Theoretical considerations on the spatial resolution limit of single-event particle radiography

Integrated-mode proton radiography with 2D lateral projections

Integrated-mode proton radiography leading to water equivalent thickness (WET) maps is an avenue of interest for motion management, patient positioning, andin vivorange verification. Radiographs can be obtained using a pencil beam scanning setup with a large 3D monolithic scintillator coupled with optical cameras. Established reconstruction methods either (1) involve a camera at the distal end of the scintillator, or (2) use a lateral view camera as a range telescope. Both approaches lead to limited image quality. The purpose of this work is to propose a third, novel reconstruction framework that exploits the 2D information provided by two lateral view cameras, to improve image quality achievable using lateral views. The three methods are first compared in a simulated Geant4 Monte Carlo framework using an extended cardiac torso (XCAT) phantom and a slanted edge. The proposed method with 2D lateral views is also compared with the range telescope approach using experimental data acquired with a plastic volumetric scintillator. Scanned phantoms include a Las Vegas (contrast), 9 tissue-substitute inserts (WET accuracy), and a paediatric head phantom. Resolution increases from 0.24 (distal) to 0.33 lp mm-1(proposed method) on the simulated slanted edge phantom, and the mean absolute error on WET maps of the XCAT phantom is reduced from 3.4 to 2.7 mm with the same methods. Experimental data from the proposed 2D lateral views indicate a 36% increase in contrast relative to the range telescope method. High WET accuracy is obtained, with a mean absolute error of 0.4 mm over 9 inserts. Results are presented for various pencil beam spacing ranging from 2 to 6 mm. This work illustrates that high quality proton radiographs can be obtained with clinical beam settings and the proposed reconstruction framework with 2D lateral views, with potential applications in adaptive proton therapy.

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.

Image quality evaluation of projection- and depth dose-based approaches to integrating proton radiography using a monolithic scintillator detector

The purpose of this study is to compare the image quality of an integrating proton radiography (PR) system, composed of a monolithic scintillator and two digital cameras, using integral lateral-dose and integral depth-dose image reconstruction techniques. Monte Carlo simulations were used to obtain the energy deposition in a 3D monolithic scintillator detector (30 × 30 × 30 cm³poly vinyl toluene organic scintillator) to create radiographs of various phantoms-a slanted aluminum cube for spatial resolution analysis and a Las Vegas phantom for contrast analysis. The light emission of the scintillator was corrected using Birks scintillation model. We compared two integrating PR methods and the expected results from an idealized proton tracking radiography system. Four different image reconstruction methods were utilized in this study: integral scintillation light projected from the beams-eye view, depth-dose based reconstruction methods both with and without optimization, and single particle tracking PR was used for reference data. Results showed that heterogeneity artifact due to medium-interface mismatch was identified from the Las Vegas phantom simulated in air. Spatial resolution was found to be highest for single-event reconstruction. Contrast levels, ranked from best to worst, were found to correspond to particle tracking, optimized depth-dose, depth-dose, and projection-based image reconstructions. The image quality of a monolithic scintillator integrating PR system was sufficient to warrant further exploration. These results show promise for potential clinical use as radiographic techniques for visualizing internal patient anatomy during proton radiotherapy.

Statistical limitations in ion imaging

In this study, we investigated the capacity of various ion beams available for radiotherapy to produce high quality relative stopping power map acquired from energy-loss measurements. The image quality metrics chosen to compare the different ions were signal-to-noise ratio (SNR) as a function of dose and spatial resolution. Geant4 Monte Carlo simulations were performed for: hydrogen, helium, lithium, boron and carbon ion beams crossing a 20 cm diameter water phantom to determine SNR and spatial resolution. It has been found that protons possess a significantly larger SNR when compared with other ions at a fixed range (up to 36% higher than helium) due to the proton nuclear stability and low dose per primary. However, it also yields the lowest spatial resolution against all other ions, with a resolution lowered by a factor 4 compared to that of carbon imaging, for a beam with the same initial range. When comparing for a fixed spatial resolution of 10 lp cm⁻¹, carbon ions produce the highest image quality metrics with proton ions producing the lowest. In conclusion, it has been found that no ion can maximize all image quality metrics simultaneously and that a choice must be made between spatial resolution, SNR, and dose.