Combining Washout and Noncontrast Data From Adrenal Protocol CT: Improving Diagnostic Performance.

Rationale and Objectives: To determine if combination of washout and noncontrast data from delayed adrenal computed tomography (CT) improves diagnostic performance, and demonstration of an optimizing analytical framework.
Materials and Methods: This retrospective study consisted of 97 adrenal lesions, in 96 patients, with pathologically proven adrenal lesions (75 benign; 22 malignant), who had undergone noncontrast, portal- and approximate 15-minute delayed-phase CT. Lesion CT attenuations (Hounsfield units [HU]) during each phase, and "absolute" and "relative" percent enhancement washouts (APEW and RPEW) were assessed. The optimum combination of sequential parameters and thresholds was determined by recursive partitioning analysis; resultant diagnostic performance was compared to commonly applied single-parameter criteria for malignancy (noncontrast > 10 HU, APEW < 60%, RPEW < 40%).
Results: The above single-parameter criteria yielded sensitivities, specificities, and accuracies for malignancy of 100.0%, 41.3%, and 54.6%; 97.9%, 61.3%, and 69.1%; and 96.6%, 74.7%, and 78.4%, respectively. Recursive partitioning analysis identified noncontrast ≥24.75 HU, with subsequent APEW ≤63.49%, as the optimum sequential parameter-threshold combination, which yielded increased sensitivity, specificity, and accuracy of 100.0%, 85.3%, and 90.7%, respectively. Discrimination using the combined sequential classifier yielded statistically significant improvements in accuracy when compared to the above conventional single-parameter criteria (all P ≤ .039).
Conclusion: Sequential application of noncontrast and washout criteria from delayed contrast-enhanced adrenal CT can improve diagnostic performance beyond that of commonly applied single-parameter criteria. Validation of the sequential ordering and refinement of the specific threshold values warrant further study.
(Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)