Evaluating Dose Optimization in Pediatric Radiography at Sunshine Children's Hospital

Thesis Abstract

Pediatric radiography is essential for accurate diagnosis yet presents unique challenges in balancing diagnostic quality with minimizing radiation exposure for a vulnerable population. This study addresses the persistent problem of suboptimal dose optimization practices in pediatric radiography at Sunshine Children’s Hospital, where variability in protocols and limited standardization can lead to unnecessary radiation exposure without commensurate diagnostic benefit. The aim is to evaluate current dose optimization practices, quantify exposure levels, and identify factors that influence optimization outcomes to inform targeted improvements. The specific objectives are (1) to assess adherence to pediatric-specific dose protocols across radiography units; (2) to quantify patient entrance skin dose (ESD) and effective dose in routine pediatric procedures; (3) to evaluate the relationship between technical parameters (kVp, mAs, compression, and automatic exposure control usage) and image quality using objective and subjective metrics; (4) to examine radiographer knowledge, attitudes, and training related to dose optimization; (5) to identify organizational and workflow factors that facilitate or hinder dose optimization; and (6) to develop evidence-based recommendations to refine protocols, training, and quality assurance processes. The study adopts a mixed-methods design, integrating quantitative dose measurements and image quality assessments with qualitative insights from staff. The population comprises all pediatric radiography examinations conducted at Sunshine Children’s Hospital over a 12-month period, with a stratified random sample of 600 radiographs (covering chest, abdomen, spine, and extremities) and a purposive sample of 24 radiographers and 6 radiology department supervisors for interviews. Data collection instruments include calibrated dose meters and dosimetry software to record ESD, dose-area product (DAP), and exposure parameters; standardized image quality scores using the IHEM (Image Quality Evaluation in Medical Imaging) framework; a validated radiographer knowledge and practice questionnaire; and semi-structured interview guides. Validity and reliability will be ensured through calibration of dosimeters, pilot testing of the image quality rubric, and triangulation of survey data with interview responses. Quantitative data will be analyzed using descriptive statistics, correlation analyses, and multiple linear regression to model the association between technical parameters and image quality while controlling for patient age and body part. Dose optimization will be evaluated against established diagnostic reference levels (DRLs) for pediatrics. Qualitative data will undergo thematic analysis guided by Braun and Clarke's approach to identify drivers of optimization practices, barriers, and facilitators, with findings integrated to illuminate contextual factors shaping dose optimization. The theoretical framework draws on the Theory of Planned Behavior to interpret radiographers’ practices, and the Diffusion of Innovations theory to understand adoption of optimized protocols across shifts and units, complemented by the Health Belief Model to contextualize staff perceptions of radiation risk. Expected findings include (a) variability in adherence to pediatric dose protocols and higher-than-DRL instances in units without standardized pediatric protocol prompts; (b) a measurable reduction in ESD and DAP when optimized automatic exposure control and pediatric-specific settings are consistently applied; (c) a positive correlation between higher radiation safety training scores and adherence to optimization practices; (d) identification of workflow-related barriers such as time pressure and equipment calibration gaps, and enablers including integrated protocol prompts and regular feedback loops; and (e) a validated checklist for dose optimization enhancements tailored to Sunshine Children’s Hospital. The study contributes to knowledge by providing context-specific evidence on dose optimization dynamics in a high-volume pediatric radiography setting, validating a mixed-methods framework for evaluating optimization outcomes, and offering a practical, scalable model for protocol refinement and continuous quality improvement. The main conclusion anticipated is that systematic protocol standardization, strengthened training, and real-time dose monitoring synergistically reduce pediatric patient radiation exposure without compromising diagnostic image quality. Recommendations include implementing a hospital-wide pediatric protocol library with automated prompts, mandatory quarterly dose audits linked to DRLs, comprehensive targeted training for radiographers, ensuring regular automatic calibration of imaging systems, and establishing an interdisciplinary dose optimization committee to sustain continuous improvement.