Abstract:
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.
journal_name
Acad Radioljournal_title
Academic radiologyauthors
Ng CS,Altinmakas E,Wei W,Ghosh P,Li X,Grubbs EG,Perrier NA,Prieto VG,Lee JE,Hobbs BPdoi
10.1016/j.acra.2017.12.005subject
Has Abstractpub_date
2018-07-01 00:00:00pages
861-868issue
7eissn
1076-6332issn
1878-4046pii
S1076-6332(17)30515-9journal_volume
25pub_type
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