A Simulation Paradigm for Evaluation of Subtle Liver Lesions at Pediatric CT: Performance and Confidence.

PURPOSE: To create and validate a systematic observer performance platform for evaluation of simulated liver lesions at pediatric CT and to test this paradigm to measure the effect of radiation dose reduction on detection performance and reader confidence. MATERIALS AND METHODS: Thirty normal pediatric (from patients aged 0-10 years) contrast material-enhanced, de-identified abdominal CT scans obtained from July 1, 2012, through July 1, 2016, were retrospectively collected from the clinical database. The study was exempt from institutional review board approval. Zero to three simulated, low-contrast liver lesions (≤6 mm) were digitally inserted by using software, and noise was added to simulate reductions in volume CT dose index (representing radiation dose estimation) of 25% and 50%. Pediatric, abdominal, and resident radiologists (three of each) reviewed 90 data sets in three sessions using an online interface, marking each lesion location and rating confidence (scale, 0-100). Statistical analysis was performed by using software. RESULTS: Mixed-effects models revealed a significant decrease in detection sensitivity as radiation dose decreased (P < .001). The mean confidence of the full-dose and 25% dose reduction examinations was significantly higher than that of the 50% dose reduction examinations (P = .011 and .012, respectively) but not different from one another (P = .866). Dose was not a significant predictor of time to complete each case, and subspecialty was not a significant predictor of sensitivity or false-positive results. CONCLUSION: Sensitivity for lesion detection significantly decreased as dose decreased; however, confidence did not change between the full-dose and 25% reduced-dose scans. This suggests that readers are unaware of this decrease in performance, which should be accounted for in clinical dose reduction efforts.Keywords: Abdomen/GI, CT, Liver, Observer Performance, Pediatrics, Perception Image© RSNA, 2019.

Duke Scholars

Author Ehsan Samei Radiology

Author Alaattin Erkanli Biostatistics & Bioinformatics, Division of Biostatistics

Author Brian C Allen Radiology, Abdominal Imaging

Author Daniele Marin Radiology, Abdominal Imaging

Author Charles Mason Maxfield Radiology, Pediatric Radiology

Author Donald Paul Frush Radiology, Pediatric Radiology