Zinc-Doped Iron Oxide Nanoparticles as a Proton-Activatable Agent for Dose Range Verification in Proton Therapy.

Proton therapy allows the treatment of specific areas and avoids the surrounding tissues. However, this technique has uncertainties in terms of the distal dose fall-off. A promising approach to studying the proton range is the use of nanoparticles as proton-activatable agents that produce detectable signals. For this, we developed an iron oxide nanoparticle doped with Zn (IONP@Zn-cit) with a hydrodynamic size of 10 nm and stability in serum. Cytotoxicity, defined as half of the surveillance, was 100 µg Zn/mL in the U251 cell line. The effect on clonogenic cell death was tested after X-ray irradiation, which suggested a radioprotective effect of these nanoparticles at low concentrations (1-10 µg Zn/mL). To evaluate the production of positron emitters and prompt-gamma signals, IONP@Zn-cit was irradiated with protons, obtaining prompt-gamma signals at the lowest measured concentration (10 mg Zn/mL). Finally, 67Ga-IONP@Zn-cit showed accumulation in the liver and spleen and an accumulation in the tumor tissue of 0.95% ID/g in a mouse model of U251 cells. These results suggest the possibility of using Zn nanoparticles as proton-activatable agents to verify the range by prompt gamma detection and face the challenges of prompt gamma detection in a specific biological situation, opening different avenues to go forward in this field.

Cherenkov Light Emission in Pure Cherenkov Emitters for Prompt Gamma Imaging.

Proton range verification (PRV) in proton therapy by means of prompt-gamma detection is a promising but challenging approach. High count rates, energies ranging between 1 MeV and 7 MeV, and a strong background complicate the detection of such particles. In this work, the Cherenkov light generated by prompt-gammas in the pure Cherenkov emitters TlBr, TlCl and PbF2 was studied. Cherenkov light in these crystals can provide a very fast timing signal with the potential to achieve very high count rates and to discern between prompt-gammas and background signals. Crystals of 1×1 cm2 and thicknesses of 1 cm, 2 cm, 3 cm and 4 cm were simulated. Different photodetector configurations were studied for 2.3 MeV, 4.4 MeV, and 6.1 MeV prompt-gammas. TlCl achieved the greatest number of detected Cherenkov photons for all energies, detector dimensions, and photodetector efficiency modeling. For the highest prompt-gamma energy simulated, TlCl yielded approximately 250 Cherenkov detected photons, using a hypothetical high-performance photodetector. Results show the crystal blocks of 1 cm × 1 cm × 1 cm have greater prompt-gamma detection efficiency per volume and a comparable average number of detected Cherenkov photons per event.

Phase-change ultrasound contrast agents for proton range verification: towards anin vivoapplication.

Objective.In proton therapy, range uncertainties prevent optimal benefit from the superior depth-dose characteristics of proton beams over conventional photon-based radiotherapy. To reduce these uncertainties we recently proposed the use of phase-change ultrasound contrast agents as an affordable and effective range verification tool. In particular, superheated nanodroplets can convert into echogenic microbubbles upon proton irradiation, whereby the resulting ultrasound contrast relates to the proton range with high reproducibility. Here, we provide a firstin vivoproof-of-concept of this technology.Approach.First, thein vitrobiocompatibility of radiation-sensitive poly(vinyl alcohol) perfluorobutane nanodroplets was investigated using several colorimetric assays. Then,in vivoultrasound contrast was characterized using acoustic droplet vaporization (ADV) and later using proton beam irradiations at varying energies (49.7 MeV and 62 MeV) in healthy Sprague Dawley rats. A preliminary evaluation of thein vivobiocompatibility was performed using ADV and a combination of physiology monitoring and histology.Main results.Nanodroplets were non-toxic over a wide concentration range (<1 mM). In healthy rats, intravenously injected nanodroplets primarily accumulated in the organs of the reticuloendothelial system, where the lifetime of the generated ultrasound contrast (<30 min) was compatible with a typical radiotherapy fraction (<5 min). Spontaneous droplet vaporization did not result in significant background signals. Online ultrasound imaging of the liver of droplet-injected rats demonstrated an energy-dependent proton response, which can be tuned by varying the nanodroplet concentration. However, caution is warranted when deciding on the exact nanodroplet dose regimen as a mild physiological response (drop in cardiac rate, granuloma formation) was observed after ADV.Significance.These findings underline the potential of phase-change ultrasound contrast agents forin vivoproton range verification and provide the next step towards eventual clinical applications.

Reconstruction of thermoacoustic emission sources induced by proton irradiation using numerical time reversal.

Objective.Mapping of dose delivery in proton beam therapy can potentially be performed by analyzing thermoacoustic emissions measured by ultrasound arrays. Here, a method is derived and demonstrated for spatial mapping of thermoacoustic sources using numerical time reversal, simulating re-transmission of measured emissions into the medium.Approach.Spatial distributions of thermoacoustic emission sources are shown to be approximated by the analytic-signal form of the time-reversed acoustic field, evaluated at the time of the initial proton pulse. Given calibration of the array sensitivity and knowledge of tissue properties, this approach approximately reconstructs the acoustic source amplitude, equal to the product of the time derivative of the radiation dose rate, mass density, and Grüneisen parameter. This approach was implemented using two models for acoustic fields of the array elements, one modeling elements as line sources and the other as rectangular radiators. Thermoacoustic source reconstructions employed previously reported measurements of emissions from proton energy deposition in tissue-mimicking phantoms. For a phantom incorporating a bone layer, reconstructions accounted for the higher sound speed in bone. Dependence of reconstruction quality on array aperture size and signal-to-noise ratio was consistent with previous acoustic simulation studies.Main results.Thermoacoustic source distributions were successfully reconstructed from acoustic emissions measured by a linear ultrasound array. Spatial resolution of reconstructions was significantly improved in the azimuthal (array) direction by incorporation of array element diffraction. Source localization agreed well with Monte Carlo simulations of energy deposition, and was improved by incorporating effects of inhomogeneous sound speed.Significance.The presented numerical time reversal approach reconstructs thermoacoustic sources from proton beam radiation, based on straightforward processing of acoustic emissions measured by ultrasound arrays. This approach may be useful for ranging and dosimetry of clinical proton beams, if acoustic emissions of sufficient amplitude and bandwidth can be generated by therapeutic proton sources.

A feasibility study of enhanced prompt gamma imaging for range verification in proton therapy using deep learning.

Background and objective. Range uncertainty is a major concern affecting the delivery precision in proton therapy. The Compton camera (CC)-based prompt-gamma (PG) imaging is a promising technique to provide 3Din vivorange verification. However, the conventional back-projected PG images suffer from severe distortions due to the limited view of the CC, significantly limiting its clinical utility. Deep learning has demonstrated effectiveness in enhancing medical images from limited-view measurements. But different from other medical images with abundant anatomical structures, the PGs emitted along the path of a proton pencil beam take up an extremely low portion of the 3D image space, presenting both the attention and the imbalance challenge for deep learning. To solve these issues, we proposed a two-tier deep learning-based method with a novel weighted axis-projection loss to generate precise 3D PG images to achieve accurate proton range verification.Materials and methods: the proposed method consists of two models: first, a localization model is trained to define a region-of-interest (ROI) in the distorted back-projected PG image that contains the proton pencil beam; second, an enhancement model is trained to restore the true PG emissions with additional attention on the ROI. In this study, we simulated 54 proton pencil beams (energy range: 75-125 MeV, dose level: 1 × 109protons/beam and 3 × 108protons/beam) delivered at clinical dose rates (20 kMU min-1and 180 kMU min-1) in a tissue-equivalent phantom using Monte-Carlo (MC). PG detection with a CC was simulated using the MC-Plus-Detector-Effects model. Images were reconstructed using the kernel-weighted-back-projection algorithm, and were then enhanced by the proposed method.Results. The method effectively restored the 3D shape of the PG images with the proton pencil beam range clearly visible in all testing cases. Range errors were within 2 pixels (4 mm) in all directions in most cases at a higher dose level. The proposed method is fully automatic, and the enhancement takes only ∼0.26 s.Significance. Overall, this preliminary study demonstrated the feasibility of the proposed method to generate accurate 3D PG images using a deep learning framework, providing a powerful tool for high-precisionin vivorange verification of proton therapy.

The effects of Compton camera data acquisition and readout timing on PG imaging for proton range verification.

The purpose of this study was to determine how the characteristics of the data acquisition (DAQ) electronics of a Compton camera (CC) affect the quality of the recorded prompt gamma (PG) interaction data and the reconstructed images, during clinical proton beam delivery. We used the Monte-Carlo-plus-Detector-Effect (MCDE) model to simulate the delivery of a 150 MeV clinical proton pencil beam to a tissue-equivalent plastic phantom. With the MCDE model we analyzed how the recorded PG interaction data changed as two characteristics of the DAQ electronics of a CC were changed: (1) the number of data readout channels; and (2) the active charge collection, readout, and reset time. As the proton beam dose rate increased, the number of recorded PG single-, double-, and triple-scatter events decreased by a factor of 60× for the current DAQ configuration of the CC. However, as the DAQ readout channels were increased and the readout/reset timing decreased, the number of recorded events decreased by <5× at the highest clinical dose rate. The increased number of readout channels and reduced readout/reset timing also resulted in higher quality recorded data. That is, a higher percentage of the recorded double- and triple-scatters were "true" events (caused by a single incident gamma) and not "false" events (caused by multiple incident gammas). The increase in the number and the quality of recorded data allowed higher quality PG images to be reconstructed even at the highest clinical dose rates.

Dictionary-based software for proton dose reconstruction and submilimetric range verification.

Objective.This paper presents a new method for fast reconstruction (compatible with in-beam use) of deposited dose during proton therapy using data acquired from a PET scanner. The most innovative feature of this novel method is the production of noiseless reconstructed dose distributions from which proton range can be derived with high precision.Approach.A new MLEM & simulated annealing (MSA) algorithm, developed especially in this work, reconstructs the deposited dose distribution from a realistic pre-calculated activity-dose dictionary. This dictionary contains the contribution of each beam in the plan to the 3D activity and dose maps, as calculated by a Monte Carlo simulation. The MSA algorithm, usinga prioriinformation of the treatment plan, seeks for the linear combination of activities of the precomputed beams that best fits the observed PET data, obtaining at the same time the deposited dose.Main results.the method has been tested using simulated data to determine its performance under 4 different test cases: (1) dependency of range detection accuracy with delivered dose, (2) in-beam versus offline verification, (3) ability to detect anatomical changes and (4) reconstruction of a realistic spread-out Bragg peak. The results show the ability of the method to accurately reconstruct doses from PET data corresponding to 1 Gy irradiations, both in intra-fraction and inter-fraction verification scenarios. For this dose level (1 Gy) the method was able to spot range variations as small as 0.6 mm.Significance.out method is able to reconstruct dose maps with remarkable accuracy from clinically relevant dose levels down to 1 Gy. Furthermore, due to the noiseless nature of reconstructed dose maps, an accuracy better than one millimeter was obtained in proton range estimates. These features make of this method a realistic option for range verification in proton therapy.

Dictionary-based protoacoustic dose map imaging for proton range verification.

Proton radiotherapy has the potential to provide state-of-the-art dose conformality in the tumor area, reducing possible adverse effects on surrounding organs at risk. However, uncertainties in the exact location of the proton Bragg peak inside the patient prevent this technique from achieving full clinical potential. In this context, in vivo verification of the range of protons in patients is key to reduce uncertainty margins. Protoacoustic range verification employs acoustic pressure waves generated by protons due to the radio-induced thermoacoustic effect to reconstruct the dose deposited in a patient during proton therapy. In this paper, we propose to use the a priori knowledge of the shape of the proton dose distribution to create a dictionary with the expected ultrasonic signals at predetermined detector locations. Using this dictionary, the reconstruction of deposited dose is performed by matching pre-calculated dictionary acoustic signals with data acquired online during treatment. The dictionary method was evaluated on a single-field proton plan for a prostate cancer patient. Dose calculation was performed with the open-source treatment planning system matRad, while acoustic wave propagation was carried out with k-Wave. We studied the ability of the proposed dictionary method to detect range variations caused by anatomical changes in tissue density, and alterations of lateral and longitudinal beam position. Our results show that the dictionary-based protoacoustic method was able to identify the changes in range originated by all the alterations introduced, with an average accuracy of 1.4 mm. This procedure could be used for in vivo verification, comparing the measured signals with the precalculated dictionary.

Secondary Particle Interactions in a Compton Camera Designed for in vivo Range Verification of Proton Therapy.

The purpose of this study was to determine the types, proportions, and energies of secondary particle interactions in a Compton camera (CC) during the delivery of clinical proton beams. The delivery of clinical proton pencil beams ranging from 70 to 200 MeV incident on a water phantom was simulated using Geant4 software (version 10.4). The simulation included a CC similar to the configuration of a Polaris J3 CC designed to image prompt gammas (PGs) emitted during proton beam irradiation for the purpose of in vivo range verification. The interaction positions and energies of secondary particles in each CC detector module were scored. For a 150-MeV proton beam, a total of 156,688(575) secondary particles per 108 protons, primarily composed of gamma rays (46.31%), neutrons (41.37%), and electrons (8.88%), were found to reach the camera modules, and 79.37% of these particles interacted with the modules. Strategies for using CCs for proton range verification should include methods of reducing the large neutron backgrounds and low-energy non-PG radiation. The proportions of interaction types by module from this study may provide information useful for background suppression.

Ionizing radiation-induced acoustics for radiotherapy and diagnostic radiology applications.

Acoustic waves are induced via the thermoacoustic effect in objects exposed to a pulsed beam of ionizing radiation. This phenomenon has interesting potential applications in both radiotherapy dosimetry and treatment guidance as well as low-dose radiological imaging. After initial work in the field in the 1980s and early 1990s, little research was done until 2013 when interest was rejuvenated, spurred on by technological advances in ultrasound transducers and the increasing complexity of radiotherapy delivery systems. Since then, many studies have been conducted and published applying ionizing radiation-induced acoustic principles into three primary research areas: Linear accelerator photon beam dosimetry, proton therapy range verification, and radiological imaging. This review article introduces the theoretical background behind ionizing radiation-induced acoustic waves, summarizes recent advances in the field, and provides an outlook on how the detection of ionizing radiation-induced acoustic waves can be used for relative and in vivo dosimetry in photon therapy, localization of the Bragg peak in proton therapy, and as a low-dose medical imaging modality. Future prospects and challenges for the clinical implementation of these techniques are discussed.

Feasibility study of using fall-off gradients of early and late PET scans for proton range verification.

PURPOSE: While positron emission tomography (PET) allows for the imaging of tissues activated by proton beams in terms of monitoring the therapy administered, most endogenous tissue elements are activated by relatively high-energy protons. Therefore, a relatively large distance off-set exists between the dose fall-off and activity fall-off. However, 16 O(p,2p,2n)13 N has a relatively low energy threshold which peaks around 12 MeV and also a residual proton range that is approximately 1 to 2 mm. In this phantom study, we tested the feasibility of utilizing the 13 N production peak as well as the differences in activity fall-off between early and late PET scans for proton range verification. One of the main purposes for this research was developing a proton range verification methodology that would not require Monte Carlo simulations. METHODS AND MATERIALS: Both monoenergetic and spread-out Bragg peak beams were delivered to two phantoms - a water-like gel and a tissue-like gel where the proton ranges came to be approximately 9.9 and 9.1 cm, respectively. After 1 min of postirradiation delay, the phantoms were scanned for a period of 30 min using an in-room PET. Two separate (Early and Late) PET images were reconstructed using two different postirradiation delays and acquisition times; Early PET: 1 min delay and 3 min acquisition, Late PET: 21 min delay and 10 min acquisition. The depth gradients of the PET signals were then normalized and plotted as functions of depth. The normalized gradient of the early PET images was subtracted from that of the late PET images, to observe the 13 N activity distribution in relation to depth. Monte Carlo simulations were also conducted with the same set-up as the measurements stated previously. RESULTS: The subtracted gradients show peaks at 9.4 and 8.6 cm in water-gel and tissue-gel respectively for both pristine and SOBP beams. These peaks are created in connection with the sudden change of 13 N signals with depth and consistently occur 2 mm upstream to where 13 N signals were most abundantly created (9.6 and 8.8 cm in water-gel and tissue-gel, respectively). Monte Carlo simulations provided similar results as the measurements. CONCLUSIONS: The subtracted PET signal gradient peaks and the proton ranges for water-gel and tissue-gel show distance off-sets of 4 to 5 mm. This off-set may potentially be used for proton range verification using only the PET measured data without Monte Carlo simulations. More studies are necessary to overcome various limitations, such as perfusion-driven washout, for the feasibility of this technique in living patients.

Sensitivity study of prompt gamma imaging of scanned beam proton therapy in heterogeneous anatomies.

BACKGROUND AND PURPOSE: To investigate the use of a fast analytical prediction algorithm in the evaluation of the accuracy in Bragg peak position estimation using prompt gamma imaging in realistic anatomies. MATERIAL AND METHODS: Brain, nasal cavity and lung spot scanning treatments were planned on an anthropomorphic phantom. Plan delivery in a clinical proton therapy facility was monitored using a prompt gamma camera. A pencil-beam algorithm was developed to simulate prompt gamma acquisition. For each spot, the sensitivity to setup and CT conversion errors was evaluated based on error scenarios. RESULTS: Good agreement was found between simulations and measurements (average shift of 0.4mm on whole-layer profiles). The spots with greatest sensitivity to setup or CT conversion errors could be identified. The comparison between expected and estimated shifts showed that the errors in shift estimation due to heterogeneities were in average lower than 1mm in all cases except the lung. In the lung case, only 40% of the spots showed accuracy better than 2mm. CONCLUSIONS: The analytical prediction algorithm was successfully used to simulate prompt gamma acquisitions of scanned treatment plans. The accuracy in Bragg peak position estimation was generally sub-millimeter in heterogeneous anatomies, except in lung tissues.

Proton therapy verification with PET imaging.

Proton therapy is very sensitive to uncertainties introduced during treatment planning and dose delivery. PET imaging of proton induced positron emitter distributions is the only practical approach for in vivo, in situ verification of proton therapy. This article reviews the current status of proton therapy verification with PET imaging. The different data detecting systems (in-beam, in-room and off-line PET), calculation methods for the prediction of proton induced PET activity distributions, and approaches for data evaluation are discussed.