Feasibility Study on Constructing Dosimetric Correlated Geometric Parameters for Automatic Segmentation Evaluation.

PURPOSE: To investigate the feasibility of constructing new geometric parameters that correlate well with dosimetric parameters. METHODS: 100 rectal cancer patients were enrolled. The targets were identified manually, while the organs at risk (bladder, small bowel, left and right femoral heads) were segmented both manually and automatically. The radiotherapy plans were optimized according to the automatically contoured organs at risk. Forty cases were randomly selected to establish the relationship between dose and distance for each organ at risk, termed "dose-distance curves," which were then applied to the new geometric parameters. The correlation between these new geometric parameters and dosimetric parameters was analyzed in the remaining 60 test cases. RESULTS: The "dose-distance curves" were similar across the four organs at risk, exhibiting an inverse function shape with a rapid decrease initially and a slower rate at a later stage. The Pearson correlation coefficients of new geometric parameters and dosimetric parameters in the bladder, small intestine, and left and right femur heads were 0.96, 0.97, 0.88, and 0.70, respectively. CONCLUSIONS: The new geometric parameters predicated on "distance from the target" showed a high correlation with corresponding dosimetric parameters in rectal cancer cases. It is feasible to utilize the new geometric parameters to evaluate the dose deviation attributable to automatic segmentation.

Risk factors for brain metastases in locally advanced non-small cell lung cancer patients treated with radical radiotherapy.

Background: Brain metastases (BM) happen frequently in lung cancer patients and lead to a poor prognosis as well as a lower quality of life. The aim of this study was to identify risk factors for BM in locally advanced non-small cell lung cancer (LA-NSCLC) patients receiving radical radiotherapy, which will be useful for selecting appropriate patient population for further intervention and future trial design. Methods: This was a retrospective cohort study. Patients with inoperable stage IIB-IIIC NSCLC were treated consecutively with definitive thoracic radiotherapy from January 2018 to December 2021, and were retrospectively reviewed and enrolled. Patients with various clinical variables were analyzed to clarify their impact on BM with competing risk models by Fine and Gray. Results: A total of 134 patients were enrolled in this study. The median follow-up for all patients was 37 months [95% confidence interval (CI): 30.5-43.5 months]. BM occurred in 25 patients at the time of analysis. The 1-year and 3-year cumulative BM incidence were 10.5% and 19.9%, respectively. Patients with BM had worse overall survival than those without BM [stratified hazard ratio (HR) for death: 2.83; 95% CI:1.31-6.11; P<0.001]. Based on univariate analyses, non-squamous cell carcinoma (non-SCC), biological effective dose (BED) and planning target volume (PTV) were used as input variables in multivariable analysis (P<0.01). According to multivariate analysis, non-SCC (P<0.001; HR: 6.08; 95% CI: 2.26-16.37), BED <72 Gy (P=0.017; HR: 2.81; 95% CI: 1.20-6.57), and PTV >157.73 cm3 (P=0.043; HR: 2.56; 95% CI: 1.03-6.35) were independent risk factors for BM. In subgroup analysis of adenocarcinoma with known epidermal growth factor receptor (EGFR) mutation status, PTV >157.73 cm3 and positive EGFR mutation were independent predictors for BM. Conclusions: In this retrospective study, we found that BED <72 Gy and PTV >157.73 cm3 were significantly associated with BM development and we validated that non-SCC and positive EGFR mutation were risk factors for BM. More research is required to screen the high-risk patient population.

[Feasibility Study of Beam Angle Optimization Based on Scripts in Automated-planning for Liver Cancer].

OBJECTIVE: To study the feasibility and potential benefits of beam angle optimization (BAO) to automated planning in liver cancer. METHODS: An approach of beam angle sampling is proposed to implement BAO along with the module Auto-planning in treatment planning system (TPS) Pinnacle. An in-house developed plan quality metric (PQM) is taken as the preferred evaluating method during the sampling. The process is driven automatically by in-house made Pinnacle scripts both in sampling and scoring. In addition, dosimetry analysis and physician's opinion are also performed as the supplementary and compared with the result of PQM. RESULTS: It is revealed by the numerical analysis of PQM scores that only 15% patients whose superior trials evaluated by PQM are also the initial trials. Gantry optimization can bring benefit to plan quality along with auto-planning in liver cancer. Similar results are provided by both dose comparison and physician's opinion. CONCLUSIONS: It is possible to introduce a full automated approach of beam angle optimization to automated planning process. The advantages of this procedure can be observed both in numerical analysis and physician's opinion.

A knowledge-based approach to automated planning for hepatocellular carcinoma.

PURPOSE: To build a knowledge-based model of liver cancer for Auto-Planning, a function in Pinnacle, which is used as an automated inverse intensity modulated radiation therapy (IMRT) planning system. METHODS AND MATERIALS: Fifty Tomotherapy patients were enrolled to extract the dose-volume histograms (DVHs) information and construct the protocol for Auto-Planning model. Twenty more patients were chosen additionally to test the model. Manual planning and automatic planning were performed blindly for all twenty test patients with the same machine and treatment planning system. The dose distributions of target and organs at risks (OARs), along with the working time for planning, were evaluated. RESULTS: Statistically significant results showed that automated plans performed better in target conformity index (CI) while mean target dose was 0.5 Gy higher than manual plans. The differences between target homogeneity indexes (HI) of the two methods were not statistically significant. Additionally, the doses of normal liver, left kidney, and small bowel were significantly reduced with automated plan. Particularly, mean dose and V15 of normal liver were 1.4 Gy and 40.5 cc lower with automated plans respectively. Mean doses of left kidney and small bowel were reduced with automated plans by 1.2 Gy and 2.1 Gy respectively. In contrast, working time was also significantly reduced with automated planning. CONCLUSIONS: Auto-Planning shows availability and effectiveness in our knowledge-based model for liver cancer.

Constraints for symptomatic radiation pneumonitis of helical tomotherapy hypofractionated simultaneous multitarget radiotherapy for pulmonary metastasis from hepatocellular carcinoma.

BACKGROUND AND PURPOSE: This study was aimed to identify the clinical and dosimetric parameters that predict symptomatic radiation pneumonitis (SRP, radiation pneumonitis≥2 grade) in patients with pulmonary metastasis from hepatocellular carcinoma (HCC) after helical tomotherapy (HT) hypofractionated simultaneous multitarget radiotherapy. MATERIALS AND METHODS: 62 patients with 407 pulmonary metastases from HCC were consecutively treated with HT. The median radiation dose was a 49.7Gy in 4.0Gy/fraction to 95% of the planning target volume (PTV). The associations between the clinical and dosimetric data and incidences of SRP were analyzed. The dose-pneumonitis relationship was analyzed based on Biologically Effective Dose (BED). RESULTS: Univariate analysis showed that the gross tumor volume (GTV), PTV, median lung dose (MLD), the number of pulmonary metastatic lesions (NPML), and the percentage of non-target normal lung (NTNL) volume receiving more than a BED of 3-50Gy (VBED3-50) were associated with SRP. Multivariate logistic regression analysis showed that VBED20 and NPML were significant parameters (both P<0.001) CONCLUSIONS: Our findings indicated that SRP can be predicted with NPML>5 and VBED20≥30.4% with the α/ß ratio of 3Gy.