Impact of delivery time factor on treatment time and plan quality in tomotherapy

Development and validation of an automated Tomotherapy planning method for cervical cancer

PURPOSE

This study aimed to develop an automated Tomotherapy (TOMO) planning method for cervical cancer treatment, and to validate its feasibility and effectiveness.

MATERIALS AND METHODS

The study enrolled 30 cervical cancer patients treated with TOMO at our center. Utilizing scripting and Python environment within the RayStation (RaySearch Labs, Sweden) treatment planning system (TPS), we developed automated planning methods for TOMO and volumetric modulated arc therapy (VMAT) techniques. The clinical manual TOMO (M-TOMO) plans for the 30 patients were re-optimized using automated planning scripts for both TOMO and VMAT, creating automated TOMO (A-TOMO) and automated VMAT (A-VMAT) plans. We compared A-TOMO with M-TOMO and A-VMAT plans. The primary evaluated relevant dosimetric parameters and treatment plan efficiency were assessed using the two-sided Wilcoxon signed-rank test for statistical analysis, with a P-value < 0.05 indicating statistical significance.

RESULTS

A-TOMO plans maintained similar target dose uniformity compared to M-TOMO plans, with improvements in target conformity and faster dose drop-off outside the target, and demonstrated significant statistical differences (P+ < 0.01). A-TOMO plans also significantly outperformed M-TOMO plans in reducing V50Gy, V40Gy and Dmean for the bladder and rectum, as well as Dmean for the bowel bag, femoral heads, and kidneys (all P+ < 0.05). Additionally, A-TOMO plans demonstrated better consistency in plan quality. Furthermore, the quality of A-TOMO plans was comparable to or superior than A-VMAT plans. In terms of efficiency, A-TOMO significantly reduced the time required for treatment planning to approximately 20 min.

CONCLUSION

We have successfully developed an A-TOMO planning method for cervical cancer. Compared to M-TOMO plans, A-TOMO plans improved target conformity and reduced radiation dose to OARs. Additionally, the quality of A-TOMO plans was on par with or surpasses that of A-VMAT plans. The A-TOMO planning method significantly improved the efficiency of treatment planning.

Comparing Efficacy Between Robust and PTV Margin-based Optimizations for Interfractional Anatomical Variations in Prostate Tomotherapy

BACKGROUND/AIM

Interfractional anatomical variations cause considerable differences between planned and actual radiotherapy doses. This study aimed to investigate the efficacy of robust and planning target volume (PTV) margin-based optimizations for the anatomical variations in helical tomotherapy for prostate cancer.

PATIENTS AND METHODS

Ten patients underwent treatment-planning kilovolt computed tomography (kVCT) and daily megavolt computed tomography (MVCT). Two types of nominal plans, with a prescription of 60 Gy/20 fractions, were created using robust and PTV margin-based optimizations on kVCT for each patient. Subsequently, the daily estimated doses were recalculated using nominal plans, and all available MVCTs modified the daily patient-setup errors. Due to the difference in dose calculation accuracy between kVCT and MVCT, three scenarios with dose corrections of 1, 2, and 3% were considered in the recalculation process. The dosimetric metrics, including target coverage with the prescription dose, Paddick's conformity index, homogeneity index, and mean dose to the rectum, were analyzed.

RESULTS

A dosimetric comparison of the nominal plans demonstrated that the robust plans had better dose conformity, lower target coverage, and dose homogeneity than the PTV plans. In the daily estimated doses of any dose-corrected scenario, the target coverage and dose sparing to the rectum in the robust plans were significantly higher than those in the PTV plans, whereas dose conformity and homogeneity were identical to those of the nominal case.

CONCLUSION

Robust optimization is recommended as it accounts for anatomical variations during treatment regarding target coverage in helical tomotherapy plans for prostate cancer.