Regression models for predicting physical and EQD(2) plan parameters of two methods of hybrid planning for stage III NSCLC

BACKGROUND/PURPOSE: To establish regression models of physical and equivalent dose in 2 Gy per fraction (EQD(2)) plan parameters of two kinds of hybrid planning for stage III NSCLC. METHODS: Two kinds of hybrid plans named conventional fraction radiotherapy & stereotactic body radiotherapy (C&S) and conventional fraction radiotherapy & simultaneous integrated boost (C&SIB) were retrospectively made for 20 patients with stage III NSCLC. Prescription dose of C&S plans was 2 Gy × 30f for planning target volume of lymph node (PTV(LN)) and 12.5 Gy × 4f for planning target volume of primary tumor (PTV(PT)), while prescription dose of C&SIB plans was 2 Gy × 26f for PTV(LN) and sequential 2 Gy × 4f for PTV(LN) combined with 12.5 Gy × 4f for PTV(PT). Regression models of physical and EQD(2) plan parameters were established based on anatomical geometry features for two kinds of hybrid plans. The features were mainly characterized by volume ratio, min distance and overlapping slices thickness of two structures. The possibilities of regression models of EQD(2) plan parameters were verified by spearman’s correlation coefficients between physical and EQD(2) plan parameters, and the influence on the consistence of fitting goodness between physical and EQD(2) models was investigated by the correlations between physical and EQD(2) plan parameters. Finally, physical and EQD(2) models predictions were compared with plan parameters for two new patients. RESULTS: Physical and EQD(2) plan parameters of PTV(LN) CI(60Gy) have shown strong positive correlations with PTV(LN) volume and min distance((PT to LN)), and strong negative correlations with PTV(PT) volume for two kinds of hybrid plans. PTV((PT+LN)) CI(60Gy) is not only correlated with above three geometry features, but also negatively correlated with overlapping slices thickness((PT and LN)). When neck lymph node metastasis was excluded from PTV(LN) volume, physical and EQD(2) total lung V(20) showed a high linear correlation with corrected volume ratio((LN to total lung).) Meanwhile, physical total lung mean dose (MLD) had a high linear correlation with corrected volume ratio((LN to total lung)), while EQD(2) total lung MLD was not only affected by corrected volume ratio((LN to total lung)) but also volume ratio((PT to total lung).) Heart D(5), D(30) and mean dose (MHD) would be more susceptible to overlapping structure((heart and LN)). Min distance((PT to ESO)) may be an important feature for predicting EQD(2) esophageal max dose for hybrid plans. It’s feasible for regression models of EQD(2) plan parameters, and the consistence of the fitting goodness of physical and EQD(2) models had a positive correlation with spearman’s correlation coefficients between physical and EQD(2) plan parameters. For total lung V(20), ipsilateral lung V(20), and ipsilateral lung MLD, the models could predict that C&SIB plans were higher than C&S plans for two new patients. CONCLUSION: The regression models of physical and EQD(2) plan parameters were established with at least moderate fitting goodness in this work, and the models have a potential to predict physical and EQD(2) plan parameters for two kinds of hybrid planning. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13014-021-01848-9.