Author: Kim Creach, Kim Howard, Julius G. Ojwang, Richard A. Shaw, Neelu Soni 👨🔬
Affiliation: Mercy Hospital Springfield 🌍
Purpose: To present a standardized MRI-CT hybrid workflow for High-Dose-Rate (HDR) Image-Guided Adaptive Brachytherapy (IGBT) in cervical cancer, aligned with AAPM TG-303, as a model to assist with implementation in other clinics.
Methods: High-resolution T1- and T2-weighted MRI sequences (1 mm slice thickness) were utilized during the first fraction to delineate the high-risk clinical target volume (HR-CTV) and organs at risk (OARs). A thin-slice CT imaging protocol was employed for all fractions to verify applicator positioning and ensure consistent dose delivery. Adaptive treatment planning incorporating solid applicator models, dwell position optimization, and adherence to Equivalent Dose in 2 Gy per fraction (EQD2) metrics as defined by ABS and EMBRACE guidelines, was conducted using BrachyVision TPS.
Workflow standardization incorporated electronic medical records (EMR), structured directives per 10 CFR 35.40, and safety checklists to ensure consistency in planning, delivery, and documentation. A risk-based quality assurance (QA) program—featuring routine imaging QA (e.g., geometric and spatial accuracy checks), applicator commissioning with a custom in-house phantom on both MRI and CT (tissue-equivalent materials), and treatment plan validation—minimized variability and ensured treatment quality.
Results: The MRI-CT workflow enhanced tumor and OAR delineation, ensuring accurate applicator reconstruction within 1 mm and optimal dose distribution. The dose delivered to 90% of the HR-CTV volume (HR-CTV D90%) consistently met prescribed targets while maintaining OAR EQD2 D2cc thresholds (bladder D2cc ≤90 Gy, rectum and sigmoid D2cc ≤75 Gy), thereby reducing the risk of gastrointestinal toxicity. Compared to CT-only workflows, this approach reduced planning time by 35% and decreased patient in-hospital time by 25%, enhancing clinical throughput and safety.
Conclusion: This standardized workflow offers a replicable framework for TG-303 compliant HDR brachytherapy and is ready for clinical adoption. Future integration of automated scripting, deep learning, and standardized planning templates will further enhance workflow efficiency and patient outcomes.