Yevgeniy Vinogradskiy

Use of 4-dimensional computed tomography-based ventilation imaging to correlate lung dose and function with clinical outcomes

PURPOSE Four-dimensional computed tomography (4DCT)-based ventilation is an emerging imaging modality that can be used in the thoracic treatment planning process. The clinical benefit of using ventilation images in radiation treatment plans remains to be tested. The purpose of the current work was to test the potential benefit of using ventilation in treatment planning by evaluating whether dose to highly ventilated regions of the lung resulted in increased incidence of clinical toxicity. METHODS AND MATERIALS Pretreatment 4DCT data were used to compute pretreatment ventilation images for 96 lung cancer patients. Ventilation images were calculated using 4DCT data, deformable image registration, and a density-change based algorithm. Dose-volume and ventilation-based dose function metrics were computed for each patient. The ability of the dose-volume and ventilation-based dose-function metrics to predict for severe (grade 3+) radiation pneumonitis was assessed using logistic regression analysis, area under the curve (AUC) metrics, and bootstrap methods. RESULTS A specific patient example is presented that demonstrates how incorporating ventilation-based functional information can help separate patients with and without toxicity. The logistic regression significance values were all lower for the dose-function metrics (range P=.093-.250) than for their dose-volume equivalents (range, P=.331-.580). The AUC values were all greater for the dose-function metrics (range, 0.569-0.620) than for their dose-volume equivalents (range, 0.500-0.544). Bootstrap results revealed an improvement in model fit using dose-function metrics compared to dose-volume metrics that approached significance (range, P=.118-.155). CONCLUSIONS To our knowledge, this is the first study that attempts to correlate lung dose and 4DCT ventilation-based function to thoracic toxicity after radiation therapy. Although the results were not significant at the .05 level, our data suggests that incorporating ventilation-based functional imaging can improve prediction for radiation pneumonitis. We present an important first step toward validating the use of 4DCT-based ventilation imaging in thoracic treatment planning.

Use of weekly 4DCT-based ventilation maps to quantify changes in lung function for patients undergoing radiation therapy

PURPOSE A method has been proposed to calculate ventilation maps from four-dimensional computed tomography (4DCT) images. Weekly 4DCT data were acquired throughout the course of radiation therapy for patients with lung cancer. The purpose of our work was to use ventilation maps calculated from weekly 4DCT data to study how ventilation changed throughout radiation therapy. METHODS Quantitative maps representing ventilation were generated for six patients. Deformable registration was used to link corresponding lung volume elements between the inhale and exhale phases of the 4DCT dataset. Following spatial registration, corresponding Hounsfield units were input into a density-change-based model for quantifying the local ventilation. The ventilation data for all weeks were registered to the pretreatment ventilation image set. We quantitatively analyzed the data by defining regions of interest (ROIs) according to dose (V(20)) and lung lobe and by tracking the weekly ventilation of each ROI throughout treatment. The slope of the linear fit to the weekly ventilation data was used to evaluate the change in ventilation throughout treatment. A positive slope indicated an increase in ventilation, a negative slope indicated a decrease in ventilation, and a slope of 0 indicated no change. The dose ROI ventilation and slope data were used to study how ventilation changed throughout treatment as a function of dose. The lung lobe ROI ventilation data were used to study the impact of the presence of tumor on pretreatment ventilation. In addition, the lobe ROI data were used to study the impact of tumor reduction on ventilation change throughout treatment. RESULTS Using the dose ROI data, we found that three patients had an increase in weekly ventilation as a function of dose (slopes of 1.1, 1.4, and 1.5) and three patients had no change or a slight decrease in ventilation as a function of dose (slopes of 0.3, -0.6, -0.5). Visually, pretreatment ventilation appeared to be lower in the lobes that contained tumor. Pretreatment ventilation was 39% for lobes that contained tumor and 54% for lobes that did not contain tumor. The difference in ventilation between the two groups was statistically significant (p = 0.017). When the weekly lobe ventilation data were qualitatively observed, two distinct patterns emerged. When the tumor volume in a lobe was reduced, ventilation increased in the lobe. When the tumor volume was not reduced, the ventilation distribution did not change. The average slope of the group of lobes that contained tumors that shrank was 1.18, while the average slope of the group that did not contain tumors (or contained tumors that did not shrink) was -0.32. The slopes for the two groups were significantly different (p = 0.014). CONCLUSIONS We did not find a consistent pattern of ventilation change as a function of radiation dose. Pretreatment ventilation was significantly lower for lobes that contained tumor, due to occlusion of the central airway. The weekly lobe ventilation data indicated that when tumor volume shrinks, ventilation increases, and when the thoracic anatomy is not visibly changed, ventilation is likely to remain unchanged.

Predicting Radiation Pneumonitis After Stereotactic Ablative Radiation Therapy in Patients Previously Treated With Conventional Thoracic Radiation Therapy

PURPOSE To determine the incidence of and risk factors for radiation pneumonitis (RP) after stereotactic ablative radiation therapy (SABR) to the lung in patients who had previously undergone conventional thoracic radiation therapy. METHODS AND MATERIALS Seventy-two patients who had previously received conventionally fractionated radiation therapy to the thorax were treated with SABR (50 Gy in 4 fractions) for recurrent disease or secondary parenchymal lung cancer (T<4 cm, N0, M0, or Mx). Severe (grade≥3) RP and potential predictive factors were analyzed by univariate and multivariate logistic regression analyses. A scoring system was established to predict the risk of RP. RESULTS At a median follow-up time of 16 months after SABR (range, 4-56 months), 15 patients had severe RP (14 [18.9%] grade 3 and 1 [1.4%] grade 5) and 1 patient (1.4%) had a local recurrence. In univariate analyses, Eastern Cooperative Oncology Group performance status (ECOG PS) before SABR, forced expiratory volume in 1 second (FEV1), and previous planning target volume (PTV) location were associated with the incidence of severe RP. The V10 and mean lung dose (MLD) of the previous plan and the V10-V40 and MLD of the composite plan were also related to RP. Multivariate analysis revealed that ECOG PS scores of 2-3 before SABR (P=.009), FEV1≤65% before SABR (P=.012), V20≥30% of the composite plan (P=.021), and an initial PTV in the bilateral mediastinum (P=.025) were all associated with RP. CONCLUSIONS We found that severe RP was relatively common, occurring in 20.8% of patients, and could be predicted by an ECOG PS score of 2-3, an FEV1≤65%, a previous PTV spanning the bilateral mediastinum, and V20≥30% on composite (previous RT+SABR) plans. Prospective studies are needed to validate these predictors and the scoring system on which they are based.

Incorporating Single-nucleotide Polymorphisms Into the Lyman Model to Improve Prediction of Radiation Pneumonitis

PURPOSE To determine whether single-nucleotide polymorphisms (SNPs) in genes associated with DNA repair, cell cycle, transforming growth factor-β, tumor necrosis factor and receptor, folic acid metabolism, and angiogenesis can significantly improve the fit of the Lyman-Kutcher-Burman (LKB) normal-tissue complication probability (NTCP) model of radiation pneumonitis (RP) risk among patients with non-small cell lung cancer (NSCLC). METHODS AND MATERIALS Sixteen SNPs from 10 different genes (XRCC1, XRCC3, APEX1, MDM2, TGFβ, TNFα, TNFR, MTHFR, MTRR, and VEGF) were genotyped in 141 NSCLC patients treated with definitive radiation therapy, with or without chemotherapy. The LKB model was used to estimate the risk of severe (grade≥3) RP as a function of mean lung dose (MLD), with SNPs and patient smoking status incorporated into the model as dose-modifying factors. Multivariate analyses were performed by adding significant factors to the MLD model in a forward stepwise procedure, with significance assessed using the likelihood-ratio test. Bootstrap analyses were used to assess the reproducibility of results under variations in the data. RESULTS Five SNPs were selected for inclusion in the multivariate NTCP model based on MLD alone. SNPs associated with an increased risk of severe RP were in genes for TGFβ, VEGF, TNFα, XRCC1 and APEX1. With smoking status included in the multivariate model, the SNPs significantly associated with increased risk of RP were in genes for TGFβ, VEGF, and XRCC3. Bootstrap analyses selected a median of 4 SNPs per model fit, with the 6 genes listed above selected most often. CONCLUSIONS This study provides evidence that SNPs can significantly improve the predictive ability of the Lyman MLD model. With a small number of SNPs, it was possible to distinguish cohorts with >50% risk vs <10% risk of RP when they were exposed to high MLDs.

Comparing the accuracy of four-dimensional photon dose calculations with three-dimensional calculations using moving and deforming phantoms.

PURPOSE Four-dimensional (4D) dose calculation algorithms, which explicitly incorporate respiratory motion in the calculation of doses, have the potential to improve the accuracy of dose calculations in thoracic treatment planning; however, they generally require greater computing power and resources than currently used for three-dimensional (3D) dose calculations. The purpose of this work was to quantify the increase in accuracy of 4D dose calculations versus 3D dose calculations. METHODS The accuracy of each dose calculation algorithm was assessed using measurements made with two phantoms. Specifically, the authors used a rigid moving anthropomorphic thoracic phantom and an anthropomorphic thoracic phantom with a deformable lung insert. To incorporate a clinically relevant range of scenarios, they programed the phantoms to move and deform with two motion patterns: A sinusoidal motion pattern and an irregular motion pattern that was extracted from an actual patients breathing profile. For each combination of phantom and motion pattern, three plans were created: A single-beam plan, a multiple-beam plan, and an intensity-modulated radiation therapy plan. Doses were calculated using 4D dose calculation methods as well as conventional 3D dose calculation methods. The rigid moving and deforming phantoms were irradiated according to the three treatment plans and doses were measured using thermoluminescent dosimeters (TLDs) and radiochromic film. The accuracy of each dose calculation algorithm was assessed using measured-to-calculated TLD doses and a gamma analysis. RESULTS No significant differences were observed between the measured-to-calculated TLD ratios among 4D and 3D dose calculations. The gamma results revealed that 4D dose calculations had significantly greater percentage of pixels passing the 5%/3 mm criteria than 3D dose calculations. CONCLUSIONS These results indicate no significant differences in the accuracy between the 4D and the 3D dose calculation methods inside the gross tumor volume. On the other hand, the film results demonstrated that the 4D dose calculations provided greater accuracy than 3D dose calculations in heterogeneous dose regions. The increase in accuracy of the 4D dose calculations was evident throughout the planning target volume.

Comparison of 4-Dimensional Computed Tomography Ventilation With Nuclear Medicine Ventilation-Perfusion Imaging: A Clinical Validation Study

PURPOSE Four-dimensional computed tomography (4DCT) ventilation imaging provides lung function information for lung cancer patients undergoing radiation therapy. Before 4DCT-ventilation can be implemented clinically it needs to be validated against an established imaging modality. The purpose of this work was to compare 4DCT-ventilation to nuclear medicine ventilation, using clinically relevant global metrics and radiologist observations. METHODS AND MATERIALS Fifteen lung cancer patients with 16 sets of 4DCT and nuclear medicine ventilation-perfusion (VQ) images were used for the study. The VQ-ventilation images were acquired in planar mode using Tc-99m-labeled diethylenetriamine-pentaacetic acid aerosol inhalation. 4DCT data, spatial registration, and a density-change-based model were used to compute a 4DCT-based ventilation map for each patient. The percent ventilation was calculated in each lung and each lung third for both the 4DCT and VQ-ventilation scans. A nuclear medicine radiologist assessed the VQ and 4DCT scans for the presence of ventilation defects. The VQ and 4DCT-based images were compared using regional percent ventilation and radiologist clinical observations. RESULTS Individual patient examples demonstrate good qualitative agreement between the 4DCT and VQ-ventilation scans. The correlation coefficients were 0.68 and 0.45, using the percent ventilation in each individual lung and lung third, respectively. Using radiologist-noted presence of ventilation defects and receiver operating characteristic analysis, the sensitivity, specificity, and accuracy of the 4DCT-ventilation were 90%, 64%, and 81%, respectively. CONCLUSIONS The current work compared 4DCT with VQ-based ventilation using clinically relevant global metrics and radiologist observations. We found good agreement between the radiologists assessment of the 4DCT and VQ-ventilation images as well as the percent ventilation in each lung. The agreement lessened when the data were analyzed on a regional level. Our study presents an important step for the integration of 4DCT-ventilation into thoracic clinical practice.

Clinical Validation of 4-Dimensional Computed Tomography Ventilation With Pulmonary Function Test Data

PURPOSE A new form of functional imaging has been proposed in the form of 4-dimensional computed tomography (4DCT) ventilation. Because 4DCTs are acquired as part of routine care for lung cancer patients, calculating ventilation maps from 4DCTs provides spatial lung function information without added dosimetric or monetary cost to the patient. Before 4DCT-ventilation is implemented it needs to be clinically validated. Pulmonary function tests (PFTs) provide a clinically established way of evaluating lung function. The purpose of our work was to perform a clinical validation by comparing 4DCT-ventilation metrics with PFT data. METHODS AND MATERIALS Ninety-eight lung cancer patients with pretreatment 4DCT and PFT data were included in the study. Pulmonary function test metrics used to diagnose obstructive lung disease were recorded: forced expiratory volume in 1 second (FEV1) and FEV1/forced vital capacity. Four-dimensional CT data sets and spatial registration were used to compute 4DCT-ventilation images using a density change-based and a Jacobian-based model. The ventilation maps were reduced to single metrics intended to reflect the degree of ventilation obstruction. Specifically, we computed the coefficient of variation (SD/mean), ventilation V20 (volume of lung ≤20% ventilation), and correlated the ventilation metrics with PFT data. Regression analysis was used to determine whether 4DCT ventilation data could predict for normal versus abnormal lung function using PFT thresholds. RESULTS Correlation coefficients comparing 4DCT-ventilation with PFT data ranged from 0.63 to 0.72, with the best agreement between FEV1 and coefficient of variation. Four-dimensional CT ventilation metrics were able to significantly delineate between clinically normal versus abnormal PFT results. CONCLUSIONS Validation of 4DCT ventilation with clinically relevant metrics is essential. We demonstrate good global agreement between PFTs and 4DCT-ventilation, indicating that 4DCT-ventilation provides a reliable assessment of lung function. Four-dimensional CT ventilation enables exciting opportunities to assess lung function and create functional avoidance radiation therapy plans. The present work provides supporting evidence for the integration of 4DCT-ventilation into clinical trials.

Verification of four-dimensional photon dose calculations

Recent work in the area of thoracic treatment planning has been focused on trying to explicitly incorporate patient-specific organ motion in the calculation of dose. Four-dimensional (4D) dose calculation algorithms have been developed and incorporated in a research version of a commercial treatment planning system (Pinnacle3, Philips Medical Systems, Milpitas, CA). Before these 4D dose calculations can be used clinically, it is necessary to verify their accuracy with measurements. The primary purpose of this study therefore was to evaluate and validate the accuracy of a 4D dose calculation algorithm with phantom measurements. A secondary objective was to determine whether the performance of the 4D dose calculation algorithm varied between different motion patterns and treatment plans. Measurements were made using two phantoms: A rigid moving phantom and a deformable phantom. The rigid moving phantom consisted of an anthropomorphic thoracic phantom that rested on a programmable motion platform. The deformable phantom used the same anthropomorphic thoracic phantom with a deformable insert for one of the lungs. Two motion patterns were investigated for each phantom: A sinusoidal motion pattern and an irregular motion pattern extracted from a patient breathing profile. A single-beam plan, a multiple-beam plan, and an intensity-modulated radiation therapy plan were created. Doses were calculated in the treatment planning system using the 4D dose calculation algorithm. Then each plan was delivered to the phantoms and delivered doses were measured using thermoluminescent dosimeters (TLDs) and film. The measured doses were compared to the 4D-calculated doses using a measured-to-calculated TLD ratio and a gamma analysis. A relevant passing criteria (3% for the TLD and 5% /3 mm for the gamma metric) was applied to determine if the 4D dose calculations were accurate to within clinical standards. All the TLD measurements in both phantoms satisfied the passing criteria. Furthermore, 42 of the 48 evaluated films fulfilled the passing criteria. All films that did not pass the criteria were from the rigid phantom moving with irregular motion. The author concluded that if patient breathing is reproducible, the 4D dose calculations are accurate to within clinically acceptable standards. Furthermore, they found no statistically significant differences in the performance of the 4D dose calculation algorithm between treatment plans.

Investigation of the relationship between gross tumor volume location and pneumonitis rates using a large clinical database of non-small-cell lung cancer patients.

PURPOSE Studies have suggested that function may vary throughout the lung, and that patients who have tumors located in the base of the lung are more susceptible to radiation pneumonitis. The purpose of our study was to investigate the relationship between gross tumor volume (GTV) location and pneumonitis rates using a large clinical database of 547 patients with non-small-cell lung cancer. METHODS AND MATERIALS The GTV centroids of all patients were mapped onto one common coordinate system, in which the boundaries of the coordinate system were defined by the extreme points of each individual patient lung. The data were qualitatively analyzed by graphing all centroids and displaying the data according to the presence of severe pneumonitis, tumor stage, and smoking status. The centroids were grouped according to superior-inferior segments, and the pneumonitis rates were analyzed. In addition, we incorporated the GTV centroid information into a Lyman-Kutcher-Burman normal tissue complication probability model and tested whether adding spatial information significantly improved the fit of the model. RESULTS Of the 547 patients analyzed, 111 (20.3%) experienced severe radiation pneumonitis. The pneumonitis incidence rates were 16%, 23%, and 21% for the superior, middle, and inferior thirds of the lung, respectively. Qualitatively, the GTV centroids of nonsmokers were notably absent from the superior portion of the lung. In addition, the GTV centroids of patients who had Stage III and IV clinical staging were concentrated toward the medial edge of the lung. The comparison between the GTV centroid model and the conventional dose-volume model did not yield a statistically significant difference in model fit. CONCLUSIONS Lower pneumonitis rates were noted for the superior portion of the lung; however the differences were not statistically significant. For our patient cohort, incorporating GTV centroid information did not lead to a statistically significant improvement in the fit of the pneumonitis model.

A complete 4DCT-ventilation functional avoidance virtual trial: Developing strategies for prospective clinical trials

Introduction 4DCT‐ventilation is an exciting new imaging modality that uses 4DCT data to calculate lung‐function maps. Because 4DCTs are acquired as standard of care for lung cancer patients undergoing radiotherapy, 4DCT‐ventiltation provides functional information at no extra dosimetric or monetary cost to the patient. The development of clinical trials is underway to use 4DCT‐ventilation imaging to spare functional lung in patients undergoing radiotherapy. The purpose of this work was to perform a virtual trial using retrospective data to develop the practical aspects of a 4DCT‐ventilation functional avoidance clinical trial. Methods The study included 96 stage III lung cancer patients. A 4DCT‐ventilation map was calculated using the patients 4DCT‐imaging, deformable registration, and a density‐change‐based algorithm. Clinical trial inclusion assessment used quantitative and qualitative metrics based on the patients spatial ventilation profile. Clinical and functional plans were generated for 25 patients. The functional plan aimed to reduce dose to functional lung while meeting standard target and critical structure constraints. Standard and dose‐function metrics were compared between the clinical and functional plans. Results Our data showed that 69% and 59% of stage III patients have regional variability in function based on qualitative and quantitative metrics, respectively. Functional planning demonstrated an average reduction of 2.8 Gy (maximum 8.2 Gy) in the mean dose to functional lung. Conclusions Our work demonstrated that 60–70% of stage III patients would be eligible for functional planning and that a typical functional lung mean dose reduction of 2.8 Gy can be expected relative to standard clinical plans. These findings provide salient data for the development of functional clinical trials.