Virtual 4DCT generated from 4DMRI in gated particle therapy: phantom validation and application to lung cancer patients.

Objective. Respiration negatively affects the outcome of a radiation therapy treatment, with potentially severe effects especially in particle therapy (PT). If compensation strategies are not applied, accuracy cannot be achieved. To support the clinical practice based on 4D computed tomography (CT), 4D magnetic resonance imaging (MRI) acquisitions can be exploited. The purpose of this study was to validate a method for virtual 4DCT generation from 4DMRI data for lung cancers on a porcine lung phantom, and to apply it to lung cancer patients in PT.Approach. Deformable image registration was used to register each respiratory phase of the 4DMRI to a reference phase. Then, a static 3DCT was registered to this reference MR image set, and the virtual 4DCT was generated by warping the registered CT according to previously obtained deformation fields. The method was validated on a physical phantom for which a ground truth 4DCT was available and tested on lung tumor patients, treated with gated PT at end-exhale, by comparing the virtual 4DCT with a re-evaluation 4DCT. The geometric and dosimetric evaluation was performed for both proton and carbon ion treatment plans.Main results. The phantom validation exhibited a geometrical accuracy within the maximum resolution of the MRI and mean dose deviations, with respect to the prescription dose, up to 3.2% for targetD95%, with a mean gamma pass rate of 98%. For patients, the virtual and re-evaluation 4DCTs showed good correspondence, with errors on targetD95%up to 2% within the gating window. For one patient, dose variations up to 10% at end-exhale were observed due to relevant inter-fraction anatomo-pathological changes that occurred between the planning and re-evaluation CTs.Significance. Results obtained on phantom data showed that the virtual 4DCT method was accurate, allowing its application on patient data for testing within a clinical scenario.

Feasibility of CycleGAN enhanced low dose CBCT imaging for prostate radiotherapy dose calculation.

Daily cone beam computed tomography (CBCT) imaging during the course of fractionated radiotherapy treatment can enable online adaptive radiotherapy but also expose patients to a non-negligible amount of radiation dose. This work investigates the feasibility of low dose CBCT imaging capable of enabling accurate prostate radiotherapy dose calculation with only 25% projections by overcoming under-sampling artifacts and correcting CT numbers by employing cycle-consistent generative adversarial networks (cycleGAN). Uncorrected CBCTs of 41 prostate cancer patients, acquired with ∼350 projections (CBCTorg), were retrospectively under-sampled to 25% dose images (CBCTLD) with only ∼90 projections and reconstructed using Feldkamp-Davis-Kress. We adapted a cycleGAN including shape loss to translate CBCTLDinto planning CT (pCT) equivalent images (CBCTLD_GAN). An alternative cycleGAN with a generator residual connection was implemented to improve anatomical fidelity (CBCTLD_ResGAN). Unpaired 4-fold cross-validation (33 patients) was performed to allow using the median of 4 models as output. Deformable image registration was used to generate virtual CTs (vCT) for Hounsfield units (HU) accuracy evaluation on 8 additional test patients. Volumetric modulated arc therapy plans were optimized on vCT, and recalculated on CBCTLD_GANand CBCTLD_ResGANto determine dose calculation accuracy. CBCTLD_GAN, CBCTLD_ResGANand CBCTorgwere registered to pCT and residual shifts were analyzed. Bladder and rectum were manually contoured on CBCTLD_GAN, CBCTLD_ResGANand CBCTorgand compared in terms of Dice similarity coefficient (DSC), average and 95th percentile Hausdorff distance (HDavg, HD95). The mean absolute error decreased from 126 HU for CBCTLDto 55 HU for CBCTLD_GANand 44 HU for CBCTLD_ResGAN. For PTV, the median differences ofD98%,D50%andD2%comparing both CBCTLD_GANto vCT were 0.3%, 0.3%, 0.3%, and comparing CBCTLD_ResGANto vCT were 0.4%, 0.3% and 0.4%. Dose accuracy was high with both 2% dose difference pass rates of 99% (10% dose threshold). Compared to the CBCTorg-to-pCT registration, the majority of mean absolute differences of rigid transformation parameters were less than 0.20 mm/0.20°. For bladder and rectum, the DSC were 0.88 and 0.77 for CBCTLD_GANand 0.92 and 0.87 for CBCTLD_ResGANcompared to CBCTorg, and HDavgwere 1.34 mm and 1.93 mm for CBCTLD_GAN, and 0.90 mm and 1.05 mm for CBCTLD_ResGAN. The computational time was ∼2 s per patient. This study investigated the feasibility of adapting two cycleGAN models to simultaneously remove under-sampling artifacts and correct image intensities of 25% dose CBCT images. High accuracy on dose calculation, HU and patient alignment were achieved. CBCTLD_ResGANachieved better anatomical fidelity.

Evaluation of the impact of a scanner prototype on proton CT and helium CT image quality and dose efficiency with Monte Carlo simulation.

Objective.The use of ion computed tomography (CT) promises to yield improved relative stopping power (RSP) estimation as input to particle therapy treatment planning. Recently, proton CT (pCT) has been shown to yield RSP accuracy on par with state-of-the-art x-ray dual energy CT. There are however concerns that the lower spatial resolution of pCT compared to x-ray CT may limit its potential, which has spurred interest in the use of helium ion CT (HeCT). The goal of this study was to investigate image quality of pCT and HeCT in terms of noise, spatial resolution, RSP accuracy and imaging dose using a detailed Monte Carlo (MC) model of an existing ion CT prototype.Approach.Three phantoms were used in simulated pCT and HeCT scans allowing estimation of noise, spatial resolution and the scoring of dose. An additional phantom was used to evaluate RSP accuracy. The imaging dose required to achieve the same image noise in a water and a head phantom was estimated at both native spatial resolution, and in a scenario where the HeCT spatial resolution was reduced and matched to that of pCT using Hann windowing of the reconstruction filter. A variance reconstruction formalism was adapted to account for Hann windowing.Main results.We confirmed that the scanner prototype would produce higher spatial resolution for HeCT than pCT by a factor 1.8 (0.86 lp mm-1versus 0.48 lp mm-1at the center of a 20 cm water phantom). At native resolution, HeCT required a factor 2.9 more dose than pCT to achieve the same noise, while at matched resolution, HeCT required only 38% of the pCT dose. Finally, RSP mean absolute percent error (MAPE) was found to be 0.59% for pCT and 0.67% for HeCT.Significance.This work compared the imaging performance of pCT and HeCT when using an existing scanner prototype, with the spatial resolution advantage of HeCT coming at the cost of increased dose. When matching spatial resolution via Hann windowing, HeCT had a substantial dose advantage. Both modalities provided state-of-the-art RSP MAPE. HeCT might therefore help reduce the dose exposure of patients with comparable image noise to pCT, enhanced spatial resolution and acceptable RSP accuracy at the same time.

Fluence-modulated proton CT optimized with patient-specific dose and variance objectives for proton dose calculation.

Particle therapy treatment planning requires accurate volumetric maps of the relative stopping power, which can directly be acquired using proton computed tomography (pCT). With fluence-modulated pCT (FMpCT) imaging fluence is concentrated in a region-of-interest (ROI), which can be the vicinity of the treatment beam path, and imaging dose is reduced elsewhere. In this work we present a novel optimization algorithm for FMpCT which, for the first time, calculates modulated imaging fluences for joint imaging dose and image variance objectives. Thereby, image quality is maintained in the ROI to ensure accurate calculations of the treatment dose, and imaging dose is minimized outside the ROI with stronger minimization penalties given to imaging organs-at-risk. The optimization requires an initial scan at uniform fluence or a previous x-ray CT scan. We simulated and optimized FMpCT images for three pediatric patients with tumors in the head region. We verified that the target image variance inside the ROI was achieved and demonstrated imaging dose reductions outside of the ROI of 74% on average, reducing the imaging dose from 1.2 to 0.3 mGy. Such dose savings are expected to be relevant compared to the therapeutic dose outside of the treatment field. Treatment doses were re-calculated on the FMpCT images and compared to treatment doses re-recalculated on uniform fluence pCT scans using a 1% criterion. Passing rates were above 98.3% for all patients. Passing rates comparing FMpCT treatment doses to the ground truth treatment dose were above 88.5% for all patients. Evaluation of the proton range with a 1 mm criterion resulted in passing rates above 97.5% (FMpCT/pCT) and 95.3% (FMpCT/ground truth). Jointly optimized fluence-modulated pCT images can be used for proton dose calculation maintaining the full dosimetric accuracy of pCT but reducing the required imaging dose considerably by three quarters. This may allow for daily imaging during particle therapy ensuring a safe and accurate delivery of the therapeutic dose and avoiding excess dose from imaging.

Animal tissue-based quantitative comparison of dual-energy CT to SPR conversion methods using high-resolution gel dosimetry.

Dual-energy computed tomography (DECT) has been shown to allow for more accurate ion therapy treatment planning by improving the estimation of tissue stopping power ratio (SPR) relative to water, among other tissue properties. In this study, we measured and compared the accuracy of SPR values derived using both dual- and single-energy CT (SECT) based on different published conversion algorithms. For this purpose, a phantom setup containing either fresh animal soft tissue samples (beef, pork) and a water reference or tissue equivalent plastic materials was designed and irradiated in a clinical proton therapy facility. Dosimetric polymer gel was positioned downstream of the samples to obtain a three-dimensional proton range distribution with high spatial resolution. The mean proton range in gel for each tissue relative to the water sample was converted to a SPR value. Additionally, the homogeneous samples were probed with a variable water column encompassed by two ionization chambers to benchmark the SPR accuracy of the gel dosimetry. The SPR values measured with both methods were consistent with a mean deviation of 0.2%, but the gel dosimetry captured range variations up to 5 mm within individual samples.Across all fresh tissue samples the SECT approach yielded significantly greater mean absolute deviations from the SPR deduced using gel range measurements, with an average difference of 1.2%, compared to just 0.3% for the most accurate DECT-based algorithm. These results show a significant advantage of DECT over SECT for stopping power prediction in a realistic setting, and for the first time allow to compare a large set of methods under the same conditions.

Firm parenting and youth adjustment: Stress reactivity and dyadic synchrony of respiratory sinus arrhythmia.

Parental behaviors are potent risk and protective factors for youth development of externalizing problems. Firm control is a parenting strategy that is inconsistently linked to youth adjustment, possibly due to variations in individual biological contexts. Growing research shows that dyadic coregulation of the autonomic nervous system (e.g., parent-child physiological synchrony) is a neurobiological mechanism that links parenting to youth adjustment. However, physiological synchrony may be context-dependent (e.g., adaptive in positive interactions, maladaptive in negative interactions). We aimed to test the role of dyadic synchrony in respiratory sinus arrhythmia (RSA) during parent-child conflict as a mediator between parent firm control and youth's externalizing problems. To capture youth's stress reactivity, we also tested how galvanic skin response reactivity (GSR-R) moderated this indirect path. The sample included 101 dyads of low socioeconomic-status at-risk preadolescents and parents. Results indicated that youth higher levels of GSR-R significantly intensified the link between parent firm control and dyadic RSA synchrony during conflict. Dyadic RSA synchrony further predicted youth increased in externalizing problems. Overall, results suggest that when parents employ firm control parenting with highly reactive teens, dyadic RSA synchrony elevates, potentially modeling less optimal coping with conflict for the youth, which is associated with increased externalizing problems.

Experimental realization of dynamic fluence field optimization for proton computed tomography.

Proton computed tomography (pCT) has high accuracy and dose efficiency in producing spatial maps of the relative stopping power (RSP) required for treatment planning in proton therapy. With fluence-modulated pCT (FMpCT), prescribed noise distributions can be achieved, which allows to decrease imaging dose by employing object-specific dynamically modulated fluence during the acquisition. For FMpCT acquisitions we divide the image into region-of-interest (ROI) and non-ROI volumes. In proton therapy, the ROI volume would encompass all treatment beams. An optimization algorithm then calculates dynamically modulated fluence that achieves low prescribed noise inside the ROI and high prescribed noise elsewhere. It also produces a planned noise distribution, which is the expected noise map for that fluence, as calculated with a Monte Carlo simulation. The optimized fluence can be achieved by acquiring pCT images with grids of intensity modulated pencil beams. In this work, we interfaced the control system of a clinical proton beam line to deliver the optimized fluence. Using three phantoms we acquired images with uniform fluence, with a constant noise prescription, and with an FMpCT task. Image noise distributions as well as fluence maps were compared to the corresponding planned distributions as well as to the prescription. Furthermore, we propose a correction method that removes image artifacts stemming from the acquisition with pencil beams having a spatially varying energy distribution that is not seen in clinical operation. RSP accuracy of FMpCT scans was compared to uniform scans and was found to be comparable to standard pCT scans. While we identified technical improvements for future experimental acquisitions, in particular related to an unexpected pencil beam size reduction and a misalignment of the fluence pattern, agreement with the planned noise was satisfactory and we conclude that FMpCT optimized for specific image noise prescriptions is experimentally feasible.

Stability and reproducibility of 6013 deep inspiration breath-holds in left-sided breast cancer.

PURPOSE: Patients with left-sided breast cancer frequently receive deep inspiration breath-hold (DIBH) radiotherapy to reduce the risk of cardiac side effects. The aim of the present study was to analyze intra-breath-hold stability and inter-fraction breath-hold reproducibility in clinical practice. MATERIAL AND METHODS: Overall, we analyzed 103 patients receiving left-sided breast cancer radiotherapy using a surface-guided DIBH technique. During each treatment session the vertical motion of the patient was continuously measured by a surface guided radiation therapy (SGRT) system and automated gating control (beam on/off) was performed using an audio-visual patient feedback system. Dose delivery was automatically triggered when the tracking point was within a predefined gating window. Intra-breath-hold stability and inter-fraction reproducibility across all fractions of the entire treatment course were analyzed per patient. RESULTS: In the present series, 6013 breath-holds during beam-on time were analyzed. The mean amplitude of the gating window from the baseline breathing curve (maximum expiration during free breathing) was 15.8 mm (95%-confidence interval: [8.5-30.6] mm) and had a width of 3.5 mm (95%-CI: [2-4.3] mm). As a measure of intra-breath-hold stability, the median standard deviation of the breath-hold level during DIBH was 0.3 mm (95%-CI: [0.1-0.9] mm). Similarly, the median absolute intra-breath-hold linear amplitude deviation was 0.4 mm (95%-CI: [0.01-2.1] mm). Reproducibility testing showed good inter-fractional reliability, as the maximum difference in the breathing amplitudes in all patients and all fractions were 1.3 mm on average (95%-CI: [0.5-2.6] mm). CONCLUSION: The clinical integration of an optical surface scanner enables a stable and reliable DIBH treatment delivery during SGRT for left-sided breast cancer in clinical routine.

Assessment of range uncertainty in lung-like tissue using a porcine lung phantom and proton radiography.

Thoracic tumours are increasingly considered indications for pencil beam scanned proton therapy (PBS-PT) treatments. Conservative robustness settings have been suggested due to potential range straggling effects caused by the lung micro-structure. Using proton radiography (PR) and a 4D porcine lung phantom, we experimentally assess range errors to be considered in robust treatment planning for thoracic indications. A human-chest-size 4D phantom hosting inflatable porcine lungs and corresponding 4D computed tomography (4DCT) were used. Five PR frames were planned to intersect the phantom at various positions. Integral depth-dose curves (IDDs) per proton spot were measured using a multi-layer ionisation chamber (MLIC). Each PR frame consisted of 81 spots with an assigned energy of 210 MeV (full width at half maximum (FWHM) 8.2 mm). Each frame was delivered five times while simultaneously acquiring the breathing signal of the 4D phantom, using an ANZAI load cell. The synchronised ANZAI and delivery log file information was used to retrospectively sort spots into their corresponding breathing phase. Based on this information, IDDs were simulated by the treatment planning system (TPS) Monte Carlo dose engine on a dose grid of 1 mm. In addition to the time-resolved TPS calculations on the 4DCT phases, IDDs were calculated on the average CT. Measured IDDs were compared with simulated ones, calculating the range error for each individual spot. In total, 2025 proton spots were individually measured and analysed. The range error of a specific spot is reported relative to its water equivalent path length (WEPL). The mean relative range error was 1.2% (1.5 SD 2.3 %) for the comparison with the time-resolved TPS calculations, and 1.0% (1.5 SD 2.2 %) when comparing to TPS calculations on the average CT. The determined mean relative range errors justify the use of 3% range uncertainty for robust treatment planning in a clinical setting for thoracic indications.

An optimization algorithm for dose reduction with fluence-modulated proton CT.

PURPOSE: Fluence-modulated proton computed tomography (FMpCT) using pencil beam scanning aims at achieving task-specific image noise distributions by modulating the imaging proton fluence spot-by-spot based on an object-specific noise model. In this work, we present a method for fluence field optimization and investigate its performance in dose reduction for various phantoms and image variance targets. METHODS: The proposed method uses Monte Carlo simulations of a proton CT (pCT) prototype scanner to estimate expected variance levels at uniform fluence. Using an iterative approach, we calculate a stack of target variance projections that are required to achieve the prescribed image variance, assuming a reconstruction using filtered backprojection. By fitting a pencil beam model to the ratio of uniform fluence variance and target variance, relative weights for each pencil beam can be calculated. The quality of the resulting fluence modulations is evaluated by scoring imaging doses and comparing them to those at uniform fluence, as well as evaluating conformity of the achieved variance with the prescription. For three different phantoms, we prescribed constant image variance as well as two regions-of-interest (ROI) imaging tasks with inhomogeneous image variance. The shape of the ROIs followed typical beam profiles for proton therapy. RESULTS: Prescription of constant image variance resulted in a dose reduction of 8.9% for a homogeneous water phantom compared to a uniform fluence scan at equal peak variance level. For a more heterogeneous head phantom, dose reduction increased to 16.0% for the same task. Prescribing two different ROIs resulted in dose reductions between 25.7% and 40.5% outside of the ROI at equal peak variance levels inside the ROI. Imaging doses inside the ROI were increased by 9.2% to 19.2% compared to the uniform fluence scan, but can be neglected assuming that the ROI agrees with the therapeutic dose region. Agreement of resulting variance maps with the prescriptions was satisfactory. CONCLUSIONS: We developed a method for fluence field optimization based on a noise model for a real scanner used in pCT. We demonstrated that it can achieve prescribed image variance targets. A uniform fluence field was shown not to be dose optimal and dose reductions achievable with the proposed method for FMpCT were considerable, opening an interesting perspective for image guidance and adaptive therapy.

Predicting reamputation risk in patients undergoing lower extremity amputation due to the complications of peripheral artery disease and/or diabetes.

BACKGROUND: Patients undergoing amputation of the lower extremity for the complications of peripheral artery disease and/or diabetes are at risk of treatment failure and the need for reamputation at a higher level. The aim of this study was to develop a patient-specific reamputation risk prediction model. METHODS: Patients with incident unilateral transmetatarsal, transtibial or transfemoral amputation between 2004 and 2014 secondary to diabetes and/or peripheral artery disease, and who survived 12 months after amputation, were identified using Veterans Health Administration databases. Procedure codes and natural language processing were used to define subsequent ipsilateral reamputation at the same or higher level. Stepdown logistic regression was used to develop the prediction model. It was then evaluated for calibration and discrimination by evaluating the goodness of fit, area under the receiver operating characteristic curve (AUC) and discrimination slope. RESULTS: Some 5260 patients were identified, of whom 1283 (24·4 per cent) underwent ipsilateral reamputation in the 12 months after initial amputation. Crude reamputation risks were 40·3, 25·9 and 9·7 per cent in the transmetatarsal, transtibial and transfemoral groups respectively. The final prediction model included 11 predictors (amputation level, sex, smoking, alcohol, rest pain, use of outpatient anticoagulants, diabetes, chronic obstructive pulmonary disease, white blood cell count, kidney failure and previous revascularization), along with four interaction terms. Evaluation of the prediction characteristics indicated good model calibration with goodness-of-fit testing, good discrimination (AUC 0·72) and a discrimination slope of 11·2 per cent. CONCLUSION: A prediction model was developed to calculate individual risk of primary healing failure and the need for reamputation surgery at each amputation level. This model may assist clinical decision-making regarding amputation-level selection.

Prediction of image noise contributions in proton computed tomography and comparison to measurements.

We present a method to accurately predict image noise in proton computed tomography (pCT) using data generated from a Monte Carlo simulation and a patient or object model that may be generated from a prior x-ray CT image. This enables noise prediction for arbitrary beam fluence settings and, therefore, the application of fluence-modulated pCT (FMpCT), which can achieve prescribed noise targets and may significantly reduce the integral patient dose. We extended an existing Monte Carlo simulation of a prototype pCT scanner to include effects of quenching in the energy detector scintillators and constructed a beam model from experimental tracking data. Simulated noise predictions were compared to experimental data both in the projection domain and in the reconstructed image. Noise prediction agreement between simulated and experimental data in terms of the root-mean-square (RMS) error was better than 7% for a homogeneous water phantom and a sensitometry phantom with tubular inserts. For an anthropomorphic head phantom, modeling the anatomy of a five-year-old child, the RMS error was better than 9% in three evaluated slices. We were able to reproduce subtle noise features near heterogeneities. To demonstrate the feasibility of Monte Carlo simulated noise maps for fluence modulation, we calculated a fluence profile that yields a homogeneous noise level in the image. Unlike for bow-tie filters in x-ray CT this does not require constant fluence at the detector and the shape of the fluence profile is fundamentally different. Using an improved Monte Carlo simulation, we demonstrated the feasibility of using simulated data for accurate image noise prediction for pCT. We believe that the agreement with experimental data is sufficient to enable the future optimization of FMpCT fluence plans to achieve prescribed noise targets in a fluence-modulated acquisition.

Mortality prediction following non-traumatic amputation of the lower extremity.

BACKGROUND: Patients who undergo lower extremity amputation secondary to the complications of diabetes or peripheral artery disease have poor long-term survival. Providing patients and surgeons with individual-patient, rather than population, survival estimates provides them with important information to make individualized treatment decisions. METHODS: Patients with peripheral artery disease and/or diabetes undergoing their first unilateral transmetatarsal, transtibial or transfemoral amputation were identified in the Veterans Affairs Surgical Quality Improvement Program (VASQIP) database. Stepdown logistic regression was used to develop a 1-year mortality risk prediction model from a list of 33 candidate predictors using data from three of five Department of Veterans Affairs national geographical regions. External geographical validation was performed using data from the remaining two regions. Calibration and discrimination were assessed in the development and validation samples. RESULTS: The development sample included 5028 patients and the validation sample 2140. The final mortality prediction model (AMPREDICT-Mortality) included amputation level, age, BMI, race, functional status, congestive heart failure, dialysis, blood urea nitrogen level, and white blood cell and platelet counts. The model fit in the validation sample was good. The area under the receiver operating characteristic (ROC) curve for the validation sample was 0·76 and Cox calibration regression indicated excellent calibration (slope 0·96, 95 per cent c.i. 0·85 to 1·06; intercept 0·02, 95 per cent c.i. -0·12 to 0·17). Given the external validation characteristics, the development and validation samples were combined, giving a total sample of 7168. CONCLUSION: The AMPREDICT-Mortality prediction model is a validated parsimonious model that can be used to inform the 1-year mortality risk following non-traumatic lower extremity amputation of patients with peripheral artery disease or diabetes.

Application of fluence field modulation to proton computed tomography for proton therapy imaging.

This simulation study presents the application of fluence field modulated computed tomography, initially developed for x-ray CT, to proton computed tomography (pCT). By using pencil beam (PB) scanning, fluence modulated pCT (FMpCT) may achieve variable image quality in a pCT image and imaging dose reduction. Three virtual phantoms, a uniform cylinder and two patients, were studied using Monte Carlo simulations of an ideal list-mode pCT scanner. Regions of interest (ROI) were selected for high image quality and only PBs intercepting them preserved full fluence (FF). Image quality was investigated in terms of accuracy (mean) and noise (standard deviation) of the reconstructed proton relative stopping power compared to reference values. Dose calculation accuracy on FMpCT images was evaluated in terms of dose volume histograms (DVH), range difference (RD) for beam-eye-view (BEV) dose profiles and gamma evaluation. Pseudo FMpCT scans were created from broad beam experimental data acquired with a list-mode pCT prototype. FMpCT noise in ROIs was equivalent to FF images and accuracy better than -1.3%(-0.7%) by using 1% of FF for the cylinder (patients). Integral imaging dose reduction of 37% and 56% was achieved for the two patients for that level of modulation. Corresponding DVHs from proton dose calculation on FMpCT images agreed to those from reference images and 96% of BEV profiles had RD below 2 mm, compared to only 1% for uniform 1% of FF. Gamma pass rates (2%, 2 mm) were 98% for FMpCT while for uniform 1% of FF they were as low as 59%. Applying FMpCT to preliminary experimental data showed that low noise levels and accuracy could be preserved in a ROI, down to 30% modulation. We have shown, using both virtual and experimental pCT scans, that FMpCT is potentially feasible and may allow a means of imaging dose reduction for a pCT scanner operating in PB scanning mode. This may be of particular importance to proton therapy given the low integral dose found outside the target.

Quantification of the uncertainties of a biological model and their impact on variable RBE proton treatment plan optimization.

PURPOSE: In proton radiation therapy, a relative biological effectiveness (RBE) equal to 1.1 is currently assumed, although biological experiments show that it is not constant. The purpose of this study was to quantify the uncertainties of a published biological model and explore their impact on variable RBE treatment plan (TP) optimization. METHODS: Two patient cases with a high and a low (α/ß)x tumor were investigated. Firstly, intensity modulated proton therapy TPs assuming constant RBE were derived, and subsequently the variable RBE weighted dose (RWD), including the uncertainty originating in the fit to the experimental data and the uncertainty of the (α/ß)x, were calculated. Secondly, TPs optimized for uniform biological effect assuming a variable RBE were created using the worst case tissue specific (α/ß)x. RESULTS: For the nasopharyngeal cancer patient, the uncertainty of (α/ß)x corresponded to a CTV D98 confidence interval (CI) of (-2, +4)% while for the fit parameter CI was (-2,+1)%. For the standard fractionation prostate case the (α/ß)x CI was (-7,+5)% and the fit parameter CI was (-3,+3)%. For the hypofractionated case both CIs were (-1,+1)%. In both patient cases, the RBE in most organs at risk (OARs) was significantly underestimated by the constant RBE approximation, whereas the situation was not as definite in the target volumes. Overdosage of OARs was reduced by using the biological effect optimization. CONCLUSION: For the two patient cases, the RWD uncertainty from the fit parameter in the biological model contributed non-negligibly to the total uncertainty, depending on the patient case and the organ. The presented optimization strategy is a basic method for robust biological effect optimization to reduce potential consequences caused by the (α/ß)x uncertainty.

Dose distribution for gynecological brachytherapy with dose accumulation between insertions: Feasibility study.

PURPOSE: For gynecological treatments, it is standard to acquire CT images and preferably also MR images before each treatment to calculate the dose of the day. The dose of the complete treatment is calculated by adding the dose metrics of each fraction. It makes the conservative assumption that the same part of the organs at risk always receives the highest dose. The dose calculated this way often limits the prescription dose or the target coverage. We investigated the use of deformable image registration (DIR) as an alternative method to assess the cumulative dose for a treatment course. METHODS AND MATERIALS: Rigid registration is preformed on CT images, followed by DIR. DIR can be based either solely on the three-dimensional images or combined with organ contours. To improve DIR in the pelvic region with low CT contrast, we propose (1) using contours drawn on CT or (2) modifying artificially the contrast in certain volumes. The dose matrix from fraction_n (n > 1) is deformed using a calculated deformation field. RESULTS: The use of the contrast-enhanced images or of contour information helps to guide the DIR. However, because of the very high dose gradients involved in brachytherapy, the uncertainty on the accumulated dose remains of the order of 5-10%. Even for good contour matching, a small local error in the deformation can have significant consequences for the dose distribution. CONCLUSIONS: Using DIR, based on image features and contours, allows to accumulate the dose from different brachytherapy fractions. A robust validation procedure should be developed.

Monte Carlo study on the sensitivity of prompt gamma imaging to proton range variations due to interfractional changes in prostate cancer patients.

Proton range verification based on prompt gamma imaging is increasingly considered in proton therapy. Tissue heterogeneity normal to the beam direction or near the end of range may considerably degrade the ability of prompt gamma imaging to detect proton range shifts. The goal of this study was to systematically investigate the accuracy and precision of range detection from prompt gamma emission profiles for various fractions for intensity modulated proton therapy of prostate cancer, using a comprehensive clinical dataset of 15 different CT scans for 5 patients. Monte Carlo simulations using Geant4 were performed to generate spot-by-spot dose distributions and prompt gamma emission profiles for prostate treatment plans. The prompt gammas were scored at their point of emission. Three CT scans of the same patient were used to evaluate the impact of inter-fractional changes on proton range. The range shifts deduced from the comparison of prompt gamma emission profiles in the planning CT and subsequent CTs were then correlated to the corresponding range shifts deduced from the dose distributions for individual pencil beams. The distributions of range shift differences between prompt gamma and dose were evaluated in terms of precision (defined as half the 95% inter-percentile range IPR) and accuracy (median). In total about 1700 individual proton pencil beams were investigated. The IPR of the relative range shift differences between the dose profiles and the prompt gamma profiles varied between ±1.4 mm and ±2.9 mm when using the more robust profile shifting analysis. The median was found smaller than 1 mm. Methods to identify and reject unreliable spots for range verification due to range mixing were derived and resulted in an average 10% spot rejection, clearly improving the prompt gamma-dose correlation. This work supports that prompt gamma imaging can offer a reliable indicator of range changes due to anatomical variations and tissue heterogeneity in scanning proton treatment of prostate cancer patients when considering prompt gamma emission profiles.

Factors influencing the accuracy of beam range estimation in proton therapy using prompt gamma emission.

In-vivo imaging is a strategy to monitor the range of protons inside the patient during radiation treatment. A possible method of in-vivo imaging is detection of secondary 'prompt' gamma (PG) photons outside the body, which are produced by inelastic proton-nuclear interactions inside the patient. In this paper, important parameters influencing the relationship between the PG profile and percentage depth dose (PDD) in a uniform cylindrical phantom are explored. Monte Carlo simulations are performed with the new Geant4 based code TOPAS for mono-energetic proton pencil beams (range: 100-250 MeV) and an idealized PG detector. PG depth profiles are evaluated using the inflection point on a sigmoid fit in the fall-off region of the profile. A strong correlation between the inflection point and the proton range determined from the PDD is found for all conditions. Variations between 1.5 mm and 2.7 mm in the distance between the proton range and the inflection point are found when either the mass density, phantom diameter, or detector acceptance angle is changed. A change in cut-off energy of the detector could induce a range difference of maximum 4 mm. Applying time-of-flight discrimination during detection, changing the primary energy of the beam or changing the elemental composition of the tissue affects the accuracy of the range prediction by less than 1 mm. The results indicate that the PG signal is rather robust to many parameter variations, but millimetre accurate range monitoring requires all medium and detector properties to be carefully taken into account.

The contribution from transit dose for (192)Ir HDR brachytherapy treatments.

Brachytherapy treatment planning systems that use model-based dose calculation algorithms employ a more accurate approach that replaces the TG43-U1 water dose formalism and adopt the TG-186 recommendations regarding composition and geometry of patients and other relevant effects. However, no recommendations were provided on the transit dose due to the source traveling inside the patient. This study describes a methodology to calculate the transit dose using information from the treatment planning system (TPS) and considering the source's instantaneous and average speed for two prostate and two gynecological cases. The trajectory of the (192)Ir HDR source was defined by importing applicator contour points and dwell positions from the TPS. The transit dose distribution was calculated using the maximum speed, the average speed and uniform accelerations obtained from the literature to obtain an approximate continuous source distribution simulated with a Monte Carlo code. The transit component can be negligible or significant depending on the speed profile adopted, which is not clearly reported in the literature. The significance of the transit dose can also be due to the treatment modality; in our study interstitial treatments exhibited the largest effects. Considering the worst case scenario the transit dose can reach 3% of the prescribed dose in a gynecological case with four catheters and up to 11.1% when comparing the average prostate dose for a case with 16 catheters. The transit dose component increases by increasing the number of catheters used for HDR brachytherapy, reducing the total dwell time per catheter or increasing the number of dwell positions with low dwell times. This contribution may become significant (>5%) if it is not corrected appropriately. The transit dose cannot be completely compensated using simple dwell time corrections since it may have a non-uniform distribution. An accurate measurement of the source acceleration and maximum speed should be incorporated in clinical practice or provided by the manufacturer to determine the transit dose component with high accuracy.

ALGEBRA: ALgorithm for the heterogeneous dosimetry based on GEANT4 for BRAchytherapy.

Task group 43 (TG43)-based dosimetry algorithms are efficient for brachytherapy dose calculation in water. However, human tissues have chemical compositions and densities different than water. Moreover, the mutual shielding effect of seeds on each other (interseed attenuation) is neglected in the TG43-based dosimetry platforms. The scientific community has expressed the need for an accurate dosimetry platform in brachytherapy. The purpose of this paper is to present ALGEBRA, a Monte Carlo platform for dosimetry in brachytherapy which is sufficiently fast and accurate for clinical and research purposes. ALGEBRA is based on the GEANT4 Monte Carlo code and is capable of handling the DICOM RT standard to recreate a virtual model of the treated site. Here, the performance of ALGEBRA is presented for the special case of LDR brachytherapy in permanent prostate and breast seed implants. However, the algorithm is also capable of handling other treatments such as HDR brachytherapy.