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.
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http://dx.doi.org/10.1016/j.ijrobp.2017.03.051 | DOI Listing |
Int J Radiat Oncol Biol Phys
October 2024
Thomas Jefferson University, Radiation Oncology, Philadelphia, Pennsylvania. Electronic address:
Purpose: A novel form of lung function imaging has been developed that uses 4-dimensional computed tomography (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 phase 2, multicenter 4DCT-ventilation functional avoidance clinical trial was completed.
View Article and Find Full Text PDFJpn J Radiol
July 2024
The Comprehensive Cancer Centre of Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, 210000, Jiangsu, China.
Purpose: Radiotherapy planning incorporating functional lung images has the potential to reduce pulmonary toxicity. Free-breathing 4DCT-derived ventilation image (CTVI) may help quantify lung function. This study introduces a novel deep-learning model directly translating planning CT images into CTVI.
View Article and Find Full Text PDFJ Med Phys
September 2023
Department of Medical Physics and Biomedical Engineering, Faculty of Medicine, Tehran, Iran.
Purpose: According to the revised Task Group number 43 recommendations, a brachytherapy source must be validated against a similar or identical source before its clinical application. The purpose of this investigation is to verify the dosimetric data of the high dose rate (HDR) BEBIG Ir source (Ir2.A85-2).
View Article and Find Full Text PDFRadiother Oncol
October 2023
Department of Radiation Oncology, Thomas Jefferson University, Philadelphia, PA, USA. Electronic address:
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.
View Article and Find Full Text PDFRadiat Oncol
January 2023
The Comprehensive Cancer Centre of Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, 210000, Jiangsu, China.
Purpose: CT ventilation image (CTVI)-guided radiotherapy that selectively avoids irradiating highly-functional lung regions has potential to reduce pulmonary toxicity. Considering Helical TomoTherapy (HT) has higher modulation capabilities, we investigated the capability and characteristic of HT at sparing functional lungs for locally advanced lung cancer.
Methods And Materials: Pretreatment 4DCT scans were carried out for 17 patients.
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