Comparative Analysis of Local Control Prediction Using Different Biophysical Models for Non-Small Cell Lung Cancer Patients Undergoing Stereotactic Body Radiotherapy. (14th June 2017)
- Record Type:
- Journal Article
- Title:
- Comparative Analysis of Local Control Prediction Using Different Biophysical Models for Non-Small Cell Lung Cancer Patients Undergoing Stereotactic Body Radiotherapy. (14th June 2017)
- Main Title:
- Comparative Analysis of Local Control Prediction Using Different Biophysical Models for Non-Small Cell Lung Cancer Patients Undergoing Stereotactic Body Radiotherapy
- Authors:
- Huang, Bao-Tian
Zhang, Wu-Zhe
Wu, Li-Li
Lin, Pei-Xian
Lu, Jia-Yang - Other Names:
- Sawabata Noriyoshi Academic Editor.
- Abstract:
- Abstract : Purpose. The consistency for predicting local control (LC) data using biophysical models for stereotactic body radiotherapy (SBRT) treatment of lung cancer is unclear. This study aims to compare the results calculated from different models using the treatment planning data. Materials and Methods. Treatment plans were designed for 17 patients diagnosed with primary non-small cell lung cancer (NSCLC) using 5 different fraction schemes. The Martel model, Ohri model, and the Tai model were used to predict the 2-year LC value. The Gucken model, Santiago model, and the Tai model were employed to estimate the 3-year LC data. Results. We found that the employed models resulted in completely different LC prediction except for the Gucken and the Santiago models which exhibited quite similar 3-year LC data. The predicted 2-year and 3-year LC values in different models were not only associated with the dose normalization but also associated with the employed fraction schemes. The greatest difference predicted by different models was up to 15.0%. Conclusions. Our results show that different biophysical models influence the LC prediction and the difference is not only correlated to the dose normalization but also correlated to the employed fraction schemes.
- Is Part Of:
- BioMed research international. Volume 2017(2017)
- Journal:
- BioMed research international
- Issue:
- Volume 2017(2017)
- Issue Display:
- Volume 2017, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 2017
- Issue:
- 2017
- Issue Sort Value:
- 2017-2017-2017-0000
- Page Start:
- Page End:
- Publication Date:
- 2017-06-14
- Subjects:
- Medicine -- Periodicals
Biology -- Periodicals
Biotechnology -- Periodicals
Life sciences -- Periodicals
610.5 - Journal URLs:
- https://www.hindawi.com/journals/bmri/ ↗
- DOI:
- 10.1155/2017/1436573 ↗
- Languages:
- English
- ISSNs:
- 2314-6133
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 23475.xml