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

Volz, Lennart; Piersimoni, Pierluigi; Johnson, R. P.; Bashkirov, V.; Schulte, R.; Seco, Joao

doi:10.1088/1361-6560/ab2671

Cited by 16 publications

(31 citation statements)

References 33 publications

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“…It has to be noted that the 𝛿E-E filter for removing secondary particles in the energy detector was applied to HeCT but not to pCT in this work, despite a previous simulation study from our group 44 reporting improved pCT accuracy from 0.55% MAE without filter to 0.19% MAE with filter. For the experimental scans presented in this work, the 𝛿E-E filter removed a similar nuclear interaction background as in the simulation, but this produced a slight decrease in overall RSP accuracy from 1.07% MAE without filter to 1.18% with filter.…”

Section: Discussionmentioning

confidence: 98%

“…The DROP-TVS iterative reconstruction method we applied has been broadly employed with the used pCT prototype. 24,28,32,41,42,44 Especially, it has been shown to be able to provide high-quality images acquired from a low number of projections. 41 On the other hand, being an iterative reconstruction method the outcome is influenced by the chosen reconstruction parameters, especially the number of iterations.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2021

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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.

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Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

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

et al. 2021

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“…For comparison using similar Monte Carlo studies, Gehrke et al (2018b) using a set of three pixel tracking detectors placed close to the Bragg peak found a ratio of 45% between the incoming primary helium beam (when cropped to the lateral dimensions of the detector) and the image-generating helium tracks. For the ∆E − E filter used in combination with the prototype pCT detector developed by the US pCT collaboration, Volz et al (2019) report a reduction to 43% compared to the data set not using the ∆E − E filter (before applying the 3 σ WEPL filter). However, this number does not consider multiplicity fragmentation events originating from within the phantom, as multiple hits on the rear tracker were automatically suppressed and therefore also not considered.…”

Section: Filter Performancementioning

confidence: 98%

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

Pettersen¹,

Volz²,

Sølie³

et al. 2021

Phys. Med. Biol.

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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

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“…Similarly, during the reconstruction, a 3σ-filter is applied to the WEPL distribution in order to remove unusually large energy losses and nuclear interactions [24]. Since the modeled WEPL does not consider the additional nuclear interactions that protons may undergo in the DTC, a 3σ-WEPL filter is sufficient to ensure high quality images [58]. For the final prototype, additional data filters will act on the track reconstruction, measured cluster sizes and the Braggpeak fitting performed [64].…”

Section: Image Reconstructionmentioning

confidence: 99%

A High-Granularity Digital Tracking Calorimeter Optimized for Proton CT

Alme¹,

Barnaföldi²,

Barthel³

et al. 2020

Front. Phys.

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A typical proton CT (pCT) detector comprises a tracking system, used to measure the proton position before and after the imaged object, and an energy/range detector to measure the residual proton range after crossing the object. The Bergen pCT collaboration was established to design and build a prototype pCT scanner with a high granularity digital tracking calorimeter used as both tracking and energy/range detector. In this work the conceptual design and the layout of the mechanical and electronics implementation, along with Monte Carlo simulations of the new pCT system are reported. The digital tracking calorimeter is a multilayer structure with a lateral aperture of 27 cm × 16.6 cm, made of 41 detector/absorber sandwich layers (calorimeter), with aluminum (3.5 mm) used both as absorber and carrier, and two additional layers used as tracking system (rear trackers) positioned downstream of the imaged object; no tracking upstream the object is included. The rear tracker's structure only differs from the calorimeter layers for the carrier made of ∼200 μm carbon fleece and carbon paper (carbon-epoxy sandwich), to minimize scattering. Each sensitive layer consists of 108 ALICE pixel detector (ALPIDE) chip sensors (developed for ALICE, CERN) bonded on a polyimide flex and subsequently bonded to a larger flexible printed circuit board. Beam tests tailored to the pCT operation have been performed using high-energetic (50-220 MeV/u) proton and ion beams at the

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

Cited by 16 publications

References 33 publications

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

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

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

A High-Granularity Digital Tracking Calorimeter Optimized for Proton CT

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