Prospective assessment of sparing the parotid ducts via MRI sialography for reducing patient reported xerostomia.

PURPOSE: To assess the impact of prospectively sparing the parotid ducts via MRI sialography on patient reported xerostomia for those receiving definitive radiotherapy (RT) for oropharyngeal squamous cell carcinoma. METHODS AND MATERIALS: Thirty-eight patients with oropharynx cancer to be treated with definitive RT underwent pre-treatment MRI sialograms to localize their parotid ducts. The parotid ducts were maximally spared during treatment planning. Patients reported symptoms (PRO-CTCAE and QLQ-H&N35) were collected at 6 and 12 months post-RT and compared to a historical cohort who underwent conventional parotid gland mean dose sparing. Regression models were generated using parotid and submandibular gland doses with and without incorporating the dose to the parotid ducts to determine the impact of parotid duct dose on patient reported xerostomia. RESULTS: At 6 months post-RT, 12/26 (46%) patients reported ≥moderate xerostomia when undergoing parotid ductal sparing compared to 43/61 (70%) in the historical cohort (p = 0.03). At 12 months post-RT, 8/22 (36%) patients reported ≥moderate xerostomia when undergoing parotid ductal sparing compared to 34/68(50%) in the historical cohort (p = 0.08). Using nested logistic regression models, the mean parotid duct dose was found to significantly relate to patient reported xerostomia severity at 6 months post-RT (p = 0.04) and trended towards statistical significance at 12 months post-RT (p = 0.09). At both 6 and 12 months post-RT, the addition of mean parotid duct dose significantly improved model fit (p < 0.05). CONCLUSIONS: MRI sialography guided parotid duct sparing appears to reduce the rates of patient-reported xerostomia. Further, logistic regression analysis found parotid duct dose to be significantly associated with patient reported xerostomia. A significant improvement in model fit was observed when adding mean parotid duct dose compared to models that only contain mean parotid gland dose and mean contralateral submandibular gland dose.

Initial assessment of 3D magnetic resonance fingerprinting (MRF) towards quantitative brain imaging for radiation therapy.

PURPOSE: Magnetic resonance fingerprinting (MRF) provides quantitative T1/T2 maps, enabling applications in clinical radiotherapy such as large-scale, multi-center clinical trials for longitudinal assessment of therapy response. We evaluated the feasibility of a quantitative three-dimensional-MRF (3D-MRF) towards its radiotherapy applications of primary brain tumors. METHODS: A fast whole-brain 3D-MRF sequence initially developed for diagnostic radiology was optimized using flexible body coils, which is the typical MR imaging setup for radiotherapy treatment planning and for MR imaging (MRI)-guided treatment delivery. Optimization criteria included the accuracy and the precision of T1/T2 quantifications of polyvinylpyrrolidone (PVP) solutions, compared to those from the 3D-MRF using a 32-channel head coil. The accuracy of T1/T2 quantifications from the optimized MRF was first examined in healthy volunteers with two different coil setups. The intra- and inter-scanner variations of image intensity from the optimized sequence were quantified by longitudinal scans of the PVP solutions on two 3T scanners. Using a 3D-printed MRI geometry phantom, susceptibility-induced distortion with the optimized 3D-MRF was quantified as the Dice coefficient of phantom contours, compared to those from CT images. By introducing intentional head motion during 10% of the scan, the robustness of the optimized 3D-MRF towards motion was evaluated through visual inspection of motion artifacts and through quantitative analysis of image sharpness in brain MRF maps. RESULTS: The optimized sequence acquired whole-brain T1, T2 and proton density maps and with a resolution of 1.2 × 1.2 × 3 mm3 in 10 min, similar to the total acquisition time of 3D T1- and T2-weighted images of the same resolution. In vivo T1 and T2 values of the white and gray matter were consistent with literature. The intra- and inter-scanner variability of the intensity-normalized MRF T1 was 1.0% ± 0.7% and 2.3% ± 1.0% respectively, in contrast to 5.3% ± 3.8% and 3.2% ± 1.6% from the normalized T1-weighted MRI. Repeatability and reproducibility of MRF T1 were independent of intensity normalization. Both phantom and human data demonstrated that the optimized 3D-MRF is more robust to subject motion and artifacts from subject-specific susceptibility difference. Compared to CT contours, the Dice coefficient of phantom contours from 3D-MRF was 0.93, improved from 0.87 from the T1-weighted MRI. CONCLUSION: Compared to conventional MRI, the optimized 3D-MRF demonstrated improved repeatability across time points and reproducibility across scanners for better tissue quantification, as well as improved robustness to subject-specific susceptibility and motion artifacts under a typical MR imaging setup for radiotherapy. More importantly, quantitative MRF T1/T2 measurements lead to promising potentials towards longitudinal quantitative assessment of treatment response for better adaptive therapy and for large-scale, multi-center clinical trials.

Assessment of PlanIQ Feasibility DVH for head and neck treatment planning.

INTRODUCTION: Designing a radiation plan that optimally delivers both target coverage and normal tissue sparing is challenging. There are limited tools to determine what is dosimetrically achievable and frequently the experience of the planner/physician is relied upon to make these determinations. PlanIQ software provides a tool that uses target and organ at risk (OAR) geometry to indicate the difficulty of achieving different points for organ dose-volume histograms (DVH). We hypothesized that PlanIQ Feasibility DVH may aid planners in reducing dose to OARs. METHODS AND MATERIALS: Clinically delivered head and neck treatments (clinical plan) were re-planned (re-plan) putting high emphasis on maximally sparing the contralateral parotid gland, contralateral submandibular gland, and larynx while maintaining routine clinical dosimetric objectives. The planner was blinded to the results of the clinically delivered plan as well as the Feasibility DVHs from PlanIQ. The re-plan treatments were designed using 3-arc VMAT in Raystation (RaySearch Laboratories, Sweden). The planner was then given the results from the PlanIQ Feasibility DVH analysis and developed an additional plan incorporating this information using 4-arc VMAT (IQ plan). The DVHs across the three treatment plans were compared with what was deemed "impossible" by PlanIQ's Feasibility DVH (Impossible DVH). The impossible DVH (red) is defined as the DVH generated using the minimal dose that any voxel outside the targets must receive given 100% target coverage. RESULTS: The re-plans performed blinded to PlanIQ Feasibilty DVH achieved superior sparing of aforementioned OARs compared to the clinically delivered plans and resulted in discrepancies from the impossible DVHs by an average of 200-700 cGy. Using the PlanIQ Feasibility DVH led to additionalOAR sparing compared to both the re-plans and clinical plans and reduced the discrepancies from the impossible DVHs to an average of approximately 100 cGy. The dose reduction from clinical to re-plan and re-plan to IQ plan were significantly different even when taking into account multiple hypothesis testing for both the contralateral parotid and the larynx (P < 0.004 for all comparisons). No significant differences were observed between the three plans for the contralateral parotid when considering multiple hypothesis testing. CONCLUSIONS: Clinical treatment plans and blinded re-plans were found to suboptimally spare OARs. PlanIQ could aid planners in generating treatment plans that push the limits of OAR sparing while maintaining routine clinical target coverage goals.

Predicting lung radiotherapy-induced pneumonitis using a model combining parametric Lyman probit with nonparametric decision trees.

PURPOSE: To develop and test a model to predict for lung radiation-induced Grade 2+ pneumonitis. METHODS AND MATERIALS: The model was built from a database of 234 lung cancer patients treated with radiotherapy (RT), of whom 43 were diagnosed with pneumonitis. The model augmented the predictive capability of the parametric dose-based Lyman normal tissue complication probability (LNTCP) metric by combining it with weighted nonparametric decision trees that use dose and nondose inputs. The decision trees were sequentially added to the model using a "boosting" process that enhances the accuracy of prediction. The model's predictive capability was estimated by 10-fold cross-validation. To facilitate dissemination, the cross-validation result was used to extract a simplified approximation to the complicated model architecture created by boosting. Application of the simplified model is demonstrated in two example cases. RESULTS: The area under the model receiver operating characteristics curve for cross-validation was 0.72, a significant improvement over the LNTCP area of 0.63 (p = 0.005). The simplified model used the following variables to output a measure of injury: LNTCP, gender, histologic type, chemotherapy schedule, and treatment schedule. For a given patient RT plan, injury prediction was highest for the combination of pre-RT chemotherapy, once-daily treatment, female gender and lowest for the combination of no pre-RT chemotherapy and nonsquamous cell histologic type. Application of the simplified model to the example cases revealed that injury prediction for a given treatment plan can range from very low to very high, depending on the settings of the nondose variables. CONCLUSIONS: Radiation pneumonitis prediction was significantly enhanced by decision trees that added the influence of nondose factors to the LNTCP formulation.

Updated assessment of the six-minute walk test as predictor of acute radiation-induced pneumonitis.

PURPOSE: To assess the utility of the 6-minute walk test (6MWT) as a predictor of symptomatic radiation-induced pneumonitis (RP). METHODS: As part of a prospective trial to study radiation-induced lung injury, 53 patients receiving thoracic radiotherapy (RT) underwent a pre-RT 6MWT, pulmonary function tests (PFTs), and had >or=3-month follow-up for prospective assessment of Grade 2 or worse RP (requiring medications or worse). Dosimetric parameters (e.g., the percentage of lung receiving >or=30 Gy) were extracted from the lung dose-volume histogram. The correlations between the 6MWT and PFT results were assessed using Pearson's correlation. The receiver operating characteristic technique was used in patient subgroups to evaluate the predictive capacities for RP of the dosimetric parameters, 6MWT results, and PFT results, or the combination (using discriminant analysis) of all three metrics. ROCKIT software was used to compare the receiver operating characteristic areas between each predictive model. The association of the decline in 6MWT with the development of RP was evaluated using Fisher's exact test. RESULTS: The pre-RT PFT and 6MWT results correlated weakly (r = 0.44-0.57, p or=30 Gy, receiver operating characteristic area 0.73, p = 0.03). Including the PFT or 6MWT results with the percentage of lung receiving >or=30 Gy did not improve the predictions. The predictive abilities of dosimetric-based models improved when the analysis was restricted to those patients whose tumors were not causing regional lung dysfunction. No correlation was found between the decline in the 6MWT result and the RP rate (p = 0.6). CONCLUSION: Although the PFTs and 6MWT are related to each other, the correlation coefficients were weak, suggesting that they could be measuring different physiologic functions. In the present data set, the addition of the PFTs or 6MWT did not increase the ability of the dosimetric parameters to predict for acute symptomatic RP. Additional work is needed to better understand the interaction among the PFT results, exercise tolerance (6MWT), and the risk of RT-induced lung dysfunction.

Optimization of a 90Sr/90Y radiation source train stepping for intravascular brachytherapy.

A steepest-descent gradient algorithm is developed to optimize the stepping of a 90Sr/90Y radiation source train (RST) for intravascular brachytherapy (IVB). The objective function is to deliver a uniform dose in a coronary target vessel and minimize the dose in adjacent normal vessel tissue at the proximal and distal edges of the coronary target vessel. Based on the target length and number of dwell points (number of steps), the algorithm modulates the dwell times and corresponding dwell positions that optimize the weighted addition of staggered EGS4 Monte Carlo (MC) calculated dose distribution from a single RST. Stepping treatment plans are generated for target vessel lengths of 3.0, 3.3, and 3.8 cm. For both the unoptimized and optimized plans, the dose heterogeneity in the target vessel wall, and length of nontarget vessel receiving 3 Gy, is assessed to compare plans. Optimization results show a 14% dose uniformity within the target is achievable for all vessel lengths. Further, the dose in the adjacent normal tissue is lower in the optimized plans than the unoptimized plans. The work presented in this paper provides a model to address the finite length of RST in IVB treatments. While the results presented are specific to the 90Sr/90Y RST, the methods should apply to other finite length RSTs.