Prompt gamma-ray emission from biological tissues during proton irradiation: a preliminary study

Hybrid-supervised deep learning for domain transfer 3D protoacoustic image reconstruction

Objective. Protoacoustic imaging showed great promise in providing real-time 3D dose verification of proton therapy. However, the limited acquisition angle in protoacoustic imaging induces severe artifacts, which impairs its accuracy for dose verification. In this study, we developed a hybrid-supervised deep learning method for protoacoustic imaging to address the limited view issue.Approach. We proposed a Recon-Enhance two-stage deep learning method. In the Recon-stage, a transformer-based network was developed to reconstruct initial pressure maps from raw acoustic signals. The network is trained in a hybrid-supervised approach, where it is first trained using supervision by the iteratively reconstructed pressure map and then fine-tuned using transfer learning and self-supervision based on the data fidelity constraint. In the enhance-stage, a 3D U-net is applied to further enhance the image quality with supervision from the ground truth pressure map. The final protoacoustic images are then converted to dose for proton verification.Main results. The results evaluated on a dataset of 126 prostate cancer patients achieved an average root mean squared errors (RMSE) of 0.0292, and an average structural similarity index measure (SSIM) of 0.9618, out-performing related start-of-the-art methods. Qualitative results also demonstrated that our approach addressed the limit-view issue with more details reconstructed. Dose verification achieved an average RMSE of 0.018, and an average SSIM of 0.9891. Gamma index evaluation demonstrated a high agreement (94.7% and 95.7% for 1%/3 mm and 1%/5 mm) between the predicted and the ground truth dose maps. Notably, the processing time was reduced to 6 s, demonstrating its feasibility for online 3D dose verification for prostate proton therapy.Significance. Our study achieved start-of-the-art performance in the challenging task of direct reconstruction from radiofrequency signals, demonstrating the great promise of PA imaging as a highly efficient and accurate tool forinvivo3D proton dose verification to minimize the range uncertainties of proton therapy to improve its precision and outcomes.

A high sensitivity Cherenkov detector for prompt gamma timing and time imaging

We recently proposed a new approach for the real-time monitoring of particle therapy treatments with the goal of achieving high sensitivities on the particle range measurement already at limited counting statistics. This method extends the Prompt Gamma (PG) timing technique to obtain the PG vertex distribution from the exclusive measurement of particle Time-Of-Flight (TOF). It was previously shown, through Monte Carlo simulation, that an original data reconstruction algorithm (Prompt Gamma Time Imaging) allows to combine the response of multiple detectors placed around the target. The sensitivity of this technique depends on both the system time resolution and the beam intensity. At reduced intensities (Single Proton Regime-SPR), a millimetric proton range sensitivity can be achieved, provided the overall PG plus proton TOF can be measured with a 235 ps (FWHM) time resolution. At nominal beam intensities, a sensitivity of a few mm can still be obtained by increasing the number of incident protons included in the monitoring procedure. In this work we focus on the experimental feasibility of PGTI in SPR through the development of a multi-channel, Cherenkov-based PG detector with a targeted time resolution of 235 ps (FWHM): the TOF Imaging ARrAy (TIARA). Since PG emission is a rare phenomenon, TIARA design is led by the concomitant optimisation of its detection efficiency and Signal to Noise Ratio (SNR). The PG module that we developed is composed of a small PbF[Formula: see text] crystal coupled to a silicon photoMultiplier to provide the time stamp of the PG. This module is currently read in time coincidence with a diamond-based beam monitor placed upstream the target/patient to measure the proton time of arrival. TIARA will be eventually composed of 30 identical modules uniformly arranged around the target. The absence of a collimation system and the use of Cherenkov radiators are both crucial to increase the detection efficiency and the SNR, respectively. A first prototype of the TIARA block detector was tested with 63 MeV protons delivered from a cyclotron: a time resolution of 276 ps (FWHM) was obtained, resulting in a proton range sensitivity of 4 mm at 2[Formula: see text] with the acquisition of only 600 PGs. A second prototype was also evaluated with 148 MeV protons delivered from a synchro-cyclotron obtaining a time resolution below 167 ps (FWHM) for the gamma detector. Moreover, using two identical PG modules, it was shown that a uniform sensitivity on the PG profiles would be achievable by combining the response of gamma detectors uniformly distributed around the target. This work provides the experimental proof-of-concept for the development of a high sensitivity detector that can be used to monitor particle therapy treatments and potentially act in real-time if the irradiation does not comply to treatment plan.

3Din vivodose verification in prostate proton therapy with deep learning-based proton-acoustic imaging

Dose delivery uncertainty is a major concern in proton therapy, adversely affecting the treatment precision and outcome. Recently, a promising technique, proton-acoustic (PA) imaging, has been developed to provide real-timein vivo3D dose verification. However, its dosimetry accuracy is limited due to the limited-angle view of the ultrasound transducer. In this study, we developed a deep learning-based method to address the limited-view issue in the PA reconstruction. A deep cascaded convolutional neural network (DC-CNN) was proposed to reconstruct 3D high-quality radiation-induced pressures using PA signals detected by a matrix array, and then derive precise 3D dosimetry from pressures for dose verification in proton therapy. To validate its performance, we collected 81 prostate cancer patients' proton therapy treatment plans. Dose was calculated using the commercial software RayStation and was normalized to the maximum dose. The PA simulation was performed using the open-source k-wave package. A matrix ultrasound array with 64 × 64 sensors and 500 kHz central frequency was simulated near the perineum to acquire radiofrequency (RF) signals during dose delivery. For realistic acoustic simulations, tissue heterogeneity and attenuation were considered, and Gaussian white noise was added to the acquired RF signals. The proposed DC-CNN was trained on 204 samples from 69 patients and tested on 26 samples from 12 other patients. Predicted 3D pressures and dose maps were compared against the ground truth qualitatively and quantitatively using root-mean-squared-error (RMSE), gamma-index (GI), and dice coefficient of isodose lines. Results demonstrated that the proposed method considerably improved the limited-view PA image quality, reconstructing pressures with clear and accurate structures and deriving doses with a high agreement with the ground truth. Quantitatively, the pressure accuracy achieved an RMSE of 0.061, and the dose accuracy achieved an RMSE of 0.044, GI (3%/3 mm) of 93.71%, and 90%-isodose line dice of 0.922. The proposed method demonstrates the feasibility of achieving high-quality quantitative 3D dosimetry in PA imaging using a matrix array, which potentially enables the online 3D dose verification for prostate proton therapy.

Validation of prompt gamma-ray spectroscopy for proton range verification in tissue-mimicking and porcine samples

Objective. Proton therapy of cancer improves dose conformality to the target and sparing of surrounding healthy tissues compared to conventional photon treatments. However, proton therapy's advantage could be even larger if proton range uncertainties were reduced. Sources of range uncertainties include computed tomography treatment planning images and variations in patient anatomy and setup. To reduce range uncertainties, we have developed a system for real-timein vivorange monitoring. The system is based on spectroscopy of prompt gamma-rays emitted through proton-nuclear interactions during irradiation. We validated the performance of our prompt gamma-ray spectroscopy detector prototype using tissue-mimicking and porcine samples.Approach. Measurements were performed in water, four tissue-mimicking samples (spongiosa, muscle, adipose tissue, and cortical bone), and two porcine samples (liver and brain). A dose of 0.9 Gy was delivered to a target at a depth of 12.5-17.5 cm. Multi-layer ionization chamber measurements were performed to determine stopping power ratios relative to water and ground truth proton ranges. Ground truth elemental compositions were determined using combustion analysis. Proton ranges and elemental compositions measured using prompt gamma-ray spectroscopy were compared to the ground truth.Main results. For all samples, the mean measured range over all pencil-beam spots differed from the ground truth by less than 1.2 mm. The mean standard deviation was 0.9 mm (range: 0.4-1.6 mm). The mean difference between ground truth and measured elemental compositions was 0.06gcm3(range: 0.00gcm3to 0.12gcm3).Significance. We verified the performance of our prompt gamma-ray spectroscopy detector prototype for proton range verification using tissue-mimicking and porcine samples. Measured proton ranges and elemental sample compositions were in good agreement with the ground truth. These measurements confirm the system's reliability for a variety of tissues and bridge the gap between previously-reported experiments and ongoingin vivopatient measurements.

Comparison of reconstructed prompt gamma emissions using maximum likelihood estimation and origin ensemble algorithms for a Compton camera system tailored to proton range monitoring

Compton-based prompt gamma (PG) imaging is being investigated by several groups as a potential solution for in vivo range monitoring in proton therapy. The performance of this technique depends on the detector system as well as the ability of the reconstruction method to obtain good spatial resolution to establish a quantitative correlation between the PG emission and the proton beam range in the patient. To evaluate the feasibility of PG imaging for range monitoring, we quantitatively evaluated the emission distributions reconstructed by a Maximum Likelihood Expectation Maximization (MLEM) and a Stochastic Origin Ensemble (SOE) algorithm. To this end, we exploit experimental and Monte Carlo (MC) simulation data acquired with the Polaris-J Compton Camera (CC) prototype. The differences between the proton beam range (R_D) defined as the 80% distal dose fall-off and the PG range (R_PG), obtained by fitting the distal end of the reconstructed profile with a sigmoid function, were quantified. A comparable performance of both reconstruction algorithms was found. For both experimental and simulated irradiation scenarios, the correlation between R_D and R_PG was within 5 mm. These values were consistent with the ground truth distance (R_D-R_PGg≈ 3 mm) calculated by using the expected PG emission available from MC simulation. Furthermore, shifts of 3 mm in the proton beam range were resolved with the MLEM algorithm by calculating the relative difference between the R_PG for each reconstructed profile. In non-homogeneous targets, the spatial changes in the PG emission due to the different materials could not be fully resolved from the reconstructed profiles; however, the fall-off region still resembled the ground truth emission. For this scenario, the PG correlation (R_D-R_PG) varied from 0.1 mm to 4 mm, which is close to the ground truth correlation (3 mm). This work provides a framework for the evaluation of the range monitoring capabilities of a CC device for PG imaging. The two investigated image reconstruction algorithms showed a comparable and consistent performance for homogeneous and heterogeneous targets.

A proof-of-concept study of an in-situ partial-ring time-of-flight PET scanner for proton beam verification

Development of a PET system capable of in-situ imaging requires a design that can accommodate the proton treatment beam nozzle. Among the several PET instrumentation approaches developed thus far, the dual-panel PET scanner is often used as it is simpler to develop and integrate within the proton therapy gantry. Partial-angle coverage of these systems can however lead to limited-angle artefacts in the reconstructed PET image. We have previously demonstrated via simulations that time-of-flight (TOF) reconstruction reduces the artifacts accompanying limited-angle data, and permits proton range measurement with 1-2 mm accuracy and precision. In this work we show measured results from a small proof-of-concept dual-panel PET system that uses TOF information to reconstruct PET data acquired after proton irradiation. The PET scanner comprises of two detector modules, each comprised of an array of 4×4×30 mm³ lanthanum bromide scintillator. Measurements are performed with an oxygen-rich gel-water, an adipose tissue equivalent material, and in vitro tissue phantoms. For each phantom measurement, 2 Gy dose was deposited using 54 - 100 MeV proton beams. For each phantom, a Monte Carlo simulation generating the expected distribution of PET isotope from the corresponding proton irradiation was also performed. Proton range was calculated by drawing multiple depth-profiles over a central region encompassing the proton dose deposition. For each profile, proton range was calculated using two techniques (a) 50% pick-off from the distal edge of the profile, and (b) comparing the measured and Monte Carlo profile to minimize the absolute sum of differences over the entire profile. A 10 min PET acquisition acquired with minimal delay post proton-irradiation is compared with a 10 min PET scan acquired after a 20 min delay. Measurements show that PET acquisition with minimal delay is necessary to collect ¹⁵O signal, and maximize ¹¹C signal collection with a short PET acquisition. In comparison with the 50% pick-off technique, the shift technique is more robust and offers better precision in measuring the proton range for the different phantoms. Range measurements from PET images acquired with minimal delay, and the shift technique demonstrate the ability to achieve <1.5 mm accuracy and precision in estimating proton range.

Monte Carlo evaluation of a LYSO-based Compton camera using two origin ensemble algorithms with resolution recovery

PURPOSE

Due to the lack of depth-of-interaction information, a Compton camera made of lutetium-yttrium orthosilicate (LYSO) crystals suffers from poor spatial resolution, which may lead to an unreliable range verification in proton therapy. The aim of this study is to evaluate the performance of a LYSO-based Compton camera using the origin ensemble algorithm with resolution recovery (OE-RR). We also proposed a regularized version of OE-RR called ROE-RR.

METHODS

We simulated a two-layer LYSO-based Compton camera which was used to detect prompt gammas (PGs) produced by a proton beam irradiated on a water phantom. PG images reconstructed by the OE-RR algorithm were evaluated and compared with those reconstructed by the proposed ROE-RR algorithm.

RESULTS

Our simulated results show that both the OE-RR and ROE-RR algorithms could provide an accurate estimate of the Bragg peak position, with a mean positioning error of 2.5 mm. Compared to the OE-RR algorithm, the proposed ROE-RR algorithm is less sensitive with respect to initial conditions and requires less iterations for converging to equilibrium. More importantly, the proposed ROE-RR algorithm could provide better image quality than the OE-RR algorithm, especially in low-count data.

CONCLUSIONS

For LYSO-based Compton cameras, using a resolution-recovery image reconstruction algorithm is essential for reliable range verification.

A time-of-flight-based reconstruction for real-time prompt-gamma imaging in proton therapy

We propose a novel prompt-gamma (PG) imaging modality for real-time monitoring in proton therapy: PG time imaging (PGTI). By measuring the time-of-flight (TOF) between a beam monitor and a PG detector, our goal is to reconstruct the PG vertex distribution in 3D. In this paper, a dedicated, non-iterative reconstruction strategy is proposed (PGTI reconstruction). Here, it was resolved under a 1D approximation to measure a proton range shift along the beam direction. In order to show the potential of PGTI in the transverse plane, a second method, based on the calculation of the centre of gravity (COG) of the TIARA pixel detectors' counts was also explored. The feasibility of PGTI was evaluated in two different scenarios. Under the assumption of a 100 ps (rms) time resolution (achievable in single proton regime), MC simulations showed that a millimetric proton range shift is detectable at 2σwith 10⁸incident protons in simplified simulation settings. With the same proton statistics, a potential 2 mm sensitivity (at 2σwith 10⁸incident protons) to beam displacements in the transverse plane was found using the COG method. This level of precision would allow to act in real-time if the treatment does not conform to the treatment plan. A worst case scenario of a 1 ns (rms) TOF resolution was also considered to demonstrate that a degraded timing information can be compensated by increasing the acquisition statistics: in this case, a 2 mm range shift would be detectable at 2σwith 10⁹incident protons. By showing the feasibility of a time-based algorithm for the reconstruction of the PG vertex distribution for a simplified anatomy, this work poses a theoretical basis for the future development of a PG imaging detector based on the measurement of particle TOF.

Feasibility of quasi-prompt PET-based range verification in proton therapy

Compared to photon therapy, proton therapy allows a better conformation of the dose to the tumor volume with reduced radiation dose to co-irradiated tissues. In vivo verification techniques including positron emission tomography (PET) have been proposed as quality assurance tools to mitigate proton range uncertainties. Detection of differences between planned and actual dose delivery on a short timescale provides a fast trigger for corrective actions. Conventional PET-based imaging of ¹⁵O (T_1/2 = 2 min) and ¹¹C (T_1/2 = 20 min) distributions precludes such immediate feedback. We here present a demonstration of near real-time range verification by means of PET imaging of ¹²N (T_1/2 = 11 ms). PMMA and graphite targets were irradiated with a 150 MeV proton pencil beam consisting of a series of pulses of 10 ms beam-on and 90 ms beam-off. Two modules of a modified Siemens Biograph mCT PET scanner (21 × 21 cm² each), installed 25 cm apart, were used to image the beam-induced PET activity during the beam-off periods. The modifications enable the detectors to be switched off during the beam-on periods. ¹²N images were reconstructed using planar tomography. Using a 1D projection of the 2D reconstructed ¹²N image, the activity range was obtained from a fit of the activity profile with a sigmoid function. Range shifts due to modified target configurations were assessed for multiples of the clinically relevant 10⁸ protons per pulse (approximately equal to the highest intensity spots in the pencil beam scanning delivery of a dose of 1 Gy over a cubic 1 l volume). The standard deviation of the activity range, determined from 30 datasets obtained from three irradiations on PMMA and graphite targets, was found to be 2.5 and 2.6 mm (1σ) with 10⁸ protons per pulse and 0.9 and 0.8 mm (1σ) with 10⁹ protons per pulse. Analytical extrapolation of the results from this study shows that using a scanner with a solid angle coverage of 57%, with optimized detector switching and spot delivery times much smaller than the ¹²N half-life, an activity range measurement precision of 2.0 mm (1σ) and 1.3 mm (1σ) within 50 ms into an irradiation with 4 × 10⁷ and 10⁸ protons per pencil beam spot can be potentially realized. Aggregated imaging of neighboring spots or, if possible, increasing the number of protons for a few probe beam spots will enable the realization of higher precision range measurement.

On-line range verification for proton beam therapy using spherical ionoacoustic waves with resonant frequency

In contrast to conventional X-ray therapy, proton beam therapy (PBT) can confine radiation doses to tumours because of the presence of the Bragg peak. However, the precision of the treatment is currently limited by the uncertainty in the beam range. Recently, a unique range verification methodology has been proposed based on simulation studies that exploit spherical ionoacoustic waves with resonant frequency (SPIREs). SPIREs are emitted from spherical gold markers in tumours initially introduced for accurate patient positioning when the proton beam is injected. These waves have a remarkable property: their amplitude is linearly correlated with the residual beam range at the marker position. Here, we present proof-of-principle experiments using short-pulsed proton beams at the clinical dose to demonstrate the feasibility of using SPIREs for beam-range verification with submillimetre accuracy. These results should substantially contribute to reducing the range uncertainty in future PBT applications.

Classification of the source of treatment deviation in proton therapy using prompt-gamma imaging information

PURPOSE

Prompt-gamma imaging (PGI)-based range verification has been successfully implemented in clinical proton therapy recently and its sensitivity to detect treatment deviations is currently investigated. The cause of treatment deviations can be multiple - for example, computed tomography (CT)-based range prediction, patient setup, and anatomical changes. Hence, it would be beneficial, if PGI-based verification would not only detect a treatment deviation but would also be able to directly identify its most probable source. Here, we propose a heuristically derived decision tree approach to automatically classify the sources of range deviation in proton pencil-beam scanning (PBS) treatments of head and neck tumors based on range information obtained with a PGI slit camera.

MATERIALS AND METHODS

The decision tree model was iteratively generated on a training dataset of different anatomical complexities, for an anthropomorphic head phantom and patient CT data (planning and control CTs) from five patients. Different range prediction errors, setup changes and relevant and nonrelevant anatomical changes were introduced or derived from control CTs, summing up to a total of 98 training scenarios. Independent validation was performed for another 98 scenarios, derived solely from patient CT data of another seven patients. PBS head and neck treatment plans were generated for the nominal scenario. For all PBS spots in the investigated field, PGI profiles were simulated using a dedicated analytical model of the slit camera for the nominal as well as the different error scenarios. From comparison of PGI profiles for nominal and error scenarios, a spot-wise range shift after spot aggregation with a kernel of 7 mm sigma was determined for each error scenario. The heuristic approach includes a prefiltering of the most suitable PBS spots for PGI treatment verification. From the validation, the accuracy, sensitivity, and specificity of the model were determined.

RESULTS

A five-step consecutive filter was developed to preselect PBS spots. On average, 25% of spots (1044 spots) remained as input for the classification model. The derived heuristic decision tree model is based on five parameters: The coefficient of determination (R² ), the slope and intercept of the linear regression between PGI-derived range shifts and the respectively predicted proton ranges for the investigated PBS spots, as well as the average and standard deviation of the PGI-derived shifts. With this approach, 94 of 98 error scenarios could be classified correctly in validation (accuracy of 96%). A sensitivity and specificity of 100% and 86% were reached.

CONCLUSIONS

In this simulation study it was demonstrated that the source of a treatment deviation can be identified from simulated noiseless PGI information in head and neck tumor treatments with high sensitivity and specificity. The application, refinement, and evaluation of the approach on measured PGI data will be the next step to show the clinical feasibility of PGI-based error source classification.

The production of positron emitters with millisecond half-life during helium beam radiotherapy

Therapy with helium ions is currently receiving significantly increasing interest because helium ions have a sharper penumbra than protons and undergo less fragmentation than carbon ions and thus require less complicated dose calculations. For any ion of interest in hadron therapy, the accuracy of dose delivery is limited by range uncertainties. This has led to efforts by several groups to develop in vivo verification techniques, including positron emission tomography (PET), for monitoring of the dose delivery. Beam-on PET monitoring during proton therapy through the detection of short-lived positron emitters such as ¹²N (T _1/2  =  11 ms), an emerging PET technique, provides an attractive option given the achievable range accuracy, minimal susceptibility to biological washout and provision of near prompt feedback. Extension of this approach to helium ions requires information on the production yield of relevant short-lived positron emitters. This study presents the first measurements of the production of short-lived positron emitters in water, graphite, calcium and phosphorus targets irradiated with 59 MeV/u ³He and 50 MeV/u ⁴He beams. For these targets, the most produced short-lived nuclides are ¹³O/¹²N (T _1/2  =  8.6/11 ms) on water, ¹³O/¹²N on graphite, ⁴³Ti/⁴¹Sc/⁴²Sc (T _1/2  =  509-680 ms) on calcium, ²⁸P (T _1/2  =  268 ms) on phosphorus. A translation of the results from elemental targets to PMMA and representative tissues such as adipose tissue, muscle, compact and cortical bone, shows the dominance of ¹³O/¹²N in at least the first 20 s of an irradiation with ⁴He and somewhat longer with ³He. As the production of ¹³O/¹²N in a ³He irradiation is 3-4 times higher than in a ⁴He irradiation, from a statistical point of view, range verification using ¹³O/¹²N PET imaging will be about 2 times more precise for a ³He irradiation compared to a ⁴He irradiation.

A novel range-verification method using ionoacoustic wave generated from spherical gold markers for particle-beam therapy: a simulation study

This study proposes a novel alternative range-verification method for proton beam with acoustic waves generated from spherical metal markers. When proton beam is incident on metal markers, most of the resulting pressure waves are confined in the markers because of the large difference in acoustic impedance between the metal and tissue. However, acoustic waves with frequency equal to marker’s resonant frequency escape this confinement; the marker briefly acts as an acoustic transmitter. Herein, this phenomenon is exploited to measure the range of the proton beam. We test the proposed strategy in 3-D simulations, combining the dose calculations with modelling of acoustic-wave propagation. A spherical gold marker of 2.0 mm diameter was placed in water with a 60 MeV proton beam incident on it. We investigated the dependence of pressure waves on the width of beam pulse and marker position. At short beam pulse, specific high-frequency acoustic waves of 1.62 MHz originating from the marker were observed in wave simulations, whose amplitude correlated with the distance between the marker and Bragg peak. Results indicate that the Bragg peak position can be estimated by measuring the acoustic wave amplitudes from the marker, using a single detector properly designed for the resonance frequency.

In vivo range verification in particle therapy

Exploitation of the full potential offered by ion beams in clinical practice is still hampered by several sources of treatment uncertainties, particularly related to the limitations of our ability to locate the position of the Bragg peak in the tumor. To this end, several efforts are ongoing to improve the characterization of patient position, anatomy, and tissue stopping power properties prior to treatment as well as to enable in vivo verification of the actual dose delivery, or at least beam range, during or shortly after treatment. This contribution critically reviews methods under development or clinical testing for verification of ion therapy, based on pretreatment range and tissue probing as well as the detection of secondary emissions or physiological changes during and after treatment, trying to disentangle approaches of general applicability from those more specific to certain anatomical locations. Moreover, it discusses future directions, which could benefit from an integration of multiple modalities or address novel exploitation of the measurable signals for biologically adapted therapy.

Advances in the use of motion management and image guidance in radiation therapy treatment for lung cancer

The development of advanced radiation technologies, including intensity-modulated radiation therapy (IMRT), stereotactic body radiation therapy (SBRT) and proton therapy, has resulted in increasingly conformal radiation treatments. Recent evidence for the importance of minimizing dose to normal critical structures including the heart and lungs has led to incorporation of these advanced treatment modalities into radiation therapy (RT) for non-small cell lung cancer (NSCLC). While such technologies have allowed for improved dose delivery, implementation requires improved target accuracy with treatments, placing increasing importance on evaluating tumor motion at the time of planning and verifying tumor position at the time of treatment. In this review article, we describe issues and updates related both to motion management and image guidance in the treatment of NSCLC.

A low-count reconstruction algorithm for Compton-based prompt gamma imaging

The Compton camera is an imaging device which has been proposed to detect prompt gammas (PGs) produced by proton-nuclear interactions within tissue during proton beam irradiation. Compton-based PG imaging has been developed to verify proton ranges because PG rays, particularly characteristic ones, have strong correlations with the distribution of the proton dose. However, accurate image reconstruction from characteristic PGs is challenging because the detector efficiency and resolution are generally low. Our previous study showed that point spread functions can be incorporated into the reconstruction process to improve image resolution. In this study, we proposed a low-count reconstruction algorithm to improve the image quality of a characteristic PG emission by pooling information from other characteristic PG emissions. PGs were simulated from a proton beam irradiated on a water phantom, and a two-stage Compton camera was used for PG detection. The results show that the image quality of the reconstructed characteristic PG emission is improved with our proposed method in contrast to the standard reconstruction method using events from only one characteristic PG emission. For the 4.44 MeV PG rays, both methods can be used to predict the positions of the peak and the distal falloff with a mean accuracy of 2 mm. Moreover, only the proposed method can improve the estimated positions of the peak and the distal falloff of 5.25 MeV PG rays, and a mean accuracy of 2 mm can be reached.

3D prompt gamma imaging for proton beam range verification

We tested the ability of a single Compton camera (CC) to produce 3-dimensional (3D) images of prompt gammas (PGs) emitted during the irradiation of a tissue-equivalent plastic phantom with proton pencil beams for clinical doses delivered at clinical dose rates. PG measurements were made with a small prototype CC placed at three different locations along the proton beam path. We evaluated the ability of the CC to produce images at each location for two clinical scenarios: (1) the delivery of a single 2 Gy pencil beam from a hypo-fractionated treatment (~9  ×  10⁸ protons), and (2) a single pencil beam from a standard treatment (~1  ×  10⁸ protons). Additionally, the data measured at each location were combined to simulate measurements with a larger scale, clinical CC and its ability to image shifts in the Bragg peak (BP) range for both clinical scenarios. With our prototype CC, the location of the distal end of the BP could be seen with the CC placed up to 4 cm proximal or distal to the BP distal falloff. Using the data from the simulated full scale clinical CC, 3D images of the PG emission were produced with the delivery of as few as 1  ×  10⁸ protons, and shifts in the proton beam range as small as 2 mm could be detected for delivery of a 2 Gy spot. From these results we conclude that 3D PG imaging for proton range verification under clinical beam delivery conditions is possible with a single CC.

Spectroscopic study of prompt-gamma emission for range verification in proton therapy

We present the results of an investigation of the prompt-gamma emission from an interaction of a proton beam with phantom materials. Measurements were conducted with a novel setup allowing the precise selection of the investigated depth in the phantom, featuring three different materials composed of carbon, oxygen and hydrogen. We studied two beam energies of 70.54 and 130.87MeV and two detection angles: 90° and 120°. The results are presented in form of profiles of the prompt-gamma yield as a function of depth. In the analysis we focused on the transitions with the largest cross sections: ¹²C_4.44→g.s. and ¹⁶O_6.13→g.s.. We compare the profiles obtained under various irradiation conditions, with emphasis on the shape of the distal fall-off. The results are also compared to calculations including different cross-section models. They are in agreement with the model exploiting published cross-section data, but the comparison with the Talys model shows discrepancies.

Nuclear physics in particle therapy: a review

Charged particle therapy has been largely driven and influenced by nuclear physics. The increase in energy deposition density along the ion path in the body allows reducing the dose to normal tissues during radiotherapy compared to photons. Clinical results of particle therapy support the physical rationale for this treatment, but the method remains controversial because of the high cost and of the lack of comparative clinical trials proving the benefit compared to x-rays. Research in applied nuclear physics, including nuclear interactions, dosimetry, image guidance, range verification, novel accelerators and beam delivery technologies, can significantly improve the clinical outcome in particle therapy. Measurements of fragmentation cross-sections, including those for the production of positron-emitting fragments, and attenuation curves are needed for tuning Monte Carlo codes, whose use in clinical environments is rapidly increasing thanks to fast calculation methods. Existing cross sections and codes are indeed not very accurate in the energy and target regions of interest for particle therapy. These measurements are especially urgent for new ions to be used in therapy, such as helium. Furthermore, nuclear physics hardware developments are frequently finding applications in ion therapy due to similar requirements concerning sensors and real-time data processing. In this review we will briefly describe the physics bases, and concentrate on the open issues.

Review of ultrasound image guidance in external beam radiotherapy part II: intra-fraction motion management and novel applications

Imaging has become an essential tool in modern radiotherapy (RT), being used to plan dose delivery prior to treatment and verify target position before and during treatment. Ultrasound (US) imaging is cost-effective in providing excellent contrast at high resolution for depicting soft tissue targets apart from those shielded by the lungs or cranium. As a result, it is increasingly used in RT setup verification for the measurement of inter-fraction motion, the subject of Part I of this review (Fontanarosa et al 2015 Phys. Med. Biol. 60 R77-114). The combination of rapid imaging and zero ionising radiation dose makes US highly suitable for estimating intra-fraction motion. The current paper (Part II of the review) covers this topic. The basic technology for US motion estimation, and its current clinical application to the prostate, is described here, along with recent developments in robust motion-estimation algorithms, and three dimensional (3D) imaging. Together, these are likely to drive an increase in the number of future clinical studies and the range of cancer sites in which US motion management is applied. Also reviewed are selections of existing and proposed novel applications of US imaging to RT. These are driven by exciting developments in structural, functional and molecular US imaging and analytical techniques such as backscatter tissue analysis, elastography, photoacoustography, contrast-specific imaging, dynamic contrast analysis, microvascular and super-resolution imaging, and targeted microbubbles. Such techniques show promise for predicting and measuring the outcome of RT, quantifying normal tissue toxicity, improving tumour definition and defining a biological target volume that describes radiation sensitive regions of the tumour. US offers easy, low cost and efficient integration of these techniques into the RT workflow. US contrast technology also has potential to be used actively to assist RT by manipulating the tumour cell environment and by improving the delivery of radiosensitising agents. Finally, US imaging offers various ways to measure dose in 3D. If technical problems can be overcome, these hold potential for wide-dissemination of cost-effective pre-treatment dose verification and in vivo dose monitoring methods. It is concluded that US imaging could eventually contribute to all aspects of the RT workflow.

Short-lived positron emitters in beam-on PET imaging during proton therapy

The only method for in vivo dose delivery verification in proton beam radiotherapy in clinical use today is positron emission tomography (PET) of the positron emitters produced in the patient during irradiation. PET imaging while the beam is on (so called beam-on PET) is an attractive option, providing the largest number of counts, the least biological washout and the fastest feedback. In this implementation, all nuclides, independent of their half-life, will contribute. As a first step towards assessing the relevance of short-lived nuclides (half-life shorter than that of (10)C, T1/2  =  19 s) for in vivo dose delivery verification using beam-on PET, we measured their production in the stopping of 55 MeV protons in water, carbon, phosphorus and calcium The most copiously produced short-lived nuclides and their production rates relative to the relevant long-lived nuclides are: (12)N (T1/2  =  11 ms) on carbon (9% of (11)C), (29)P (T1/2  =  4.1 s) on phosphorus (20% of (30)P) and (38m)K (T1/2  =  0.92 s) on calcium (113% of (38g)K). No short-lived nuclides are produced on oxygen. The number of decays integrated from the start of an irradiation as a function of time during the irradiation of PMMA and 4 tissue materials has been determined. For (carbon-rich) adipose tissue, (12)N dominates up to 70 s. On bone tissue, (12)N dominates over (15)O during the first 8-15 s (depending on carbon-to-oxygen ratio). The short-lived nuclides created on phosphorus and calcium provide 2.5 times more beam-on PET counts than the long-lived ones produced on these elements during a 70 s irradiation. From the estimated number of (12)N PET counts, we conclude that, for any tissue, (12)N PET imaging potentially provides equal to superior proton range information compared to prompt gamma imaging with an optimized knife-edge slit camera. The practical implementation of (12)N PET imaging is discussed.

Time-resolved imaging of prompt-gamma rays for proton range verification using a knife-edge slit camera based on digital photon counters

Proton range monitoring may facilitate online adaptive proton therapy and improve treatment outcomes. Imaging of proton-induced prompt gamma (PG) rays using a knife-edge slit collimator is currently under investigation as a potential tool for real-time proton range monitoring. A major challenge in collimated PG imaging is the suppression of neutron-induced background counts. In this work, we present an initial performance test of two knife-edge slit camera prototypes based on arrays of digital photon counters (DPCs). PG profiles emitted from a PMMA target upon irradiation with a 160 MeV proton pencil beams (about 6.5 × 10(9) protons delivered in total) were measured using detector modules equipped with four DPC arrays coupled to BGO or LYSO : Ce crystal matrices. The knife-edge slit collimator and detector module were placed at 15 cm and 30 cm from the beam axis, respectively, in all cases. The use of LYSO : Ce enabled time-of-flight (TOF) rejection of background events, by synchronizing the DPC readout electronics with the 106 MHz radiofrequency signal of the cyclotron. The signal-to-background (S/B) ratio of 1.6 obtained with a 1.5 ns TOF window and a 3 MeV-7 MeV energy window was about 3 times higher than that obtained with the same detector module without TOF discrimination and 2 times higher than the S/B ratio obtained with the BGO module. Even 1 mm shifts of the Bragg peak position translated into clear and consistent shifts of the PG profile if TOF discrimination was applied, for a total number of protons as low as about 6.5 × 10(8) and a detector surface of 6.6 cm × 6.6 cm.

Detecting prompt gamma emission during proton therapy: the effects of detector size and distance from the patient

Recent studies have suggested that the characteristics of prompt gammas (PGs) emitted from excited nuclei during proton therapy are advantageous for determining beam range during treatment delivery. Since PGs are only emitted while the beam is on, the feasibility of using PGs for online treatment verification depends greatly on the design of highly efficient detectors. The purpose of this work is to characterize how PG detection changes as a function of distance from the patient as a means of guiding the design and usage of clinical PG imaging detectors. Using a Monte Carlo model (GEANT4.9.4) we studied the detection rate (PGs per incident proton) of a high purity germanium detector for both the total PG emission and the characteristic 6.13 MeV PG emission from (16)O emitted during proton irradiation. The PG detection rate was calculated as a function of distance from the isocenter of the proton treatment nozzle for: (1) a water phantom irradiated with a proton pencil beam and (2) a prostate patient irradiated with a scanning beam proton therapy treatment field (lateral field size: ∼6 cm × 6 cm, beam range: 23.5 cm). An analytical expression of the PG detection rate as a function of distance from isocenter, detector size, and proton beam energy was then developed. The detection rates were found to be 1.3 × 10(-6) for oxygen and 3.9 × 10(-4) for the total PG emission, respectively, with the detector placed 11 cm from isocenter for a 40 MeV pencil beam irradiating a water phantom. The total PG detection rate increased by ∼85 ± 3% for beam energies greater than 150 MeV. The detection rate was found to be approximately 2.1 × 10(-6) and 1.7 × 10(-3) for oxygen and total PG emission, respectively, during delivery of a single pencil beam during a scanning beam treatment for prostate cancer. The PG detection rate as a function of distance from isocenter during irradiation of a water phantom with a single proton pencil beam was described well by the model of a point source irradiating a cylindrical detector of a known diameter over the range of beam energies commonly used for proton therapy. For the patient studies, it was necessary to divide the point source equation by an exponential factor in order to correctly predict the falloff of the PG detection rate as a function of distance from isocenter.

Range verification for eye proton therapy based on proton-induced x-ray emissions from implanted metal markers

Metal fiducial markers are often implanted on the back of the eye before proton therapy to improve target localization and reduce patient setup errors. We aim to detect characteristic x-ray emissions from metal targets during proton therapy to verify the treatment range accuracy. Initially gold was chosen for its biocompatibility properties. Proton-induced x-ray emissions (PIXE) from a 15 mm diameter gold marker were detected at different penetration depths of a 59 MeV proton beam at the CATANA proton facility at INFN-LNS (Italy). The Monte Carlo code Geant4 was used to reproduce the experiment and to investigate the effect of different size markers, materials, and the response to both mono-energetic and fully modulated beams. The intensity of the emitted x-rays decreases with decreasing proton energy and thus decreases with depth. If we assume the range to be the depth at which the dose is reduced to 10% of its maximum value and we define the residual range as the distance between the marker and the range of the beam, then the minimum residual range which can be detected with 95% confidence level is the depth at which the PIXE peak is equal to 1.96 σ(bkg), which is the standard variation of the background noise. With our system and experimental setup this value is 3 mm, when 20 GyE are delivered to a gold marker of 15 mm diameter. Results from silver are more promising. Even when a 5 mm diameter silver marker is placed at a depth equal to the range, the PIXE peak is 2.1 σ(bkg). Although these quantitative results are dependent on the experimental setup used in this research study, they demonstrate that the real-time analysis of the PIXE emitted by fiducial metal markers can be used to derive beam range. Further analysis are needed to demonstrate the feasibility of the technique in a clinical setup.

The effects of Doppler broadening and detector resolution on the performance of three-stage Compton cameras

PURPOSE

The authors investigated how the characteristics of the detectors used in a three-stage Compton camera (CC) affect the CC's ability to accurately measure the emission distribution and energy spectrum of prompt gammas (PG) emitted by nuclear de-excitations during proton therapy. The detector characteristics they studied included the material (high-purity germanium [HPGe] and cadmium zinc telluride [CZT]), Doppler broadening (DB), and resolution (lateral, depth, and energy).

METHODS

The authors simulated three-stage HPGe and CZT CCs of various configurations, detecting gammas from point sources with energies ranging from 0.511 to 7.12 MeV. They also simulated a proton pencil beam irradiating a tissue target to study how the detector characteristics affect the PG data measured by CCs in a clinical proton therapy setting. They used three figures of merit: the distance of closest approach (DCA) and the point of closest approach (PCA) between the measured and actual position of the PG emission origin, and the calculated energy resolution.

RESULTS

For CCs with HPGe detectors, DB caused the DCA to be greater than 3 mm for 14% of the 6.13 MeV gammas and 20% of the 0.511 MeV gammas. For CCs with CZT detectors, DB caused the DCA to be greater than 3 mm for 18% of the 6.13 MeV gammas and 25% of the 0.511 MeV gammas. The full width at half maximum (FWHM) of the PCA in the ẑ direction for HPGe and CZT detectors ranged from 1.3 to 0.4 mm for gammas with incident energy ranging from 0.511 to 7.12 MeV. For CCs composed of HPGe detectors, the resolution of incident gamma energy calculated by the CC ranged from 6% to 1% for gammas with true incident energies from 0.511 to 7.12 MeV. For CCs composed of CZT detectors, the resolution of gamma energy calculated by the CC ranged from 10% to 1% for gammas with true incident energies from 0.511 to 7.12 MeV. For HPGe and CZT CCs in which all detector effect were included, the DCA was less than 3 mm for 75% and 68% of the detected gammas, respectively, and restricting gammas to those having energy greater than 2.0 MeV increased these percentages to 83% and 77% for HPGe and CZT, respectively. Distributions of the true gamma origins and the PCA after detector characteristics had been included showed good agreement on beam range and some loss of resolution for the lateral profile of the PG emission. Characteristic energy lines were evident in the calculated gamma energy spectrum.

CONCLUSIONS

The authors found the following: (1) DB is the dominant source of spatial and energy resolution loss in the CCs at all energy levels; (2) the largest difference in the spatial resolution of HPGe and CZT CCs is that the spatial resolution distributions of CZT have broader tails. The differences in the FWHM of these distributions are small; (3) the energy resolution of both HPGe and CZT three-stage CCs is adequate for PG spectroscopy; and (4) restricting the gammas to those having energy greater than 2.0 MeV can improve the achievable image resolution.

Measurement of characteristic prompt gamma rays emitted from oxygen and carbon in tissue-equivalent samples during proton beam irradiation

The purpose of this work was to characterize how prompt gamma (PG) emission from tissue changes as a function of carbon and oxygen concentration, and to assess the feasibility of determining elemental concentration in tissues irradiated with proton beams. For this study, four tissue-equivalent water-sucrose samples with differing densities and concentrations of carbon, hydrogen, and oxygen were irradiated with a 48 MeV proton pencil beam. The PG spectrum emitted from each sample was measured using a high-purity germanium detector, and the absolute detection efficiency of the detector, average beam current, and delivered dose distribution were also measured. Changes to the total PG emission from (12)C (4.44 MeV) and (16)O (6.13 MeV) per incident proton and per Gray of absorbed dose were characterized as a function of carbon and oxygen concentration in the sample. The intensity of the 4.44 MeV PG emission per incident proton was found to be nearly constant for all samples regardless of their carbon concentration. However, we found that the 6.13 MeV PG emission increased linearly with the total amount (in grams) of oxygen irradiated in the sample. From the measured PG data, we determined that 1.64 × 10(7) oxygen PGs were emitted per gram of oxygen irradiated per Gray of absorbed dose delivered with a 48 MeV proton beam. These results indicate that the 6.13 MeV PG emission from (16)O is proportional to the concentration of oxygen in tissue irradiated with proton beams, showing that it is possible to determine the concentration of oxygen within tissues irradiated with proton beams by measuring (16)O PG emission.

In vivo proton range verification: a review

Protons are an interesting modality for radiotherapy because of their well defined range and favourable depth dose characteristics. On the other hand, these same characteristics lead to added uncertainties in their delivery. This is particularly the case at the distal end of proton dose distributions, where the dose gradient can be extremely steep. In practice however, this gradient is rarely used to spare critical normal tissues due to such worries about its exact position in the patient. Reasons for this uncertainty are inaccuracies and non-uniqueness of the calibration from CT Hounsfield units to proton stopping powers, imaging artefacts (e.g. due to metal implants) and anatomical changes of the patient during treatment. In order to improve the precision of proton therapy therefore, it would be extremely desirable to verify proton range in vivo, either prior to, during, or after therapy. In this review, we describe and compare state-of-the art in vivo proton range verification methods currently being proposed, developed or clinically implemented.

Deriving concentrations of oxygen and carbon in human tissues using single- and dual-energy CT for ion therapy applications

Dedicated methods of in-vivo verification of ion treatment based on the detection of secondary emitted radiation, such as positron-emission-tomography and prompt gamma detection require high accuracy in the assignment of the elemental composition. This especially concerns the content in carbon and oxygen, which are the most abundant elements of human tissue. The standard single-energy computed tomography (SECT) approach to carbon and oxygen concentration determination has been shown to introduce significant discrepancies in the carbon and oxygen content of tissues. We propose a dual-energy CT (DECT)-based approach for carbon and oxygen content assignment and investigate the accuracy gains of the method. SECT and DECT Hounsfield units (HU) were calculated using the stoichiometric calibration procedure for a comprehensive set of human tissues. Fit parameters for the stoichiometric calibration were obtained from phantom scans. Gaussian distributions with standard deviations equal to those derived from phantom scans were subsequently generated for each tissue for several values of the computed tomography dose index (CTDIvol). The assignment of %weight carbon and oxygen (%wC,%wO) was performed based on SECT and DECT. The SECT scheme employed a HU versus %wC,O approach while for DECT we explored a Zeff versus %wC,O approach and a (Zeff, ρe) space approach. The accuracy of each scheme was estimated by calculating the root mean square (RMS) error on %wC,O derived from the input Gaussian distribution of HU for each tissue and also for the noiseless case as a limiting case. The (Zeff, ρe) space approach was also compared to SECT by comparing RMS error for hydrogen and nitrogen (%wH,%wN). Systematic shifts were applied to the tissue HU distributions to assess the robustness of the method against systematic uncertainties in the stoichiometric calibration procedure. In the absence of noise the (Zeff, ρe) space approach showed more accurate %wC,O assignment (largest error of 2%) than the Zeff versus %wC,O and HU versus %wC,O approaches (largest errors of 15% and 30%, respectively). When noise was present, the accuracy of the (Zeff, ρe) space (DECT approach) was decreased but the RMS error over all tissues was lower than the HU versus %wC,O (SECT approach) (5.8%wC versus 7.5%wC at CTDIvol = 20 mGy). The DECT approach showed decreasing RMS error with decreasing image noise (or increasing CTDIvol). At CTDIvol = 80 mGy the RMS error over all tissues was 3.7% for DECT and 6.2% for SECT approaches. However, systematic shifts greater than ±5HU undermined the accuracy gains afforded by DECT at any dose level. DECT provides more accurate %wC,O assignment than SECT when imaging noise and systematic uncertainties in HU values are not considered. The presence of imaging noise degrades the DECT accuracy on %wC,O assignment but it remains superior to SECT. However, DECT was found to be sensitive to systematic shifts of human tissue HU.

Quantitative assessment of lesion detection accuracy, resolution, and reconstruction algorithms in neutron stimulated emission computed tomography

We present a quantitative analysis of the image quality obtained using filtered back-projection (FBP) with Ram-Lak filtering and maximum likelihood-expectation maximization (ML-EM)-with no post-reconstruction filtering in either case-in neutron stimulated emission computed tomography (NSECT) imaging using Monte Carlo simulations in the context of clinically relevant models of liver iron overload. The ratios of pixel intensities for several regions of interest and lesion shape detection using an active-contours segmentation algorithm are assessed for accuracy across different scanning configurations and reconstruction algorithms. The modulation transfer functions (MTFs) are also computed for the cases under study and are applied to determine a minimum detectable lesion spacing as a form of sensitivity analysis. The accuracy of NSECT imaging in measuring relative tissue concentration is presented for simulated clinical liver cases. When using the 15th iteration, ML-EM provides at least 25% better resolution than FBP and proves to be highly robust under low-signal high-noise conditions prevalent in NSECT. However, FBP gives more accurate lesion pixel intensity ratios and size estimates in some cases; due to advantages provided by both reconstruction algorithms, it is worth exploring the development of an algorithm that is a hybrid of the two. We also show that NSECT imaging can be used to accurately detect 3-cm lesions in backgrounds that are a significant fraction (one-quarter) of the concentration of the lesion, down to a 4-cm spacing between lesions.