Divergent clonal selection dominates medulloblastoma at recurrence.

The development of targeted anti-cancer therapies through the study of cancer genomes is intended to increase survival rates and decrease treatment-related toxicity. We treated a transposon-driven, functional genomic mouse model of medulloblastoma with 'humanized' in vivo therapy (microneurosurgical tumour resection followed by multi-fractionated, image-guided radiotherapy). Genetic events in recurrent murine medulloblastoma exhibit a very poor overlap with those in matched murine diagnostic samples (<5%). Whole-genome sequencing of 33 pairs of human diagnostic and post-therapy medulloblastomas demonstrated substantial genetic divergence of the dominant clone after therapy (<12% diagnostic events were retained at recurrence). In both mice and humans, the dominant clone at recurrence arose through clonal selection of a pre-existing minor clone present at diagnosis. Targeted therapy is unlikely to be effective in the absence of the target, therefore our results offer a simple, proximal, and remediable explanation for the failure of prior clinical trials of targeted therapy.

Assessing the Accuracy of Bioluminescence Image-Guided Stereotactic Body Radiation Therapy of Orthotopic Pancreatic Tumors Using a Small Animal Irradiator.

Stereotactic body radiation therapy (SBRT) has shown promising results in the treatment of pancreatic cancer and other solid tumors. However, wide adoption of SBRT remains limited largely due to uncertainty about the treatment's optimal fractionation schedules to elicit maximal tumor response while limiting the dose to adjacent structures. A small animal irradiator in combination with a clinically relevant oncological animal model could address these questions. Accurate delivery of X rays to animal tumors may be hampered by suboptimal image-guided targeting of the X-ray beam in vivo. Integration of bioluminescence imaging (BLI) into small animal irradiators in addition to standard cone-beam computed tomography (CBCT) imaging improves target identification and high-precision therapy delivery to deep tumors with poor soft tissue contrast, such as pancreatic tumors. Using bioluminescent BxPC3 pancreatic adenocarcinoma human cells grown orthotopically in mice, we examined the performance of a small animal irradiator equipped with both CBCT and BLI in delivering targeted, hypo-fractionated, multi-beam SBRT. Its targeting accuracy was compared with magnetic resonance imaging (MRI)-guided targeting based on co-registration between CBCT and corresponding sequential magnetic resonance scans, which offer greater soft tissue contrast compared with CT alone. Evaluation of our platform's BLI-guided targeting accuracy was performed by quantifying in vivo changes in bioluminescence signal after treatment as well as staining of ex vivo tissues with γH2AX, Ki67, TUNEL, CD31 and CD11b to assess SBRT treatment effects. Using our platform, we found that BLI-guided SBRT enabled more accurate delivery of X rays to the tumor resulting in greater cancer cell DNA damage and proliferation inhibition compared with MRI-guided SBRT. Furthermore, BLI-guided SBRT allowed higher animal throughput and was more cost effective to use in the preclinical setting than MRI-guided SBRT. Taken together, our preclinical platform could be employed in translational research of SBRT of pancreatic cancer.

The Impact of Disease Progression on Health-Related Quality of Life Outcomes in Patients With Oligometastatic Disease at 12 Months Post Stereotactic Body Radiation Therapy.

PURPOSE: There is a paucity of published health-related quality of life (HRQOL) outcomes in patients with oligometastatic disease (OMD) who receive stereotactic body radiation therapy (SBRT) and no available data assessing the effect of disease progression post-SBRT on HRQOL in this patient population. METHODS AND MATERIALS: Patients with OMD who received SBRT in a phase II single-arm research ethics board approved study were included. HRQOL was a secondary outcome. This study hypothesized that there is a different pattern of change from baseline HRQOL in patients with OMD treated with SBRT that have disease progression by 12 months (progressors) compared with those that do not progress by 12 months (nonprogressors), as measured by the European Organisation of Research and Treatment in Cancer Quality of Life Questionnaire Core 30. RESULTS: A total of 107 patients were included in this analysis, 41 without progression and 66 with progression by 12 months; median time to progression was 7.7 (0.3-57) months. A statistically significant decline in the mean global health/quality of life (GHQOL) score (73 [SD, 21.8] to 67.2 [SD, 27.1]; P = .04) from baseline in the entire population at the 12-month follow-up was found. Mean GHQOL change score in nonprogressors was -0.8 and in progressors was -8.8 (P = .07). However, only progressors demonstrated a difference between baseline and 12-month mean GHQOL scores (71.2 vs 62.4; P = .01), which was both statistically and clinically significant (-8.8) in the range of small minimal clinically important difference. There was a higher proportion of patients who experienced a minimal clinically important difference deterioration in progressors compared with nonprogressors (37.4% vs 24.4%; P = .14). CONCLUSIONS: Patients who progressed by 12 months did not have a statistical or clinically significant difference in mean GHQOL change score compared with nonprogressors. However, there were signals to suggest that patients who progressed by 12 months post-SBRT experienced a different pattern of change compared with nonprogressors, which was worse compared with baseline.

Heart irradiation as a risk factor for radiation pneumonitis.

PURPOSE: to investigate the potential role of incidental heart irradiation on the risk of radiation pneumonitis (RP) for patients receiving definitive radiation therapy for non-small-cell lung cancer (NSCLC). MATERIAL AND METHODS: two hundred and nine patient datasets were available for this study. Heart and lung dose-volume parameters were extracted for modeling, based on Monte Carlo-based heterogeneity corrected dose distributions. Clinical variables tested included age, gender, chemotherapy, pre-treatment weight-loss, performance status, and smoking history. The risk of RP was modeled using logistic regression. RESULTS: the most significant univariate variables were heart related, such as heart heart V65 (percent volume receiving at least 65 Gy) (Spearman Rs = 0.245, p < 0.001). The best-performing logistic regression model included heart D10 (minimum dose to the hottest 10% of the heart), lung D35, and maximum lung dose (Spearman Rs = 0.268, p < 0.0001). When classified by predicted risk, the RP incidence ratio between the most and least risky 1/3 of treatments was 4.8. The improvement in risk modeling using lung and heart variables was better than using lung variables alone. CONCLUSIONS: these results suggest a previously unsuspected role of heart irradiation in many cases of RP.

Limited-stage small cell lung cancer: Outcomes associated with prophylactic cranial irradiation over a 20-year period at the Princess Margaret Cancer Centre.

BACKGROUND & PURPOSE: Prophylactic cranial irradiation (PCI) is recommended for limited-stage small-cell lung cancer (LS-SCLC) patients with good response to concurrent chemoradiation. We report our institution's 20-year experience with this patient population and associated clinical outcomes. MATERIALS & METHODS: A retrospective cohort of consecutive LS-SCLC patients treated with curative intent chemoradiation at our institution (1997-2018) was reviewed. Overall survival (OS) was calculated using the Kaplan-Meier method, and significant covariates determined by the Cox proportional hazards model. Covariates predictive of PCI were determined using Fisher's exact test and the Mann-Whitney test. Brain failure risk (BFR) was calculated using the cumulative incidence method treating death as a competing event. Treatment cohorts (historic vs. contemporary) were stratified by the median year of diagnosis (2005). RESULTS: A total of 369 patients with LS-SCLC were identified, of which 278 patients were notionally PCI eligible. PCI was given to 196 patients (71%). Younger age was associated with PCI utilization (p < 0.001). PCI utilization rates did not change between the historic and contemporary treatment era (p = 0.11), whereas magnetic resonance imaging (MRI) use at baseline and follow-up became more prevalent in the contemporary era (p = <0.001). On multivariable analysis, PCI utilization was associated with improved OS (HR 1.88, 95% CI 1.32-2.69) and decreased BFR (HR 4.66, 95% CI 2.58-8.40). Patients who had MRI follow-up had a higher incidence of BFR (HR 0.35, 95% CI 0.18-0.66) in multivariable analyses. CONCLUSIONS: For LS-SCLC patients at our institution, PCI is more frequently utilized in younger patients, and the utilization rate did not change significantly over the past 20 years. PCI was independently associated with improved OS and lower BFR. Omission of PCI in LS-SCLC patients should not be routinely practiced in the absence of further prospective data.

A Comparison of Hypofractionated and Twice-Daily Thoracic Irradiation in Limited-Stage Small-Cell Lung Cancer: An Overlap-Weighted Analysis.

Despite evidence for the superiority of twice-daily (BID) radiotherapy schedules, their utilization in practice remains logistically challenging. Hypofractionation (HFRT) is a commonly implemented alternative. We aim to compare the outcomes and toxicities in limited-stage small-cell lung cancer (LS-SCLC) patients treated with hypofractionated versus BID schedules. A bi-institutional retrospective cohort review was conducted of LS-SCLC patients treated with BID (45 Gy/30 fractions) or HFRT (40 Gy/15 fractions) schedules from 2007 to 2019. Overlap weighting using propensity scores was performed to balance observed covariates between the two radiotherapy schedule groups. Effect estimates of radiotherapy schedule on overall survival (OS), locoregional recurrence (LRR) risk, thoracic response, any ≥grade 3 (including lung, and esophageal) toxicity were determined using multivariable regression modelling. A total of 173 patients were included in the overlap-weighted analysis, with 110 patients having received BID treatment, and 63 treated by HFRT. The median follow-up was 20.4 months. Multivariable regression modelling did not reveal any significant differences in OS (hazard ratio [HR] 1.67, p = 0.38), LRR risk (HR 1.48, p = 0.38), thoracic response (odds ratio [OR] 0.23, p = 0.21), any ≥grade 3+ toxicity (OR 1.67, p = 0.33), ≥grade 3 pneumonitis (OR 1.14, p = 0.84), or ≥grade 3 esophagitis (OR 1.41, p = 0.62). HFRT, in comparison to BID radiotherapy schedules, does not appear to result in significantly different survival, locoregional control, or toxicity outcomes.

Dosimetric variation due to the photon beam energy in the small-animal irradiation: a Monte Carlo study.

PURPOSE: The impact of photon beam energy and tissue heterogeneities on dose distributions and dosimetric characteristics such as point dose, mean dose, and maximum dose was investigated in the context of small-animal irradiation using Monte Carlo simulations based on the EGSnrc code. METHODS: Three Monte Carlo mouse phantoms, namely, heterogeneous, homogeneous, and bone homogeneous were generated based on the same mouse computed tomography image set. These phantoms were generated by overriding the tissue type of none of the voxels (heterogeneous), all voxels (homogeneous), and only the bone voxels (bone homogeneous) to that of soft tissue. Phase space files of the 100 and 225 kVp photon beams based on a small-animal irradiator (XRad225Cx, Precision X-Ray Inc., North Branford, CT) were generated using BEAMnrc. A 360 degrees photon arc was simulated and three-dimensional (3D) dose calculations were carried out using the DOSXYZnrc code through DOSCTP in the above three phantoms. For comparison, the 3D dose distributions, dose profiles, mean, maximum, and point doses at different locations such as the isocenter, lung, rib, and spine were determined in the three phantoms. RESULTS: The dose gradient resulting from the 225 kVp arc was found to be steeper than for the 100 kVp arc. The mean dose was found to be 1.29 and 1.14 times higher for the heterogeneous phantom when compared to the mean dose in the homogeneous phantom using the 100 and 225 kVp photon arcs, respectively. The bone doses (rib and spine) in the heterogeneous mouse phantom were about five (100 kVp) and three (225 kVp) times higher when compared to the homogeneous phantom. However, the lung dose did not vary significantly between the heterogeneous, homogeneous, and bone homogeneous phantom for the 225 kVp compared to the 100 kVp photon beams. CONCLUSIONS: A significant bone dose enhancement was found when the 100 and 225 kVp photon beams were used in small-animal irradiation. This dosimetric effect, due to the presence of the bone heterogeneity, was more significant than that due to the lung heterogeneity. Hence, for kV photon energies of the range used in small-animal irradiation, the increase of the mean and bone dose due to the photoelectric effect could be a dosimetric concern.

Datamining approaches for modeling tumor control probability.

BACKGROUND: Tumor control probability (TCP) to radiotherapy is determined by complex interactions between tumor biology, tumor microenvironment, radiation dosimetry, and patient-related variables. The complexity of these heterogeneous variable interactions constitutes a challenge for building predictive models for routine clinical practice. We describe a datamining framework that can unravel the higher order relationships among dosimetric dose-volume prognostic variables, interrogate various radiobiological processes, and generalize to unseen data before when applied prospectively. MATERIAL AND METHODS: Several datamining approaches are discussed that include dose-volume metrics, equivalent uniform dose, mechanistic Poisson model, and model building methods using statistical regression and machine learning techniques. Institutional datasets of non-small cell lung cancer (NSCLC) patients are used to demonstrate these methods. The performance of the different methods was evaluated using bivariate Spearman rank correlations (rs). Over-fitting was controlled via resampling methods. RESULTS: Using a dataset of 56 patients with primary NCSLC tumors and 23 candidate variables, we estimated GTV volume and V75 to be the best model parameters for predicting TCP using statistical resampling and a logistic model. Using these variables, the support vector machine (SVM) kernel method provided superior performance for TCP prediction with an rs=0.68 on leave-one-out testing compared to logistic regression (rs=0.4), Poisson-based TCP (rs=0.33), and cell kill equivalent uniform dose model (rs=0.17). CONCLUSIONS: The prediction of treatment response can be improved by utilizing datamining approaches, which are able to unravel important non-linear complex interactions among model variables and have the capacity to predict on unseen data for prospective clinical applications.

A Mail Audit Independent Peer Review System for Dosimetry Verification of a Small Animal Irradiator.

Dedicated precision orthovoltage small animal irradiators have become widely available in the past decade and are commonly used for radiation biology research. However, there is a lack of dosimetric standardization among these irradiators, which affects the reproducibility of radiation-based animal studies. The purpose of this study was to develop a mail-based, independent peer review system to verify dose delivery among institutions using X-RAD 225Cx irradiators (Precision X-Ray, North Branford, CT). A robust, user-friendly mouse phantom was constructed from high-impact polystyrene and designed with dimensions similar to those of a typical laboratory mouse. The phantom accommodates three thermoluminescent dosimeters (TLDs) to measure dose. The mouse peer review system was commissioned in a small animal irradiator using anterior-posterior and posterior-anterior beams of 225 kVp and then mailed to three institutions to test the feasibility of the audit service. The energy correction factor for TLDs in the mouse phantom was derived to validate the delivered dose using this particular animal irradiation system. This feasibility study indicated that three institutions were able to deliver a radiation dose to the mouse phantom within ±10% of the target dose. The developed mail audit independent peer review system for the verification of mouse dosimetry can be expanded to characterize other commercially available orthovoltage irradiators, thereby enhancing the reproducibility of studies employing these irradiators.

Predicting radiotherapy outcomes using statistical learning techniques.

Radiotherapy outcomes are determined by complex interactions between treatment, anatomical and patient-related variables. A common obstacle to building maximally predictive outcome models for clinical practice is the failure to capture potential complexity of heterogeneous variable interactions and applicability beyond institutional data. We describe a statistical learning methodology that can automatically screen for nonlinear relations among prognostic variables and generalize to unseen data before. In this work, several types of linear and nonlinear kernels to generate interaction terms and approximate the treatment-response function are evaluated. Examples of institutional datasets of esophagitis, pneumonitis and xerostomia endpoints were used. Furthermore, an independent RTOG dataset was used for 'generalizabilty' validation. We formulated the discrimination between risk groups as a supervised learning problem. The distribution of patient groups was initially analyzed using principle components analysis (PCA) to uncover potential nonlinear behavior. The performance of the different methods was evaluated using bivariate correlations and actuarial analysis. Over-fitting was controlled via cross-validation resampling. Our results suggest that a modified support vector machine (SVM) kernel method provided superior performance on leave-one-out testing compared to logistic regression and neural networks in cases where the data exhibited nonlinear behavior on PCA. For instance, in prediction of esophagitis and pneumonitis endpoints, which exhibited nonlinear behavior on PCA, the method provided 21% and 60% improvements, respectively. Furthermore, evaluation on the independent pneumonitis RTOG dataset demonstrated good generalizabilty beyond institutional data in contrast with other models. This indicates that the prediction of treatment response can be improved by utilizing nonlinear kernel methods for discovering important nonlinear interactions among model variables. These models have the capacity to predict on unseen data.

Spatial frequency performance limitations of radiation dose optimization and beam positioning.

The flexibility and sophistication of modern radiotherapy treatment planning and delivery methods have advanced techniques to improve the therapeutic ratio. Contemporary dose optimization and calculation algorithms facilitate radiotherapy plans which closely conform the three-dimensional dose distribution to the target, with beam shaping devices and image guided field targeting ensuring the fidelity and accuracy of treatment delivery. Ultimately, dose distribution conformity is limited by the maximum deliverable dose gradient; shallow dose gradients challenge techniques to deliver a tumoricidal radiation dose while minimizing dose to surrounding tissue. In this work, this 'dose delivery resolution' observation is rigorously formalized for a general dose delivery model based on the superposition of dose kernel primitives. It is proven that the spatial resolution of a delivered dose is bounded by the spatial frequency content of the underlying dose kernel, which in turn defines a lower bound in the minimization of a dose optimization objective function. In addition, it is shown that this optimization is penalized by a dose deposition strategy which enforces a constant relative phase (or constant spacing) between individual radiation beams. These results are further refined to provide a direct, analytic method to estimate the dose distribution arising from the minimization of such an optimization function. The efficacy of the overall framework is demonstrated on an image guided small animal microirradiator for a set of two-dimensional hypoxia guided dose prescriptions.

A nomogram to predict radiation pneumonitis, derived from a combined analysis of RTOG 9311 and institutional data.

PURPOSE: To test the Washington University (WU) patient dataset, analysis of which suggested that superior-to-inferior tumor position, maximum dose, and D35 (minimum dose to the hottest 35% of the lung volume) were valuable to predict radiation pneumonitis (RP), against the patient database from Radiation Therapy Oncology Group (RTOG) trial 9311. METHODS AND MATERIALS: The entire dataset consisted of 324 patients receiving definitive conformal radiotherapy for non-small-cell lung cancer (WU = 219, RTOG 9311 = 129). Clinical, dosimetric, and tumor location parameters were modeled to predict RP in the individual datasets and in a combined dataset. Association quality with RP was assessed using Spearman's rank correlation (r) for univariate analysis and multivariate analysis; comparison between subgroups was tested using the Wilcoxon rank sum test. RESULTS: The WU model to predict RP performed poorly for the RTOG 9311 data. The most predictive model in the RTOG 9311 dataset was a single-parameter model, D15 (r = 0.28). Combining the datasets, the best derived model was a two-parameter model consisting of mean lung dose and superior-to-inferior gross tumor volume position (r = 0.303). An equation and nomogram to predict the probability of RP was derived using the combined patient population. CONCLUSIONS: Statistical models derived from a large pool of candidate models resulted in well-tuned models for each subset (WU or RTOG 9311), which did not perform well when applied to the other dataset. However, when the data were combined, a model was generated that performed well on each data subset. The final model incorporates two effects: greater risk due to inferior lung irradiation, and greater risk for increasing normal lung mean dose. This formula and nomogram may aid clinicians during radiation treatment planning for lung cancer.

Retrospective monte carlo dose calculations with limited beam weight information.

An important unresolved issue in outcomes analysis for lung complications is the effect of poor or completely lacking heterogeneity corrections in previously archived treatment plans. To estimate this effect, we developed a novel method based on Monte Carlo (MC) dose calculations which can be applied retrospectively to RTOG/AAPM-style archived treatment plans (ATP). We applied this method to 218 archived nonsmall cell lung cancer lung treatment plans that were originally calculated either without heterogeneity corrections or with primitive corrections. To retrospectively specify beam weights and wedges, beams were broken into Monte Carlo-generated beamlets, simulated using the VMC++ code, and mathematical optimization was used to match the archived water-based dose distributions. The derived beam weights (and any wedge effects) were then applied to Monte Carlo beamlets regenerated based on the patient computed tomography densities. Validation of the process was performed against five comparable lung treatment plans generated using a commercial convolution/superposition implementation. For the application here (normal lung, esophagus, and planning target volume dose distributions), the agreement was very good. Resulting MC and convolution/superposition values were similar when dose distributions without heterogeneity corrections or dose distributions with corrections were compared. When applied to the archived plans (218), the average absolute percent difference between water-based MC and water-based ATPs, for doses above 2.5% of the maximum dose was 1.8+/-0.6%. The average absolute percent difference between heterogeneity-corrected MC and water-based ATPs increased to 3.1+/-0.9%. The average absolute percent difference between the MC heterogeneity-corrected and the ATP heterogeneity-corrected dose distributions was 3.8+/-1.6% (available in 132/218 archives). The entire dose-volume-histograms for lung, tumor, and esophagus from the different calculation methods, as well as specific dose metrics, were compared. The average difference in maximum lung dose between water-based ATPs and heterogeneity-corrected MC dose distributions was -1.0+/-2.1 Gy. Potential errors in relying on primitive heterogeneity corrections are most evident from a comparison of maximum lung doses, for which the average MC heterogeneity-corrected values were 5.3+/-2.8 Gy less than the ATP heterogeneity-corrected values. We have demonstrated that recalculation of archived dose distributions, without explicit information about beam weights or wedges, is feasible using beamlet-based optimization methods. The method provides heterogeneity-corrected dose data consistent with convolution-superposition calculations and is one feasible approach for improving dosimetric data for outcomes analyses.

Multivariable modeling of radiotherapy outcomes, including dose-volume and clinical factors.

PURPOSE: The probability of a specific radiotherapy outcome is typically a complex, unknown function of dosimetric and clinical factors. Current models are usually oversimplified. We describe alternative methods for building multivariable dose-response models. METHODS: Representative data sets of esophagitis and xerostomia are used. We use a logistic regression framework to approximate the treatment-response function. Bootstrap replications are performed to explore variable selection stability. To guard against under/overfitting, we compare several analytical and data-driven methods for model-order estimation. Spearman's coefficient is used to evaluate performance robustness. Novel graphical displays of variable cross correlations and bootstrap selection are demonstrated. RESULTS: Bootstrap variable selection techniques improve model building by reducing sample size effects and unveiling variable cross correlations. Inference by resampling and Bayesian approaches produced generally consistent guidance for model order estimation. The optimal esophagitis model consisted of 5 dosimetric/clinical variables. Although the xerostomia model could be improved by combining clinical and dose-volume factors, the improvement would be small. CONCLUSIONS: Prediction of treatment response can be improved by mixing clinical and dose-volume factors. Graphical tools can mitigate the inherent complexity of multivariable modeling. Bootstrap-based variable selection analysis increases the reliability of reported models. Statistical inference methods combined with Spearman's coefficient provide an efficient approach to estimating optimal model order.

Modeling radiation pneumonitis risk with clinical, dosimetric, and spatial parameters.

PURPOSE: To determine the clinical, dosimetric, and spatial parameters that correlate with radiation pneumonitis. METHODS AND MATERIALS: Patients treated with high-dose radiation for non-small-cell lung cancer with three-dimensional treatment planning were reviewed for clinical information and radiation pneumonitis (RP) events. Three-dimensional treatment plans for 219 eligible patients were recovered. Treatment plan information, including parameters defining tumor position and dose-volume parameters, was extracted from non-heterogeneity-corrected dose distributions. Correlation to RP events was assessed by Spearman's rank correlation coefficient (R). Mathematical models were generated that correlate with RP. RESULTS: Of 219 patients, 52 required treatment for RP (median interval, 142 days). Tumor location was the most highly correlated parameter on univariate analysis (R = 0.24). Multiple dose-volume parameters were correlated with RP. Models most frequently selected by bootstrap resampling included tumor position, maximum dose, and D35 (minimum dose to the 35% volume receiving the highest doses) (R = 0.28). The most frequently selected two- or three-parameter models outperformed commonly used metrics, including V20 (fractional volume of normal lung receiving >20 Gy) and mean lung dose (R = 0.18). CONCLUSIONS: Inferior tumor position was highly correlated with pneumonitis events within our population. Models that account for inferior tumor position and dosimetric information, including both high- and low-dose regions (D(35), International Commission on Radiation Units and Measurements maximum dose), risk-stratify patients more accurately than any single dosimetric or clinical parameter.

Online virtual isocenter based radiation field targeting for high performance small animal microirradiation.

Advances in precision microirradiators for small animal radiation oncology studies have provided the framework for novel translational radiobiological studies. Such systems target radiation fields at the scale required for small animal investigations, typically through a combination of on-board computed tomography image guidance and fixed, interchangeable collimators. Robust targeting accuracy of these radiation fields remains challenging, particularly at the millimetre scale field sizes achievable by the majority of microirradiators. Consistent and reproducible targeting accuracy is further hindered as collimators are removed and inserted during a typical experimental workflow. This investigation quantified this targeting uncertainty and developed an online method based on a virtual treatment isocenter to actively ensure high performance targeting accuracy for all radiation field sizes. The results indicated that the two-dimensional field placement uncertainty was as high as 1.16 mm at isocenter, with simulations suggesting this error could be reduced to 0.20 mm using the online correction method. End-to-end targeting analysis of a ball bearing target on radiochromic film sections showed an improved targeting accuracy with the three-dimensional vector targeting error across six different collimators reduced from [Formula: see text] mm (mean ± SD) to [Formula: see text] mm for an isotropic imaging voxel size of 0.1 mm.

Correlation of dosimetric and clinical factors with the development of esophagitis and radiation pneumonitis in patients with limited-stage small-cell lung carcinoma.

BACKGROUND: The purpose of the study was to correlate clinical and dosimetric factors with the development of esophagitis and radiation pneumonitis in patients with limited-stage small-cell lung carcinoma (LS SCLC). PATIENTS AND METHODS: One hundred eighteen patients who received curative intent chemoradiotherapy for LS SCLC and had electronically archived radiation treatment plans were included. The medical charts were reviewed for clinical data. The treatment plan was reviewed for critical structure delineation and dose delivered. Treatment planning data were analyzed using Computational Environment for Radiotherapy Research (V3.3). Dosimetric parameters were correlated with the risk of toxicity using Spearman rank correlation. RESULTS: Radiotherapy dose was 40 Gy in 15 fractions (fx) (n = 80) and 45 Gy in 30 fractions twice per day (n = 38). The 6-month cumulative incidence of Grade ≥ 2 radiation pneumonitis was 6.5% and 7.9% for the 40 Gy/15 fx and 45 Gy/30 fx groups, respectively (P = .40). The 3-month cumulative incidence of Grade 3 esophagitis was 7.5% and 13.2% for the 40 Gy/15 fx and 45 Gy/30 fx groups, respectively (P = .31). Grade ≥ 3 pneumonitis was correlated with volume of lung receiving 20 Gy (V20) and mean lung dose. Grade ≥ 3 esophagitis was correlated with mean esophagus dose and minimum dose to the hottest 45% of the esophagus (D45). CONCLUSION: Mean lung dose and V20 were significant predictors of radiation pneumonitis in LS SCLC. Mean esophageal dose and D45 were significant predictors of esophagitis. These 2 treatment schedules have similar toxicity profiles.

A systematic study of imaging uncertainties and their impact on 125I prostate brachytherapy dose evaluation.

In order to calculate the dose distribution delivered by a prostate brachytherapy implant, the seed positions and prostate volume are normally identified on post-implant CT images. We have systematically considered the impact of uncertainties in contouring the prostate, seed localization, and visualization of all the seeds on the calculated dose distributions, dose-volume histograms, and predicted radiobiological outcome. This study was done for a collection of 27 clinical 125I prostate brachytherapy implants, performed at the London Regional Cancer Centre during our early adoption of this technique. For these clinical dose distributions, the median D90 was 76% of the prescription dose, or 110 Gy, and the median V90 was 80%. We calculated the changes in these dosimetric indices (D90 and V90) and radiobiological outcome (SF2 TCP) as a function of contouring uncertainty, seed localization uncertainty, inability to localize all of the seeds, and binary combinations of these three. The results are presented for a range of uncertainties, which allows the possible application of these results to a variety of imaging modalities that have differing spatial resolutions. We found that both contouring uncertainties and seed localization uncertainties had a large impact on the predicted radiobiological outcome, but that seed localization uncertainties of 6 mm had the largest impact on the dosimetric indices. We also found that the variability in both the predicted radiobiological and dosimetric outcome was largest for contouring uncertainties of 4-8 mm. We conclude that accounting for contouring uncertainties is crucial in accurately deducing the DVHs for post-implant prostate brachytherapy, and hence enabling valid correlation with ultimate clinical outcome.

Integration of optical imaging with a small animal irradiator.

PURPOSE: The authors describe the integration of optical imaging with a targeted small animal irradiator device, focusing on design, instrumentation, 2D to 3D image registration, 2D targeting, and the accuracy of recovering and mapping the optical signal to a 3D surface generated from the cone-beam computed tomography (CBCT) imaging. The integration of optical imaging will improve targeting of the radiation treatment and offer longitudinal tracking of tumor response of small animal models treated using the system. METHODS: The existing image-guided small animal irradiator consists of a variable kilovolt (peak) x-ray tube mounted opposite an aSi flat panel detector, both mounted on a c-arm gantry. The tube is used for both CBCT imaging and targeted irradiation. The optical component employs a CCD camera perpendicular to the x-ray treatment/imaging axis with a computer controlled filter for spectral decomposition. Multiple optical images can be acquired at any angle as the gantry rotates. The optical to CBCT registration, which uses a standard pinhole camera model, was modeled and tested using phantoms with markers visible in both optical and CBCT images. Optically guided 2D targeting in the anterior/posterior direction was tested on an anthropomorphic mouse phantom with embedded light sources. The accuracy of the mapping of optical signal to the CBCT surface was tested using the same mouse phantom. A surface mesh of the phantom was generated based on the CBCT image and optical intensities projected onto the surface. The measured surface intensity was compared to calculated surface for a point source at the actual source position. The point-source position was also optimized to provide the closest match between measured and calculated intensities, and the distance between the optimized and actual source positions was then calculated. This process was repeated for multiple wavelengths and sources. RESULTS: The optical to CBCT registration error was 0.8 mm. Two-dimensional targeting of a light source in the mouse phantom based on optical imaging along the anterior/posterior direction was accurate to 0.55 mm. The mean square residual error in the normalized measured projected surface intensities versus the calculated normalized intensities ranged between 0.0016 and 0.006. Optimizing the position reduced this error from 0.00016 to 0.0004 with distances ranging between 0.7 and 1 mm between the actual and calculated position source positions. CONCLUSIONS: The integration of optical imaging on an existing small animal irradiation platform has been accomplished. A targeting accuracy of 1 mm can be achieved in rigid, homogeneous phantoms. The combination of optical imaging with a CBCT image-guided small animal irradiator offers the potential to deliver functionally targeted dose distributions, as well as monitor spatial and temporal functional changes that occur with radiation therapy.

Two-dimensional inverse planning and delivery with a preclinical image guided microirradiator.

PURPOSE: Recent advances in preclinical radiotherapy systems have provided the foundation for scaling many of the elements of clinical radiation therapy practice to the dimensions and energy demanded in small animal studies. Such systems support the technical capabilities to accurately deliver highly complex dose distributions, but methods to optimize and deliver such distributions remain in their infancy. This study developed an optimization method based on empirically measured two-dimensional dose kernel measurements to deliver arbitrary planar dose distributions on a recently developed small animal radiotherapy platform. METHODS: A two-dimensional dose kernel was measured with repeated radiochromic film measurements for the circular 1 mm diameter fixed collimator of the small animal radiotherapy system at 1 cm depth in a solid water phantom. This kernel was utilized in a sequential quadratic programming optimization framework to determine optimal beam positions and weights to deliver an arbitrary desired dose distribution. The positions and weights were then translated to a set of stage motions to automatically deliver the optimized dose distribution. End-to-end efficacy of the framework was quantified through five repeated deliveries of two dosimetric challenges: (1) a 5 mm radius bullseye distribution, and (2) a "sock" distribution contained within a 9 × 13 mm bounding box incorporating rectangular, semicircular, and exponentially decaying geometric constructs and a rectangular linear dose gradient region. These two challenges were designed to gauge targeting, geometric, and dosimetric fidelity. RESULTS: Optimization of the bullseye and sock distributions required 2.1 and 5.9 min and utilized 50 and 77 individual beams for delivery, respectively. Automated delivery of the resulting optimized distributions, validated using radiochromic film measurements, revealed an average targeting accuracy of 0.32 mm, and a dosimetric delivery error along four line profiles taken through the sock distribution of 3.9%. Mean absolute delivery error across the 0-1 Gy linear dose gradient over 7.5 mm was 0.01 Gy. CONCLUSIONS: The work presented here demonstrates the potential for complex dose distributions to be planned and automatically delivered with millimeter scale heterogeneity at submillimeter accuracy. This capability establishes the technical foundation for preclinical validation of biologically guided radiotherapy investigations and development of unique radiobiological experiments.