Myths and realities of range uncertainty

Measurement of the12C(p,n)12N reaction cross section below 150 MeV

Objective. Proton therapy currently faces challenges from clinical complications on organs-at-risk due to range uncertainties. To address this issue, positron emission tomography (PET) of the proton-induced11C and15O activity has been used to provide feedback on the proton range. However, this approach is not instantaneous due to the relatively long half-lives of these nuclides. An alternative nuclide,12N (half-life 11 ms), shows promise for real-timein vivoproton range verification. Development of12N imaging requires better knowledge of its production reaction cross section.Approach. The12C(p,n)12N reaction cross section was measured by detecting positron activity of graphite targets irradiated with 66.5, 120, and 150 MeV protons. A pulsed beam delivery with 0.7-2 × 108protons per pulse was used. The positron activity was measured during the beam-off periods using a dual-head Siemens Biograph mCT PET scanner. The12N production was determined from activity time histograms.Main results. The cross section was calculated for 11 energies, ranging from 23.5 to 147 MeV, using information on the experimental setup and beam delivery. Through a comprehensive uncertainty propagation analysis, a statistical uncertainty of 2.6%-5.8% and a systematic uncertainty of 3.3%-4.6% were achieved. Additionally, a comparison between measured and simulated scanner sensitivity showed a scaling factor of 1.25 (±3%). Despite this, there was an improvement in the precision of the cross section measurement compared to values reported by the only previous study.Significance. Short-lived12N imaging is promising for real-timein vivoverification of the proton range to reduce clinical complications in proton therapy. The verification procedure requires experimental knowledge of the12N production cross section for proton energies of clinical importance, to be incorporated in a Monte Carlo framework for12N imaging prediction. This study is the first to achieve a precise measurement of the12C(p,n)12N nuclear cross section for such proton energies.

A review of the clinical introduction of 4D particle therapy research concepts

Background and purpose

Many 4D particle therapy research concepts have been recently translated into clinics, however, remaining substantial differences depend on the indication and institute-related aspects. This work aims to summarise current state-of-the-art 4D particle therapy technology and outline a roadmap for future research and developments.

Material and methods

This review focused on the clinical implementation of 4D approaches for imaging, treatment planning, delivery and evaluation based on the 2021 and 2022 4D Treatment Workshops for Particle Therapy as well as a review of the most recent surveys, guidelines and scientific papers dedicated to this topic.

Results

Available technological capabilities for motion surveillance and compensation determined the course of each 4D particle treatment. 4D motion management, delivery techniques and strategies including imaging were diverse and depended on many factors. These included aspects of motion amplitude, tumour location, as well as accelerator technology driving the necessity of centre-specific dosimetric validation. Novel methodologies for X-ray based image processing and MRI for real-time tumour tracking and motion management were shown to have a large potential for online and offline adaptation schemes compensating for potential anatomical changes over the treatment course. The latest research developments were dominated by particle imaging, artificial intelligence methods and FLASH adding another level of complexity but also opportunities in the context of 4D treatments.

Conclusion

This review showed that the rapid technological advances in radiation oncology together with the available intrafractional motion management and adaptive strategies paved the way towards clinical implementation.

Multimodal imaging-based material mass density estimation for proton therapy using supervised deep learning

OBJECTIVE

Mapping CT number to material property dominates the proton range uncertainty. This work aims to develop a physics-constrained deep learning-based multimodal imaging (PDMI) framework to integrate physics, deep learning, MRI, and advanced dual-energy CT (DECT) to derive accurate patient mass density maps.

METHODS

Seven tissue substitute MRI phantoms were used for validation including adipose, brain, muscle, liver, skin, spongiosa, 45% hydroxyapatite (HA) bone. MRI images were acquired using T1 weighted Dixon and T2 weighted short tau inversion recovery sequences. Training inputs are from MRI and twin-beam dual-energy images acquired at 120 kVp with gold/tin filters. The feasibility investigation included an empirical model and four residual networks (ResNet) derived from different training inputs and strategies by PDMI framework. PRN-MR-DE and RN-MR-DE denote ResNet (RN) trained with and without a physics constraint (P) using MRI (MR) and DECT (DE) images. PRN-DE stands for RN trained with a physics constraint using only DE images. A retrospective study using institutional patient data was also conducted to investigate the feasibility of the proposed framework.

RESULTS

For the tissue surrogate study, PRN-MR-DE, PRN-DE, and RN-MR-DE result in mean mass density errors: -0.72%/2.62%/-3.58% for adipose; -0.03%/-0.61%/-0.18% for muscle; -0.58%/-1.36%/-4.86% for 45% HA bone. The retrospective patient study indicated that PRN-MR-DE predicted the densities of soft tissue and bone within expected intervals based on the literature survey, while PRN-DE generated large density deviations.

CONCLUSION

The proposed PDMI framework can generate accurate mass density maps using MRI and DECT images. The supervised learning can further enhance model efficacy, making PRN-MR-DE outperform RN-MR-DE. The patient investigation also shows that the framework can potentially improve proton range uncertainty with accurate patient mass density maps.

ADVANCES IN KNOWLEDGE

PDMI framework is proposed for the first time to inform deep learning models by physics insights and leverage the information from MRI to derive accurate mass density maps.

Clinical benefit of range uncertainty reduction in proton treatment planning based on dual-energy CT for neuro-oncological patients

OBJECTIVE

Several studies have shown that dual-energy CT (DECT) can lead to improved accuracy for proton range estimation. This study investigated the clinical benefit of reduced range uncertainty, enabled by DECT, in robust optimisation for neuro-oncological patients.

METHODS

DECT scans for 27 neuro-oncological patients were included. Commercial software was applied to create stopping-power ratio (SPR) maps based on the DECT scan. Two plans were robustly optimised on the SPR map, keeping the beam and plan settings identical to the clinical plan. One plan was robustly optimised and evaluated with a range uncertainty of 3% (as used clinically; denoted 3%-plan); the second plan applied a range uncertainty of 2% (2%-plan). Both plans were clinical acceptable and optimal. The dose-volume histogram parameters were compared between the two plans. Two experienced neuro-radiation oncologists determined the relevant dose difference for each organ-at-risk (OAR). Moreover, the OAR toxicity levels were assessed.

RESULTS

For 24 patients, a dose reduction >0.5/1 Gy (relevant dose difference depending on the OAR) was seen in one or more OARs for the 2%-plan; e.g. for brainstem D0.03cc in 10 patients, and hippocampus D40% in 6 patients. Furthermore, 12 patients had a reduction in toxicity level for one or two OARs, showing a clear benefit for the patient.

CONCLUSION

Robust optimisation with reduced range uncertainty allows for reduction of OAR toxicity, providing a rationale for clinical implementation. Based on these results, we have clinically introduced DECT-based proton treatment planning for neuro-oncological patients, accompanied with a reduced range uncertainty of 2%.

ADVANCES IN KNOWLEDGE

This study shows the clinical benefit of range uncertainty reduction from 3% to 2% in robustly optimised proton plans. A dose reduction to one or more OARs was seen for 89% of the patients, and 44% of the patients had an expected toxicity level decrease.

Emerging technologies for cancer therapy using accelerated particles

Cancer therapy with accelerated charged particles is one of the most valuable biomedical applications of nuclear physics. The technology has vastly evolved in the past 50 years, the number of clinical centers is exponentially growing, and recent clinical results support the physics and radiobiology rationale that particles should be less toxic and more effective than conventional X-rays for many cancer patients. Charged particles are also the most mature technology for clinical translation of ultra-high dose rate (FLASH) radiotherapy. However, the fraction of patients treated with accelerated particles is still very small and the therapy is only applied to a few solid cancer indications. The growth of particle therapy strongly depends on technological innovations aiming to make the therapy cheaper, more conformal and faster. The most promising solutions to reach these goals are superconductive magnets to build compact accelerators; gantryless beam delivery; online image-guidance and adaptive therapy with the support of machine learning algorithms; and high-intensity accelerators coupled to online imaging. Large international collaborations are needed to hasten the clinical translation of the research results.

Challenges and opportunities in stereotactic body proton radiotherapy of liver malignancies

Stereotactic body proton radiotherapy (SBPT) has the potential to be an effective tool for treating liver malignancies. While proton therapy enables near-zero exit dose and could improve normal tissue sparing, including liver and other surrounding structures, there are challenges in implementing the SBPT technique for proton therapy, including respiratory motion, range uncertainties, dose regimen, treatment planning, and image guidance. This article summarizes the technical and clinical challenges facing SBPT, along with the potential benefits of SBPT for liver malignancies. The clinical implementation of the technique is also described for the first six patients treated at the Johns Hopkins Proton Therapy Center using liver SBPT.

Automation of pencil beam scanning proton treatment planning for intracranial tumours

PURPOSE

To evaluate the feasibility of comprehensive automation of an intra-cranial proton treatment planning.

MATERIALS AND METHODS

Class solution (CS) beam configuration selection allows the user to identify predefined beam configuration based on target localization; automatic CS (aCS) will then explore all the possible CS beam geometries. Ten patients, already used for the evaluation of the automatic selection of the beam configuration, have been also employed to training an algorithm based on the computation of a benchmark dose exploit automatic general planning solution (GPS) optimization with a wish list approach for the planning optimization. An independent cohort of ten patients has been then used for the evaluation step between the clinical and the GPS plan in terms of dosimetric quality of plans and the time needed to generate a plan.

RESULTS

The definition of a beam configuration requires on average 22 min (range 9-29 min). The average time for GPS plan generation is 18 min (range 7-26 min). Median dose differences (GPS-Manual) for each OAR constraints are: brainstem -1.60 Gy, left cochlea -1.22 Gy, right cochlea -1.42 Gy, left eye 0.55 Gy, right eye -2.33 Gy, optic chiasm -1.87 Gy, left optic nerve -4.45 Gy, right optic nerve -2.48 Gy and optic tract -0.31 Gy. Dosimetric CS and aCS plan evaluation shows a slightly worsening of the OARs values except for the optic tract and optic chiasm for both CS and aCS, where better results have been observed.

CONCLUSION

This study has shown the feasibility and implementation of the automatic planning system for intracranial tumors. The method developed in this work is ready to be implemented in a clinical workflow.

Ionoacoustic application of an optical hydrophone to detect proton beam range in water

BACKGROUND

Proton range uncertainty has been the main factor limiting the ability of proton therapy to concentrate doses to tumors to their full potential. Ionoacoustic (IA) range verification is an approach to reducing this uncertainty by detecting thermoacoustic waves emitted from an irradiated volume immediately following a pulsed proton beam delivery; however, the signal weakness has been an obstacle to its clinical application. To increase the signal-to-noise ratio (SNR) with the conventional piezoelectric hydrophone (PH), the detector-sensitive volume needs to be large, but it could narrow the range of available beam angles and disturb real-time images obtained during beam delivery.

PURPOSE

To prevent this issue, we investigated a millimeter-sized optical hydrophone (OH) that exploits the laser interferometric principle. For two types of IA waves [γ-wave emitted from the Bragg peak (BP) and a spherical IA wave with resonant frequency (SPIRE) emitted from the gold fiducial marker (GM)], comparisons were made with PH in terms of waveforms, SNR, range detection accuracy, and signal intensity robustness against the small detector misalignment, particularly for SPIRE.

METHODS

A 100-MeV proton beam with a 27 ns pulse width and 4 mm beam size was produced using a fixed-field alternating gradient accelerator and was irradiated to the water phantom. The GM was set on the beam's central axis. Acrylic plates of various thicknesses, up to 12 mm, were set in front of the phantoms to shift the proton range. OH was set distal and lateral to the beam, and the range was estimated using the time-of-flight method for γ-wave and by comparing with the calibration data (SPIRE intensity versus the distance between the GM and BP) derived from an IA wave transport simulation for SPIRE. The BP dose per pulse was 0.5-0.6 Gy. To measure the variation in SPIRE amplitude against the hydrophone misalignment, the hydrophone was shifted by ± 2 mm at a maximum in lateral directions.

RESULTS

Despite its small size, OH could detect γ-wave with a higher SNR than the conventional PH (diameter, 29 mm), and a single measurement was sufficient to detect the beam range with a submillimeter accuracy in water. In the SPIRE measurement, OH was far more robust against the detector misalignment than the focused PH (FPH) used in our previous study [5%/mm (OH) versus 80%/mm (FPH)], and the correlation between the measured SPIRE intensity and the distance between the GM and BP agreed well with the simulation results. However, the OH sensitivity was lower than the FPH sensitivity, and about 5.6-Gy dose was required to decrease the intensity variation among measurements to less than 10%.

CONCLUSION

The miniature OH was found to detect weak IA signals produced by proton beams with a BP dose used in hypofractionated regimens. The OH sensitivity improvement at the MHz regime is worth exploring as the next step.

Depth dose measurements in water for 11C and 10C beams with therapy relevant energies

Owing to the favorable depth-dose distribution and the radiobiological properties of heavy ion radiation, ion beam therapy shows an improved success/toxicity ratio compared to conventional radiotherapy. The sharp dose gradients and very high doses in the Bragg peak region, which represent the larger physical advantage of ion beam therapy, make it also extremely sensitive to range uncertainties. The use of β ⁺-radioactive ion beams would be ideal for simultaneous treatment and accurate online range monitoring through PET imaging. Since all the unfragmented primary ions are potentially contributing to the PET signal, these beams offer an improved image quality while preserving the physical and radiobiological advantages of the stable counterparts. The challenging production of radioactive ion beams and the difficulties in reaching high intensities, have discouraged their clinical application. In this context, the project Biomedical Applications of Radioactive ion Beams (BARB) started at GSI (Helmholtzzentrum für Schwerionenforschung GmbH) with the main goal to assess the technical feasibility and investigate possible advantages of radioactive ion beams on the pre-clinical level. During the first experimental campaign ¹¹C and ¹⁰C beams were produced and isotopically separated with the FRagment Separator (FRS) at GSI. The β ⁺-radioactive ion beams were produced with a beam purity of 99% for all the beam investigated (except one case where it was 94%) and intensities potentially sufficient to treat a small animal tumors within few minutes of irradiation time, ∼ 10⁶ particle per spill for the ¹⁰C and ∼ 10⁷ particle per spill for the ¹¹C beam, respectively. The impact of different ion optical parameters on the depth dose distribution was studied with a precision water column system. In this work, the measured depth dose distributions are presented together with results from Monte Carlo simulations using the FLUKA software.

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.

Quantification of biological range uncertainties in patients treated at the Krakow proton therapy centre

Background

Variable relative biological effectiveness (vRBE) in proton therapy might significantly modify the prediction of RBE-weighted dose delivered to a patient during proton therapy. In this study we will present a method to quantify the biological range extension of the proton beam, which results from the application of vRBE approach in RBE-weighted dose calculation.

Methods and materials

The treatment plans of 95 patients (brain and skull base patients) were used for RBE-weighted dose calculation with constant and the McNamara RBE model. For this purpose the Monte Carlo tool FRED was used. The RBE-weighted dose distributions were analysed using indices from dose-volume histograms. We used the volumes receiving at least 95% of the prescribed dose (V95) to estimate the biological range extension resulting from vRBE approach.

Results

The vRBE model shows higher median value of relative deposited dose and D95 in the planning target volume by around 1% for brain patients and 4% for skull base patients. The maximum doses in organs at risk calculated with vRBE was up to 14 Gy above dose limit. The mean biological range extension was greater than 0.4 cm.

Discussion

Our method of estimation of biological range extension is insensitive for dose inhomogeneities and can be easily used for different proton plans with intensity-modulated proton therapy (IMPT) optimization. Using volumes instead of dose profiles, which is the common method, is more universal. However it was tested only for IMPT plans on fields arranged around the tumor area.

Conclusions

Adopting a vRBE model results in an increase in dose and an extension of the beam range, which is especially disadvantageous in cancers close to organs at risk. Our results support the need to re-optimization of proton treatment plans when considering vRBE.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13014-022-02022-5.

An Iterative Least Squares Method for Proton CT Image Reconstruction

Clinically useful proton Computed Tomography images will rely on algorithms to find the three-dimensional proton stopping power distribution that optimally fits the measured proton data. We present a least squares iterative method with many features to put proton imaging into a more quantitative framework. These include the definition of a unique solution that optimally fits the protons, the definition of an iteration vector that takes into account proton measurement uncertainties, the definition of an optimal step size for each iteration individually, the ability to simultaneously optimize the step sizes of many iterations, the ability to divide the proton data into arbitrary numbers of blocks for parallel processing and use of graphical processing units, and the definition of stopping criteria to determine when to stop iterating. We find that it is possible, for any object being imaged, to provide assurance that the image is quantifiably close to an optimal solution, and the optimization of step sizes reduces the total number of iterations required for convergence. We demonstrate the use of these algorithms on real data.

Physics and biomedical challenges of cancer therapy with accelerated heavy ions

Radiotherapy should have low toxicity in the entrance channel (normal tissue) and be very effective in cell killing in the target region (tumour). In this regard, ions heavier than protons have both physical and radiobiological advantages over conventional X-rays. Carbon ions represent an excellent combination of physical and biological advantages. There are a dozen carbon-ion clinical centres in Europe and Asia, and more under construction or at the planning stage, including the first in the USA. Clinical results from Japan and Germany are promising, but a heated debate on the cost-effectiveness is ongoing in the clinical community, owing to the larger footprint and greater expense of heavy ion facilities compared with proton therapy centres. We review here the physical basis and the clinical data with carbon ions and the use of different ions, such as helium and oxygen. Research towards smaller and cheaper machines with more effective beam delivery is necessary to make particle therapy affordable. The potential of heavy ions has not been fully exploited in clinics and, rather than there being a single 'silver bullet', different particles and their combination can provide a breakthrough in radiotherapy treatments in specific cases.

A comparison of proton stopping power measured with proton CT and x-ray CT in fresh postmortem porcine structures

PURPOSE

Currently, calculations of proton range in proton therapy patients are based on a conversion of CT Hounsfield units of patient tissues into proton relative stopping power. Uncertainties in this conversion necessitate larger proximal and distal planned target volume margins. Proton CT can potentially reduce these uncertainties by directly measuring proton stopping power. We aim to demonstrate proton CT imaging with complex porcine samples, to analyze in detail three-dimensional regions of interest, and to compare proton stopping powers directly measured by proton CT to those determined from x-ray CT scans.

METHODS

We have used a prototype proton imaging system with single proton tracking to acquire proton radiography and proton CT images of a sample of porcine pectoral girdle and ribs, and a pig's head. We also acquired close in time x-ray CT scans of the same samples and compared proton stopping power measurements from the two modalities. In the case of the pig's head, we obtained x-ray CT scans from two different scanners and compared results from high-dose and low-dose settings.

RESULTS

Comparing our reconstructed proton CT images with images derived from x-ray CT scans, we find agreement within 1% to 2% for soft tissues and discrepancies of up to 6% for compact bone. We also observed large discrepancies, up to 40%, for cavitated regions with mixed content of air, soft tissue, and bone, such as sinus cavities or tympanic bullae.

CONCLUSIONS

Our images and findings from a clinically realistic proton CT scanner demonstrate the potential for proton CT to be used for low-dose treatment planning with reduced margins.

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

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

Combined proton-photon treatment for breast cancer

Objective.Proton therapy remains a limited resource due to gantry size and its cost. Recently, a new design without a gantry has been suggested. It may enable combined proton-photon therapy (CPPT) in conventional bunkers and allow the widespread use of protons. In this work, we explore this concept for breast cancer.Methods.The treatment room consists of a LINAC for intensity modulated radiation therapy (IMRT), a fixed proton beamline (FBL) with beam scanning and a motorized couch for treatments in lying positions with accurate patient setup. Thereby, proton and photon beams are delivered in the same fraction. Treatment planning is performed by simultaneously optimizing IMRT and IMPT plans based on the cumulative dose. The concept is investigated for three breast cancers where the goal is to minimize mean dose to the heart and lung while delivering 40.05 Gy in 15 fractions to the PTV with a SIB of 48 Gy to the tumor bed. The probabilistic approach is applied to mitigate the sensitivity to range uncertainties.Results. CPPT is particularly advantageous for irradiating concave target volumes that wrap around a curved chest wall. There, protons may deliver dose to the peripheral and medial parts of the target volume including lymph nodes. Thereby, the mean dose in normal tissues is reduced compared to single-modality IMRT. However, tangential photon beams may treat parts of the target volume near the interface to the lung. To ensure target coverage for range undershoot in an IMPT plan, proton beams have to deliberately overshoot into the lung tissue-a problem that can be mitigated via the photon component which ensures plan conformity and robustness.Conclusion.CPPT using an FBL may represent a realistic approach to make protons available to more patients. In addition, CPPT may generally improve treatment quality compared to both single-modality proton and photon treatments.

Further investigation of 3D dose verification in proton therapy utilizing acoustic signal, wavelet decomposition and machine learning

Online dose verification in proton therapy is a critical task for quality assurance. We further studied the feasibility of using a wavelet-based machine learning framework to accomplishing that goal in three dimensions, built upon our previous work in 1D. The wavelet decomposition was utilized to extract features of acoustic signals and a bidirectional long-short-term memory (Bi-LSTM) recurrent neural network (RNN) was used. The 3D dose distributions of mono-energetic proton beams (multiple beam energies) inside a 3D CT phantom, were generated using Monte-Carlo simulation. The 3D propagation of acoustic signal was modeled using the k-Wave toolbox. Three different beamlets (i.e. acoustic pathways) were tested, one with its own model. The performance was quantitatively evaluated in terms of mean relative error (MRE) of dose distribution and positioning error of Bragg peak (ΔBP), for two signal-to-noise ratios (SNRs). Due to the lack of experimental data for the time being, two SNR conditions were modeled (SNR = 1 and 5). The model is found to yield good accuracy and noise immunity for all three beamlets. The results exhibit an MRE below 0.6% (without noise) and 1.2% (SNR = 5), andΔBPbelow 1.2 mm (without noise) and 1.3 mm (SNR = 5). For the worst-case scenario (SNR = 1), the MRE andΔBPare below 2.3% and 1.9 mm, respectively. It is encouraging to find out that our model is able to identify the correlation between acoustic waveforms and dose distributions in 3D heterogeneous tissues, as in the 1D case. The work lays a good foundation for us to advance the study and fully validate the feasibility with experimental results.

Adaptive proton therapy

Radiation therapy treatments are typically planned based on a single image set, assuming that the patient's anatomy and its position relative to the delivery system remains constant during the course of treatment. Similarly, the prescription dose assumes constant biological dose-response over the treatment course. However, variations can and do occur on multiple time scales. For treatment sites with significant intra-fractional motion, geometric changes happen over seconds or minutes, while biological considerations change over days or weeks. At an intermediate timescale, geometric changes occur between daily treatment fractions. Adaptive radiation therapy is applied to consider changes in patient anatomy during the course of fractionated treatment delivery. While traditionally adaptation has been done off-line with replanning based on new CT images, online treatment adaptation based on on-board imaging has gained momentum in recent years due to advanced imaging techniques combined with treatment delivery systems. Adaptation is particularly important in proton therapy where small changes in patient anatomy can lead to significant dose perturbations due to the dose conformality and finite range of proton beams. This review summarizes the current state-of-the-art of on-line adaptive proton therapy and identifies areas requiring further research.

Experimental validation of daily adaptive proton therapy

Anatomical changes during proton therapy require rapid treatment plan adaption to mitigate the associated dosimetric impact. This in turn requires a highly efficient workflow that minimizes the time between imaging and delivery. At the Paul Scherrer Institute, we have developed an online adaptive workflow, which is specifically designed for treatments in the skull-base/cranium, with the focus set on simplicity and minimizing changes to the conventional workflow. The dosimetric and timing performance of this daily adaptive proton therapy (DAPT) workflow has been experimentally investigated using an in-house developed DAPT software and specifically developed anthropomorphic phantom. After a standard treatment preparation, which includes the generation of a template plan, the treatment can then be adapted each day, based on daily imaging acquired on an in-room CT. The template structures are then rigidly propagated to this CT and the daily plan is fully re-optimized using the same field arrangement, DVH constraints and optimization settings of the template plan. After a dedicated plan QA, the daily plan is delivered. To minimize the time between imaging and delivery, clinically integrated software for efficient execution of all online adaption steps, as well as tools for comprehensive and automated QA checks, have been developed. Film measurements of an end-to-end validation of a multi-fraction DAPT treatment showed high agreement to the calculated doses. Gamma pass rates with a 3%/3 mm criteria were >92% when comparing the measured dose to the template plan. Additionally, a gamma pass rate >99% was found comparing measurements to the Monte Carlo dose of the daily plans reconstructed from the logfile, accumulated over the delivered fractions. With this, we experimentally demonstrate that the described adaptive workflow can be delivered accurately in a timescale similar to a standard delivery.

Radioactive Beams for Image-Guided Particle Therapy: The BARB Experiment at GSI

Several techniques are under development for image-guidance in particle therapy. Positron (β⁺) emission tomography (PET) is in use since many years, because accelerated ions generate positron-emitting isotopes by nuclear fragmentation in the human body. In heavy ion therapy, a major part of the PET signals is produced by β⁺-emitters generated via projectile fragmentation. A much higher intensity for the PET signal can be obtained using β⁺-radioactive beams directly for treatment. This idea has always been hampered by the low intensity of the secondary beams, produced by fragmentation of the primary, stable beams. With the intensity upgrade of the SIS-18 synchrotron and the isotopic separation with the fragment separator FRS in the FAIR-phase-0 in Darmstadt, it is now possible to reach radioactive ion beams with sufficient intensity to treat a tumor in small animals. This was the motivation of the BARB (Biomedical Applications of Radioactive ion Beams) experiment that is ongoing at GSI in Darmstadt. This paper will present the plans and instruments developed by the BARB collaboration for testing the use of radioactive beams in cancer therapy.

Dose Calculation Algorithms for External Radiation Therapy: An Overview for Practitioners

Radiation therapy (RT) is a constantly evolving therapeutic technique; improvements are continuously being introduced for both methodological and practical aspects. Among the features that have undergone a huge evolution in recent decades, dose calculation algorithms are still rapidly changing. This process is propelled by the awareness that the agreement between the delivered and calculated doses is of paramount relevance in RT, since it could largely affect clinical outcomes. The aim of this work is to provide an overall picture of the main dose calculation algorithms currently used in RT, summarizing their underlying physical models and mathematical bases, and highlighting their strengths and weaknesses, referring to the most recent studies on algorithm comparisons. This handy guide is meant to provide a clear and concise overview of the topic, which will prove useful in helping clinical medical physicists to perform their responsibilities more effectively and efficiently, increasing patient benefits and improving the overall quality of the management of radiation treatment.

Beam-Specific Spot Guidance and Optimization for PBS Proton Treatment of Bilateral Head and Neck Cancers

Purpose

A multi-field optimization (MFO) technique that uses beam-specific spot placement volumes (SPVs) and spot avoidance volumes (SAVs) is introduced for bilateral head and neck (H&N) cancers. These beam-specific volumes are used to guide the optimizer to consistently achieve optimal organ-at-risk (OAR) sparing with target coverage and plan robustness.

Materials and Methods

Implementation of this technique using a 4-beam, 5-beam, and variant 5-beam arrangement is discussed. The generation of beam-specific SPVs and SAVs derived from target and OARs are shown. The SPVs for select fields are further partitioned into optimization volumes for uniform dose distributions that resemble those of single-field optimization (SFO). A conventional MFO plan that does not use beam-specific spot placement guidance (MFOcon) and an MFO plan that uses only beam-specific SPV (MFOspv) are compared with current technique (MFOspv/sav), using both simulated scenarios and forward-calculated plans on weekly verification computed tomography (VFCT) scans.

Results

Dose distribution characteristics of the 4-beam, 5-beam, and variant 5-beam technique are demonstrated with discussion on OAR sparing. When comparing the MFOcon, MFOspv, and MFOspv/sav, the MFOspv/sav is shown to have superior OAR sparing in 9 of the 14 OARs examined. It also shows clinical plan robustness when evaluated by using both simulated uncertainty scenarios and forward-calculated weekly VFCTs throughout the 7-week treatment course.

Conclusion

The MFOspv/sav technique is a systematic approach using SPVs and SAVs to guide the optimizer to consistently reach desired OAR dose values and plan robustness.

Analysis of characteristics of images acquired with a prototype clinical proton radiography system

PURPOSE

Verification of patient-specific proton stopping powers obtained in the patient's treatment position can be used to reduce the distal and proximal margins needed in particle beam planning. Proton radiography can be used as a pretreatment instrument to verify integrated stopping power consistency with the treatment planning CT. Although a proton radiograph is a pixel by pixel representation of integrated stopping powers, the image may also be of high enough quality and contrast to be used for patient alignment. This investigation quantifies the accuracy and image quality of a prototype proton radiography system on a clinical proton delivery system.

METHODS

We have developed a clinical prototype proton radiography system designed for integration into efficient clinical workflows. We tested the images obtained by this system for water-equivalent thickness (WET) accuracy, image noise, and spatial resolution. We evaluated the WET accuracy by comparing the average WET and rms error in several regions of interest (ROI) on a proton radiograph of a custom peg phantom. We measured the spatial resolution on a CATPHAN Line Pair phantom and a custom edge phantom by measuring the 10% value of the modulation transfer function (MTF). In addition, we tested the ability to detect proton range errors due to anatomical changes in a patient with a customized CIRS pediatric head phantom and inserts of varying WET placed in the posterior fossae of the brain. We took proton radiographs of the phantom with each insert in place and created difference maps between the resulting images. Integrated proton range was measured from an ROI in the difference maps.

RESULTS

We measured the WET accuracy of the proton radiographic images to be ±0.2 mm (0.33%) from known values. The spatial resolution of the images was 0.6 lp/mm on the line pair phantom and 1.13 lp/mm on the edge phantom. We were able to detect anatomical changes producing changes in WET as low as 0.6 mm.

CONCLUSION

The proton radiography system produces images with image quality sufficient for pretreatment range consistency verification.

Clinical Progress in Proton Radiotherapy: Biological Unknowns

Simple Summary

Proton radiation therapy is a more recent type of radiotherapy that uses proton beams instead of classical photon or X-rays beams. The clinical benefit of proton therapy is that it allows to treat tumors more precisely. As a result, proton radiotherapy induces less toxicity to healthy tissue near the tumor site. Despite the experience in the clinical use of protons, the response of cells to proton radiation, the radiobiology, is less understood. In this review, we describe the current knowledge about proton radiobiology.

Abstract

Clinical use of proton radiation has massively increased over the past years. The main reason for this is the beneficial depth-dose distribution of protons that allows to reduce toxicity to normal tissues surrounding the tumor. Despite the experience in the clinical use of protons, the radiobiology after proton irradiation compared to photon irradiation remains to be completely elucidated. Proton radiation may lead to differential damages and activation of biological processes. Here, we will review the current knowledge of proton radiobiology in terms of induction of reactive oxygen species, hypoxia, DNA damage response, as well as cell death after proton irradiation and radioresistance.

The 20th Gray lecture 2019: health and heavy ions

Objective

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

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

Methods

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

Results

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

Conclusion

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

Advances in knowledge

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

Radioactive Beams in Particle Therapy: Past, Present, and Future

Heavy ion therapy can deliver high doses with high precision. However, image guidance is needed to reduce range uncertainty. Radioactive ions are potentially ideal projectiles for radiotherapy because their decay can be used to visualize the beam. Positron-emitting ions that can be visualized with PET imaging were already studied for therapy application during the pilot therapy project at the Lawrence Berkeley Laboratory, and later within the EULIMA EU project, the GSI therapy trial in Germany, MEDICIS at CERN, and at HIMAC in Japan. The results show that radioactive ion beams provide a large improvement in image quality and signal-to-noise ratio compared to stable ions. The main hindrance toward a clinical use of radioactive ions is their challenging production and the low intensities of the beams. New research projects are ongoing in Europe and Japan to assess the advantages of radioactive ion beams for therapy, to develop new detectors, and to build sources of radioactive ions for medical synchrotrons.