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Purpose: The study aims to investigate whether including the inflammation-related parameters would enhance the accuracy of a nomogram for local control (LC) prediction in lung cancer patients undergoing stereotactic body radiation therapy (SBRT). Methods: 158 primary or metastatic lung cancer patients treated with SBRT were retrospectively analyzed. The clinical, dosimetric and inflammation-related parameters were collected for the Cox regression analysis. The ACPB model was constructed by employing the clinical and dosimetric factors. And the ACPBLN model was established by adding the inflammation-related factors to the ACPB model. The two models were compared in terms of ROC, Akaike Information Criterion (AIC), C-index, time-dependent AUC, continuous net reclassification index (NRI), integrated discrimination improvement (IDI), calibration plots and decision curve analysis (DCA). Results: Multivariate Cox regression analysis revealed that six prognostic factors were independently associated with LC, including age, clinical stage, planning target volume (PTV) volume, BED of the prescribed dose (BEDPD), the lymphocyte count and neutrocyte count. The ACPBLN model performed better in AIC, bootstrap-corrected C-index, time-dependent AUC, NRI and IDI than the ACPB model. The calibration plots showed good consistency between the probabilities and observed values in the two models. The DCA curves showed that the ACPBLN nomogram had higher overall net benefit than the ACPB model across a majority of threshold probabilities. Conclusion: The inflammation-related parameters were associated with LC for lung cancer patients treated with SBRT. The inclusion of the inflammation-related parameters improved the predictive performance of the nomogram for LC prediction. [ABSTRACT FROM AUTHOR]

Purpose: The study aims to develop and validate a combined model for predicting 3-year cancer-specific survival (CSS) in lung cancer patients treated with stereotactic body radiation therapy (SBRT) by integrating clinical and radiomic parameters. Methods: Clinical data and pre-treatment CT images were collected from 102 patients treated with lung SBRT. Multivariate logistic regression and the least absolute shrinkage and selection operator were used to determine the clinical and radiomic factors associated with 3-year CSS. Three prediction models were developed using clinical factors, radiomic factors, and a combination of both. The performance of the models was assessed using receiver operating characteristic curve and calibration curve. A nomogram was also created to visualize the 3-year CSS prediction. Results: With a 36-month follow-up, 40 patients (39.2%) died of lung cancer and 62 patients (60.8%) survived. Three clinical factors, including gender, clinical stage, and lymphocyte ratio, along with three radiomic features, were found to be independent factors correlated with 3-year CSS. The area under the curve values for the clinical, radiomic, and combined model were 0.839 (95% CI 0.735–0.914), 0.886 (95% CI 0.790–0.948), and 0.914 (95% CI 0.825–0.966) in the training cohort, and 0.757 (95% CI 0.580–0.887), 0.818 (95% CI 0.648–0.929), and 0.843 (95% CI 0.677–0.944) in the validation cohort, respectively. Additionally, the calibration curve demonstrated good calibration performance and the nomogram created from the combined model showed potential for clinical utility. Conclusion: A clinical-radiomic model was developed to predict the 3-year CSS for lung cancer patients treated with SBRT. [ABSTRACT FROM AUTHOR]

Homogeneous target dose distribution in intensity-modulated radiotherapy (IMRT) for sinonasal cancer (SNC) is challenging to achieve. To solve this problem, we established and evaluated a basal-dose-compensation (BDC) optimization approach, in which the treatment plan is further optimized based on the initial plans. Generally acceptable initial IMRT plans for thirteen patients were created and further optimized individually by (1) the BDC approach and (2) a local-dose-control (LDC) approach, in which the initial plan is further optimized by addressing hot and cold spots. We compared the plan qualities, total planning time and monitor units (MUs) among the initial, BDC, LDC IMRT plans and volumetric modulated arc therapy (VMAT) plans. The BDC approach provided significantly superior dose homogeneity/conformity by 23%-48%/6%-9% compared with both the initial and LDC IMRT plans, as well as reduced doses to the organs at risk (OARs) by up to 18%, with acceptable MU numbers. Compared with VMAT, BDC IMRT yielded superior homogeneity, inferior conformity and comparable overall OAR sparing. The planning of BDC, LDC IMRT and VMAT required 30, 59 and 58 minutes on average, respectively. Our results indicated that the BDC optimization approach can achieve significantly better dose distributions with shorter planning time in the IMRT for SNC. [ABSTRACT FROM AUTHOR]