Factors Influencing Unplanned Repeat CT Simulations in Radiotherapy: A Retrospective Analysis of Clinical Impact and Disease-Specific Causes

Abstract

Aims and Objectives: This study investigates the factors necessitating unplanned repeat computed tomography (CT) simulations in radiotherapy and evaluates their clinical impact on treatment delivery, particularly in terms of treatment delays and disease-specific causes.
Materials and Methods: A single-arm retrospective study was conducted, analyzing medical records of 1,329 patients who underwent CT simulation for radiotherapy at the Barnard Institute of Radiation Oncology, Madras Medical College, between January 2022 and December 2022. Of these, 32 patients required repeat simulations. Factors analyzed included disease site, stage, anatomical changes (e.g., weight loss/gain), immobilization issues, and tumor/nodal shrinkage. Initial CT images were compared with cone-beam CT (CBCT) images taken every fifth day during radiotherapy. Statistical significance was assessed using univariate binomial regression with odds ratios (OR) and chi-square testing (p < 0.05 considered significant).
Results: Of the 32 patients requiring repeat simulations, 15 were male, 14 were female, and 3 were pediatric. The overall resimulation rate was 2.4%, with a median duration of 28 days post-initial simulation and a median treatment delay of 8 days (range: 5–23 days). Head and neck cancers were the most common site requiring resimulation (n = 26, p < 0.05, OR = 1.93, 95% CI [0.95, 3.85]), primarily due to tumor/nodal shrinkage. Gynecological malignancies (n = 14, p = 0.11, OR = 1.64, 95% CI [0.89, 3.02]) were predominantly influenced by soft tissue changes, while central nervous system (CNS) malignancies (n = 10, p < 0.05, OR = 1.93, 95% CI [0.96, 3.85]) were associated with weight gain. Resimulations occurred at a median of the 22nd fraction (range: 12–27 fractions).
Conclusion: Unplanned repeat CT simulations, though infrequent (2.4%), significantly impact treatment timelines, with head and neck cancers being the most affected site. Understanding disease-specific factors can inform strategies to minimize resimulations, optimize resource utilization, and reduce treatment delays, thereby enhancing radiotherapy quality.