Doses in planning computed tomography in one radiotherapy department: Description of exposure parameters and estimation of organ doses, effective doses and typical doses

Introduction Computed tomography (CT) used in radiotherapy (RT) planning involves complex acquisitions protocols, making it essential to evaluate doses and ensure patients' radiological safety. This study aims to evaluate organ doses based on RT planning CT scans, Effective Doses (ED), and Typical Doses, in a Portuguese RT department. Methods The sample included 151 patients who underwent planning CT using the General Electric (GE) Discovery ™ RT scanner. Dosimetric estimates were obtained with the National Cancer Institute Dosimetry System for Computed Tomography (NCICT). For each examination, acquisition parameters, patient anatomical diameters, Volume Computed Tomography Dose Index (CTDI vol ), Dose-Length Product (DLP), organ absorbed doses, and ED were analysed. Results Typical Dose values were proposed, based on the 50th percentile of CTDI vol and DLP distributions of the main RT protocols: head and neck (H&N), central nervous system (CNS), breast, breast and axilla, breast deep inspiration breath hold (DIBH), 4D lung, stereotactic body radiation therapy (SBRT) lung and prostate. Results were compared with the literature, to assess practice and identify optimization areas. Conclusion These findings improve understanding of local practices and highlight the importance of periodic protocol evaluation. Furthermore, this study provides a basis for dose optimization strategies and supports the definition of diagnostic reference levels (DRL) in RT services. Implication for practice This study demonstrates the importance of evaluating and monitoring CT protocols in RT planning to ensure patient safety and minimize radiation exposure. The analysis of organ doses, ED, and local DRL provides concrete values reflecting current practice. These findings can guide protocol adjustments, support definition of typical dose levels and contribute to future optimisation strategies in RT.