Feasibility of patient-specific quality assurance (PSQA) for real-time robotic stereotactic body radiotherapy (SBRT) based on tumor motion traces

PURPOSE

To design a patient specific quality assurance (PSQA) process for the CyberKnife Synchrony system and quantify its dosimetric accuracy using a motion platform driven by patient tumor traces with rotation.

METHODS

The CyberKnife Synchrony system was evaluated using a motion platform (MODUSQA) and a SRS MapCHECK phantom. The platform was programed to move in the superior-inferior (SI) direction based on tumor traces. The detector array housed by the StereoPhan was placed on the platform. Extra rotational angles in pitch (head down, 4.0° ± 0.15° or 1.2° ± 0.1°) were added to the moving phantom to examine robot capability of angle correction during delivery. A total of 15 Synchrony patients were performed SBRT PSQA on the moving phantom. All the results were benchmarked by the PSQA results based on static phantom.

RESULTS

For smaller pitch angles, the mean gamma passing rates were 99.75% ± 0.87%, 98.63% ± 2.05%, and 93.11% ± 5.52%, for 3%/1 mm, 2%/1 mm, and 1%/1 mm, respectively. Large discrepancy in the passing rates was observed for different pitch angles due to limited angle correction by the robot. For larger pitch angles, the corresponding mean passing rates were dropped to 93.00% ± 10.91%, 88.05% ± 14.93%, and 80.38% ± 17.40%. When comparing with the static phantom, no significant statistic difference was observed for smaller pitch angles (p = 0.1 for 3%/1 mm), whereas a larger statistic difference was observed for larger pitch angles (p < 0.02 for all criteria). All the gamma passing rates were improved, if applying shift and rotation correction.

CONCLUSIONS

The significance of this work is that it is the first study to benchmark PSQA for the CyberKnife Synchrony system using realistically moving phantoms with rotation. With reasonable delivery time, we found it may be feasible to perform PSQA for Synchrony patients with a realistic breathing pattern.

Incorporating functional lung imaging (FLI) into radiation therapy planning in patients with lung cancer: A systematic review and meta-analysis

PURPOSE

To provide an understanding of current FLI techniques, and their potential to improve dosimetry and outcomes for lung cancer patients receiving radiation therapy (RT).

METHODS

EMBASE, PubMed, and Cochrane Library were searched from 1990 until April 2023. Articles were included if they reported on FLI in one of: techniques, incorporation into RT planning for lung cancer, quantification of RT-related outcomes for lung cancer patients. Studies involving all RT modalities, including stereotactic body radiotherapy and particle therapy, were included. Meta-analyses were conducted to investigate differences in dose-function parameters between anatomical and functional RT planning techniques, as well as to investigate correlations of dose-function parameters with grade 2+ radiation pneumonitis (RP).

RESULTS

178 studies were included in the narrative synthesis. We report on FLI modalities, dose-response quantification, functional lung (FL) definitions, FL avoidance techniques, and correlations between FL irradiation and toxicity. Meta-analysis results show that FL avoidance planning gives statistically significant absolute reductions of 3.22% to the fraction of well-ventilated lung receiving 20 Gy or more (vent-fV20), 3.52% to the fraction of well-perfused lung receiving 20 Gy or more (perf-fV20), 1.3 Gy to the mean dose to the well-ventilated lung (vent-fMLD), and 2.41 Gy to the mean dose to the well-perfused lung (perf-fMLD). Increases in the threshold value for defining FL are associated with decreases in functional parameters. For intensity-modulated radiation therapy and volumetric modulated arc therapy, avoidance planning results in a 13% rate of grade 2+ RP, which seems reduced compared to results from conventional planning cohorts. A trend of increased predictive ability for grade 2+ RP was seen in models using FL information, but was not statistically significant.

CONCLUSIONS

FLI shows promise as a method to spare FL during thoracic RT, but interventional trials related to FL avoidance planning are sparse. Such trials are critical to understanding the impact of FL avoidance planning on toxicity reduction and patient outcomes.

Prospective trial of Functional Lung Avoidance Radiation Therapy for Lung Cancer: Quality of Life Report

PURPOSE

A novel form of lung function imaging has been developed that uses 4DCT data to generate lung ventilation images (4DCT-ventilation). Functional avoidance uses 4DCT-ventilation to reduce doses to functional lung with the aim of reducing pulmonary side-effects. A 4DCT-ventilation functional avoidance, phase II, multi-center clinical trial was completed. The purpose of this work is to quantify patient reported outcomes (PRO) changes for patients treated with functional avoidance and to determine which metrics are predictive of PRO changes.

MATERIALS AND METHODS

Patients with locally advanced lung cancer receiving curative intent radiotherapy were accrued. Each patient had a 4DCT-ventilation image generated using 4DCT data and image processing. PRO instruments included the Functional Assessment of Cancer Therapy-Lung (FACT-L) questionnaire, administered pre-treatment, 3, 6, and 12 months post-treatment. FACT-TOI (Trial Outcome Index) and the FACT-LCS (Lung Cancer Subscale) percentage of clinically meaningful declines (CMD) were determined. A linear mixed-effects model was used to determine which patient, clinical, dose, and dose-function metrics were predictive of PRO decline.

RESULTS

59 patients completed baseline PRO surveys. 83% of patients had non-small-cell lung cancer, with 75% having stage III disease. The median dose was 60 Gy in 30 fractions. CMD FACT-TOI decline was 46.3%, 38.5%, and 26.8%, at 3, 6, and 12 months, respectively. CMD FACT-LCS decline was 33.3%, 33.3%, and 29.3%, at 3, 6, and 12 months, respectively. While an increase in most dose and dose-function parameters was associated with a modest decline in PROs, none of the results were significant (all p>0.053).

CONCLUSION

The current work provides an innovative combination of functional avoidance and PROs and is the first report of PROs for patients treated with prospective 4DCT-ventilation functional avoidance. Approximately 30% of patients had clinically significant decline in PROs at 12 months. The study provides additional data on outcomes with 4DCT-ventilation functional avoidance.

Radiation Oncology Ransomware Attack Response Risk Analysis Using Failure Modes and Effects Analysis

PURPOSE

There have been numerous significant ransomware attacks impacting Radiation Oncology in the past 5 years. Research into ransomware attack response in Radiation Oncology has consisted of case reports and descriptive articles and has lacked quantitative studies. The purpose of this work was to identify the significant safety risks to patients being treated with radiation therapy during a ransomware attack scenario, using Failure Modes and Effects Analysis.

METHODS AND MATERIALS

A multi-institutional and multidisciplinary team conducted a Failure Modes and Effects Analysis by developing process maps and using Risk Priority Number (RPN) scores to quantify the increased likelihood of incidents in a ransomware attack scenario. The situation that was simulated was a ransomware attack that had removed the capability to access the Record and Verify (R&V) system. Five situations were considered: 1) a standard treatment of a patient with and without an R&V, 2) a standard treatment of a patient for the first fraction right after the R&V capabilities are disabled, and 3) 3 situations in which a plan modification was required. RPN scores were compared with and without R&V functionality.

RESULTS

The data indicate that RPN scores increased by 71% (range, 38%-96%) when R&V functionality is disabled compared with a nonransomware attack state where R&V functionality is available. The failure modes with the highest RPN in the simulated ransomware attack state included incorrectly identifying patients on treatment, incorrectly identifying where a patient is in their course of treatment, treating the incorrect patient, and incorrectly tracking delivered fractions.

CONCLUSIONS

The presented study quantifies the increased risk of incidents when treating in a ransomware attack state, identifies key failure modes that should be prioritized when preparing for a ransomware attack, and provides data that can be used to guide future ransomware resiliency research.

Novel Functional Radiomics for Prediction of Cardiac Positron Emission Tomography Avidity in Lung Cancer Radiotherapy

PURPOSE

Traditional methods of evaluating cardiotoxicity focus on radiation doses to the heart. Functional imaging has the potential to provide improved prediction for cardiotoxicity for patients with lung cancer. Fluorine-18 (18F) fluorodeoxyglucose (FDG)-positron emission tomography (PET)/computed tomography (CT) imaging is routinely obtained in a standard cancer staging workup. This work aimed to develop a radiomics model predicting clinical cardiac assessment using 18F-FDG PET/CT scans before thoracic radiation therapy.

METHODS

Pretreatment 18F-FDG PET/CT scans from three study populations (N = 100, N = 39, N = 70) were used, comprising two single-institutional protocols and one publicly available data set. A clinician (V.J.) classified the PET/CT scans per clinical cardiac guidelines as no uptake, diffuse uptake, or focal uptake. The heart was delineated, and 210 novel functional radiomics features were selected to classify cardiac FDG uptake patterns. Training data were divided into training (80%)/validation (20%) sets. Feature reduction was performed using the Wilcoxon test, hierarchical clustering, and recursive feature elimination. Ten-fold cross-validation was carried out for training, and the accuracy of the models to predict clinical cardiac assessment was reported.

RESULTS

From 202 of 209 scans, cardiac FDG uptake was scored as no uptake (39.6%), diffuse uptake (25.3%), and focal uptake (35.1%), respectively. Sixty-two independent radiomics features were reduced to nine clinically pertinent features. The best model showed 93% predictive accuracy in the training data set and 80% and 92% predictive accuracy in two external validation data sets.

CONCLUSION

This work used an extensive patient data set to develop a functional cardiac radiomic model from standard-of-care 18F-FDG PET/CT scans, showing good predictive accuracy. The radiomics model has the potential to provide an automated method to predict existing cardiac conditions and provide an early functional biomarker to identify patients at risk of developing cardiac complications after radiotherapy.

Clinical and Dosimetric Impact of 2D kV Motion Monitoring and Intervention in Liver Stereotactic Body Radiation Therapy

Purpose

Positional errors resulting from motion are a principal challenge across all disease sites in radiation therapy. This is particularly pertinent when treating lesions in the liver with stereotactic body radiation therapy (SBRT). To achieve dose escalation and margin reduction for liver SBRT, kV real-time imaging interventions may serve as a potential solution. In this study, we report results of a retrospective cohort of liver patients treated using real-time 2D kV-image guidance SBRT with emphasis on the impact of (1) clinical workflow, (2) treatment accuracy, and (3) tumor dose.

Methods and Materials

Data from 33 patients treated with 41 courses of liver SBRT were analyzed. During treatment, planar kV images orthogonal to the treatment beam were acquired to determine treatment interventions, namely treatment pauses (ie, adequacy of gating thresholds) or treatment shifts. Patients were shifted if internal markers were >3 mm, corresponding to the PTV margin used, from the expected reference condition. The frequency, duration, and nature of treatment interventions (ie, pause vs shift) were recorded, and the dosimetric impact associated with treatment shifts was estimated using a machine learning dosimetric model.

Results

Of all fractions delivered, 39% required intervention, which took on average 1.9 ± 1.6 minutes and occurred more frequently in treatments lasting longer than 7 minutes. The median realignment shift was 5.7 mm in size, and the effect of these shifts on minimum tumor dose in simulated clinical scenarios ranged from 0% to 50% of prescription dose per fraction.

Conclusion

Real-time kV-based imaging interventions for liver SBRT minimally affect clinical workflow and dosimetrically benefit patients. This potential solution for addressing positional errors from motion addresses concerns about target accuracy and may enable safe dose escalation and margin reduction in the context of liver SBRT.

Evaluation of a novel patient-specific quality assurance phantom for robotic single-isocentre, multiple-target stereotactic radiosurgery, and stereotactic radiotherapy

OBJECTIVES

To evaluate patient-specific quality assurance (PSQA) of 3 targets in a single delivery using a novel film-based phantom.

METHODS

The phantom was designed to rotate freely as a sphere and could measure 3 targets with film in a single delivery. After identifying the coordinates of 3 targets in the skull, the rotation angles about the equator and meridian were computed for optimal phantom setup, ensuring the film plane intersected the 3 targets. The plans were delivered on the CyberKnife system using fiducial tracking. The irradiated films were scanned and processed. All films were analysed using 3 gamma criteria.

RESULTS

Fifteen CyberKnife test plans with 3 different modalities were delivered on the phantom. Both automatic and marker-based registration methods were applied when registering the irradiated film and dose plane. Gamma analysis was performed using a 3%/1 mm, 2%/1 mm, and 1%/1 mm criteria with a 10% threshold. For the automatic registration method, the passing rates were 98.2% ± 1.9%, 94.2% ± 3.7%, and 80.9% ± 6.3%, respectively. For the marker-based registration approach, the passing rates were 96.4% ± 2.7%, 91.7% ± 4.3%, and 78.4% ± 6.2%, respectively.

CONCLUSIONS

A novel spherical phantom was evaluated for the CyberKnife system and achieved acceptable PSQA passing rates using TG218 recommendations. The phantom can measure true-composite dose and offers high-resolution results for PSQA, making it a valuable device for robotic radiosurgery.

ADVANCES IN KNOWLEDGE

This is the first study on PSQA of 3 targets concurrently on the CyberKnife system.

Systematic Evaluation of the Impact of Lung Segmentation Methods on 4-Dimensional Computed Tomography Ventilation Imaging Using a Large Patient Database

PURPOSE

A novel form of lung functional imaging applied for functional avoidance radiation therapy has been developed that uses 4-dimensional computed tomography (4DCT) data and image processing techniques to calculate lung ventilation (4DCT-ventilation). Lung segmentation is a common step to define a region of interest for 4DCT-ventilation generation. The purpose of this study was to quantitatively evaluate the sensitivity of 4DCT-ventilation imaging using different lung segmentation methods.

METHODS AND MATERIALS

The 4DCT data of 350 patients from 2 institutions were used. Lung contours were generated using 3 methods: (1) reference segmentations that removed airways and pulmonary vasculature manually (Lung-Manual), (2) standard lung contours used for planning (Lung-RadOnc), and (3) artificial intelligence (AI)-based contours that removed the airways and pulmonary vasculature (Lung-AI). The AI model was based on a residual 3-dimensional U-Net and was trained using the Lung-Manual contours of 279 patients. We compared the Lung-RadOnc or Lung-AI with Lung-Manual contours for the entire 4DCT-ventilation functional avoidance process including lung segmentation (surface Dice similarity coefficient [Surface DSC]), 4DCT-ventilation generation (correlation), and subanalysis of 10 patients on a dosimetric endpoint (percentage of high functional volume of lung receiving ≥20 Gy [fV20{%}]).

RESULTS

Surface DSC comparing Lung-Manual/Lung-RadOnc and Lung-Manual/Lung-AI contours was 0.40 ± 0.06 and 0.86 ± 0.04, respectively. The correlation between 4DCT-ventilation images generated with Lung-Manual/Lung-RadOnc and Lung-Manual/Lung-AI were 0.48 ± 0.14 and 0.85 ± 0.14, respectively. The difference in fV20[%] between 4DCT-ventilation generated with Lung-Manual/Lung-RadOnc and Lung-Manual/Lung-AI was 2.5% ± 4.1% and 0.3% ± 0.5%, respectively.

CONCLUSIONS

Our work showed that using standard planning lung contours can result in significantly variable 4DCT-ventilation images. The study demonstrated that AI-based segmentations generate lung contours and 4DCT-ventilation images that are similar to those generated using manual methods. The significance of the study is that it characterizes the lung segmentation sensitivity of the 4DCT-ventilation process and develops methods that can facilitate the integration of this novel imaging in busy clinics.

Novel Deep Learning Segmentation Models for Accurate GTV and OAR Segmentation in MR-Guided Adaptive Radiotherapy for Pancreatic Cancer Patients

PURPOSE/OBJECTIVE(S)

MR-guided adaptive radiotherapy (MRgART) improves target coverage and organ-at-risk (OAR) sparing in pancreatic cancer radiation therapy (RT). Inter-fractional changes in patients undergoing RT require time intensive re-delineation of gross tumor volume (GTV) and OARs prior to adaptive optimization. Accurate automatic segmentation has the potential to significantly improve efficiency of the adaptive workflow. We hypothesized that state-of-the-art deep learning (DL) segmentation models could adequately segment GTV and OARs in both planning and daily fractional MR scans.

MATERIALS/METHODS

The study included 21 patients with pancreatic cancer treated with MRgART (10 Gy x 5 fractions). The planning MR as well as all daily MR images and registrations were collected (6 image sets per patient and a total of 126 image sets). The planning MR and fraction 1-4 image sets were used as the training set (N = 105), while the test set (N = 21) comprised images for fraction 5, to simulate the last step of incremental learning from planning to final fraction. Evaluated contours included the GTV, Small Bowel, Large Bowel, Duodenum, Left and Right Kidney, Liver, Spinal Cord, and Stomach. To mimic clinical conditions, contour accuracy was evaluated within the ring structure surrounding the PTV, inside of which daily adaptive re-contouring is applied (2 cm expansion in the cradio-caudal direction, 3 cm expansion otherwise). We evaluated three DL model architectures: SegResNet, SegResNet 2D, and SwinUNETR to autosegment GTV and OARs. The segmentation models were trained on the training set using 5-fold cross-validation (CV) and quantitatively analyzed by comparing against clinically used contours with DICE scores. Qualitative analysis was performed by a radiation oncologist using a scoring scale: 1 = perfect, 2 = minor discrepancy, 3 = moderate discrepancy, and 4 = rejected.

RESULTS

Overall, the DL segmentations were in acceptable agreement with clinical contours. The best performing model was the SwinUNETR model with overall training DICE = 0.88±0.06, test DICE = 0.78±0.11, and qualitative score of 1.6±0.8. The agreement between the DL model and clinical segmentation for the GTV was 0.79±0.08, with a qualitative score of 2.2±0.9. The highest and lowest OAR DICE scores were for the Left Kidney (DICE = 0.93) and Small Bowel (DICE = 0.68), respectively. The highest qualitative OAR scores were for the Kidney, Liver, and Spinal Cord (score = 1.0) and the lowest qualitative score was for the Duodenum (score = 2.3) CONCLUSION: We report here the most comprehensive work on DL segmentation for pancreatic cancer MRgART, including quantitative and clinically-pertinent qualitative evaluations of 126 image sets and 3 DL architectures. Our data show good quantitative agreement between DL and clinical contours, and acceptable clinician evaluations for the majority of GTVs and OARs. The current work has great potential to significantly reduce a major bottleneck in the MRgART workflow for pancreatic cancer patients.

Comprehensive Quality of Life Report from a Prospective Clinical Trial of 4DCT-Ventilation Functional Lung Avoidance Radiation Therapy

PURPOSE/OBJECTIVE(S)

Functional imaging has been developed that uses 4DCT images and image processing to generate lung ventilation maps (4DCT-ventilation). 4DCT-ventilation functional avoidance uses 4DCT-images to generate plans that avoid functional regions of the lung with the goal of reducing pulmonary toxicity. A 4DCT-ventilation functional avoidance, phase II, multi-center clinical trial was completed, and patient reported outcomes (PRO) measured. PROs are an essential measure of quality-of-life following radiotherapy. The purpose of this work is to quantify PRO changes for lung cancer patients treated with functional avoidance and to compare PROs against clinical pneumonitis.

MATERIALS/METHODS

Patients with locally advanced lung cancer receiving curative intent radiotherapy (prescriptions of 45-75 Gy) and chemotherapy were accrued. Each patient had a 4DCT-ventilation image generated using 4DCT data. Favorable arc geometry and optimization techniques were used to generate functional avoidance plans. PRO instruments included the Functional Assessment of Cancer Therapy Lung (FACT-L) questionnaire and the Visual Analog Scale (VAS) administered pre-treatment and 3-, 6-, and 12-months post-treatment to gather data on physical, social, emotional, functional, and pulmonary well-being. The percentage of patients with clinically significant decline was calculated using the FACT-TOI (Trial Outcome Index), FACT-LCS (Lung Cancer Subscale), and VAS instruments. To evaluate the correlation between PROs and clinical toxicity, the percentage of clinically significant FACT-LCS decline was compared (Chi-square test) for patients who did or did not experience grade 2+ pneumonitis.

RESULTS

Fifty-nine patients completed baseline PRO surveys. Median age was 65, 83% of patients had non-small-cell lung cancer, with 75% having stage III disease. Clinically significant FACT-TOI decline at, 3, 6, and 12 months was 46.3%, 38.5%, and 26.8%, respectively. The percentage of patients with clinically significant FACT-LCS decline was 33.3%, 33.3%, and 29.3%, at 3 months, 6 months, and 12 months, respectively. The percentage of patients with clinically significant VAS decline at 3, 6, and 12 months was 18.9%, 20.0%, and 18.6%, respectively. Patients who experienced grade 2+ pneumonitis had a greater percentage of clinically significant decline at all time-points with the results reaching significance (p = 0.045) at 6 months.

CONCLUSION

The study presents the first comprehensive evaluation of PROs for patients treated with 4DCT-ventilation functional avoidance. The data show that 20-40% of patients had clinically significant decline and that PROs had a strong correlation with pneumonitis. The PRO data demonstrate that functional avoidance results in low rates of patient reported outcome clinical decline and provide seminal results to be used in phase III studies.

Novel Functional Radiomics for Prediction of Cardiac PET Avidity in Lung Cancer Radiotherapy

PURPOSE/OBJECTIVE(S)

Traditional methods of evaluating cardiotoxicity focus solely on radiation doses to the heart and do not incorporate functional imaging information. Functional imaging has great potential to improve the ability to provide early prediction for cardiotoxicity for lung cancer patients undergoing radiotherapy. FDG-based PET/CT imaging is routinely obtained as part of standard staging work up for lung cancer patients. Although FDG PET/CT scans are typically used to evaluate the tumor, imaging guidelines note that FDG PET/CT scans are an FDA-approved method to image for cardiac inflammation, and studies have noted that the PET cardiac signal can be predictive of clinical outcomes. The purpose of this work was to develop a radiomics model to predict clinical cardiac assessment of standard of care FDG PET/CT scans.

MATERIALS/METHODS

The study included 100 consecutive lung cancer patients treated with radiotherapy who underwent standard pre-treatment FDG-PET/CT staging scans. A clinician reviewed the PET/CT scans per clinical cardiac assessment guidelines and classified the cardiac uptake as: 0 = uniform diffuse, 1 = absent, 2 = heterogeneous, with event rates of 20%, 44%, and 35%, respectively. The heart was delineated and 200 novel functional radiomics features were selected to classify cardiac FDG uptake patterns. We divided the data into an 80% training set and a 20% test set to train and evaluate the classification models. Feature reduction was carried out using the Wilcoxon test (with Bonferroni adjusted p<0.05), hierarchical clustering, and Recursive Feature Elimination. Two automatic machine learning (AutoML) frameworks were used to determine classification models: a Random Forest Classifier (Tree-based Pipeline Optimization Tool, TPOT) and Linear Discriminant Analysis (AutoSklearn). 10-fold cross validation was carried out for training and the accuracy of the ability of the models to predict for clinical cardiac assessment is reported.

RESULTS

Fifty-one independent radiomics features were reduced to 3 clinically pertinent features (PET 2D Skewness, PET Grey Level Co-occurrence Matrix Correlation, and PET Median) using feature reduction techniques. The model selected by TPOT showed 89.8% predictive accuracy in the cross validation of the training set and 85% predictive accuracy on the test set. The model selected by AutoSklearn showed 89.7% predictive accuracy in the cross validation of the training set and 80% predictive accuracy on the test set.

CONCLUSION

The novelty of this work is that it is the first study to develop and evaluate functional cardiac radiomic features from standard of care FDG PET/CT scans with the data showing good predictive accuracy with clinical imaging evaluation. If validated, the current work provides automated methods to provide functional cardiac information using standard of care imaging that can be used as an imaging biomarker for early clinical toxicity prediction for lung cancer patients.

Evaluation of variables predicting PFT changes for lung cancer patients treated on a prospective 4DCT-ventilation functional avoidance clinical trial

PURPOSE

Functional avoidance radiotherapy uses functional imaging to reduce pulmonary toxicity by designing radiotherapy plans that reduce doses to functional regions of the lung. A phase-II, multi-center, prospective study of 4DCT-ventilation functional avoidance was completed. Pre and post-treatment pulmonary function tests (PFTs) were acquired and assessed pulmonary function change. This study aims to evaluate which clinical, dose and dose-function factors predict PFT changes for patients treated with 4DCT-ventilation functional avoidance radiotherapy.

MATERIALS AND METHODS

56 patients with locally advanced lung cancer receiving radiotherapy were accrued. PFTs were obtained at baseline and three months following radiotherapy and included forced expiratory volume in 1-second (FEV1), forced vital capacity (FVC), and FEV1/FVC. The ability of patient, clinical, dose (lung and heart), and dose-function metrics (metrics that combine dose and 4DCT-ventilation-based function) to predict PFT changes were evaluated using univariate and multivariate linear regression.

RESULTS

Univariate analysis showed that only dose-function metrics and the presence of chronic obstructive pulmonary disease (COPD) were significant (p<0.05) in predicting FEV1 decline. Multivariate analysis identified a combination of clinical (immunotherapy status, presence of thoracic comorbidities, smoking status, and age), along with lung dose, heart dose, and dose-function metrics in predicting FEV1 and FEV1/FVC changes.

CONCLUSION

The current work evaluated factors predicting PFT changes for patients treated in a prospective functional avoidance radiotherapy study. The data revealed that lung dose- function metrics could predict PFT changes, validating the significance of reducing the dose to the functional lung to mitigate the decline in pulmonary function and providing guidance for future clinical trials.

Phase 1 Dose Escalation Study of SBRT Using 3 Fractions for Locally Advanced Pancreatic Cancer

PURPOSE

The optimal dose and fractionation of stereotactic body radiation therapy (SBRT) for locally advanced pancreatic cancer (LAPC) have not been defined. Single-fraction SBRT was associated with more gastrointestinal toxicity, so 5-fraction regimens have become more commonly employed. We aimed to determine the safety and maximally tolerated dose of 3-fraction SBRT for LAPC.

METHODS AND MATERIALS

Two parallel phase 1 dose escalation trials were conducted from 2016 to 2019 at Memorial Sloan Kettering Cancer Center and University of Colorado. Patients with histologically confirmed LAPC without distant progression after at least 2 months of induction chemotherapy were eligible. Patients received 3-fraction linear accelerator-based SBRT at 3 dose levels, 27, 30, and 33 Gy, following a modified 3+3 design. Dose-limiting toxicity, defined as grade ≥3 gastrointestinal toxicity within 90 days, was scored by National Cancer Institute Common Terminology Criteria for Adverse Events, version 4. The secondary endpoints included cumulative incidence of local failure (LF) and distant metastasis (DM), as well as progression-free and overall survival PFS and OS, respectively, toxicity, and quality of life (QoL) using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (QLQ-C30) and the pancreatic cancer-specific QLQ-PAN26 questionnaire.

RESULTS

Twenty-four consecutive patients were enrolled (27 Gy: 9, 30 Gy: 8, 33 Gy: 7). The median (range) age was 67 (52-79) years, and 12 (50%) had a head/uncinate tumor location, with a median tumor size of 3.8 (1.1-11) cm and CA19-9 of 60 (1-4880) U/mL. All received chemotherapy for a median of 4 (1.4-10) months. There were no grade ≥3 toxicities. Two-year rates (95% confidence interval) of LF, DM, PFS, and OS were 31.7% (8.6%-54.8%), 70.2% (49.7%-90.8%), 20.8% (4.6%-37.1%), and 29.2% (11.0%-47.4%), respectively. Three- and 6-month QoL assessment showed no detriment.

CONCLUSIONS

For select patients with LAPC, dose escalation to 33 Gy in 3 fractions resulted in no dose-limiting toxicities, no detriments to QoL, and disease outcomes comparable with conventional RT. Further exploration of SBRT schemes to maximize tumor control while enabling efficient integration with systemic therapy is warranted.

Cardiac metabolic changes on 18 F-positron emission tomography after thoracic radiotherapy predict for overall survival in esophageal cancer patients

PURPOSE

Heart doses have been shown to be predictive of cardiac toxicity and overall survival (OS) for esophageal cancer patients. There is potential for functional imaging to provide valuable cardiac information. The purpose of this study was to evaluate the cardiac metabolic dose-response using 18 F-deoxyglucose (FDG)-PET and to assess whether standard uptake value (SUV) changes in the heart were predictive of OS.

METHODS

Fifty-one patients with esophageal cancer treated with radiation who underwent pre- and post-treatment FDG-PET scans were retrospectively evaluated. Pre- and post-treatment PET-scans were rigidly registered to the planning CT for each patient. Pre-treatment to post-treatment absolute mean SUV (SUVmean) changes in the heart were calculated to assess dose-response. A dose-response curve was generated by binning each voxel in the heart into 10 Gy dose-bins and analyzing the SUVmean changes in each dose-bin. Multivariate cox proportional hazard models were used to assess whether pre-to-post treatment cardiac SUVmean changes predicted for OS.

RESULTS

The cardiac dose-response curve demonstrated a trend of increasing cardiac SUV changes as a function of dose with an average increase of 0.044 SUV for every 10 Gy dose bin. In multivariate analysis, disease stage and SUVmean change in the heart were predictive (p < 0.05) for OS.

CONCLUSIONS

Changes in pre- to post-treatment cardiac SUV were predictive of OS with patients having a higher pre- to post-treatment cardiac SUV change surviving longer.

Characterizing Pulmonary Function Test Changes for Patients With Lung Cancer Treated on a 2-Institution, 4-Dimensional Computed Tomography-Ventilation Functional Avoidance Prospective Clinical Trial

Purpose

Four-dimensional computed tomography (4DCT)-ventilation-based functional avoidance uses 4DCT images to generate plans that avoid functional regions of the lung with the goal of reducing pulmonary toxic effects. A phase 2, multicenter, prospective study was completed to evaluate 4DCT-ventilation functional avoidance radiation therapy. The purpose of this study was to report the results for pretreatment to posttreatment pulmonary function test (PFT) changes for patients treated with functional avoidance radiation therapy.

Methods and Materials

Patients with locally advanced lung cancer receiving chemoradiation were accrued. Functional avoidance plans based on 4DCT-ventilation images were generated. PFTs were obtained at baseline and 3 months after chemoradiation. Differences for PFT metrics are reported, including diffusing capacity for carbon monoxide (DLCO), forced expiratory volume in 1 second (FEV1), and forced vital capacity (FVC). PFT metrics were compared for patients who did and did not experience grade 2 or higher pneumonitis.

Results

Fifty-six patients enrolled on the study had baseline and posttreatment PFTs evaluable for analysis. The mean change in DLCO, FEV1, and FVC was -11.6% ± 14.2%, -5.6% ± 16.9%, and -9.0% ± 20.1%, respectively. The mean change in DLCO was -15.4% ± 14.4% for patients with grade 2 or higher radiation pneumonitis and -10.8% ± 14.1% for patients with grade <2 radiation pneumonitis (P = .37). The mean change in FEV1 was -14.3% ± 22.1% for patients with grade 2 or higher radiation pneumonitis and -3.9% ± 15.4% for patients with grade <2 radiation pneumonitis (P = .09).

Conclusions

The current work is the first to quantitatively characterize PFT changes for patients with lung cancer treated on a prospective functional avoidance radiation therapy study. In comparison with patients treated with standard thoracic radiation planning, the data qualitatively show that functional avoidance resulted in less of a decline in DLCO and FEV1. The presented data can help elucidate the potential pulmonary function improvement with functional avoidance radiation therapy.

Is individual perfusion dose-response different than ventilation dose-response for lung cancer patients treated with radiotherapy?

OBJECTIVE

Current ventilation and perfusion dose-response studies focus on single-modalities (ventilation or perfusion) and perform pulmonary-toxicity assessment related to radiotherapy on a population-based basis. This study aims at quantitative and clinical evaluation of intrapatient differences between ventilation and perfusion dose-responses among lung cancer patients treated with radiotherapy.

METHODS

20 patients enrolled on a prospective functional avoidance protocol underwent single photon emission computed tomography-CT ventilation and perfusion scans pre- and post-radiotherapy. Relative changes in pre- to post-treatment ventilation and perfusion in lung regions receiving ≥20 Gy were calculated. In addition, the slopes of the linear fit to the relative ventilation and perfusion changes in regions receiving 0-60 Gy were calculated. A radiologist read and assigned a functional defect score to pre- and post-treatment ventilation/perfusion scans.

RESULTS

25% of patients had a difference >35% between ventilation and perfusion pre- to post-treatment changes and 20-30% of patients had opposite directions for ventilation and perfusion pre- to post-treatment changes. Using a semi-quantitative scale, radiologist assessment showed that 20% of patients had different pre- to post-treatment ventilation changes when compared to pre- to post-treatment perfusion changes.

CONCLUSION

Our data showed that ventilation dose-response can differ from perfusion dose-response for 20-30% of patients. Therefore, when performing thoracic dose-response in cancer patients, it is insufficient to look at ventilation or perfusion alone; but rather both modes of functional imaging may be needed when predicting for clinical outcomes.

ADVANCES IN KNOWLEDGE

The significance of this study can be highlighted by the differences between the intrapatient dose-response assessments of this analysis compared to existing population-based dose-response analyses. Elucidating intrapatient ventilation and perfusion dose-response differences may be valuable in predicting pulmonary toxicity in lung cancer patients post-radiotherapy.

Results of a Multi-Institutional Phase 2 Clinical Trial for 4DCT-Ventilation Functional Avoidance Thoracic Radiation Therapy

PURPOSE

Radiation pneumonitis remains a major limitation in the radiation therapy treatment of patients with lung cancer. Functional avoidance radiation therapy uses functional imaging to reduce pulmonary toxic effects by designing radiation therapy plans that reduce doses to functional regions of the lung. Lung functional imaging has been developed that uses 4-dimensional computed tomography (4DCT) imaging to calculate 4DCT-based lung ventilation (4DCT-ventilation). A phase 2 multicenter study was initiated to evaluate 4DCT-ventilation functional avoidance radiation therapy. The study hypothesis was that functional avoidance radiation therapy could reduce the rate of grade ≥2 radiation pneumonitis to 12% compared with a 25% historical rate, with the trial being positive if ≤16.4% of patients experienced grade ≥2 pneumonitis.

METHODS AND MATERIALS

Lung cancer patients receiving curative-intent radiation therapy (prescription doses of 45-75 Gy) and chemotherapy were accrued. Patient 4DCT scans were used to generate 4DCT-ventilation images. The 4DCT-ventilation images were used to generate functional avoidance plans that reduced doses to functional portions of the lung while delivering the prescribed tumor dose. Pneumonitis was evaluated by a clinician at 3, 6, and 12 months after radiation therapy.

RESULTS

Sixty-seven evaluable patients were accrued between April 2015 and December 2019. The median prescription dose was 60 Gy (range, 45-66 Gy) delivered in 30 fractions (range, 15-33 fractions). The average reduction in the functional volume of lung receiving ≥20 Gy with functional avoidance was 3.5% (range, 0%-12.8%). The median follow-up was 312 days. The rate of grade ≥2 radiation pneumonitis was 10 of 67 patients (14.9%; 95% upper CI, 24.0%), meeting the phase 2 criteria.

CONCLUSIONS

4DCT-ventilation offers an imaging modality that is convenient and provides functional imaging without an extra procedure necessary. This first report of a multicenter study of 4DCT-ventilation functional avoidance radiation therapy provided data showing that the trial met phase 2 criteria and that evaluation in a phase 3 study is warranted.

Clinical Evaluation of an Auto-Segmentation Tool for Spine SBRT Treatment

Purpose

Spine SBRT target delineation is time-consuming due to the complex bone structure. Recently, Elements SmartBrush Spine (ESS) was developed by Brainlab to automatically generate a clinical target volume (CTV) based on gross tumor volume (GTV). The aim of this project is to evaluate the accuracy and efficiency of ESS auto-segmentation.

Methods

Twenty spine SBRT patients with 21 target sites treated at our institution were used for this retrospective comparison study. Planning CT/MRI images and physician-drawn GTVs were inputs for ESS. ESS can automatically segment the vertebra, split the vertebra into 6 sectors, and generate a CTV based on the GTV location, according to the International Spine Radiosurgery Consortium (ISRC) Consensus guidelines. The auto-segmented CTV can be edited by including/excluding sectors of the vertebra, if necessary. The ESS-generated CTV contour was then compared to the clinically used CTV using qualitative and quantitative methods. The CTV contours were compared using visual assessment by the clinicians, relative volume differences (RVD), distance of center of mass (DCM), and three other common contour similarity measurements such as dice similarity coefficient (DICE), Hausdorff distance (HD), and 95% Hausdorff distance (HD95).

Results

Qualitatively, the study showed that ESS can segment vertebra more accurately and consistently than humans at normal curvature conditions. The accuracy of CTV delineation can be improved significantly if the auto-segmentation is used as the first step. Conversely, ESS may mistakenly split or join different vertebrae when large curvatures in anatomy exist. In this study, human interactions were needed in 7 of 21 cases to generate the final CTVs by including/excluding sectors of the vertebra. In 90% of cases, the RVD were within ±15%. The RVD, DCM, DICE, HD, and HD95 for the 21 cases were 3% ± 12%, 1.9 ± 1.5 mm, 0.86 ± 0.06, 13.34 ± 7.47 mm, and 4.67 ± 2.21 mm, respectively.

Conclusion

ESS can auto-segment a CTV quickly and accurately and has a good agreement with clinically used CTV. Inter-person variation and contouring time can be reduced with ESS. Physician editing is needed for some occasions. Our study supports the idea of using ESS as the first step for spine SBRT target delineation to improve the contouring consistency as well as to reduce the contouring time.

Association of pretreatment CA19-9 with survival after 3-fraction SBRT for locally advanced pancreatic cancer: Results from a phase I dose-escalation trial

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Background: The optimal dose and fractionation scheme for stereotactic body radiotherapy (SBRT) is unknown. The biologic effects of ultra-high doses per fraction (>8Gy) are theoretical, but may include eliciting an effect on the endothelial cells of the tumor vasculature which could improve treatment response. This study aimed to determine the safety and maximally tolerated dose of 3-fraction SBRT for locally advanced pancreatic cancer (LAPC). Methods: A multi-site phase 1 dose escalation trial was conducted from March 2016 to April 2019 at Memorial Sloan Kettering Cancer Center (NCT02643498) and University of Colorado (NCT02873598). Patients with localized histologically confirmed pancreatic adenocarcinoma deemed unresectable on multidisciplinary review without distant progression following induction chemotherapy for ≥ 2 months were eligible. Patients received 3-fraction LINAC-based SBRT at 3 dose levels, 27Gy, 30Gy and 33Gy following a modified 3+3 design, allowing for enrollment of additional patients at the last dose level during the 90-day observation period, provided no dose-limiting toxicities (DLTs) were observed. DLTs were defined as ≥ Grade 3 treatment-related GI toxicity within 90 days of RT by CTCAE v.4. The secondary endpoints were overall survival (OS), local progression-free and distant metastasis-free survival (LPFS and DMFS, respectively). Univariate analysis using log-rank test was performed to identify factors associated with OS. Results: Twenty-three evaluable patients were enrolled, including 8 patients at 27Gy, 8 patients at 30Gy and 7 patients at 33Gy. The median age was 67 years (range 52 - 79), 9 patients (39%) were male, all were stage IIIwith a median tumor size of 3.5cm (range, 1.0 - 6.4) and CA19-9 of 60U/mL (range, <1 - 4880). All received chemotherapy for a median of 4.0 months (range 2.5 -11.4). There were no grade ≥ 3 abdominal pain, dyspepsia, diarrhea, nausea, vomiting, or gastrointestinal hemorrhage. Four patients underwent resections (pancreaticoduodenectomy=3, Appleby=1). Twelve-month rates of OS, DMFS and LPFS were 45.8 %, 37.7% and 53.0%, respectively. On univariate analysis, CA19-9 (HR=0.2365, 95%CI 0.07999 to 0.6990), but not dose level, size, N stage, tumor location, duration of chemotherapy were associated with OS. Twelve-month OS for patients with CA19-9 ≤ 60U/mL vs > 60U/mL were 80% vs 27% (p=0.0023). Conclusions: For select LAPC patients, dose escalation to the target dose of 33Gy in 3 fractions resulted in no DLTs and disease outcomes comparable to conventional RT. Lower pre-SBRT CA19-9 values were associated with improved OS and could help identify patients most likely to benefit from local therapies. Continued exploration of (ultra)hypofractionated schemes to maximize tumor control while enabling efficient integration of RT with systemic therapy is warranted. Clinical trial information: NCT02643498/NCT02873598.

How to Respond to a Ransomware Attack? One Radiation Oncology Department's Response to a Cyber-Attack on Their Record and Verify System

The digitization of healthcare for patient safety and efficiency introduced third party networks into closed hospital systems increasing the probability of cyberattacks and their consequences(1). In April 2021, a major vendor of a Radiation Oncology (RO) record and verify system (RVS) suffered a ransomware attack, affecting our department and many others across the United States. This article summarizes our response to the ransomware event including workflows, team member roles, responsibilities, communications and departmental recovery. The RVS created or housed accurate patient dose records for 6 locations. The immediate response to the ransomware attack was to shut down the system including the ability to treat patients. With the utilization of the hospital EMR and pre-existing interfaces with RVS, the department was able to safely continue patient radiotherapy treatments innovatively utilizing a direct Digital Imaging and Communications in Medicine (DICOM) transfer of patient data to the linear accelerators and implementing paper charting. No patients were treated in the first 24 hours of the attack. Within 48 hours of the ransomware event, 50% of patients were treated, and within 1 week, 95% of all patients were treated using direct DICOM transfer and paper charts. The RVS was completely unavailable for 2.5 weeks and full functionality was not restored for 4.5 weeks. A phased approach was adopted for re-introduction of patient treatments back into the RVS. Human capital costs included communication, outreach, workflow creation, quality assurance and extended clinical hours. Key lessons learned were to have a back-up of essential information, employ 'dry run' emergency training, having consistent parameter requirements across different vendor hardware and software, and having a plan for the recovery effort of restoring normal operations once software is operational. The provided report presents valuable information for the development of cyber-attack preparedness for RO departments.

Characterizing spatial differences between SPECT-ventilation and SPECT-perfusion in patients with lung cancer undergoing radiotherapy

This study investigates agreement between ventilation and perfusion for lung cancer patients undergoing radiotherapy. Ventilation-perfusion scans of nineteen patients with stage III lung cancer from a prospective protocol were compared using voxel-wise Spearman correlation-coefficients. The presented results show in about 25% of patients, ventilation and perfusion exhibit lower agreement.

Functional avoidance-based intensity modulated proton therapy with 4DCT derived ventilation imaging for lung cancer

The primary objective is to evaluate the potential dosimetric gains of performing functional avoidance‐based proton treatment planning using 4DCT derived ventilation imaging. 4DCT data of 31 patients from a prospective functional avoidance clinical trial were evaluated with intensity modulated proton therapy (IMPT) plans and compared with clinical volumetric modulated arc therapy (VMAT) plans. Dosimetric parameters were compared between standard and functional plans with IMPT and VMAT with one‐way analysis of variance and post hoc paired student t‐test. Normal Tissue Complication Probability (NTCP) models were employed to estimate the risk of two toxicity endpoints for healthy lung tissues. Dose degradation due to proton motion interplay effect was evaluated. Functional IMPT plans led to significant dose reduction to functional lung structures when compared with functional VMAT without significant dose increase to Organ at Risk (OAR) structures. When interplay effect is considered, no significant dose degradation was observed for the OARs or the clinical target volume (CTV) volumes for functional IMPT. Using fV20 as the dose metric and Grade 2+ pneumonitis as toxicity endpoint, there is a mean 5.7% reduction in Grade 2+ RP with the functional IMPT and as high as 26% in reduction for individual patient when compared to the standard IMPT planning. Functional IMPT was able to spare healthy lung tissue to avoid excess dose to normal structures while maintaining satisfying target coverage. NTCP calculation also shows that the risk of pulmonary complications can be further reduced with functional based IMPT.

Quantifying pulmonary perfusion from noncontrast computed tomography

Purpose

Computed tomography (CT)‐derived ventilation methods compute respiratory induced volume changes as a surrogate for pulmonary ventilation. Currently, there are no known methods to derive perfusion information from noncontrast CT. We introduce a novel CT‐Perfusion (CT‐P) method for computing the magnitude mass changes apparent on dynamic noncontrast CT as a surrogate for pulmonary perfusion.

Methods

CT‐Perfusion is based on a mass conservation model which describes the unknown mass change as a linear combination of spatially corresponding inhale and exhale HU estimated voxel densities. CT‐P requires a deformable image registration (DIR) between the inhale/exhale lung CT pair, a preprocessing lung volume segmentation, and an estimate for the Jacobian of the DIR transformation. Given this information, the CT‐P image, which provides the magnitude mass change for each voxel within the lung volume, is formulated as the solution to a constrained linear least squares problem defined by a series of subregional mean magnitude mass change measurements. Similar to previous robust CT‐ventilation methods, the amount of uncertainty in a subregional sample mean measurement is related to measurement resolution and can be characterized with respect to a tolerance parameter τ. Spatial Spearman correlation between single photon emission CT perfusion (SPECT‐P) and the proposed CT‐P method was assessed in two patient cohorts via a parameter sweep of τ. The first cohort was comprised of 15 patients diagnosed with pulmonary embolism (PE) who had SPECT‐P and 4DCT imaging acquired within 24 h of PE diagnosis. The second cohort was comprised of 15 nonsmall cell lung cancer patients who had SPECT‐P and 4DCT images acquired prior to radiotherapy. For each test case, CT‐P images were computed for 30 different uncertainty parameter values, uniformly sampled from the range [0.01, 0.125], and the Spearman correlation between the SPECT‐P and the resulting CT‐P images were computed.

Results

The median correlations between CT‐P and SPECT‐P taken over all 30 test cases ranged between 0.49 and 0.57 across the parameter sweep. For the optimal tolerance τ = 0.0385, the CT‐P and SPECT‐P correlations across all 30 test cases ranged between 0.02 and 0.82. A one‐sample sign test was applied separately to the PE and lung cancer cohorts. A low Spearmen correlation of 15% was set as the null median value and two‐sided alternative was tested. The PE patients showed a median correlation of 0.57 (IQR = 0.305). One‐sample sign test was statistically significant with 96.5 % confidence interval: 0.20–0.63, P < 0.00001. Lung cancer patients had a median correlation of 0.57(IQR = 0.230). Again, a one‐sample sign test for median was statistically significant with 96.5 percent confidence interval: 0.45–0.71, P < 0.00001.

Conclusion

CT‐Perfusion is the first mechanistic model designed to quantify magnitude blood mass changes on noncontrast dynamic CT as a surrogate for pulmonary perfusion. While the reported correlations with SPECT‐P are promising, further investigation is required to determine the optimal CT acquisition protocol and numerical method implementation for CT‐P imaging.

Initial Data Pooling for Radiation Dose-Volume Tolerance for Carotid Artery Blowout and Other Bleeding Events in Hypofractionated Head and Neck Retreatments

PURPOSE

Dose-volume data for injury to carotid artery and other major vessels in stereotactic body radiation therapy (SBRT)/SABR head and neck reirradiation were reviewed, modeled, and summarized.

METHODS AND MATERIALS

A PubMed search of the English-language literature (stereotactic and carotid and radiation) in April 2018 found 238 major vessel maximum point doses in 6 articles that were pooled for logistic modeling. Two subsequent studies with dose-volume major vessel data were modeled separately for comparison. Attempts were made to separate carotid blowout syndrome from other bleeding events (BE) in the analysis, but we acknowledge that all except 1 data set has some element of BE interspersed.

RESULTS

Prior radiation therapy (RT) dose was not uniformly reported per patient in the studies included, but a course on the order of conventionally fractionated 70 Gy was considered for the purposes of the analysis (with an approximately ≥6-month estimated interval between prior and subsequent treatment in most cases). Factors likely associated with reduced risk of BE include nonconsecutive daily treatment, lower extent of circumferential tumor involvement around the vessel, and no surgical manipulation before or after SBRT.

CONCLUSIONS

Initial data pooling for reirradiation involving the carotid artery resulted in 3 preliminary models compared in this Hypofractionated Treatment Effects in the Clinic (HyTEC) report. More recent experiences with alternating fractionation schedules and additional risk-reduction strategies are also presented. Complications data for the most critical structures such as spinal cord and carotid artery are so limited that they cannot be viewed as strong conclusions of probability of risk, but rather, as a general guideline for consideration. There is a great need for better reporting standards as noted in the High Dose per Fraction, Hypofractionated Treatment Effects in the Clinic introductory paper.

Technical Note: On the spatial correlation between robust CT-ventilation methods and SPECT ventilation

Purpose

The computed tomography (CT)‐derived ventilation imaging methodology employs deformable image registration (DIR) to recover respiratory motion‐induced volume changes from an inhale/exhale CT image pair, as a surrogate for ventilation. The Integrated Jacobian Formulation (IJF) and Mass Conserving Volume Change (MCVC) numerical methods for volume change estimation represent two classes of ventilation methods, namely transformation based and intensity (Hounsfield Unit) based, respectively. Both the IJF and MCVC methods utilize subregional volume change measurements that satisfy a specified uncertainty tolerance. In previous publications, the ventilation images resulting from this numerical strategy demonstrated robustness to DIR variations. However, the reduced measurement uncertainty comes at the expense of measurement resolution. The purpose of this study was to examine the spatial correlation between robust CT‐ventilation images and single photon emission CT‐ventilation (SPECT‐V).

Methods

Previously described implementations of IJF and MCVC require the solution of a large scale, constrained linear least squares problem defined by a series of robust subregional volume change measurements. We introduce a simpler parameterized implementation that reduces the number of unknowns while increasing the number of data points in the resulting least squares problem. A parameter sweep of the measurement uncertainty tolerance, τ, was conducted using the 4DCT and SPECT‐V images acquired for 15 non‐small cell lung cancer patients prior to radiotherapy. For each test case, MCVC and IJF CT‐ventilation images were created for 30 different uncertainty parameter values, uniformly sampled from the range 0.01,0.25. Voxel‐wise Spearman correlation between the SPECT‐V and the resulting CT‐ventilation images was computed.

Results

The median correlations between MCVC and SPECT‐V ranged from 0.20 to 0.48 across the parameter sweep, while the median correlations for IJF and SPECT‐V ranged between 0.79 and 0.82. For the optimal IJF tolerance τ=0.07, the IJF and SPECT‐V correlations across all 15 test cases ranged between 0.12 and 0.90. For the optimal MCVC tolerance τ=0.03, the MCVC and SPECT‐V correlations across all 15 test cases ranged between −0.06 and 0.84.

Conclusion

The reported correlations indicate that robust methods generate ventilation images that are spatially consistent with SPECT‐V, with the transformation‐based IJF method yielding higher correlations than those previously reported in the literature. For both methods, overall correlations were found to marginally vary for τ∈[0.03,0.15], indicating that the clinical utility of both methods is robust to both uncertainty tolerance and DIR solution.

Evaluating Positron Emission Tomography-Based Functional Imaging Changes in the Heart After Chemo-Radiation for Patients With Lung Cancer

PURPOSE

Studies have noted a link between radiation dose to the heart and overall survival (OS) for patients with lung cancer treated with chemoradiation. The purpose of this study was to characterize pre- to posttreatment cardiac metabolic changes using fluorodeoxyglucose/positron emission tomography (FDG-PET) images and to evaluate whether changes in cardiac metabolism predict for OS.

METHODS AND MATERIALS

Thirty-nine patients enrolled in a functional avoidance prospective study who had undergone pre- and postchemoradiation FDG-PET imaging were evaluated. For each patient, the pretreatment and posttreatment PET/CTs were rigidly registered to the planning CT, dose, and structure set. PET-based metabolic dose-response was assessed by comparing pretreatment to posttreatment mean standardized uptake values (SUVmean) in the heart as a function of dose-bin. OS analysis was performed by comparing SUVmean changes for patients who were alive or had died at last follow-up and by using a multivariate model to assess whether pre- to posttreatment SUVmean changes were a predictor of OS.

RESULTS

The dose-response curve revealed increasing changes in SUV as a function of cardiac dose with an average SUVmean increase of 1.7% per 10 Gy. Patients were followed for a median of 437 days (range, 201-1131 days). SUVmean change was significantly predictive of OS on multivariate analysis with a hazard ratio of 0.541 (95% confidence intervals, 0.312-0.937). Patients alive at follow-up had an average increase of 17.2% in cardiac SUVmean while patients that died had an average decrease in SUVmean decrease of 13.5% (P = .048).

CONCLUSIONS

Our data demonstrated that posttreatment SUV changes in the heart were significant indicators of dose-response and predictors of OS. The present work is hypothesis generating and must be validated in an independent cohort. If validated, our data show the potential for cardiac metabolic changes to be an early predictor for clinical outcomes.

Robust HU-based CT ventilation from an integrated mass conservation formulation

Computed tomography (CT) ventilation algorithms estimate volume changes induced by respiratory motion. Existing Hounsfield Unit (HU) methods approximate volume change from the measured HU variations between spatially corresponding voxel locations within a temporally resolved CT image pair, assuming that volume changes are caused solely by changes in air content. Numerical implementations require a deformable image registration to determine the inhale/exhale spatial correspondence, a preprocessing lung volume segmentation, a preprocessing high-intensity vessel segmentation, and a post-processing smoothing applied to the raw volume change estimates obtained for each lung tissue voxel.

PURPOSE

We introduce the novel mass-conserving volume change (MCVC) method for estimating voxel volume changes from the HU values within an inhale/exhale CT image pair. MCVC is based on subregional volume change estimates that possess quantitatively characterized and controllable levels of uncertainty. MCVC is therefore robust to small variations in DIR solutions and the resulting ventilation images are overall more reproducible. In contrast to existing HU methods, MCVC does not require a preprocessing lung vessel segmentation or pre/post-processing Gaussian smoothing.

METHODS

Subregional volume change estimates are defined in terms of mean density ratios. As such, the corresponding uncertainty is characterized using Gaussian statistics and standard error analysis of the sample density means. A numerical solution is obtained from the MCVC formulation by solving a constrained linear least squares problem defined by a series of subregional volume change estimates. Reproducibility of the MCVC method with respect to DIR solution was assessed using expert-determined landmark point pairs and inhale/exhale phases from 10 four-dimensional CTs (4DCTs) available on www.dir-lab.com. MCVC was also compared to the robust Integrated Jacobian Formulation (IJF), a transformation-based ventilation method.

RESULTS

The ten Dir-Lab 4DCT cases were registered twice with the same DIR algorithm, but using different degrees of freedom (DIR 1 and DIR 2). Standard HU ventilation (HUV) and MCVC ventilation images were computed for both solutions. The average spatial errors (300 landmarks per case) for DIR 1 ranged between 0.74 and 1.50 mm, whereas for DIR 2 they ranged between 0.68 and 1.18 mm. Despite the differences in spatial errors between the two DIR solutions, the average Pearson correlation between the corresponding HUV images was 0.94 (0.03), while for the MCVC images it was 1.00 (0.00). The average correlation between MCVC and IJF ventilation over the ten test cases was 0.81 (0.14), whereas for HUV and IJF it was 0.56 (1.11).

CONCLUSION

While HUV is robust to DIR solution, its implementation depends on heuristic Gaussian smoothing and vessel segmentation. MCVC is based on subregional volume change measurements with quantifiable and controllable levels of uncertainty. The subregional approach eliminates the need for Gaussian smoothing and lung vasculature segmentation. Numerical experiments are consistent with the underlying mathematical theory and indicate that MCVC ventilation is more reproducible with respect to DIR algorithm than standard HU methods. MCVC results are also more consistent with the robust IJF method, which suggests that incorporating robustness leads to more consistent results across both DIRs and ventilation algorithms.

Quantifying Allowable Motion to Achieve Safe Dose Escalation in Pancreatic SBRT

PURPOSE

Tumor motion plays a key role in the safe delivery of stereotactic body radiation therapy (SBRT) for pancreatic cancer. The purpose of this study was to use tumor motion measured in patients to establish limits on motion magnitude for safe delivery of pancreatic SBRT and to help guide motion-management decisions in potential dose-escalation scenarios.

METHODS AND MATERIALS

Using 91 sets of pancreatic tumor motion data, we calculated the motion-convolved dose of the gross tumor volume, duodenum, and stomach for 25 patients with pancreatic cancer. We derived simple linear or quadratic models relating motion to changes in dose and used these models to establish the maximum amount of motion allowable while satisfying error thresholds on key dose metrics. In the same way, we studied the effects of dose escalation and tumor volume on allowable motion.

RESULTS

In our patient cohort, the mean (range) allowable motion for 33, 40, and 50 Gy to the planning target volume was 11.9 (6.3-22.4), 10.4 (5.2-19.1), and 9.0 (4.2-16.0) mm, respectively. The maximum allowable motion decreased as the dose was escalated and was smaller in patients with larger tumors. We found significant differences in allowable motion between the different plans, suggesting a patient-specific approach to motion management is possible.

CONCLUSIONS

The effects of motion on pancreatic SBRT are highly variable among patients, and there is potential to allow more motion in certain patients, even in dose-escalated scenarios. In our dataset, a conservative limit of 6.3 mm would ensure safe treatment of all patients treated to 33 Gy in 5 fractions.

Objective assessment of the effects of tumor motion in radiation therapy

PURPOSE

Internal organ motion reduces the accuracy and efficacy of radiation therapy. However, there is a lack of tools to objectively (based on a medical or scientific task) assess the dosimetric consequences of motion, especially on an individual basis. We propose to use therapy operating characteristic (TOC) analysis to quantify the effects of motion on treatment efficacy for individual patients. We demonstrate the application of this tool with pancreatic stereotactic body radiation therapy (SBRT) clinical data and explore the origin of motion sensitivity.

METHODS

The technique is described as follows. (a) Use tumor-motion data measured from patients to calculate the motion-convolved dose of the gross tumor volume (GTV) and the organs at risk (OARs). (b) Calculate tumor control probability (TCP) and normal tissue complication probability (NTCP) from the motion-convolved dose-volume histograms. (c) Construct TOC curves from TCP and NTCP models. (d) Calculate the area under the TOC curve (AUTOC) and use it as a figure of merit for treatment efficacy. We used tumor motion data measured from patients to calculate the relation between AUTOC and motion magnitude for 25 pancreatic SBRT treatment plans. Furthermore, to explore the driving factor of motion sensitivity of a given plan, we compared the dose distribution of motion-sensitive plans and motion-robust plans and studied the dependence of motion sensitivity to motion directions.

RESULTS

Our technique is able to recognize treatment plans that are sensitive to motion. Under the presence of motion, the treatment efficacy of some plans changes from providing high tumor control and low risks of complications to providing no tumor control and high risks of side effects. Several treatment plans experience falloffs in AUTOC at a smaller magnitude of motion than other plans. In our dataset, a potential indicator of a motion-sensitive treatment plan is that the duodenum is in proximity to the tumor in the SI direction.

CONCLUSIONS

The TOC framework can serve as a tool to quantify the effects of internal organ motion in radiation therapy. With pancreatic SBRT clinical data, we applied this tool to study the change in treatment efficacy induced by motion for individual treatment plans. This framework could potentially be used clinically to understand the effects of motion in an individual patient and to design a patient-specific motion management plan. This framework could also be used in research to evaluate different components of the treatment process, such as motion-management techniques, treatment-planning algorithms, and treatment margins.

CT-based ventilation imaging in radiation oncology

A form of lung function imaging is emerging that uses phase-resolved four-dimensional CT (4DCT or breath-hold CT) images along with image processing techniques to generate lung function maps that provide a surrogate of lung ventilation. CT-based ventilation (referred to as CT-ventilation) research has gained momentum in Radiation Oncology because many lung cancer patients undergo four-dimensional CT simulation as part of the standard treatment planning process. Therefore, generating CT-ventilation images provides functional information without burdening the patient with an extra imaging procedure. CT-ventilation has progressed from an image processing calculation methodology, to validation efforts, to retrospective demonstration of clinical utility in Radiation Oncology. In particular, CT-ventilation has been proposed for two main clinical applications: functional avoidance radiation therapy and thoracic dose-response assessment. The idea of functional avoidance radiation therapy is to preferentially spare functional portions of the lung (as measured by CT-ventilation) during radiation therapy with the hypothesis that reducing dose to functional portions of the lung will lead to reduced rates of radiation-related thoracic toxicity. The idea of imaging-based dose-response assessment is to evaluate pre- to post-treatment CT-ventilation-based imaging changes. The hypothesis is that early, imaging-change-based response can be an early predictor of subsequent thoracic toxicity. Based on the retrospective evidence, the clinical applications of CT-ventilation have progressed from the retrospective setting to on-going prospective clinical trials. This review will cover basic CT-ventilation calculation methodologies, validation efforts, presentation of clinical applications, summarize on-going clinical trials, review potential uncertainties and shortcomings of CT-ventilation, and discuss future directions of CT-ventilation research.

Robust CT ventilation from the integral formulation of the Jacobian

Computed tomography (CT) derived ventilation algorithms estimate the apparent voxel volume changes within an inhale/exhale CT image pair. Transformation‐based methods compute these estimates solely from the spatial transformation acquired by applying a deformable image registration (DIR) algorithm to the image pair. However, approaches based on finite difference approximations of the transformation's Jacobian have been shown to be numerically unstable. As a result, transformation‐based CT ventilation is poorly reproducible with respect to both DIR algorithm and CT acquisition method.

Purpose

We introduce a novel Integrated Jacobian Formulation (IJF) method for estimating voxel volume changes under a DIR‐recovered spatial transformation. The method is based on computing volume estimates of DIR mapped subregions using the hit‐or‐miss sampling algorithm for integral approximation. The novel approach allows for regional volume change estimates that (a) respect the resolution of the digital grid and (b) are based on approximations with quantitatively characterized and controllable levels of uncertainty. As such, the IJF method is designed to be robust to variations in DIR solutions and thus overall more reproducible.

Methods

Numerically, Jacobian estimates are recovered by solving a simple constrained linear least squares problem that guarantees the recovered global volume change is equal to the global volume change obtained from the inhale and exhale lung segmentation masks. Reproducibility of the IJF method with respect to DIR solution was assessed using the expert‐determined landmark point pairs and inhale/exhale phases from 10 four‐dimensional computed tomographies (4DCTs) available on http://www.dir-lab.com. Reproducibility with respect to CT acquisition was assessed on the 4DCT and 4D cone beam CT (4DCBCT) images acquired for five lung cancer patients prior to radiotherapy.

Results

The ten Dir‐Lab 4DCT cases were registered twice with the same DIR algorithm, but with different smoothing parameter. Finite difference Jacobian (FDJ) and IFJ images were computed for both solutions. The average spatial errors (300 landmarks per case) for the two DIR solution methods were 0.98 (1.10) and 1.02 (1.11). The average Pearson correlation between the FDJ images computed from the two DIR solutions was 0.83 (0.03), while for the IJF images it was 1.00 (0.00). For intermodality assessment, the IJF and FDJ images were computed from the 4DCT and 4DCBCT of five patients. The average Pearson correlation of the spatially aligned FDJ images was 0.27 (0.11), while it was 0.77 (0.13) for the IFJ method.

Conclusion

The mathematical theory underpinning the IJF method allows for the generation of ventilation images that are (a) computed with respect to DIR spatial accuracy on the digital voxel grid and (b) based on DIR‐measured subregional volume change estimates acquired with quantifiable and controllable levels of uncertainty. Analyses of the experiments are consistent with the mathematical theory and indicate that IJF ventilation imaging has a higher reproducibility with respect to both DIR algorithm and CT acquisition method, in comparison to the standard finite difference approach.

Technical Note: Deriving ventilation imaging from 4DCT by deep convolutional neural network

PURPOSE

Ventilation images can be derived from four-dimensional computed tomography (4DCT) by analyzing the change in HU values and deformable vector fields between different respiration phases of computed tomography (CT). As deformable image registration (DIR) is involved, accuracy of 4DCT-derived ventilation image is sensitive to the choice of DIR algorithms. To overcome the uncertainty associated with DIR, we develop a method based on deep convolutional neural network (CNN) to derive ventilation images directly from the 4DCT without explicit image registration.

METHODS

A total of 82 sets of 4DCT and ventilation images from patients with lung cancer were used in this study. In the proposed CNN architecture, the CT two-channel input data consist of CT at the end of exhale and the end of inhale phases. The first convolutional layer has 32 different kernels of size 5 × 5 × 5, followed by another eight convolutional layers each of which is equipped with an activation layer (ReLU). The loss function is the mean-squared-error (MSE) to measure the intensity difference between the predicted and reference ventilation images.

RESULTS

The predicted images were comparable to the label images of the test data. The similarity index, correlation coefficient, and Gamma index passing rate averaged over the tenfold cross validation were 0.880 ± 0.035, 0.874 ± 0.024, and 0.806 ± 0.014, respectively.

CONCLUSIONS

The results demonstrate that deep CNN can generate ventilation imaging from 4DCT without explicit deformable image registration, reducing the associated uncertainty.

Interim Analysis of a Two-Institution, Prospective Clinical Trial of 4DCT-Ventilation-based Functional Avoidance Radiation Therapy

PURPOSE

Functional imaging has been proposed that uses 4DCT images to calculate 4DCT-based lung ventilation (4DCT-ventilation). We have started a 2-institution, phase 2 prospective trial evaluating the feasibility, safety, and preliminary efficacy of 4DCT-ventilation functional avoidance. The trial hypothesis is that the rate of grade ≥2 radiation pneumonitis could be reduced to 12% with functional avoidance, compared with a 25% rate of pneumonitis with a historical control. The trial employed a Simon 2-stage design with a planned futility analysis after 17 evaluable patients. The purpose of this work is to present the trial design and implementation, dosimetric data, and clinical results for the planned futility analysis.

METHODS AND MATERIALS

Eligible patients were patients with lung cancer who were prescribed doses of 45 to 75 Gy. For each patient, the 4DCT data were used to generate a 4DCT-ventilation image using the Hounsfield unit technique along with a compressible flow-based image registration algorithm. Two intensity modulated radiation therapy treatment plans were generated: (1) a standard lung plan and (2) a functional avoidance treatment plan that aimed to reduce dose to functional lung while meeting target and normal tissue constraints. Patients were treated with the functional avoidance plan and evaluated for thoracic toxicity (presented as rate and 95% confidence intervals [CI]) with a 1-year follow-up.

RESULTS

The V20 to functional lung was 21.6% ± 9.5% (mean ± standard deviation) with functional avoidance, representing a decrease of 3.2% (P < .01) relative to standard, nonfunctional treatment plans. The rates of grade ≥2 and grade ≥3 radiation pneumonitis were 17.6% (95% CI, 3.8%-43.4%) and 5.9% (95% CI, 0.1%-28.7%), respectively.

CONCLUSIONS

Dosimetrically, functional avoidance achieved reduction in doses to functional lung while meeting target and organ at risk constraints. On the basis of Simon's 2-stage design and the 17.6% grade ≥2 pneumonitis rate, the trial met its futility criteria and has continued accrual.

Implementation and operation of incident learning across a newly-created health system

PURPOSE

The purpose of this work is to describe our experience launching an expanded incident learning system for patient safety and quality that takes into account aspects beyond therapeutic dose delivery, specifically imaging/simulation incidents, medical care incidents, and operational issues.

METHODS

Our ILS was designed for a newly created health system comprised of a midsized academic hospital and two smaller community hospitals. The main design goal was to create a highly sensitive system to capture as much information throughout the department as possible. Reports were classified according to incidents and near misses involving therapeutic radiation, imaging/simulation, and patient care (not involving radiation), unsafe conditions, operational issues, and accolades/suggestions. Reports were analyzed according to impact on various steps in the process of care. Actions made in response to reports were assessed and characterized by intervention reliability.

RESULTS

A total of 1125 reports were submitted in the first 23 months. For all three departments, therapeutic radiation incidents and near misses consisted of less than one-third of all reports submitted. For the midsized academic department, operational issues and unsafe conditions comprised the largest percentage of reports (70%). Although the majority of reports impacted steps related to the technical aspects of treatment (simulation, planning, and treatment delivery), 20% impacted other steps such as scheduling or clinic visits. More than 160 actions were performed in response to reports. Of these actions, 63 were quality improvement interventions to improve practices, while 97 were learning actions for raising awareness.

CONCLUSIONS

We have developed an ILS that identifies issues related to the entire process of care delivery in radiation oncology, as evidenced by frequent and varied reported events. By identifying a broad spectrum of issues in a department, opportunities for improvement can be identified.

Using 4DCT-ventilation to characterize lung function changes for pediatric patients getting thoracic radiotherapy

PURPOSE

A form of lung functional imaging has been developed that uses 4DCT data to calculate ventilation (4DCT-ventilation). Because 4DCTs are acquired as standard-of-care to manage breathing motion during radiotherapy, 4DCT-ventilation provides functional information at no extra dosimetric or monetary cost. 4DCT-ventilation has yet to be described in children. 4DCT-ventilation can be used as a tool to help assess post-treatment lung function and predict for future clinical thoracic toxicities for pediatric patients receiving radiotherapy to the chest. The purpose of this work was to perform a preliminary evaluation of 4DCT-ventilation-based lung function changes for pediatric patients receiving radiotherapy to the lungs.

METHODS

The study used four patients with pre and postradiotherapy 4DCTs. The 4DCTs, deformable image registration, and a density-change-based algorithm were used to compute pre and post-treatment 4DCT-ventilation images. The post-treatment 4DCT-ventilation images were compared to the pretreatment 4DCT-ventilation images for a global lung response and for an intrapatient dose-response (providing an assessment for dose-dependent regional dose-response).

RESULTS

For three of the four patients, a global ventilation decline of 7-37% was observed, while one patient did not demonstrate a global functional decline. Dose-response analysis did not reveal an intrapatient dose-response from 0 to 20 Gy for three patients while one patient demonstrated increased 4DCT-ventilation decline as a function of increasing lung doses up to 50 Gy.

CONCLUSIONS

Compared to adults, pediatric patients have unique lung function, dosimetric, and toxicity profiles. The presented work is the first to evaluate spatial lung function changes in pediatric patients using 4DCT-ventilation and showed lung function changes for three of the four patients. The early changes demonstrated with lung function imaging warrant further longitudinal work to determine whether the imaging-based early changes can be predicted for long-term clinical toxicity.

Functional-guided radiotherapy using knowledge-based planning

BACKGROUND AND PURPOSE

There are two significant challenges when implementing functional-guided radiotherapy using 4DCT-ventilation imaging: (1) lack of knowledge of realistic patient specific dosimetric goals for functional lung and (2) ensuring consistent plan quality across multiple planners. Knowledge-based planning (KBP) is positioned to address both concerns.

MATERIAL AND METHODS

A KBP model was created from 30 previously planned functional-guided lung patients. Standard organs at risk (OAR) in lung radiotherapy and a ventilation contour delineating areas of high ventilation were included. Model validation compared dose-metrics to standard OARs and functional dose-metrics from 20 independent cases that were planned with and without KBP.

RESULTS

A significant improvement was observed for KBP optimized plans in V20Gy and mean dose to functional lung (p = 0.005 and 0.001, respectively), V20Gy and mean dose to total lung minus GTV (p = 0.002 and 0.01, respectively), and mean doses to esophagus (p = 0.005).

CONCLUSION

The current work developed a KBP model for functional-guided radiotherapy. Modest, but statistically significant, improvements were observed in functional lung and total lung doses.

Head and Neck Tumor Control Probability: Radiation Dose-Volume Effects in Stereotactic Body Radiation Therapy for Locally Recurrent Previously-Irradiated Head and Neck Cancer: Report of the AAPM Working Group

PURPOSE

Stereotactic body radiation therapy (SBRT) has emerged as a viable reirradiation strategy for locally recurrent previously-irradiated head and neck cancer. Doses in the literature have varied, which challenges clinical application of SBRT as well as clinical trial design.

MATERIAL & METHODS

A working group was formed through the American Association of Physicists in Medicine to study tumor control probabilities for SBRT in head and neck cancer. We herein present a systematic review of the available literature addressing the dose/volume data for tumor control probability with SBRT in patients with locally recurrent previously-irradiated head and neck cancer. Dose-response models are generated that present tumor control probability as a function of dose.

RESULTS

Data from more than 300 cases in 8 publications suggest that there is a dose-response relationship, with superior local control and possibly improved overall survival for doses of 35 to 45 Gy (in 5 fractions) compared with <30 Gy.

CONCLUSION

Stereotactic body radiation therapy doses equivalent to 5-fraction doses of 40 to 50 Gy are suggested for retreatment.