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    AJR Am J Roentgenol. 2006 Mar;186(3):665-72.

    Enhancing component on CT to predict malignancy in cystic renal masses and interobserver agreement of different CT features.

    Source

    Present address: Department of Medical Imaging, Rabin Medical Center, Beilinson Campus, Sackler School of Medicine, University of Tel-Aviv, Jabutinsky St., Petach Tikva, Israel, 49100.

    Abstract

    OBJECTIVE:

    The objective of our study was to determine the CT features of complex cystic renal masses that are the most predictive of malignancy and to assess interobserver variability when interpreting these features.

    MATERIALS AND METHODS:

    Two radiologists blinded to pathology results retrospectively reviewed CT scans of 36 consecutive cystic renal masses in 30 patients (19 men and 11 women; age range, 28-76 years; mean age, 59 +/- 13 years) who had undergone surgery. The study population included only masses with a cystic component on gross pathology and imaging. All patients underwent contrast-enhanced CT. The reviewers recorded the CT features of each cystic mass, including the presence of enhancing components. Accuracy values and odds ratio to predict malignancy were calculated for each CT feature. Weighted kappa was used to measure interobserver agreement.

    RESULTS:

    There were 21 cystic renal cell cancers and 11 benign cystic lesions. All cystic renal cell carcinomas showed an enhancing septal or nodular component. The mean sensitivity and specificity of the two reviewers in predicting malignancy for the presence of septal enhancement were 83% (95% confidence interval [CI], 65-93%) and 82% (95% CI, 56-94%); for nodular enhancement, 67% (95% CI, 49-81%) and 96% (95% CI, 75-99%); and for either septal or nodular enhancement, 100% (95% CI, 86-100%) and 86% (95% CI, 67-95%), respectively. The interobserver agreements for septal and nodular enhancement were good (kappa = 0.67) and moderate (kappa = 0.57), respectively.

    CONCLUSION:

    The presence of either nodular or septal enhancement shows the highest sensitivity for predicting malignancy with moderate to good interobserver agreement.

    PMID:
    16498093
    [PubMed - indexed for MEDLINE]
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