Incorporation of functional status into dose-volume analysis

AAPM Task Group Report 267: A joint AAPM GEC-ESTRO report on biophysical models and tools for the planning and evaluation of brachytherapy

Brachytherapy utilizes a multitude of radioactive sources and treatment techniques that often exhibit widely different spatial and temporal dose delivery patterns. Biophysical models, capable of modeling the key interacting effects of dose delivery patterns with the underlying cellular processes of the irradiated tissues, can be a potentially useful tool for elucidating the radiobiological effects of complex brachytherapy dose delivery patterns and for comparing their relative clinical effectiveness. While the biophysical models have been used largely in research settings by experts, it has also been used increasingly by clinical medical physicists over the last two decades. A good understanding of the potentials and limitations of the biophysical models and their intended use is critically important in the widespread use of these models. To facilitate meaningful and consistent use of biophysical models in brachytherapy, Task Group 267 (TG-267) was formed jointly with the American Association of Physics in Medicine (AAPM) and The Groupe Européen de Curiethérapie and the European Society for Radiotherapy & Oncology (GEC-ESTRO) to review the existing biophysical models, model parameters, and their use in selected brachytherapy modalities and to develop practice guidelines for clinical medical physicists regarding the selection, use, and interpretation of biophysical models. The report provides an overview of the clinical background and the rationale for the development of biophysical models in radiation oncology and, particularly, in brachytherapy; a summary of the results of literature review of the existing biophysical models that have been used in brachytherapy; a focused discussion of the applications of relevant biophysical models for five selected brachytherapy modalities; and the task group recommendations on the use, reporting, and implementation of biophysical models for brachytherapy treatment planning and evaluation. The report concludes with discussions on the challenges and opportunities in using biophysical models for brachytherapy and with an outlook for future developments.

Four-dimensional computed tomography-based ventilation imaging in intensity-modulated radiation therapy treatment planning for pulmonary functional avoidance

PURPOSE

To incorporate four-dimensional computed tomography (4DCT)-based ventilation imaging into intensity-modulated radiation therapy (IMRT) treatment planning for pulmonary functional avoidance.

METHODS AND MATERIALS

Nineteen locally advanced lung cancer patients are retrospectively studied. 4DCT images are employed to create ventilation maps for each patient via a density-change-based algorithm with mass correction. The regional ventilation is directly incorporated into the mathematical formulation of a direct aperture optimization model in IMRT treatment planning to achieve functional avoidance and a voxel-based treatment plan. The proposed functional avoidance planning and voxel-based planning are compared to the conventional treatment planning approach purely based on the anatomy of patients. Paired sample t-tests are conducted to see whether dosimetric differences among the three approaches are significant.

RESULTS

Similar planning target volume (PTV) coverage is achieved by anatomical, functional avoidance, and voxel-based approaches. The voxel-based treatment planning performs better than both functional avoidance and anatomical planning to the lung. For a total lung, the average volume reductions in a functional avoidance plan from an anatomical plan, a voxel-based plan from an anatomical plan, and a voxel-based plan from a functional avoidance plan are 7.0% , 16.8%, and 10.6%, respectively for V₄₀ ; and 0.4%, 6.4%, and 6.0%, respectively for mean Lung Dose (MLD). For a functional lung, the reductions are 8.8% , 17.2%, and 9.2%, respectively, for fV₄₀ ; and 1.1%, 6.2%, and 5.2%, respectively, for functional mean lung dose (fMLD). These reductions are obtained without significantly increasing doses to other organs-at-risk. All the pairwise treatment planning comparisons for both total lung and functional lung are statistically significant (p-value < α = 0.05 $&lt; \alpha =0.05$ ) except for the functional avoidance plan with the anatomical plan pair in which the p-value > α = 0.05 $&gt; \alpha =0.05$ . From these results, we can conclude that voxel-based treatment planning outperforms both anatomical and functional-avoidance planning.

CONCLUSIONS

We propose a treatment planning framework that directly utilizes functional images and compares voxel-based treatment planning with functional avoidance and anatomical treatment planning.

Radiation pneumonitis prediction model with integrating multiple dose-function features on 4DCT ventilation images

PURPOSE

Radiation pneumonitis (RP) is dose-limiting toxicity for non-small-cell cancer (NSCLC). This study developed an RP prediction model by integrating dose-function features from computed four-dimensional computed tomography (4DCT) ventilation using the least absolute shrinkage and selection operator (LASSO).

METHODS

Between 2013 and 2020, 126 NSCLC patients were included in this study who underwent a 4DCT scan to calculate ventilation images. We computed two sets of candidate dose-function features from (1) the percentage volume receiving > 20 Gy or the mean dose on the functioning zones determined with the lower cutoff percentile ventilation value, (2) the functioning zones determined with lower and upper cutoff percentile ventilation value using 4DCT ventilation images. An RP prediction model was developed by LASSO while simultaneously determining the regression coefficient and feature selection through fivefold cross-validation.

RESULTS

We found 39.3 % of our patients had a ≥ grade 2 RP. The mean area under the curve (AUC) values for the developed models using clinical, dose-volume, and dose-function features with a lower cutoff were 0.791, and the mean AUC values with lower and upper cutoffs were 0.814. The relative regression coefficient (RRC) on dose-function features with upper and lower cutoffs revealed a relative impact of dose to each functioning zone to RP. RRCs were 0.52 for the mean dose on the functioning zone, with top 20 % of all functioning zone was two times greater than that of 0.19 for these with 60 %-80 % and 0.17 with 40 %-60 % (P < 0.01).

CONCLUSIONS

The introduction of dose-function features computed from functioning zones with lower and upper cutoffs in a machine learning framework can improve RP prediction. The RRC given by LASSO using dose-function features allows for the quantification of the RP impact of dose on each functioning zones and having the potential to support treatment planning on functional image-guided radiotherapy.

The role of artificial intelligence in veterinary radiation oncology

Veterinary radiation oncology regularly deploys sophisticated contouring, image registration, and treatment planning optimization software for patient care. Over the past decade, advances in computing power and the rapid development of neural networks, open-source software packages, and data science have been realized and resulted in new research and clinical applications of artificial intelligent (AI) systems in radiation oncology. These technologies differ from conventional software in their level of complexity and ability to learn from representative and local data. We provide clinical and research application examples of AI in human radiation oncology and their potential applications in veterinary medicine throughout the patient's care-path: from treatment simulation, deformable registration, auto-segmentation, automated treatment planning and plan selection, quality assurance, adaptive radiotherapy, and outcomes modeling. These technologies have the potential to offer significant time and cost savings in the veterinary setting; however, since the range of usefulness of these technologies have not been well studied nor understood, care must be taken if adopting AI technologies in clinical practice. Over the next several years, some practical and realizable applications of AI in veterinary radiation oncology include automated segmentation of normal tissues and tumor volumes, deformable registration, multi-criteria plan optimization, and adaptive radiotherapy. Keys in achieving success in adopting AI in veterinary radiation oncology include: establishing "truth-data"; data harmonization; multi-institutional data and collaborations; standardized dose reporting and taxonomy; adopting an open access philosophy, data collection and curation; open-source algorithm development; and transparent and platform-independent code development.

Prediction of radiation pneumonitis with machine learning using 4D-CT based dose-function features

In this article, we highlight the fundamental importance of the simultaneous use of dose-volume histogram (DVH) and dose-function histogram (DFH) features based on functional images calculated from 4-dimensional computed tomography (4D-CT) and deformable image registration (DIR) in developing a multivariate radiation pneumonitis (RP) prediction model. The patient characteristics, DVH features and DFH features were calculated from functional images by Hounsfield unit (HU) and Jacobian metrics, for an RP grade ≥ 2 multivariate prediction models were computed from 85 non-small cell lung cancer patients. The prediction model is developed using machine learning via a kernel-based support vector machine (SVM) machine. In the patient cohort, 21 of the 85 patients (24.7%) presented with RP grade ≥ 2. The median area under curve (AUC) was 0.58 for the generated 50 prediction models with patient clinical features and DVH features. When HU metric and Jacobian metric DFH features were added, the AUC improved to 0.73 and 0.68, respectively. We conclude that predictive RP models that incorporate DFH features were successfully developed via kernel-based SVM. These results demonstrate that effectiveness of the simultaneous use of DVH features and DFH features calculated from 4D-CT and DIR on functional image-guided radiotherapy.

Predicting radiation pneumonitis with fuzzy clustering neural network using 4DCT ventilation image based dosimetric parameters

Background

To develop a fuzzy clustering neural network to predict radiation-induced pneumonitis (RP) using four-dimensional computed tomography (4DCT) ventilation image (VI) based dosimetric parameters for thoracic cancer patients.

Methods

The VI were retrospectively calculated from pre-treatment 4DCT data using a deformable image registration (DIR) and an improved VI algorithm. Similar to dose-volume histogram (DVH) of intensity modulated radiotherapy (IMRT), dose-function histogram (DFH) was derived from dose distribution and VI. Then, the dose-function metrics were calculated from DFH. For comparison, the dose-volume metrics were calculated from DVH. Correspondingly, two sets of feature vectors were formed from the dose-volume metrics and the dose-function metrics, respectively. For the feature vectors of each set, they were first pre-processed by principal component analysis (PCA) to reduce feature dimensions. Then, they were grouped to few clusters determined by fuzzy c-means (FCM) algorithm. Next, the neural network was trained to correlate the dosimetric parameters with RP based on the feature vectors of each cluster. Finally, the occurrence of RP was predicted by the neural network on the test data.

Results

Through PCA analysis, the top 5 principal components were selected. Their contribution is more than 98%, which is adequate to represent the original feature space of input data. Based on the clustering validity indexes, the optimal number of clusters is 4 and used for subsequent fuzzy clustering of the input data. After network training, the areas under the curve (AUC) of the prediction model is 0.77 using VI-based dosimetric parameters and 0.67 using structure-based dosimetric parameters.

Conclusions

Compared to the structure-based dosimetric features, the VI-based dosimetric features are more relevant to lung function and presented higher prediction accuracy of RP. The fuzzy clustering neural network improved the prediction accuracy of RP compared to the conventional neural network. The combination of VI-based dose-function metrics and fuzzy clustering neural network provides an effective predictive model for assessing lung toxicity risk after radiotherapy.

Hyperpolarized 129Xe Magnetic Resonance Imaging for Functional Avoidance Treatment Planning in Thoracic Radiation Therapy: A Comparison of Ventilation- and Gas Exchange-Guided Treatment Plans

PURPOSE

To present a methodology to use pulmonary gas exchange maps to guide functional avoidance treatment planning in radiation therapy (RT) and evaluate its efficacy compared with ventilation-guided treatment planning.

METHODS AND MATERIALS

Before receiving conventional RT for non-small cell lung cancer, 11 patients underwent hyperpolarized ¹²⁹Xe gas exchange magnetic resonance imaging to map the distribution of xenon in its gas phase (ventilation) and transiently bound to red blood cells in the alveolar capillaries (gas exchange). Both ventilation and gas exchange maps were independently used to guide development of new functional avoidance treatment plans for every patient, while adhering to institutional dose-volume constraints for normal tissues and target coverage. Furthermore, dose-volume histogram (DVH)-based reoptimizations of the clinical plan, with reductions in mean lung dose (MLD) equal to the functional avoidance plans, were created to serve as the control group. To evaluate each plan (regardless of type), gas exchange maps, representing end-to-end lung function, were used to calculate gas exchange-weighted MLD (fMLD), gas exchange-weighted volume receiving ≥20 Gy (fV20), and mean dose in the highest gas exchanging 33% and 50% volumes of lung (MLD-f33% and MLD-f50%). Using each clinically approved plan as a baseline, the reductions in functional metrics were compared for ventilation-optimization, gas exchange optimization, and DVH-based reoptimization. Statistical significance was determined using the Freidman test, with subsequent subdivision when indicated by P values less than .10 and post hoc testing with Wilcoxon signed rank tests to determine significant differences (P < .05). Toxicity modeling was performed using an established function-based model to estimate clinical significance of the results.

RESULTS

Compared with DVH-based reoptimization of the clinically approved plans, gas exchange-guided functional avoidance planning more effectively reduced the gas exchange-weighted metrics fMLD (average ± SD, -78 ± 79 cGy for gas exchange, compared with -45 ± 34 cGy for DVH-based; P = .03), MLD-f33% (-135 ± 136 cGy, compared with -52 ± 47 cGy; P = .004), and MLD-f50% (-96 ± 95 cGy, compared with -47 ± 40 cGy; P = .01). Comparing the 2 functional planning types, gas exchange-guided planning more effectively reduced MLD-f33% compared with ventilation-guided planning (-64 ± 95; P = .009). For some patients, gas exchange-guided functional avoidance plans demonstrated clinically significant reductions in model-predicted toxicity, more so than the accompanying ventilation-guided plans and DVH-based reoptimizations.

CONCLUSION

Gas exchange-guided planning effectively reduced dose to high gas exchanging regions of lung while maintaining clinically acceptable plan quality. In many patients, ventilation-guided planning incidentally reduced dose to higher gas exchange regions, to a lesser extent. This methodology enables future prospective trials to examine patient outcomes.

A deep learning-based dual-omics prediction model for radiation pneumonitis

PURPOSE

Radiation pneumonitis (RP) is the main source of toxicity in thoracic radiotherapy. This study proposed a deep learning-based dual-omics model, which aims to improve the RP prediction performance by integrating more data points and exploring the data in greater depth.

MATERIALS AND METHODS

The bimodality data were the original dose (OD) distribution and the ventilation image (VI) derived from four-dimensional computed tomography (4DCT). The functional dose (FD) distribution was obtained by weighting OD with VI. A pre-trained three-dimensional convolution (C3D) network was used to extract the features from FD, VI, and OD. The extracted features were then filtered and selected using entropy-based methods. The prediction models were constructed with four most commonly used binary classifiers. Cross-validation, bootstrap, and nested sampling methods were adopted in the process of training and hyper-tuning.

RESULTS

Data from 217 thoracic cancer patients treated with radiotherapy were used to train and validate the prediction model. The 4DCT-based VI showed the inhomogeneous pulmonary function of the lungs. More than half of the extracted features were singular (of none-zero value for few patients), which were eliminated to improve the stability of the model. The area under curve (AUC) of the dual-omics model was 0.874 (95% confidence interval: 0.871-0.877), and the AUC of the single-omics model was 0.780 (0.775-0.785, VI) and 0.810 (0.804-0.811, OD), respectively.

CONCLUSIONS

The dual-omics outperformed single-omics for RP prediction, which can be contributed to: (1) using more data points; (2) exploring the data in greater depth; and (3) incorporating of the bimodality data.

Single photon emission computed tomography (SPECT) or positron emission tomography (PET) imaging for radiotherapy planning in patients with lung cancer: a meta-analysis

Functional imaging modalities enable practitioners to identify functional lung regions. This analysis evaluated the feasibility of nuclear medicine imaging to avoid doses to the functional lung in radiotherapy (RT) planning for patients with lung cancer. This systematic review and meta-analysis was carried out according to PRISMA-P guidelines. A search of EMBASE and PubMed for studies published throughout the last 20 years was performed using the following search criteria: (a) ‘lung cancer’ or ‘lung malignancy’ and (b) ‘radiotherapy’ or ‘radiation therapy’ or ‘RT planning’ and (c) ‘SPECT’ or ‘single positron emission computed tomography’ or ‘functional image.’ The analyzed planning parameters were the volumes of the normal lung that have received ≥ 10 Gy and ≥ 20 Gy of radiation (V10 and V20, respectively) and the mean lung dose (MLD). We compared the planning parameters obtained from anatomical RT planning and functional RT planning using perfusion or ventilation imaging (‘V10, V20 or MLD’ in anatomical plan vs. ‘fV10, fV20 or fMLD’ in functional plan). A total of 309 patients with 344 RT plan sets from 15 publications (11 perfusion SPECT, 2 ventilation SPECT, and 1 SPECT and 1 PET with both perfusion and ventilation) were included in the meta-analysis. The standard mean differences in planning parameters in functional plans using nuclear imaging were significantly reduced compared to those of anatomical plans (P < 0.01 for all): − 0.42 (95% confidence interval (CI) − 0.78 to − 0.07) for ‘V10 vs. fV10′, − 0.41 (95% CI − 0.64 to − 0.17) for ‘V20 vs. fV20′, and − 0.24 (95% CI − 0.45 to − 0.03) for ‘MLD vs. fMLD’. In subgroup analysis, the functional plan using perfusion was significantly lower than the anatomical plan in all planning parameters, but there was no significant difference for ventilation. RT planning with nuclear functional lung imaging has potential to reduce radiation-induced lung injury. Perfusion imaging seems to be more promising than ventilation imaging for all planning parameters. There were not enough studies using ventilation imaging to determine what the effect is on the lung plan parameters.

The impact of 4DCT-ventilation imaging-guided proton therapy on stereotactic body radiotherapy for lung cancer

Functional lung avoidance during radiotherapy can help reduce pulmonary toxicity. This study assessed the potential impact of four-dimensional computed tomography (4DCT)-ventilation imaging-guided proton radiotherapy (PT) on stereotactic body radiotherapy (SBRT) by comparing it with three-dimensional conformal radiotherapy (3D-CRT) and volumetric modulated arc therapy (VMAT), which employ photon beams. Thirteen lung cancer patients who received SBRT with 3D-CRT were included in the study. 4DCT ventilation was calculated using the patients' 4DCT data, deformable image registration, and a density-change-based algorithm. Three functional treatment plans sparing the functional lung regions were developed for each patient using 3D-CRT, VMAT, and PT. The prescribed doses and dose constraints were based on the Radiation Therapy Oncology Group 0618 protocol. We evaluated the region of interest (ROI) and functional map-based dose-function metrics for 4DCT ventilation and the irradiated dose. Using 3D-CRT, VMAT, and PT, the percentages of the functional lung regions that received ≥ 5 Gy (fV5) were 26.0%, 21.9%, and 10.7%, respectively; the fV10 were 14.4%, 11.4%, and 9.0%, respectively; and fV20 were 6.5%, 6.4%, and 6.6%, respectively, and the functional mean lung doses (fMLD) were 5.6 Gy, 5.2 Gy, and 3.8 Gy, respectively. These results indicated that PT resulted in a significant reduction in fMLD, fV5, and fV10, but not fV20. The use of PT reduced the radiation to highly functional lung regions compared with those for 3D-CRT and VMAT while meeting all dose constraints.

Variations Between Dose-Ventilation and Dose-Perfusion Metrics in Radiation Therapy Planning for Lung Cancer

Purpose

Currently, several active clinical trials of functional lung avoidance radiation therapy using different imaging modalities for ventilation or perfusion are underway. Patients with lung cancer often show ventilation-perfusion mismatch, whereas the significance of dose-function metric remains unclear. The aim of the present study was to compare dose-ventilation metrics with dose-perfusion metrics for radiation therapy plan evaluation.

Methods and Materials

Pretreatment 4-dimensional computed tomography and ^99mTc-macroaggregated albumin single-photon emission computed tomography perfusion images of 60 patients with lung cancer treated with radiation therapy were analyzed. Ventilation images were created using the deformable image registration of 4-dimensional computed tomography image sets and image analysis for regional volume changes as a surrogate for ventilation. Ventilation and perfusion images were converted into percentile distribution images. Analyses included Pearson’s correlation coefficient and comparison of agreements between the following dose-ventilation and dose-perfusion metrics: functional mean lung dose and functional percent lung function receiving 5, 10, 20, 30, and 40 Gy (fV₅, fV₁₀, fV₂₀, fV₃₀, and fV₄₀, respectively).

Results

Overall, the dose-ventilation metrics were greater than the dose-perfusion metrics (ie, fV₂₀, 26.3% ± 9.9% vs 23.9% ± 9.8%). Correlations between the dose-ventilation and dose-perfusion metrics were strong (range, r = 0.94-0.97), whereas the agreements widely varied among patients, with differences as large as 6.6 Gy for functional mean lung dose and 11.1% for fV₂₀. Paired t test indicated that the dose-ventilation and dose-perfusion metrics were significantly different.

Conclusions

Strong correlations were present between the dose-ventilation and dose-perfusion metrics. However, the agreement between the dose-ventilation and dose-perfusion metrics widely varied among patients, suggesting that ventilation-based radiation therapy plan evaluation may not be comparable to that based on perfusion. Future studies should elucidate the correlation of dose-function metrics with clinical pulmonary toxicity metrics.

Four-dimensional computed tomography-based biomechanical measurements of pulmonary function and their correlation with clinical outcome for lung stereotactic body radiation therapy patients

BACKGROUND

Functional image guided radiotherapy allows for the delivery of an equivalent dose to tumor targets while sparing high ventilation lung tissues. In this study, we investigate whether radiation dose to functional lung is associated with clinical outcome for stereotactic body radiation therapy (SBRT) patients.

METHODS

Four-dimensional computed tomography (4DCT) images were used to assess lung function. Deformable image registration (DIR) was performed from the end-inhale phase to the end-exhale phase with resultant displacement vectors used to calculate ventilation maps. In addition to the Jacobian-based ventilation we introduce a volumetric variation method (Rv) based on a biomechanical finite element method (FEM), to assess lung ventilation. Thirty NSCLC patients, treated with SBRT, were evaluated in this study. 4DCT images were used to calculate both Jacobian and Rv-based ventilation images. Areas under the receiver operating characteristic curve (AUC) were used to assess the predictive power of functional metrics. Metrics were calculated over the whole lung as well as high and low ventilated regions.

RESULTS

Ventilation in dose regions between 1 and 5 Gy had higher AUC values compared to other dose regions. Rv based ventilation imaging method also showed to be less spatially variant and less heterogeneous, and the resultant Rv metrics had higher AUC values for predicting grade 2+ dyspnea.

CONCLUSIONS

Low dose delivered to high ventilation areas may also increase the risk of compromised pulmonary function. Rv based ventilation images could be useful for the prediction of clinical toxicity for lung SBRT patients.

4-Dimensional computed tomography-based ventilation and compliance images for quantification of radiation-induced changes in pulmonary function

INTRODUCTION

4-Dimensional computed tomography (4DCT)-based ventilation imaging is a promising technique for evaluating pulmonary function, but lung elasticity and mechanics are usually not part of the ventilation image analysis. In this study we demonstrate a 4DCT-based imaging technique that can be used to calculate regional lung compliance changes after radiotherapy (RT).

METHODS

Six lung cancer patients were included in this study. Four of the patients had 4DCT images acquired pre-RT, 3 and 9 months post-RT. Ventilation and compliance were calculated from the deformable image registration (DIR) of 4DCTs, performed from the end-inhale to the end-exhale breathing phase. Regional compliance was defined as the ratio of volumetric variation and associated stress in each voxel, representing lung elasticity and computed using a FEM-based framework. Ventilation, compliance and CT density were calculated for all pre-RT and post-RT 4DCTs and evaluation metrics were computed.

RESULTS

Average CT density changes were 13.6 ± 11.4HU after 3 months and 26.9 ± 15.8HU after 9 months. Ventilation was reduced at 3 months, but improved at 9 months in regions with dose ≥ 35 Gy, encompassing about 10% of the lung volume; compliance was reduced at both time-points. Radiation dose ≥ 35 Gy caused major change in lung density and ventilation, which was higher than that previously reported in the literature (i.e. 24 Gy).

CONCLUSION

Lung tissue response is diverse with respect to CT density, ventilation and compliance. Combination of ventilation and compliance with CT density could be beneficial for understanding radiation-induced lung damage and consequently could help develop improved treatment protocols for lung cancer patients.

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.

Correlation of Regional Lung Ventilation and Gas Transfer to Red Blood Cells: Implications for Functional-Avoidance Radiation Therapy Planning

PURPOSE

To investigate the degree to which lung ventilation and gas exchange are regionally correlated, using the emerging technology of hyperpolarized (HP)-129Xe magnetic resonance imaging (MRI).

METHODS AND MATERIALS

Hyperpolarized-129Xe MRI studies were performed on 17 institutional review board-approved human subjects, including 13 healthy volunteers, 1 emphysema patient, and 3 non-small cell lung cancer patients imaged before and approximately 11 weeks after radiation therapy (RT). Subjects inhaled 1 L of HP-129Xe mixture, followed by the acquisition of interleaved ventilation and gas exchange images, from which maps were obtained of the relative HP-129Xe distribution in three states: (1) gaseous, in lung airspaces; (2) dissolved interstitially, in alveolar barrier tissue; and (3) transferred to red blood cells (RBCs), in the capillary vasculature. The relative spatial distributions of HP-129Xe in airspaces (regional ventilation) and RBCs (regional gas transfer) were compared. Further, we investigated the degree to which ventilation and RBC transfer images identified similar functional regions of interest (ROIs) suitable for functionally guided RT. For the RT patients, both ventilation and RBC functional images were used to calculate differences in the lung dose-function histogram and functional effective uniform dose.

RESULTS

The correlation of ventilation and RBC transfer was ρ = 0.39 ± 0.15 in healthy volunteers. For the RT patients, this correlation was ρ = 0.53 ± 0.02 before treatment and ρ = 0.39 ± 0.07 after treatment; for the emphysema patient it was ρ = 0.24. Comparing functional ROIs, ventilation and RBC transfer demonstrated poor spatial agreement: Dice similarity coefficient = 0.50 ± 0.07 and 0.26 ± 0.12 for the highest-33%- and highest-10%-function ROIs in healthy volunteers, and in RT patients (before treatment) these were 0.58 ± 0.04 and 0.40 ± 0.04. The average magnitude of the differences between RBC- and ventilation-derived functional effective uniform dose, fV20Gy, fV10Gy, and fV5Gy were 1.5 ± 1.4 Gy, 4.1% ± 3.8%, 5.0% ± 3.8%, and 5.3% ± 3.9%, respectively.

CONCLUSION

Ventilation may not be an effective surrogate for true regional lung function for all patients.

Modeling Patient-Specific Dose-Function Response for Enhanced Characterization of Personalized Functional Damage

PURPOSE

Functional-guided radiation therapy (RT) plans have the potential to limit damage to normal tissue and reduce toxicity. Although functional imaging modalities have continued to improve, a limited understanding of the functional response to radiation and its application to personalized therapy has hindered clinical implementation. The purpose of this study was to retrospectively model the longitudinal, patient-specific dose-function response in non-small cell lung cancer patients treated with RT to better characterize the expected functional damage in future, unknown patients.

METHODS AND MATERIALS

Perfusion single-photon emission computed tomography/computed tomography scans were obtained at baseline (n = 81), midtreatment (n = 74), 3 months post-treatment (n = 51), and 1 year post-treatment (n = 26) and retrospectively analyzed. Patients were treated with conventionally fractionated RT or stereotactic body RT. Normalized perfusion single-photon emission computed tomography voxel intensity was used as a surrogate for local lung function. A patient-specific logistic model was applied to each individual patient's dose-function response to characterize functional reduction at each imaging time point. Patient-specific model parameters were averaged to create a population-level logistic dose-response model.

RESULTS

A significant longitudinal decrease in lung function was observed after RT by analyzing the voxelwise change in normalized perfusion intensity. Generated dose-function response models represent the expected voxelwise reduction in function, and the associated uncertainty, for an unknown patient receiving conventionally fractionated RT or stereotactic body RT. Differential treatment responses based on the functional status of the voxel at baseline suggest that initially higher functioning voxels are damaged at a higher rate than lower functioning voxels.

CONCLUSIONS

This study modeled the patient-specific dose-function response in patients with non-small cell lung cancer during and after radiation treatment. The generated population-level dose-function response models were derived from individual patient assessment and have the potential to inform functional-guided treatment plans regarding the expected functional lung damage. This type of patient-specific modeling approach can be applied broadly to other functional response analyses to better capture intrapatient dependencies and characterize personalized functional damage.

Analyses of regional radiosensitivity of white matter structures along tract axes using novel white matter segmentation and diffusion imaging biomarkers

BACKGROUND AND PURPOSE

Brain radiotherapy (RT) can cause white matter damage and downstream neurocognitive decline. We developed a computational neuroimaging tool to regionally partition individual white matter tracts, then analyze regional changes in diffusion metrics of white matter damage following brain RT.

MATERIALS AND METHODS

RT dose, diffusion metrics and white matter tract structures were extracted and mapped to a reference brain for 49 patients who received brain RT, and underwent diffusion tensor imaging pre- and 9-12 months post-RT. Based on their elongation, 23 of 48 white matter tracts were selected. The Tract-Crawler software was developed in MATLAB to create cross-sectional slice planes normal to a tract's computed medial axis. We then performed slice- and voxel-wise analysis of radiosensitivity, defined as percent change in mean diffusivity (MD) and fractional anisotropy (FA) as a function of dose relative to baseline.

RESULTS

Distinct patterns of FA/MD radiosensitivity were seen for specific tracts, including the corticospinal tract, medial lemniscus, and inferior cerebellar peduncle, in particular at terminal ends. These patterns persisted for corresponding tracts in left and right hemispheres. Local sensitivities were as high as 40%/Gy (e.g., voxel-wise: -39 ± 31%/Gy in right corticospinal tract FA, -45 ± 25%/Gy in right inferior cerebellar peduncle FA), p < 0.05.

CONCLUSIONS

Tract-Crawler, a novel tool to visualize and analyze cuts of white matter structures normal to medial axes, was used to demonstrate that particular white matter tracts exhibit significant regional variations in radiosensitivity based on diffusion biomarkers.

Regional Lung Function Profiles of Stage I and III Lung Cancer Patients: An Evaluation for Functional Avoidance Radiation Therapy

PURPOSE

The development of clinical trials is underway to use 4-dimensional computed tomography (4DCT) ventilation imaging to preferentially spare functional lung in patients undergoing radiation therapy. The purpose of this work was to generate data to aide with clinical trial design by retrospectively characterizing dosimetric and functional profiles for patients with different stages of lung cancer.

METHODS AND MATERIALS

A total of 118 lung cancer patients (36% stage I and 64% stage III) from 2 institutions were used for the study. A 4DCT-ventilation map was calculated using the patient's 4DCT imaging, deformable image registration, and a density-change-based algorithm. To assess each patient's spatial ventilation profile both quantitative and qualitative metrics were developed, including an observer-based defect observation and metrics based on the ventilation in each lung third. For each patient we used the clinical doses to calculate functionally weighted mean lung doses and metrics that assessed the interplay between the spatial location of the dose and high-functioning lung.

RESULTS

Both qualitative and quantitative metrics revealed a significant difference in functional profiles between the 2 stage groups (P<.01). We determined that 65% of stage III and 28% of stage I patients had ventilation defects. Average functionally weighted mean lung dose was 19.6 Gy and 5.4 Gy for stage III and I patients, respectively, with both groups containing patients with large spatial overlap between dose and high-function regions.

CONCLUSION

Our 118-patient retrospective study found that 65% of stage III patients have regionally variant ventilation profiles that are suitable for functional avoidance. Our results suggest that regardless of disease stage, it is possible to have unique spatial interplay between dose and high-functional lung, highlighting the importance of evaluating the function of each patient and developing a personalized functional avoidance treatment approach.

Framework for radiation pneumonitis risk stratification based on anatomic and perfused lung dosimetry

PURPOSE

To design and apply a framework for predicting symptomatic radiation pneumonitis in patients undergoing thoracic radiation, using both pretreatment anatomic and perfused lung dose-volume parameters.

MATERIALS AND METHODS

Radiation treatment planning CT scans were coregistered with pretreatment [99mTc]MAA perfusion SPECT/CT scans of 20 patients who underwent definitive thoracic radiation. Clinical radiation pneumonitis was defined as grade ≥ 2 (CTCAE v4 grading system). Anatomic lung dose-volume parameters were collected from the treatment planning scans. Perfusion dose-volume parameters were calculated from pretreatment SPECT/CT scans. Equivalent doses in 2 Gy per fraction were calculated in the lung to account for differences in treatment regimens and spatial variations in lung dose (EQD2lung).

RESULTS

Anatomic lung dosimetric parameters (MLD) and functional lung dosimetric parameters (pMLD70%) were identified as candidate predictors of grade ≥ 2 radiation pneumonitis (AUC > 0.93, p < 0.01). Pairing of an anatomic and functional dosimetric parameter (e. g., MLD and pMLD70%) may further improve prediction accuracy. Not all individuals with high anatomic lung dose (MLD > 13.6 GyEQD2lung, 19.3 Gy for patients receiving 60 Gy in 30 fractions) developed radiation pneumonitis, but all individuals who also had high mean dose to perfused lung (pMLD70% > 13.3 GyEQD2) developed radiation pneumonitis.

CONCLUSIONS

The preliminary application of this framework revealed differences between anatomic and perfused lung dosimetry in this limited patient cohort. The addition of perfused lung parameters may help risk stratify patients for radiation pneumonitis, especially in treatment plans with high anatomic mean lung dose. Further investigations are warranted.

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 patient's 4DCT‐imaging, deformable registration, and a density‐change‐based algorithm. Clinical trial inclusion assessment used quantitative and qualitative metrics based on the patient's 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.

Evaluating Which Dose-Function Metrics Are Most Critical for Functional-Guided Radiation Therapy

PURPOSE

Four-dimensional (4D) computed tomography (CT) ventilation imaging is increasingly being used to calculate lung ventilation and implement functional-guided radiation therapy in clinical trials. There has been little exhaustive work evaluating which dose-function metrics should be used for treatment planning and plan evaluation. The purpose of our study was to evaluate which dose-function metrics best predict for radiation pneumonitis (RP).

METHODS AND MATERIALS

Seventy lung cancer patients who underwent 4D CT imaging and pneumonitis grading were assessed. Pretreatment 4D CT scans of each patient were used to calculate ventilation images. We evaluated 3 types of dose-function metrics that combined the patient's 4D CT ventilation image and treatment planning dose distribution: (1) structure-based approaches; (2) image-based approaches using the dose-function histogram; and (3) nonlinear weighting schemes. Log-likelihood methods were used to generate normal tissue complication probability models predicting grade 3 or higher (ie, grade 3+) pneumonitis for all dose-function schemes. The area under the curve (AUC) was used to assess the predictive power of the models. All techniques were compared with normal tissue complication probability models based on traditional, total lung dose metrics.

RESULTS

The most predictive models were structure-based approaches that focused on the volume of functional lung receiving ≥20 Gy (AUC, 0.70). Probabilities of grade 3+ RP of 20% and 10% correspond to V20 (percentage of volume receiving ≥20 Gy) to the functional subvolumes of 26.8% and 9.3%, respectively. Imaging-based analysis with the dose-function histogram and nonlinear weighted ventilation values yielded AUCs of 0.66 and 0.67, respectively, when we evaluated the percentage of functionality receiving ≥20 Gy. All dose-function metrics outperformed the traditional dose metrics (mean lung dose, AUC of 0.55).

CONCLUSIONS

A full range of dose-function metrics and functional thresholds was examined. The calculated AUC values for the most predictive functional models occupied a narrow range (0.66-0.70), and all showed notable improvements over AUC from traditional lung dose metrics (0.55). Identifying the combinations most predictive of grade 3+ RP provides valuable data to inform the functional-guided radiation therapy process.

Should regional ventilation function be considered during radiation treatment planning to prevent radiation-induced complications?

PURPOSE

To investigate the incorporation of pretherapy regional ventilation function in predicting radiation fibrosis (RF) in stage III nonsmall cell lung cancer (NSCLC) patients treated with concurrent thoracic chemoradiotherapy.

METHODS

Thirty-seven patients with stage III NSCLC were retrospectively studied. Patients received one cycle of cisplatin-gemcitabine, followed by two to three cycles of cisplatin-etoposide concurrently with involved-field thoracic radiotherapy (46-66 Gy; 2 Gy/fraction). Pretherapy regional ventilation images of the lung were derived from 4D computed tomography via a density change-based algorithm with mass correction. In addition to the conventional dose-volume metrics (V20, V30, V40, and mean lung dose), dose-function metrics (fV20, fV30, fV40, and functional mean lung dose) were generated by combining regional ventilation and radiation dose. A new class of metrics was derived and referred to as dose-subvolume metrics (sV20, sV30, sV40, and subvolume mean lung dose); these were defined as the conventional dose-volume metrics computed on the functional lung. Area under the receiver operating characteristic curve (AUC) values and logistic regression analyses were used to evaluate these metrics in predicting hallmark characteristics of RF (lung consolidation, volume loss, and airway dilation).

RESULTS

AUC values for the dose-volume metrics in predicting lung consolidation, volume loss, and airway dilation were 0.65-0.69, 0.57-0.70, and 0.69-0.76, respectively. The respective ranges for dose-function metrics were 0.63-0.66, 0.61-0.71, and 0.72-0.80 and for dose-subvolume metrics were 0.50-0.65, 0.65-0.75, and 0.73-0.85. Using an AUC value = 0.70 as cutoff value suggested that at least one of each type of metrics (dose-volume, dose-function, dose-subvolume) was predictive for volume loss and airway dilation, whereas lung consolidation cannot be accurately predicted by any of the metrics. Logistic regression analyses showed that dose-function and dose-subvolume metrics were significant (P values ≤ 0.02) in predicting volume airway dilation. Likelihood ratio test showed that when combining dose-function and/or dose-subvolume metrics with dose-volume metrics, the achieved improvements of prediction accuracy on volume loss and airway dilation were significant (P values ≤ 0.04).

CONCLUSIONS

The authors' results demonstrated that the inclusion of regional ventilation function improved accuracy in predicting RF. In particular, dose-subvolume metrics provided a promising method for preventing radiation-induced pulmonary complications.

Local and Global Function Model of the Liver

PURPOSE

To develop a local and global function model in the liver based on regional and organ function measurements to support individualized adaptive radiation therapy (RT).

METHODS AND MATERIALS

A local and global model for liver function was developed to include both functional volume and the effect of functional variation of subunits. Adopting the assumption of parallel architecture in the liver, the global function was composed of a sum of local function probabilities of subunits, varying between 0 and 1. The model was fit to 59 datasets of liver regional and organ function measures from 23 patients obtained before, during, and 1 month after RT. The local function probabilities of subunits were modeled by a sigmoid function in relating to MRI-derived portal venous perfusion values. The global function was fitted to a logarithm of an indocyanine green retention rate at 15 minutes (an overall liver function measure). Cross-validation was performed by leave-m-out tests. The model was further evaluated by fitting to the data divided according to whether the patients had hepatocellular carcinoma (HCC) or not.

RESULTS

The liver function model showed that (1) a perfusion value of 68.6 mL/(100 g · min) yielded a local function probability of 0.5; (2) the probability reached 0.9 at a perfusion value of 98 mL/(100 g · min); and (3) at a probability of 0.03 [corresponding perfusion of 38 mL/(100 g · min)] or lower, the contribution to global function was lost. Cross-validations showed that the model parameters were stable. The model fitted to the data from the patients with HCC indicated that the same amount of portal venous perfusion was translated into less local function probability than in the patients with non-HCC tumors.

CONCLUSIONS

The developed liver function model could provide a means to better assess individual and regional dose-responses of hepatic functions, and provide guidance for individualized treatment planning of RT.

Incorporating GSA-SPECT into CT-based dose-volume histograms for advanced hepatocellular carcinoma radiotherapy

In single photon emission computed tomography-based three-dimensional radiotherapy (SPECT-B-3DCRT), images of Tc-99m galactosyl human serum albumin (GSA), which bind to receptors on functional liver cells, are merged with the computed tomography simulation images. Functional liver is defined as the area of normal liver where GSA accumulation exceeds that of hepatocellular carcinoma (HCC). In cirrhotic patients with a gigantic, proton-beam-untreatable HCC of ≥ 14 cm in diameter, the use of SPECT-B-3DCRT in combination with transcatheter arterial chemoembolization achieved a 2-year local tumor control rate of 78.6% and a 2-year survival rate of 33.3%. SPECT-B-3DCRT was applied to HCC to preserve as much functional liver as possible. Sixty-four patients with HCC, including 30 with Child B liver cirrhosis, received SPECT-B-3DCRT and none experienced fatal radiation-induced liver disease (RILD). The Child-Pugh score deteriorated by 1 or 2 in > 20% of functional liver volume that was irradiated with ≥ 20 Gy. The deterioration in the Child-Pugh score decreased when the radiation plan was designed to irradiate ≤ 20% of the functional liver volume in patients given doses of ≥ 20 Gy (_FLV_20Gy). Therefore, _FLV_20Gy≤ 20% may represent a safety index to prevent RILD during 3DCRT for HCC. To supplement _FLV_20Gy as a qualitative index, we propose a quantitative indicator, F_20Gy, which was calculated as F_20Gy = 100% × (the GSA count in the area irradiated with ≥ 20 Gy)/(the GSA count in the whole liver).

Dependence of ventilation image derived from 4D CT on deformable image registration and ventilation algorithms

Ventilation imaging using 4D CT is a convenient and low-cost functional imaging methodology which might be of value in radiotherapy treatment planning to spare functional lung volumes. Deformable image registration (DIR) is needed to calculate ventilation imaging from 4D CT. This study investigates the dependence of calculated ventilation on DIR methods and ventilation algorithms. DIR of the normal end expiration and normal end inspiration phases of the 4D CT images was used to correlate the voxels between the two respiratory phases. Three different DIR algorithms, optical flow (OF), diffeomorphic demons (DD), and diffeomorphic morphons (DM) were retrospectively applied to ten esophagus and ten lung cancer cases with 4D CT image sets that encompassed the entire lung volume. The three ventilation extraction methods were used based on either the Jacobian, the change in volume of the voxel, or directly calculated from Hounsfield units. The ventilation calculation algorithms used are the Jacobian, ΔV, and HU method. They were compared using the Dice similarity coefficient (DSC) index and Bland-Altman plots. Dependence of ventilation images on the DIR was greater for the ΔV and the Jacobian methods than for the HU method. The DSC index for 20% of low-ventilation volume for ΔV was 0.33 ± 0.03 (1 SD) between OF and DM, 0.44 ± 0.05 between OF and DD, and 0.51 ± 0.04 between DM and DD. The similarity comparisons for Jacobian were 0.32 ± 0.03, 0.44 ± 0.05, and 0.51 ± 0.04, respectively, and for HU they were 0.53 ± 0.03, 0.56 ± 0.03, and 0.76 ± 0.04, respectively. Dependence of extracted ventilation on the ventilation algorithm used showed good agreement between the ΔV and Jacobian methods, but differed significantly for the HU method. DSC index for using OF as DIR was 0.86 ± 0.01 between ΔV and Jacobian, 0.28 ± 0.04 between ΔV and HU, and 0.28 ± 0.04 between Jacobian and HU, respectively. When using DM or DD as DIR, similar values were obtained when comparing the different ventilation calculation methods. The similarity values for the 20% high-ventilation volume were close to those found for the 20% low-ventilation volume. The results obtained with DSC index were confirmed when using the Bland-Altman plots for comparing the ventilation images. Our data suggest that ventilation calculated from 4D CT depends on the DIR algorithm employed. Similarities between ΔV and Jacobian are higher than between ΔV and HU, and Jacobian and HU.

The use and QA of biologically related models for treatment planning: short report of the TG-166 of the therapy physics committee of the AAPM

Treatment planning tools that use biologically related models for plan optimization and/or evaluation are being introduced for clinical use. A variety of dose-response models and quantities along with a series of organ-specific model parameters are included in these tools. However, due to various limitations, such as the limitations of models and available model parameters, the incomplete understanding of dose responses, and the inadequate clinical data, the use of biologically based treatment planning system (BBTPS) represents a paradigm shift and can be potentially dangerous. There will be a steep learning curve for most planners. The purpose of this task group is to address some of these relevant issues before the use of BBTPS becomes widely spread. In this report, the authors (1) discuss strategies, limitations, conditions, and cautions for using biologically based models and parameters in clinical treatment planning; (2) demonstrate the practical use of the three most commonly used commercially available BBTPS and potential dosimetric differences between biologically model based and dose-volume based treatment plan optimization and evaluation; (3) identify the desirable features and future directions in developing BBTPS; and (4) provide general guidelines and methodology for the acceptance testing, commissioning, and routine quality assurance (QA) of BBTPS.

Utility of single photon emission computed tomography perfusion scans in radiation treatment planning of locally advanced lung cancers

PURPOSE

Lung perfusion scan provides a map of the spatial distribution of lung perfusion. This can be used to design radiation portals to spare functional lung (FL), potentially reducing lung toxicity. The purpose of this study was to assess the utility of lung perfusion single photon emission computed tomography (SPECT) in treatment planning for lung cancer patients.

MATERIALS AND METHODS

Radiotherapy treatment planning computed tomography (CT) scans and SPECT scans of 11 patients of lung cancer suitable for external radiotherapy were co-registered. Conventional treatment plans (anatomic plan) and plans with FL information (functional plan) was generated. The difference in dose volume parameters (V20, V30 and mean lung doses) due to these two plans were compared using Bland-Altman plots.

RESULTS

Functional plans produced a more favorable plan compared with anatomic plan in all except three cases. FL V20 values and FL mean lung dose were reduced for all patients by an average of 5.45 Gy and 7.72 Gy respectively which were statistically significant.

CONCLUSIONS

Lung perfusion scans provide functional information which is not provided by CT scans. SPECT-guidance aids in reducing the dose delivered to highly perfused regions which could reduce the incidence of pneumonitis.

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.

Functional avoidance of lung in plan optimization with an aperture-based inverse planning system

PURPOSE

To implement SPECT-based optimization in an anatomy-based aperture inverse planning system for the functional avoidance of lung in thoracic irradiation.

MATERIAL AND METHODS

SPECT information has been introduced as a voxel-by-voxel modulation of lung importance factors proportionally to the local perfusion count. Fifteen cases of lung cancer have been retrospectively analyzed by generating angle-optimized non-coplanar plans, comparing a purely anatomical approach and our functional approach. Planning target volume coverage and lung sparing have been compared. Statistical significance was assessed by a Wilcoxon matched pairs test.

RESULTS

For similar target coverage, perfusion-weighted volume receiving 10 Gy was reduced by a median of 2.2% (p=0.022) and mean perfusion-weighted lung dose, by a median of 0.9 Gy (p=0.001). A separate analysis of patients with localized or non-uniform hypoperfusion could not show which would benefit more from SPECT-based treatment planning. Redirection of dose sometimes created overdosage regions in the target volume. Plans consisted of a similar number of segments and monitor units.

CONCLUSIONS

Angle optimization and SPECT-based modulation of importance factors allowed for functional avoidance of the lung while preserving target coverage. The technique could be also applied to implement PET-based modulation inside the target volume, leading to a safer dose escalation.

Measurement of regional compliance using 4DCT images for assessment of radiation treatment

PURPOSE

Radiation-induced damage, such as inflammation and fibrosis, can compromise ventilation capability of local functional units (alveoli) of the lung. Ventilation function as measured with ventilation images, however, is often complicated by the underlying mechanical variations. The purpose of this study is to present a 4DCT-based method to measure the regional ventilation capability, namely, regional compliance, for the evaluation of radiation-induced lung damage.

METHODS

Six 4DCT images were investigated in this study: One previously used in the generation of a POPI model and the other five acquired at Henry Ford Health System. A tetrahedral geometrical model was created and scaled to encompass each of the 4DCT image domains. Image registrations were performed on each of the 4DCT images using a multiresolution Demons algorithm. The images at the end of exhalation were selected as a reference. Images at other exhalation phases were registered to the reference phase. For the POPI-modeled patient, each of these registration instances was validated using 40 landmarks. The displacement vector fields (DVFs) were used first to calculate the volumetric variation of each tetrahedron, which represents the change in the air volume. The calculated results were interpolated to generate 3D ventilation images. With the computed DVF, a finite element method (FEM) framework was developed to compute the stress images of the lung tissue. The regional compliance was then defined as the ratio of the ventilation and stress values and was calculated for each phase. Based on iterative FEM simulations, the potential range of the mechanical parameters for the lung was determined by comparing the model-computed average stress to the clinical reference value of airway pressure. The effect of the parameter variations on the computed stress distributions was estimated using Pearson correlation coefficients.

RESULTS

For the POPI-modeled patient, five exhalation phases from the start to the end of exhalation were denoted by P(i), i = 1, ..., 5, respectively. The average lung volume variation relative to the reference phase (P5) was reduced from 18% at P1 to 4.8% at P4. The average stress at phase P(i) was 1.42, 1.34, 0.74, and 0.28 kPa, and the average regional compliance was 0.19, 0.20, 0.20, and 0.24 for i = 1, ..., 4, respectively. For the other five patients, their average R(v) value at the end-inhalation phase was 21.1%, 19.6%, 22.4%, 22.5%, and 18.8%, respectively, and the regional compliance averaged over all six patients is 0.2. For elasticity parameters chosen from the potential parameter range, the resultant stress distributions were found to be similar to each other with Pearson correlation coefficients greater than 0.81.

CONCLUSIONS

A 4DCT-based mechanical model has been developed to calculate the ventilation and stress images of the lung. The resultant regional compliance represents the lung's elasticity property and is potentially useful in correlating regions of lung damage with radiation dose following a course of radiation therapy.

Helical tomotherapy planning for lung cancer based on ventilation magnetic resonance imaging

To investigate the feasibility of lung ventilation-based treatment planning, computed tomography and hyperpolarized (HP) helium-3 (He-3) magnetic resonance imaging (MRI) ventilation images of 6 subjects were coregistered for intensity-modulated radiation therapy planning in Tomotherapy. Highly-functional lungs (HFL) and less-functional lungs (LFL) were contoured based on their ventilation image intensities, and a cylindrical planning-target-volume was simulated at locations adjacent to both HFL and LFL. Annals of an anatomy-based plan (Plan 1) and a ventilation-based plan (Plan 2) were generated. The following dosimetric parameters were determined and compared between the 2 plans: percentage of total/HFL volume receiving ≥20 Gy, 15 Gy, 10 Gy, and 5 Gy (TLV(20), HFLV(20), TLV(15), HFLV(15), TLV(10), HFLV(10), TLV(5), HFLV(5)), mean total/HFL dose (MTLD/HFLD), maximum doses to all organs at risk (OARs), and target dose conformality. Compared with Plan 1, Plan 2 reduced mean HFLD (mean reduction, 0.8 Gy), MTLD (mean reduction, 0.6 Gy), HFLV(20) (mean reduction, 1.9%), TLV(20) (mean reduction, 1.5%), TLV(15) (mean reduction, 1.7%), and TLV(10) (mean reduction, 2.1%). P-values of the above comparisons are less than 0.05 using the Wilcoxon signed rank test. For HFLV(15), HFLV(10), TLV(5), and HTLV(5), Plan 2 resulted in lower values than plan 1 but the differences are not significant (P-value range, 0.063-0.219). Plan 2 did not significantly change maximum doses to OARs (P-value range, 0.063-0.563) and target conformality (P = 1.000). HP He-3 MRI of patients with lung disease shows a highly heterogeneous ventilation capacity that can be utilized for functional treatment planning. Moderate but statistically significant improvements in sparing functional lungs were achieved using helical tomotherapy plans.

Radiobiological evaluation of the influence of dwell time modulation restriction in HIPO optimized HDR prostate brachytherapy implants

Purpose

One of the issues that a planner is often facing in HDR brachytherapy is the selective existence of high dose volumes around some few dominating dwell positions. If there is no information available about its necessity (e.g. location of a GTV), then it is reasonable to investigate whether this can be avoided. This effect can be eliminated by limiting the free modulation of the dwell times. HIPO, an inverse treatment plan optimization algorithm, offers this option. In treatment plan optimization there are various methods that try to regularize the variation of dose non-uniformity using purely dosimetric measures. However, although these methods can help in finding a good dose distribution they do not provide any information regarding the expected treatment outcome as described by radiobiology based indices.

Material and methods

The quality of 12 clinical HDR brachytherapy implants for prostate utilizing HIPO and modulation restriction (MR) has been compared to alternative plans with HIPO and free modulation (without MR). All common dose-volume indices for the prostate and the organs at risk have been considered together with radiobiological measures. The clinical effectiveness of the different dose distributions was investigated by calculating the response probabilities of the tumors and organs-at-risk (OARs) involved in these prostate cancer cases. The radiobiological models used are the Poisson and the relative seriality models. Furthermore, the complication-free tumor control probability, P₊ and the biologically effective uniform dose (D¯¯) were used for treatment plan evaluation and comparison.

Results

Our results demonstrate that HIPO with a modulation restriction value of 0.1-0.2 delivers high quality plans which are practically equivalent to those achieved with free modulation regarding the clinically used dosimetric indices. In the comparison, many of the dosimetric and radiobiological indices showed significantly different results. The modulation restricted clinical plans demonstrated a lower total dwell time by a mean of 1.4% that was proved to be statistically significant (p = 0.002). The HIPO with MR treatment plans produced a higher P₊ by 0.5%, which stemmed from a better sparing of the OARs by 1.0%.

Conclusions

Both the dosimetric and radiobiological comparison shows that the modulation restricted optimization gives on average similar results with the optimization without modulation restriction in the examined clinical cases. Concluding, based on our results, it appears that the applied dwell time regularization technique is expected to introduce a minor improvement in the effectiveness of the optimized HDR dose distributions.

["Dose-painting": myth or reality?]

"Dose-painting" radiotherapy allows for a heterogeneous delivery of radiation within the tumour volume by targeting radioresistant areas defined by functional imaging. Within gross tumour volume, it is possible to define one or more target volumes based on biology (biological target volume [BTV]) and to apply a strategy of intensity modulated radiation therapy (IMRT) that will deliver a higher dose to these regions. In this review of the literature, we will highlight the biological elements responsible for radioresistance, and how to image them, then we will detail the radiotherapy techniques necessary for this approach, before presenting clinical results in various situations (head and neck tumours, prostate, brain tumours, etc.). Despite many difficulties that make dose-painting IMRT unusable in routine nowadays, biology-guided radiation therapy represents one of the major pathways of development of radiotherapy in the coming years.

Complexity and accuracy of image registration methods in SPECT-guided radiation therapy

The use of functional imaging in radiotherapy treatment (RT) planning requires accurate co-registration of functional imaging scans to CT scans. We evaluated six methods of image registration for use in SPECT-guided radiotherapy treatment planning. Methods varied in complexity from 3D affine transform based on control points to diffeomorphic demons and level set non-rigid registration. Ten lung cancer patients underwent perfusion SPECT-scans prior to their radiotherapy. CT images from a hybrid SPECT/CT scanner were registered to a planning CT, and then the same transformation was applied to the SPECT images. According to registration evaluation measures computed based on the intensity difference between the registered CT images or based on target registration error, non-rigid registrations provided a higher degree of accuracy than rigid methods. However, due to the irregularities in some of the obtained deformation fields, warping the SPECT using these fields may result in unacceptable changes to the SPECT intensity distribution that would preclude use in RT planning. Moreover, the differences between intensity histograms in the original and registered SPECT image sets were the largest for diffeomorphic demons and level set methods. In conclusion, the use of intensity-based validation measures alone is not sufficient for SPECT/CT registration for RTTP. It was also found that the proper evaluation of image registration requires the use of several accuracy metrics.

A methodology for selecting the beam arrangement to reduce the intensity-modulated radiation therapy (IMRT) dose to the SPECT-defined functioning lung

Macroaggregated albumin single-photon emission computed tomography (MAA-SPECT) provides a map of the spatial distribution of lung perfusion. Our previous work developed a methodology to use SPECT guidance to reduce the dose to the functional lung in IMRT planning. This study aims to investigate the role of beam arrangement on both low and high doses in the functional lung. In our previous work, nine-beam IMRT plans were generated with and without SPECT guidance and compared for five patients. For the current study, the dose-function histogram (DFH) contribution for each of the nine beams for each patient was calculated. Four beams were chosen based on orientation and DFH contributions to create a SPECT-guided plan that spared the functional lung and maintained target coverage. Four-beam SPECT-guided IMRT plans reduced the F(20) and F(30) values by (16.5 +/- 6.8)% and (6.1 +/- 9.2)%, respectively, when compared to nine-beam conventional IMRT plans. Moreover, the SPECT-4F Plan reduces F(5) and F(13) for all patients by (11.0 +/- 8.2)% and (6.1 +/- 3.6)%, respectively, compared to the SPECT Plan. Using fewer beams in IMRT planning may reduce the amount of functional lung that receives 5 and 13 Gy, a factor that has recently been associated with radiation pneumonitis.

AAPM recommendations on dose prescription and reporting methods for permanent interstitial brachytherapy for prostate cancer: report of Task Group 137

During the past decade, permanent radioactive source implantation of the prostate has become the standard of care for selected prostate cancer patients, and the techniques for implantation have evolved in many different forms. Although most implants use 125I or 103Pd sources, clinical use of 131Cs sources has also recently been introduced. These sources produce different dose distributions and irradiate the tumors at different dose rates. Ultrasound was used originally to guide the planning and implantation of sources in the tumor. More recently, CT and/or MR are used routinely in many clinics for dose evaluation and planning. Several investigators reported that the tumor volumes and target volumes delineated from ultrasound, CT, and MR can vary substantially because of the inherent differences in these imaging modalities. It has also been reported that these volumes depend critically on the time of imaging after the implant. Many clinics, in particular those using intraoperative implantation, perform imaging only on the day of the implant. Because the effects of edema caused by surgical trauma can vary from one patient to another and resolve at different rates, the timing of imaging for dosimetry evaluation can have a profound effect on the dose reported (to have been delivered), i.e., for the same implant (same dose delivered), CT at different timing can yield different doses reported. Also, many different loading patterns and margins around the tumor volumes have been used, and these may lead to variations in the dose delivered. In this report, the current literature on these issues is reviewed, and the impact of these issues on the radiobiological response is estimated. The radiobiological models for the biological equivalent dose (BED) are reviewed. Starting with the BED model for acute single doses, the models for fractionated doses, continuous low-dose-rate irradiation, and both homogeneous and inhomogeneous dose distributions, as well as tumor cure probability models, are reviewed. Based on these developments in literature, the AAPM recommends guidelines for dose prescription from a physics perspective for routine patient treatment, clinical trials, and for treatment planning software developers. The authors continue to follow the current recommendations on using D90 and V100 as the primary quantitles, with more specific guidelines on the use of the imaging modalities and the timing of the imaging. The AAPM recommends that the postimplant evaluation should be performed at the optimum time for specific radionuclides. In addition, they encourage the use of a radiobiological model with a specific set of parameters to facilitate relative comparisons of treatment plans reported by different institutions using different loading patterns or radionuclides.

An image acquisition and registration strategy for the fusion of hyperpolarized helium-3 MRI and x-ray CT images of the lung

The purpose of this ethics committee approved prospective study was to evaluate an image acquisition and registration protocol for hyperpolarized helium-3 magnetic resonance imaging ((3)He-MRI) and x-ray computed tomography. Nine patients with non-small cell lung cancer (NSCLC) gave written informed consent to undergo a free-breathing CT, an inspiration breath-hold CT and a 3D ventilation (3)He-MRI in CT position using an elliptical birdcage radiofrequency (RF) body coil. (3)He-MRI to CT image fusion was performed using a rigid registration algorithm which was assessed by two observers using anatomical landmarks and a percentage volume overlap coefficient. Registration of (3)He-MRI to breath-hold CT was more accurate than to free-breathing CT; overlap 82.9 +/- 4.2% versus 59.8 +/- 9.0% (p < 0.001) and mean landmark error 0.75 +/- 0.24 cm versus 1.25 +/- 0.60 cm (p = 0.002). Image registration is significantly improved by using an imaging protocol that enables both (3)He-MRI and CT to be acquired with similar breath holds and body position through the use of a birdcage (3)He-MRI body RF coil and an inspiration breath-hold CT. Fusion of (3)He-MRI to CT may be useful for the assessment of patients with lung diseases.

On Voxel based Iso-Tumor Control Probabilty and Iso-Complication Maps for Selective Boosting and Selective Avoidance Intensity Modulated Radiotherapy

Voxel based iso-Tumor Control Probability (TCP) maps and iso-Complication maps are proposed as a plan-review tool especially for functional image-guided intensity-modulated radiotherapy (IMRT) strategies such as selective boosting (dose painting) and conformal avoidance IMRT. The maps employ voxel-based phenomenological biological dose-response models for target volumes and normal organs. Two IMRT strategies for prostate cancer, namely conventional uniform IMRT delivering an EUD = 84 Gy (equivalent uniform dose) to the entire PTV and selective boosting delivering an EUD = 82 Gy to the entire PTV, are investigated, to illustrate the advantages of this approach over iso-dose maps. Conventional uniform IMRT did yield a more uniform isodose map to the entire PTV while selective boosting did result in a nonuniform isodose map. However, when employing voxel based iso-TCP maps selective boosting exhibited a more uniform tumor control probability map compared to what could be achieved using conventional uniform IMRT, which showed TCP cold spots in high-risk tumor subvolumes despite delivering a higher EUD to the entire PTV. Voxel based iso-Complication maps are presented for rectum and bladder, and their utilization for selective avoidance IMRT strategies are discussed. We believe as the need for functional image guided treatment planning grows, voxel based iso-TCP and iso-Complication maps will become an important tool to assess the integrity of such treatment plans.

Advanced Technologies in Image-Guided Radiation Therapy

In addition to rapid developments in the use of stationary radiographs and computed tomography scans in treatment rooms, a variety of additional technologies is on the horizon to aid in guided treatment. Some of these (fluoroscopy and tomosynthesis) are variations on the use of existing hardware, whereas others (electromagnetic localization, magnetic resonance imaging) represent significant departures from recently adopted technologic concepts. This review introduces these methods and explores their potential for initial use in guidance.

Preserving Functional Lung Using Perfusion Imaging and Intensity-Modulated Radiation Therapy for Advanced-Stage Non–Small Cell Lung Cancer

PURPOSE

To assess quantitatively the impact of incorporating functional lung imaging into intensity-modulated radiation therapy planning for locally advanced non-small cell lung cancer (NSCLC).

METHODS AND MATERIALS

Sixteen patients with advanced-stage NSCLC who underwent radiotherapy were included in this study. Before radiotherapy, each patient underwent lung perfusion imaging with single-photon-emission computed tomography and X-ray computed tomography (SPECT-CT). The SPECT-CT was registered with simulation CT and was used to segment the 50- and 90-percentile hyperperfusion lung (F50 lung and F90 lung). Two IMRT plans were designed and compared in each patient: an anatomic plan using simulation CT alone and a functional plan using SPECT-CT in addition to the simulation CT. Dosimetric parameters of the two types of plans were compared in terms of tumor coverage and avoidance of normal tissues.

RESULTS

In incorporating perfusion information in IMRT planning, the median reductions in the mean doses to the F50 and F90 lung in the functional plan were 2.2 and 4.2 Gy, respectively, compared with those in the anatomic plans. The median reductions in the percentage of volume irradiated with >5 Gy, >10 Gy, and >20 Gy in the functional plans were 7.1%, 6.0%, and 5.1%, respectively, for F50 lung, and 11.7%, 12.0%, and 6.8%, respectively, for F90 lung. A greater degree of sparing of the functional lung was achieved for patients with large perfusion defects compared with those with relatively uniform perfusion distribution.

CONCLUSION

Function-guided IMRT planning appears to be effective in preserving functional lung in locally advanced-stage NSCLC patients.

Feasibility of image registration and intensity-modulated radiotherapy planning with hyperpolarized helium-3 magnetic resonance imaging for non-small-cell lung cancer

Purpose: To demonstrate the feasibility of registering hyperpolarized helium-3 magnetic resonance images (³He-MRI) to X-ray computed tomography (CT) for functionally weighted intensity-modulated radiotherapy (IMRT) planning.

Methods and Materials: Six patients with non–small-cell lung cancer underwent ³He ventilation MRI, which was fused with radiotherapy planning CT using rigid registration. Registration accuracy was assessed using an overlap coefficient, calculated as the proportion of the segmented ³He-MR volume (V_MRI) that intersects the segmented CT lung volume expressed as a percentage of V_MRI. For each patient, an IMRT plan that minimized the volume of total lung receiving a dose ≥20 Gy (V₂₀) was compared with a plan that minimized the V₂₀ to well-ventilated lung defined by the registered ³He-MRI.

Results: The ³He-MRI and CT were registered with sufficient accuracy to enable functionally guided IMRT planning (median overlap, 89%; range, 72–97%). In comparison with the total lung IMRT plans, IMRT constrained with ³He-MRI reduced the V₂₀ not only for the well-ventilated lung (median reduction, 3.1%; range, 0.4–5.1%; p = 0.028) but also for the total lung volume (median reduction, 1.6%; range, 0.2–3.7%; p = 0.028).

Conclusions: Statistically significant improvements to IMRT plans are possible using functional information provided by ³He-MRI that has been registered to radiotherapy planning CT.

Reduction of normal lung irradiation in locally advanced non-small-cell lung cancer patients, using ventilation images for functional avoidance

PURPOSE

To investigate the ability of four-dimensional computed tomography (4D-CT)-derived ventilation images to identify regions of highly functional lung for avoidance in intensity-modulated radiotherapy (IMRT) planning in locally advanced non-small-cell lung cancer (NSCLC).

METHODS AND MATERIALS

The treatment-planning records from 21 patients with Stage III NSCLC were selected. Ventilation images were generated from the 4D-CT sets, and each was imported into the treatment-planning system. Ninetieth percentile functional volumes (PFV90), constituting the 10% of the lung volume where the highest ventilation occurs, were generated. Baseline IMRT plans were generated using the lung volume constraint on V20 (<35%), and two additional plans were generated using constraints on the PFV90 without a volume constraint. Dose-volume and dose-function histograms (DVH, DFH) were generated and used to evaluate the planning target volume coverage, lung volume, and functional parameters for comparison of the plans.

RESULTS

The mean dose to the PFV90 was reduced by 2.9 Gy, and the DFH at 5 Gy (F5) was reduced by 9.6% (SE = 2.03%). The F5, F10, V5, and V10 were all significantly reduced from the baseline values. We identified a favorable subset of patients for whom there was a further significant improvement in the mean lung dose.

CONCLUSIONS

Four-dimensional computed tomography-derived ventilation regions were successfully used as avoidance structures to reduce the DVH and DFH at 5 Gy in all cases. In a subset, there was also a reduction in the F10 and V10 without a change in the V20, suggesting that this technique could be safely used.

A methodology for using SPECT to reduce intensity-modulated radiation therapy (IMRT) dose to functioning lung

PURPOSE

Single photon emission computed tomography (SPECT) provides a map of the spatial distribution of lung perfusion. Thus, SPECT guidance can be used to divert dose away from higher-functioning lung, potentially reducing lung toxicity. We present a methodology for achieving this aim and test it in intensity-modulated radiotherapy (IMRT) treatment-planning.

METHODS AND MATERIALS

IMRT treatment plans were generated with and without SPECT guidance and compared for 5 patients. Healthy lung was segmented into four regions on the basis of SPECT intensity in the SPECT plan. Dose was sequentially allowed to the target via regions of increasing SPECT intensity. This process results in reduction of dose to functional lung, reflected in the dose-function histogram (DFH). The plans were compared using DFHs and F(20)/F(30) values (F(x) is the functional lung receiving dose above x Gy).

RESULTS

In all cases, the SPECT-guided plan produced a more favorable DFH compared with the non-SPECT-guided plan. Additionally, the F(20) and F(30) values were reduced for all patients by an average of 13.6% +/- 5.2% and 10.5% +/- 5.8%, respectively. In all patients, DFHs of the two highest-functioning SPECT regions were reduced, whereas DFHs of the two lower-functioning regions were increased, illustrating the dose "give-take" between SPECT regions during redistribution.

CONCLUSIONS

SPECT-guided IMRT shows potential for reducing the dose delivered to highly functional lung regions. This dose reduction could reduce the number of high-grade pneumonitis cases that develop after radiation treatment and improve patient quality of life.

The role and strategy of IMRT in radiotherapy of pelvic tumors: Dose escalation and critical organ sparing in prostate cancer

PURPOSE

To investigate the intensity-modulated radiotherapy (IMRT) strategy in dose escalation of prostate and pelvic lymph nodes.

METHODS AND MATERIALS

Plan dosimetric data of 10 prostate cancer patients were compared with two-dimensional (2D) or IMRT techniques for pelvis (two-dimensional whole pelvic radiation therapy [2D-WPRT] or IM-WPRT) to receive 50 Gy or 54 Gy and additional prostate boost by three-dimensional conformal radiation therapy or IMRT (3D-PBRT or IM-PBRT) techniques up to 72 Gy or 78 Gy. Dose-volume histograms (DVHs), normal tissue complication probabilities (NTCP) of critical organ, and conformity of target volume in various combinations were calculated.

RESULTS

In DVH analysis, the plans with IM-WPRT (54 Gy) and additional boost up to 78 Gy had lower rectal and bladder volume percentage at 50 Gy and 60 Gy, compared with those with 2D-WPRT (50 Gy) and additional boost up to 72 Gy or 78 Gy. Those with IM-WPRT (54 Gy) also had better small bowel sparing at 30 Gy and 50 Gy, compared with those with 2D-WPRT (50 Gy). In NTCP, those with IM-WPRT and total dose of 78 Gy achieved lower complication rates in rectum and small bowel, compared with those of 2D-WPRT with total dose of 72 Gy. In conformity, those with IM-WPRT had better conformity compared with those with 2D-WPRT with significance (p < 0.005). No significant difference in DVHs, NTCP, or conformity was found between IM-PBRT and 3D-PBRT after IM-WPRT.

CONCLUSIONS

Initial pelvic IMRT is the most important strategy in dose escalation and critical organ sparing. IM-WPRT is recommended for patients requiring WPRT. There is not much benefit for critical organ sparing by IMRT after 2D-WPRT.

Does transforming growth factor-beta1 predict for radiation-induced pneumonitis in patients treated for lung cancer?

The purpose of the study was to reassess the utility of transforming growth factor-beta-1 (TGF-beta1) together with dosimetric and tumor parameters as a predictor for radiation pneumonitis (RP). Of the 121 patients studied, 32 (26.4%) developed grade > or =1 RP, and 27 (22.3%) developed grade > or =2 RP. For the endpoint of grade > or =1 RP, those with V30>30% and an end-RT/baseline TGF-beta1 ratio> or =1 had a significantly higher incidence of RP than did those with V30>30% and an end-RT/baseline TGF-beta1 ratio<1. For most other patient groups, there were no clear associations between TGF-beta1 values and rates of RP. These findings suggest that TGF-beta1 is generally not predictive for RP except for the group of patients with a high V30.