David Larson

Publication Details

  • System for Verifiable CT Radiation Dose Optimization Based on Image Quality. Part II. Process Control System RADIOLOGY Larson, D. B., Malarik, R. J., Hall, S. M., Podberesky, D. J. 2013; 269 (1): 177-185


    To evaluate the effect of an automated computed tomography (CT) radiation dose optimization and process control system on the consistency of estimated image noise and size-specific dose estimates (SSDEs) of radiation in CT examinations of the chest, abdomen, and pelvis.This quality improvement project was determined not to constitute human subject research. An automated system was developed to analyze each examination immediately after completion, and to report individual axial-image-level and study-level summary data for patient size, image noise, and SSDE. The system acquired data for 4 months beginning October 1, 2011. Protocol changes were made by using parameters recommended by the prediction application, and 3 months of additional data were acquired. Preimplementation and postimplementation mean image noise and SSDE were compared by using unpaired t tests and F tests. Common-cause variation was differentiated from special-cause variation by using a statistical process control individual chart.A total of 817 CT examinations, 490 acquired before and 327 acquired after the initial protocol changes, were included in the study. Mean patient age and water-equivalent diameter were 12.0 years and 23.0 cm, respectively. The difference between actual and target noise increased from -1.4 to 0.3 HU (P < .01) and the standard deviation decreased from 3.9 to 1.6 HU (P < .01). Mean SSDE decreased from 11.9 to 7.5 mGy, a 37% reduction (P < .01). The process control chart identified several special causes of variation.Implementation of an automated CT radiation dose optimization system led to verifiable simultaneous decrease in image noise variation and SSDE. The automated nature of the system provides the opportunity for consistent CT radiation dose optimization on a broad scale.

    View details for DOI 10.1148/radiol.13122321

    View details for Web of Science ID 000325000700020

    View details for PubMedID 23784877

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