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

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

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 (RD) defined as the 80% distal dose fall-off and the PG range (RPG), 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 RD and RPG was within 5 mm. These values were consistent with the ground truth distance (RD-RPGg≈ 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 RPG 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 (RD-RPG) 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.

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

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

Applications of Machine Learning to Improve the Clinical Viability of Compton Camera Based in vivo Range Verification in Proton Radiotherapy.

We studied the application of a deep, fully connected Neural Network (NN) to process prompt gamma (PG) data measured by a Compton camera (CC) during the delivery of clinical proton radiotherapy beams. The network identifies 1) recorded "bad" PG events arising from background noise during the measurement, and 2) the correct ordering of PG interactions in the CC to help improve the fidelity of "good" data used for image reconstruction. PG emission from a tissue-equivalent target during irradiation with a 150 MeV proton beam delivered at clinical dose rates was measured with a prototype CC. Images were reconstructed from both the raw measured data and the measured data that was further processed with a neural network (NN) trained to identify "good" and "bad" PG events and predict the ordering of individual interactions within the good PG events. We determine if NN processing of the CC data could improve the reconstructed PG images to a level in which they could provide clinically useful information about the in vivo range and range shifts of the proton beams delivered at full clinical dose rates. Results showed that a deep, fully connected NN improved the achievable contrast to noise ratio (CNR) in our images by more than a factor of 8x. This allowed the path, range, and lateral width of the clinical proton beam within a tissue equivalent target to easily be identified from the PG images, even at the highest dose rates of a 150 MeV proton beam used for clinical treatments. On average, shifts in the beam range as small as 3 mm could be identified. However, when limited by the amount of PG data measured with our prototype CC during the delivery of a single proton pencil beam (~1 × 109 protons), the uncertainty in the reconstructed PG images limited the identification of range shift to ~5 mm. Substantial improvements in CC images were obtained during clinical beam delivery through NN pre-processing of the measured PG data. We believe this shows the potential of NNs to help improve and push CC-based PG imaging toward eventual clinical application for proton RT treatment delivery verification.

Use of CBCT plus plan robustness for reducing QACT frequency in intensity-modulated proton therapy: Head-and-neck cases.

PURPOSE: Anatomic variation has a significant dosimetric impact in intensity-modulated proton therapy. Weekly or biweekly computed tomography (CT) scans, called quality assurance CTs (QACTs), are used to monitor anatomic and resultant dose changes to determine whether adaptive plans are needed. Frequent CT scans result in unwanted QACT dose and increased clinical workloads. This study proposed utilizing patient setup cone-beam CTs (CBCTs) and treatment plan robustness to reduce the frequency of QACTs. METHODS: We retrospectively analyzed data from 27 patients with head-and-neck cancer, including 594 CBCTs, 136 QACTs, and 19 adaptive plans. For each CBCT, water-equivalent thickness (WET) along the pencil-beam path was calculated. For each treatment plan, the WET of the first-day CBCT was used as the reference, and the mean WET changes (ΔWET) in each following CBCT was used as the surrogate of proton range change. Using CBCTs acquired prior to a QACT, we predicted the ΔWET on the QACT day by a linear regression model. The impact of range change on target dose was calculated as the predicted ΔWET weighted by the monitor units of each field. In addition, plan robustness was estimated from the robust dose-volume histograms (DVHs) and combined with ΔWET to reduce QACT frequency. Robustness was estimated from the distance between the DVH curves of the nominal and worst scenarios. RESULTS: When the estimated mean ΔWET was <6.5 mm (or <7.5 mm if the robustness was >95%), the QACT could be skipped without missing any adaptive planning; otherwise a QACT was required. Overall, 41% of QACTs could be eliminated when ΔWET was <6.5 mm and 56% when ΔWET was <7.5 mm, and robustness was >95%. At least one QACT could have been omitted in 25 of the 27 cases under skipping thresholds at ΔWETs <7.5 mm and R > 95%. CONCLUSION: This study suggests that the number of QACTs can be greatly reduced by calculating range change in patient setup CBCTs and can be further reduced by combining this information with analyses of plan robustness.

Pancreatic cancer derived 3D organoids as a clinical tool to evaluate the treatment response.

Background and purpose: Pancreatic cancer (PC) is the fourth leading cause of cancer death in both men and women. The standard of care for patients with locally advanced PC of chemotherapy, stereotactic radiotherapy (RT), or chemo-radiation-therapy has shown highly variable and limited success rates. However, three-dimensional (3D) Pancreatic tumor organoids (PTOs) have shown promise to study tumor response to drugs, and emerging treatments under in vitro conditions. We investigated the potential for using 3D organoids to evaluate the precise radiation and drug dose responses of in vivo PC tumors. Methods: PTOs were created from mouse pancreatic tumor tissues, and their microenvironment was compared to that of in vivo tumors using immunohistochemical and immunofluorescence staining. The organoids and in vivo PC tumors were treated with fractionated X-ray RT, 3-bromopyruvate (3BP) anti-tumor drug, and combination of 3BP + fractionated RT. Results: Pancreatic tumor organoids (PTOs) exhibited a similar fibrotic microenvironment and molecular response (as seen by apoptosis biomarker expression) as in vivo tumors. Untreated tumor organoids and in vivo tumor both exhibited proliferative growth of 6 folds the original size after 10 days, whereas no growth was seen for organoids and in vivo tumors treated with 8 (Gray) Gy of fractionated RT. Tumor organoids showed reduced growth rates of 3.2x and 1.8x when treated with 4 and 6 Gy fractionated RT, respectively. Interestingly, combination of 100 µM of 3BP + 4 Gy of RT showed pronounced growth inhibition as compared to 3-BP alone or 4 Gy of radiation alone. Further, positive identification of SOX2, SOX10 and TGFß indicated presence of cancer stem cells in tumor organoids which might have some role in resistance to therapies in pancreatic cancer. Conclusions: PTOs produced a similar microenvironment and exhibited similar growth characteristics as in vivo tumors following treatment, indicating their potential for predicting in vivo tumor sensitivity and response to RT and combined chemo-RT treatments.

Therapeutic Efficacy of Variable Biological Effectiveness of Proton Therapy in U-CH2 and MUG-Chor1 Human Chordoma Cell Death.

BACKGROUND: Chordoma is a cancer of spinal cord, skull base, and sacral area. Currently, the standard of care to treat chordoma is resection followed by radiation therapy. Since, chordoma is present in the spinal cord and these are very sensitive structures and often complete removal by surgery is not possible. As a result, chordoma has a high chance of recurrence and developing resistance to radiation therapy. In addition, treatment of chordoma by conventional radiation therapy can also damage normal tissues surrounding chordoma. Thus, current therapeutic options to treat chordoma are insufficient and novel therapies are desperately needed to treat locally advanced and metastatic chordoma. (2) Methods: In the present investigation, human chordoma cell lines of sacral origin MUG-Chor1 and U-CH2 were cultured and irradiated with Proton Beam Radiation using the clinical superconducting cyclotron and pencil-beam (active) scanning at Middle and End of the Spread-Out Bragg Peak (SOBP). Proton radiation was given at the following doses: Mug-Chor1 at 0, 1, 2, 4, and 8 Gy and U-CH2 at 0, 4, 8, 12, and 16 Gy. These doses were selected based on a pilot study in our lab and attempted to produce approximate survival fractions in the range of 1, 0.9, 0.5, 0.1, and 0.01, respectively, chosen for linear quadratic model fitting of the dose response. (3) Results: In this study, we investigated relative biological effectiveness (RBE) of proton radiation at the end of Spread Out Bragg Peak assuming that the reference radiation is a proton radiation in the middle of the SOBP. We observed differences in the survival of both Human chordoma cell lines, U-CH2 and MUG-Chor1. The data showed that there was a significantly higher cell death at the end of the Bragg peak as compared to middle of the Bragg peak. Based on the linear quadratic (LQ) fit for cell survival we calculated the RBE between M-SOBP and E-SOBP at 95% CI level and it was observed that RBE was higher than 1 at E-SOBP and caused significantly higher cell killing. Proton field at E-SOBP caused complex DNA damage in comparison to M-EOBP and the genes such as DNA topoisomerase 1, GTSE1, RAD51B were downregulated in E-SOBP treated cells. Thus, we conclude that there seems to be substantial variation in RBE (1.3-1.7) at the E-SOBP compared with the M-SOBP.

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

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

Initial Validation of Proton Dose Calculations on SPR Images from DECT in Treatment Planning System.

PURPOSE: To investigate and quantify the potential benefits associated with the use of stopping-power-ratio (SPR) images created from dual-energy computed tomography (DECT) images for proton dose calculation in a clinical proton treatment planning system (TPS). MATERIALS AND METHODS: The DECT and single-energy computed tomography (SECT) scans obtained for 26 plastic tissue surrogate plugs were placed individually in a tissue-equivalent plastic phantom. Relative-electron density (ρe) and effective atomic number (Z eff) images were reconstructed from the DECT scans and used to create an SPR image set for each plug. Next, the SPR for each plug was measured in a clinical proton beam for comparison of the calculated values in the SPR images. The SPR images and SECTs were then imported into a clinical TPS, and treatment plans were developed consisting of a single field delivering a 10 × 10 × 10-cm3 spread-out Bragg peak to a clinical target volume that contained the plugs. To verify the accuracy of the TPS dose calculated from the SPR images and SECTs, treatment plans were delivered to the phantom containing each plug, and comparisons of point-dose measurements and 2-dimensional γ-analysis were performed. RESULTS: For all 26 plugs considered in this study, SPR values for each plug from the SPR images were within 2% agreement with measurements. Additionally, treatment plans developed with the SPR images agreed with the measured point dose to within 2%, whereas a 3% agreement was observed for SECT-based plans. γ-Index pass rates were > 90% for all SECT plans and > 97% for all SPR image-based plans. CONCLUSION: Treatment plans created in a TPS with SPR images obtained from DECT scans are accurate to within guidelines set for validation of clinical treatment plans at our center. The calculated doses from the SPR image-based treatment plans showed better agreement to measured doses than identical plans created with standard SECT scans.

Impact of bowel and rectum air on target dose with robustly optimized intensity-modulated proton therapy plans.

PURPOSE: Pelvic target dose from intensity-modulated proton therapy (IMPT) is sensitive to patient bowel motion. Robustly optimized plans in regard to bowel filling may improve the dose coverage in the treatment course. Our purpose is to investigate the effect of air volume in large and small bowel and rectum on target dose from IMPT plans. METHODS AND MATERIAL: Data from 17 cancer patients (11 prostate, 3 gynecologic, 2 colon, and 1 embryonal rhabdomyosarcoma) with planning CT (pCT) and weekly or biweekly scanned quality assurance CTs (QACTs; 82 QACT scans total) were studied. Air in bowels and rectum traversed by proton pencil beams was contoured. The robust treatment plan was made by using 3 CT sets: the pCT set and 2 virtual CT sets that were copies of pCT but in which the fillings of bowels and rectum were overridden to be either air or muscle. Each plan had 2-5 beams with a mean of 3 beams. Targets in the pCT were mapped to the QACTs by deformable image registration, and the dose in QACTs was calculated. Dose coverage (D99 and D95) and correlations between dose coverage and changes in air volume were analyzed. The significance of the correlation was analyzed by t test. RESULTS: Mean changes of D99 in QACTs were within 3% of those in the pCT for all prostate and colon cases but >3% in 2 of the 3 gynecologic cases and in the embryonal rhabdomyosarcoma case. Of these three cases with mean change of D99 > 3%, air volume may be the main cause in 2. For the prostate cases, correlation coefficients were <0.7 between change in air volume and change in D99 and D95, because other anatomy changes also contributed to dose deviation. Correlation coefficients in the non-prostate cases were >0.9 between D99 change and rectum and between D95 change and small bowel, indicating a greater effect of the air volume on target dose. CONCLUSION: The air volume may still have an important effect on target dose coverage in treatment plans using 3 CT sets, particularly when the air is traversed by multiple beams.

Computational model for detector timing effects in Compton-camera based prompt-gamma imaging for proton radiotherapy.

This paper describes a realistic simulation of a Compton-camera (CC) based prompt-gamma (PG) imaging system for proton range verification for a range of clinical dose rates, and its comparison to PG measured data with a pre-clinical CC. We used a Monte Carlo plus Detector Effects (MCDE) model to simulate the production of prompt gamma-rays (PG) and their energy depositions in the CC. With Monte Carlo, we simulated PG emission resulting from irradiation of a high density polyethylene phantom with a 150 MeV proton pencil beam at dose rates of 5.0 × 108, 2.6 × 109, and 4.6 × 109 p+ s-1. Realistic detector timing effects (e.g. delayed triggering time, event-coincidence, dead time, etc,) were added in post-processing to allow for flexible count rate variations. We acquired PG emission measurements with our pre-clinical CC during irradiation with a clinical 150 MeV proton pencil beam at the same dose rates. For simulations and measurements, three primary changes could be seen in the PG emission data as the dose rate increased: (1) reduction in the total number of detected events due to increased dead-time percentage; (2) increase in false-coincidence events (i.e. multiple PGs interacting, rather than a single PG scatter); and (3) loss of distinct PG emission peaks in the energy spectrum. We used the MCDE model to estimate the quality of our measured PG data, primarily with regards to true and false double-scatters and triple-scatters recorded by the CC. The simulation results showed that of the recorded double-scatter PG interactions 22%, 57%, and 70% were false double-scatters and for triple-scatter interactions 3%, 21%, and 35% were false events at 5.0 × 108, 2.6 × 109, and 4.6 × 109 p+ s-1, respectively. These false scatter events represent noise in the data, and the high percentage of these events in the data represents a major limitation in our ability to produce usable PG images with our prototype CC.

A Monte Carlo model for organ dose reconstruction of patients in pencil beam scanning (PBS) proton therapy for epidemiologic studies of late effects.

Significant efforts such as the Pediatric Proton/Photon Consortium Registry (PPCR) involving multiple proton therapy centers have been made to conduct collaborative studies evaluating outcomes following proton therapy. As a groundwork dosimetry effort for the late effect investigation, we developed a Monte Carlo (MC) model of proton pencil beam scanning (PBS) to estimate organ/tissue doses of pediatric patients at the Maryland Proton Treatment Center (MPTC), one of the proton centers involved in the PPCR. The MC beam modeling was performed using the TOPAS (TOol for PArticle Simulation) MC code and commissioned to match measurement data within 1% for range, and 0.3 mm for spot sizes. The established MC model was then tested by calculating organ/tissue doses for sample intracranial and craniospinal irradiations on whole-body pediatric computational human phantoms. The simulated dose distributions were compared with the treatment planning system dose distributions, showing the 3 mm/3% gamma index passing rates of 94%-99%, validating our simulations with the MC model. The calculated organ/tissue doses per prescribed doses for the craniospinal irradiations (1 mGy Gy-1 to 1 Gy Gy-1) were generally much higher than those for the intracranial irradiations (2.1 µGy Gy-1 to 0.1 Gy Gy-1), which is due to the larger field coverage of the craniospinal irradiations. The largest difference was observed at the adrenal dose, i.e. ∼3000 times. In addition, the calculated organ/tissue doses were compared with those calculated with a simplified MC model, showing that the beam properties (i.e. spot size, spot divergence, mean energy, and energy spread) do not significantly influence dose calculations despite the limited irradiation cases. This implies that the use of the MC model commissioned to the MPTC measurement data might be dosimetrically acceptable for patient dose reconstructions at other proton centers particularly when their measurement data are unavailable. The developed MC model will be used to reconstruct organ/tissue doses for MPTC pediatric patients collected in the PPCR.

Determination of proton stopping power ratio with dual-energy CT in 3D-printed tissue/air cavity surrogates.

PURPOSE: To study the accuracy with which proton stopping power ratio (SPR) can be determined with dual-energy computed tomography (DECT) for small structures and bone-tissue-air interfaces like those found in the head or in the neck. METHODS: Hollow cylindrical polylactic acid (PLA) plugs (3 cm diameter, 5 cm height) were 3D printed containing either one or three septa with thicknesses tsepta  = 0.8, 1.6, 3.2, and 6.4 mm running along the length of the plug. The cylinders were inserted individually into a tissue-equivalent head phantom (16 cm diameter, 5 cm height). First, DECT scans were obtained using a Siemens SOMATOM Definition Edge CT scanner. Effective atomic number (Zeff ) and electron density (ρe ) images were reconstructed from the DECT to produce SPR-CT images of each plug. Second, independent elemental composition analysis of the PLA plastic was used to determine the Zeff and ρe for calculating the theoretical SPR (SPR-TH) using the Bethe-Bloch equation. Finally, for each plug, a direct measurement of SPR (SPR-DM) was obtained in a clinical proton beam. The values of SPR-CT, SPR-TH, and SPR-DM were compared. RESULTS: The SPR-CT for PLA agreed with SPR-DM for tsepta  ≥ 3 mm (for CT slice thicknesses of 0.5, 1.0, and 3.0 mm). The density of PLA was found to decrease with thickness when tsepta  < 3 mm. As tsepta (and density) decreased, the SPR-CT values also decreased, in good agreement with SPR-DM and SPR-TH. CONCLUSION: Overall, the DECT-based SPR-CT was within 3% of SPR-TH and SPR-DM in the high-density gradient regions of the 3D-printed plugs for septa greater than ~ 3mm in thickness.

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.

Liposomes: Clinical Applications and Potential for Image-Guided Drug Delivery.

Liposomes have been extensively studied and are used in the treatment of several diseases. Liposomes improve the therapeutic efficacy by enhancing drug absorption while avoiding or minimizing rapid degradation and side effects, prolonging the biological half-life and reducing toxicity. The unique feature of liposomes is that they are biocompatible and biodegradable lipids, and are inert and non-immunogenic. Liposomes can compartmentalize and solubilize both hydrophilic and hydrophobic materials. All these properties of liposomes and their flexibility for surface modification to add targeting moieties make liposomes more attractive candidates for use as drug delivery vehicles. There are many novel liposomal formulations that are in various stages of development, to enhance therapeutic effectiveness of new and established drugs that are in preclinical and clinical trials. Recent developments in multimodality imaging to better diagnose disease and monitor treatments embarked on using liposomes as diagnostic tool. Conjugating liposomes with different labeling probes enables precise localization of these liposomal formulations using various modalities such as PET, SPECT, and MRI. In this review, we will briefly review the clinical applications of liposomal formulation and their potential imaging properties.

Spectroscopic Compton imaging of prompt gamma emission at the MeV energy range.

This work explores a novel tomographic approach to PGAA that is both quantitative and spatially resolved, adapted from a clinical "proton beam range finder" in which MeV gamma rays are imaged by coincidence measurements of Compton scattered gamma rays with multi-detector arrays. We performed preliminary measurements using a Compton camera made with CdZnTe detector arrays on a series of test samples with high-energy (> 1 MeV) gamma emission lines. 3D image reconstructions were performed on the 2.2 MeV peak from H. The image reconstruction methods were also evaluated using the emission data generated by Monte Carlo simulations under ideal conditions.

Evaluation of Computed Tomography Scanners for Feasibility of Using Averaged Hounsfield Unit-to-Stopping Power Ratio Calibration Curve.

PURPOSE: The purpose of this study was to quantify the variability of stoichiometric calibration curves for different computed tomography (CT) scanners and determine whether an averaged Hounsfield unit (HU)-to-stopping power ratio (SPR) calibration curve can be used across multiple CT scanners. MATERIALS AND METHODS: Five CT scanners were used to scan an electron density phantom to establish HU values of known material plugs. A stoichiometric calibration curve was calculated for CT scanners and for the average curve. Animal tissue surrogates were used to compare the water-equivalent thickness (WET) of the animal tissue surrogates calculated by the treatment planning system (TPS) and the WET values measured with a multilayered ionization chamber. The calibration curves were optimized to reduce the percentage of difference between measured and TPS-calculated WET values. A second set of tissue surrogates was then used to evaluate the overall range of uncertainty for the optimized CT-specific and average calibration curves. RESULTS: Overall, the average variation in HU for all 6 calibration curves before optimization was 8.3 HU. For both the averaged and CT-specific calibrations, the root mean square error (RMSE) of the percentage of difference between TPS-calculated and measured WET values before optimization was 4%. The RMSE of the percentage of difference for the TPS-calculated and multilayered ionization chamber measured WET values after the optimization for both averaged and CT-specific calibration curves was reduced to less than 1.5%. The overall RMSE of the TPS and the measured WET percentage of difference after optimization was 2.1% for both averaged and CT-specific calibration curves. CONCLUSION: Averaged CT calibration curves can be used to map the HU-to-SPR in TPSs, if the variations in HU values across all scanners is relatively small. Performing tissue surrogate optimization of the HU-to-SPR calibration curve has been shown to reduce the overall uncertainty of the calibration for averaged and CT-specific calibration curves and is recommended, especially if an averaged HU-to-SPR calibration curve is used.

Rectal dose to prostate cancer patients treated with proton therapy with or without rectal spacer.

The purpose of this study was to evaluate whether a spacer inserted in the prerectal space could reduce modeled rectal dose and toxicity rates for patients with prostate cancer treated in silico with pencil beam scanning (PBS) proton therapy. A total of 20 patients were included in this study who received photon therapy (12 with rectal spacer (DuraSeal™ gel) and 8 without). Two PBS treatment plans were retrospectively created for each patient using the following beam arrangements: (1) lateral-opposed (LAT) fields and (2) left and right anterior oblique (LAO/RAO) fields. Dose volume histograms (DVH) were generated for the prostate, rectum, bladder, and right and left femoral heads. The normal tissue complication probability (NTCP) for ≥grade 2 rectal toxicity was calculated using the Lyman-Kutcher-Burman model and compared between patients with and without the rectal spacer. A significantly lower mean rectal DVH was achieved in patients with rectal spacer compared to those without. For LAT plans, the mean rectal V70 with and without rectal spacer was 4.19 and 13.5%, respectively. For LAO/RAO plans, the mean rectal V70 with and without rectal spacer was 5.07 and 13.5%, respectively. No significant differences were found in any rectal dosimetric parameters between the LAT and the LAO/RAO plans generated with the rectal spacers. We found that ≥ 9 mm space resulted in a significant decrease in NTCP modeled for ≥grade 2 rectal toxicity. Rectal spacers can significantly decrease modeled rectal dose and predicted ≥grade 2 rectal toxicity in prostate cancer patients treated in silico with PBS. A minimum of 9 mm separation between the prostate and anterior rectal wall yields the largest benefit.

Reply to Comment on 'Imaging of prompt gamma rays emitted during delivery of clinical proton beams with a Compton camera: feasibility studies for range verification'.

A reply is provided to the points raised in the comment by Dr Sitek (2016 Phys. Med. Biol. 61 8941) on Polf et al (2015 Phys. Med. Biol. 60 7085).

Anteriorly Oriented Beam Arrangements with Daily in Vivo Range Verification for Proton Therapy of Prostate Cancer: Rectal Toxicity Rates.

PURPOSE: To model whether in vivo range verification could reduce high-grade rectal toxicity for patients with prostate cancer treated with pencil beam scanning proton therapy by allowing novel proton beam arrangements compared to standard lateral opposed beams. MATERIALS AND METHODS: Proton plans were generated for 8 patients with prostate cancer previously treated with photons by volumetric-modulated arc therapy (VMAT). The VMAT plans were generated by using a uniform 6-mm planning target volume (PTV) expansion. For the proton plans an additional distal margin (3.5% of beam range) was added to the uniform 6-mm PTV to account for range uncertainty, using 3 beam arrangements: (1) lateral opposed beams (LAT), (2) left and right anterior oblique beams (LAO/RAO), and (3) a single anterior-posterior beam (AP). Assuming use of in vivo range verification, plans were generated by using a reduced distal PTV and distal range uncertainty expansion (2 mm each) with AP (AP-2 mm) and LAO/RAO (LAO/RAO-2 mm) beam arrangements. Estimates of normal tissue complication probability (NTCP) for ≥grade 2 rectal bleeding were generated by using the Lyman-Kutcher-Burman model. RESULTS: Each proton and photon plan was able to achieve all prespecified rectal and bladder constraints. For the VMAT, LAT, AP, and LAO/RAO plans, estimated NTCP values for ≥grade 2 rectal bleeding were 0.19, 0.21, 0.24, and 0.2, respectively. For the AP-2 mm and LAO/RAO-2 mm plans, NTCP values were reduced to 0.11 and 0.1 with respect to ≥grade 2 rectal bleeding. CONCLUSION: Presuming that in vivo range verification for pencil beam scanning proton therapy could localize the distal falloff of the Bragg peak to within 2 mm, novel beam arrangements (AP and LAO/RAO) may reduce the risk of serious rectal bleeding, compared to VMAT and LAT proton treatment techniques. These are achieved without an increase in modeled bladder complication rates.