Estimation of lung tumor position from multiple anatomical features on 4D‐ CT using multiple regression analysis
| Autor: | Mitsuhiro Nakamura, Takashi Ishigaki, Tomohiro Ono, Yuka Ono, Yoshinori Hirose, Kenji Kitsuda, Masahiro Hiraoka |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
medicine.medical_specialty
Lung Neoplasms Diaphragm 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Linear regression medicine Radiation Oncology Physics Humans Organ Motion Radiology Nuclear Medicine and imaging Lung volumes Four-Dimensional Computed Tomography Thoracic Wall Lung cancer Lung Instrumentation Contouring Radiation business.industry anatomical features Respiration estimation of lung tumor position Abdominal Wall multi regression analysis 4D‐CT medicine.disease medicine.anatomical_structure 030220 oncology & carcinogenesis 87.50.yt 87.55.?x 87.55.kd 87.57.Q? Regression Analysis Radiology Nuclear medicine business Anatomical feature Thoracic wall |
| Zdroj: | Journal of Applied Clinical Medical Physics |
| ISSN: | 1526-9914 |
| DOI: | 10.1002/acm2.12121 |
| Popis: | To estimate the lung tumor position from multiple anatomical features on four‐dimensional computed tomography (4D‐CT) data sets using single regression analysis (SRA) and multiple regression analysis (MRA) approach and evaluate an impact of the approach on internal target volume (ITV) for stereotactic body radiotherapy (SBRT) of the lung. Eleven consecutive lung cancer patients (12 cases) underwent 4D‐CT scanning. The three‐dimensional (3D) lung tumor motion exceeded 5 mm. The 3D tumor position and anatomical features, including lung volume, diaphragm, abdominal wall, and chest wall positions, were measured on 4D‐CT images. The tumor position was estimated by SRA using each anatomical feature and MRA using all anatomical features. The difference between the actual and estimated tumor positions was defined as the root‐mean‐square error (RMSE). A standard partial regression coefficient for the MRA was evaluated. The 3D lung tumor position showed a high correlation with the lung volume (R = 0.92 ± 0.10). Additionally, ITVs derived from SRA and MRA approaches were compared with ITV derived from contouring gross tumor volumes on all 10 phases of the 4D‐CT (conventional ITV). The RMSE of the SRA was within 3.7 mm in all directions. Also, the RMSE of the MRA was within 1.6 mm in all directions. The standard partial regression coefficient for the lung volume was the largest and had the most influence on the estimated tumor position. Compared with conventional ITV, average percentage decrease of ITV were 31.9% and 38.3% using SRA and MRA approaches, respectively. The estimation accuracy of lung tumor position was improved by the MRA approach, which provided smaller ITV than conventional ITV. |
| Databáze: | OpenAIRE |
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