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Three-Tesla dynamic contrast-enhanced MRI: a critical assessment of its use for differentiation of renal lesion subtypes
Authors:S Sevcenco  L Ponhold  D Javor  F E Kuehhas  J Mauermann  A Miernik  M Schoenthaler  P A Baltzer
Institution:1. Department of Urology, Medical University of Vienna, W?hringer Gürtel 18-20, 1090, Vienna, Austria
2. Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, W?hringer Gürtel 18-20, 1020, Vienna, Austria
3. Department of Urology, Medical University of Freiburg, Hugstetter Stra?e 49, 79106, Freiburg, Germany
Abstract:

Purpose

To evaluate the ability of dynamic contrast-enhanced (DCE) 3-T MRI for preoperative differentiation between benign and malignant renal tumors and RCC subtypes.

Methods

Sixty consecutive patients undergoing preoperative DCE 3-T MRI of the kidney were evaluated in this retrospective IRB-approved evaluation. Fifty-four malignant tumors and 17 benign tumors upon surgical verification were included. Relative enhancement values of complete lesions and the most enhancing part of the lesions (hotspot) were measured using four repetitions: precontrast, arterial, venous, and delayed.

Results

Mean relative enhancement patterns between malignant and benign lesions did not differ significantly during any postcontrast phase (p > 0.05). The highest mean enhancement during all postcontrast phases was identified in clear cell RCC followed by chromophobic RCC. The enhancement pattern in papillary RCC was significantly less than that of non-papillary RCC lesions. Arterial enhancement was an independent predictor for RCC subtypes (papillary vs. non-papillary, p = 0.008). The diagnostic accuracy for differentiation of papillary from non-papillary RCC based on ROC analysis was 76.4 % 95 % CI 62.2–87.2 %]; p < 0.0001.

Conclusions

Dynamic contrast-enhanced MRI at 3 T showed intermediate diagnostic capability for differentiation between papillary and non-papillary RCC subtypes but could not differentiate between benign and malignant renal lesions.
Keywords:
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