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Characterizing T2 iso- and hypo-intense renal masses on MRI: Can templated algorithms improve accuracy?

Published:November 05, 2020DOI:https://doi.org/10.1016/j.clinimag.2020.10.051

      Highlights

      • Algorithms perform similarly to trained subspecialists in diagnosing T2 iso- and hypointense renal mass.
      • Higher inter-reader agreement with algorithm utilization likely due to use of quantitative MR parameters
      • Substantial diagnosis-limiting overlap in the MR appearance of T2 iso- and hypointense renal masses

      Abstract

      Purpose

      To assess if a templated algorithm can improve the diagnostic performance of MRI for characterization of T2 isointense and hypointense renal masses.

      Methods

      In this retrospective study, 60 renal masses with histopathologic diagnoses that were also confirmed as T2 iso- or hypointense on MRI were identified (mean ± standard deviation, range: 3.9 ± 2.5, 1.0–13.7 cm). Two semi-quantitative diagnostic algorithms were created based on MRI features of renal masses reported in the literature. Three body-MRI trained radiologists provided clinical diagnoses based on their experience and separately provided semiquantitative data for each components of the two algorithms. The algorithms were applied separately by a radiology trainee without additional interpretive input. Logistic regression was used to compare the accuracy of the three methods in distinguishing malignant versus benign lesions and in diagnosing the exact histopathology. Inter-reader agreement for each method was calculated using Fleiss' kappa statistics.

      Results

      The accuracy of the two algorithms and clinical experience were similar (70%, 69%, and 64%, respectively, p = 0.22–0.32), with fair to moderate inter-reader agreement (Fleiss's kappa: r = 0.375, r = 0.308, r = 0.375, respectively, all p < 0.0001). The accuracy of the two algorithms and clinical experience in diagnosing specific histopathology were also no different from each other (34%, 29%, and 32%, respectively, p = 0.49–0.74), with fair to moderate inter-reader agreement (Fleiss's kappa: r = 0.20, r = 0.28, r = 0.375, respectively, all p < 0.0001).

      Conclusion

      Semi-quantitative templated algorithms based on MRI features of renal masses did not improve the ability to diagnose T2 iso- and hypointense renal masses when compared to unassisted interpretation by body MR trained subspecialists.

      Keywords

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