2305 - Dosimetric Impact of CT Simulation vs. Diagnostic CT in Palliative Radiation Therapy Planning in a Low-Resource Clinic: A DVH Analysis

02:30pm - 04:00pm PT

Hall F

Screen: 24

POSTER

Presenter(s)

Baozhou Sun, PhD, MBA - Baylor College of Medicine, Houston, TX

B. Zhou¹, Y. Han¹, A. N. Hanania², D. A. Hamstra¹, Z. A. Siddiqui¹, and B. Sun¹; ¹Department of Radiation Oncology, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, ²Department of Radiation Oncology, Dan. L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX

Purpose/Objective(s):

The morbidity associated with advanced cancer is frequently irreversible. Early administration of palliative radiation can help prevent, delay, or even ameliorate these adverse effects. However, treatment initiation may be postponed due to a congested CT simulation schedule or logistical challenges, such as the expense and inconvenience of arranging ambulance transportation when radiation centers are located off-site. The primary objective was to evaluate the dosimetric differences between CT simulation (CT-SIM) and diagnostic CT (CT-DIAG) for palliative treatment planning of stomach, lung, pelvis, and whole brain cases. We assess the impact on target coverage and organ-at-risk (OAR) sparing using dose-volume histogram (DVH) analysis to determine feasibility and clinical acceptability. Secondary objective looked into how much earlier treatment could start if planned on a diagnostic scan.

Materials/Methods: Radiotherapy planning was performed retrospectively to 35 patients treated palliative (stomach: 9; lung: 11; pelvis: 8; whole brain: 7). For each patient receiving palliative radiation, a recent diagnostic CT scan was imported into the treatment planning system. Image registration focused on planning treatment volumes (PTV) was performed between CT-SIM and CT-DIAG. PTV and organs at risk (OAR) from CT-SIM were copied to CT-DIAG. Treatment plans created on CT-SIM were recalculated on CT-DIAG with identical beam arrangements. These plans will be assessed against their counterparts planned on CT-SIM, focusing on target volume coverage and OAR sparing. Our secondary outcome is the mean time between diagnostic scan and CT simulation.

Results: No significant change in V100 were seen for whole brain (99% for CT-SIM vs. 99% for CT-DIAG, p = 0.87) and pelvis (95.2% for CT-SIM vs. 93.6% for CT-DIAG, p = 0.62). Significant changes in V100 were seen for stomach (94.7% for CT-SIM vs. 80.2% for CT-DIAG, p = 0.02) and lung (94.9% for CT-SIM vs. 85.6% for CT-DIAG, p = 0.01) due to differences in soft tissue delineation and anatomy changes between CT-DIAG and CT-SIM. All OAR constraints were met in both groups. The mean time between diagnostic CT and CT simulation was 9.9 ± 7.4 days for whole brain, 21.6 ± 21.8 days for pelvis, 30.6 ± 29.3 days for stomach and 13.9 ± 15.4 days for lung.

Conclusion: While CT-SIM remains the gold standard for accurate dose calculations, CT-DIAG can be a viable alternative in palliative settings when CT-SIM is unavailable, particularly for whole-brain and simple palliative pelvis treatments. However, significant variations in lung and stomach cases highlight the need for caution. Strategies such as density overrides and image correction techniques should be explored to improve dose accuracy when using CT-DIAG in low-resource clinics.