Purpose: To quantify the dosimetric impact of four-dimensional computed tomography (4D-CT) pulmonary ventilation imaging-based functional treatment planning that avoids high-functional lung regions.
Methods And Materials: 4D-CT ventilation images were created from 15 non-small-cell lung cancer patients using deformable image registration and quantitative analysis of the resultant displacement vector field. For each patient, anatomic and functional plans were created for intensity-modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT). Consistent beam angles and dose-volume constraints were used for all cases. The plans with Radiation Therapy Oncology Group (RTOG) 0617-defined major deviations were modified until clinically acceptable. Functional planning spared the high-functional lung, and anatomic planning treated the lungs as uniformly functional. We quantified the impact of functional planning compared with anatomic planning using the two- or one-tailed t test.
Results: Functional planning led to significant reductions in the high-functional lung dose, without significantly increasing other critical organ doses, but at the expense of significantly degraded the planning target volume (PTV) conformity and homogeneity. The average reduction in the high-functional lung mean dose was 1.8 Gy for IMRT (p < .001) and 2.0 Gy for VMAT (p < .001). Significantly larger changes occurred in the metrics for patients with a larger amount of high-functional lung adjacent to the PTV.
Conclusion: The results of the present study have demonstrated the impact of 4D-CT ventilation imaging-based functional planning for IMRT and VMAT for the first time. Our findings indicate the potential of functional planning in lung functional avoidance for both IMRT and VMAT, particularly for patients who have high-functional lung adjacent to the PTV.
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http://dx.doi.org/10.1016/j.ijrobp.2010.02.008 | DOI Listing |
Med Phys
January 2025
Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, Hong Kong.
Curr Oncol
June 2024
Division of Medical Oncology, Department of Oncology, London Health Sciences Centre, Western University, London, ON N6A 5W9, Canada.
Small-cell lung cancer (SCLC) remains a disease with poor prognosis, particularly in extensive-stage SCLC (ES-SCLC). Current standard-of-care treatment includes chemotherapy with platinum agents and etoposide plus immunotherapy with atezolizumab or durvalumab, which has achieved a mean overall survival of 12-13 months in clinical trials. However, long-term survival in ES-SCLC, even with the addition of immunotherapy, continues to be rare.
View Article and Find Full Text PDFPhys Med Biol
July 2024
Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region of China, People's Republic of China.
This study aims to develop a fully automatic planning framework for functional lung avoidance radiotherapy (AP-FLART).The AP-FLART integrates a dosimetric score-based beam angle selection method and a meta-optimization-based plan optimization method, both of which incorporate lung function information to guide dose redirection from high functional lung (HFL) to low functional lung (LFL). It is applicable to both contour-based FLART (cFLART) and voxel-based FLART (vFLART) optimization options.
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 PDFInt J Radiat Oncol Biol Phys
January 2024
Department of Radiation Oncology, Thomas Jefferson University, Philadelphia, Pennsylvania. Electronic address:
Purpose: A novel form of lung functional imaging applied for functional avoidance radiation therapy has been developed that uses 4-dimensional computed tomography (4DCT) data and image processing techniques to calculate lung ventilation (4DCT-ventilation). Lung segmentation is a common step to define a region of interest for 4DCT-ventilation generation. The purpose of this study was to quantitatively evaluate the sensitivity of 4DCT-ventilation imaging using different lung segmentation methods.
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