, TOPAS provides all of the flexibility of Geant4.

RESULTS

After 5 years of development followed by its initial release, TOPAS was subsequently expanded from its focus on proton therapy physics to incorporate radiobiology modeling. Next, in 2018, the developers expanded their user support and code maintenance as well as the scope of TOPAS towards supporting X-ray and electron therapy and medical imaging. Improvements have been achieved in user enhancement through software engineering and a graphical user interface, calculational efficiency, validation through experimental benchmarks and QA measurements, and either newly available or recently published applications. A large and rapidly increasing user base demonstrates success in our approach to dissemination of this uniquely accessible and flexible MC research tool.

CONCLUSIONS

The TOPAS developers continue to make strides in addressing the needs of the medical community in applications of ionizing radiation to medicine, creating the only fully integrated platform for four-dimensional simulation of all forms of radiotherapy and imaging with ionizing radiation, with a design that promotes inter-institutional collaboration.