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Preoperative spirometry and BMI in deep inspiration breath-hold radiotherapy: the early detection of cardiac and lung dose predictors without radiation exposure.

Authors :
Koide, Yutaro
Shimizu, Hidetoshi
Aoyama, Takahiro
Kitagawa, Tomoki
Miyauchi, Risei
Watanabe, Yui
Tachibana, Hiroyuki
Kodaira, Takeshi
Source :
Radiation Oncology. 2/19/2022, Vol. 17 Issue 1, p1-8. 8p.
Publication Year :
2022

Abstract

<bold>Background: </bold>This study aimed to investigate preoperative spirometry and BMI as early predictors of the mean heart and lung dose (MHD, MLD) in deep inspiration breath-hold (DIBH) radiotherapy.<bold>Methods: </bold>Left-sided breast cancer patients underwent breast-conserving surgery followed by DIBH radiotherapy enrolled. Patients who were not available for preoperative spirometry were excluded. One hundred eligible patients were performed free-breathing (FB-) CT and DIBH-CT for plan comparison. We completed the correlative and multivariate analysis to develop the linear regression models for dose prediction. The residuals were calculated to explore the unpreferable subgroups and compare the prediction accuracy.<bold>Results: </bold>Among the parameters, vital capacity (VC) and BMI showed the strongest negative correlation with MHD (r = - 0.33) and MLD (r = - 0.34), respectively. They were also significant in multivariate analysis (P < 0.001). Elderly and less VC were independent predictors of increasing absolute residuals (AR). The VC model showed no significant difference in AR compared to the model using the CT parameter of lung volume in FB (LV-FB): median AR of the LV-FB model vs. the VC model was 0.12 vs. 0.11 Gy (P = 0.79). On the other hand, the median AR of the MLD model was 0.38 Gy, showing no specific subgroups of larger AR.<bold>Conclusion: </bold>Preoperative spirometry and BMI are significant predictors of MHD and MLD, respectively. Although elderly and low-VC patients may have larger predictive variations, spirometry might be a substitute for LV-FB as a predictor of MHD. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1748717X
Volume :
17
Issue :
1
Database :
Academic Search Index
Journal :
Radiation Oncology
Publication Type :
Academic Journal
Accession number :
155339885
Full Text :
https://doi.org/10.1186/s13014-022-02002-9