Diane M Renz

Publications (2)5.92 Total impact

• Article: Correlation of contrast agent kinetics between iodinated contrast-enhanced spectral tomosynthesis and gadolinium-enhanced MRI of breast lesions.

  Vera Froeling, Felix Diekmann, Diane M Renz, Eva M Fallenberg, Ingo G Steffen, Susanne Diekmann, Rüdiger Lawaczeck, Florian F Schmitzberger
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  ABSTRACT: OBJECTIVES: Assessment of contrast agent kinetics in contrast-enhanced MRI (CE-MRI) with gadolinium-containing contrast agents offers the opportunity to predict breast lesion malignancy. The goal of our study was to determine if similar patterns exist for spectral contrast-enhanced digital breast tomosynthesis (CE-DBT) using an iodinated contrast agent. METHODS: The protocol of our prospective study was approved by the relevant institutional review board and the German Federal Office for Radiation Protection. All patients provided written informed consent. We included 21 women with a mean age of 62.4 years. All underwent ultrasound-guided biopsy of a suspect breast lesion, spectral CE-DBT and CE-MRI. For every breast lesion, contrast agent kinetics was assessed by signal intensity-time curves for spectral CE-DBT and CE-MRI. Statistical comparison used Cohen's kappa and Spearman's rho test. RESULTS: Spearman's rho of 0.49 showed significant (P = 0.036) correlation regarding the contrast agent kinetics in signal intensity-time curves for spectral CE-DBT and CE-MRI. Cohen's kappa indicated moderate agreement (kappa = 0.438). CONCLUSION: There is a statistically significant correlation between contrast agent kinetics in the signal intensity-time curves for spectral CE-DBT and CE-MRI. Observing intralesional contrast agent kinetics in spectral CE-DBT may aid evaluation of malignant breast lesions. KEY POINTS : • Contrast agent kinetics can be assessed using spectral digital breast tomosynthesis (DBT). • Contrast agent kinetics patterns in spectral DBT are similar to those in contrast-enhanced MRI. • Multiple contrast enhancement for spectral DBT gives additional diagnostic information.
  European Radiology 01/2013; · 3.22 Impact Factor
• Article: Detection and classification of contrast-enhancing masses by a fully automatic computer-assisted diagnosis system for breast MRI.

  Diane M Renz, Joachim Böttcher, Felix Diekmann, Alexander Poellinger, Martin H Maurer, Alexander Pfeil, Florian Streitparth, Federico Collettini, Ulrich Bick, Bernd Hamm, Eva M Fallenberg
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  ABSTRACT: To evaluate a fully automatic computer-assisted diagnosis (CAD) method for breast magnetic resonance imaging (MRI), which considered dynamic as well as morphologic parameters and linked those to descriptions laid down in the Breast Imaging Reporting and Data System (BI-RADS) MRI atlas. MR images of 108 patients with 141 histologically proven mass-like lesions (88 malignant, 53 benign) were included. The CAD system automatically performed the following processing steps: 3D nonrigid motion correction, detection of lesions by a segmentation algorithm, extraction of multiple dynamic and morphologic parameters, and classification of lesions. As one final result, the lesions were categorized by defining their probability of malignancy; this so-called morpho-dynamic index (MDI) ranged from 0%-100%. The results of the CAD system were correlated with histopathologic findings. The CAD system had a high detection rate of the histologically proven lesions, missing only two malignancies of invasive multifocal carcinomas and four benign lesions (three fibroadenomas, one atypical ductal hyperplasia). The 86 detected malignant lesions showed a mean MDI of 86.1% (± 15.4%); the mean MDI of the 49 coded benign lesions was 41.8% (± 22.0%; P < 0.001). Based on receiver-operating characteristic analysis, the diagnostic accuracy of the CAD system was 93.5%. Using an appropriate cutoff value (MDI 50%), sensitivity was 96.5% combined with specificity of 75.5%. The fully automatic CAD technique seems to reliably distinguish between benign and malignant mass-like breast tumors. Observer-independent CAD may be a promising additional tool for the interpretation of breast MRI in the clinical routine.
  Journal of Magnetic Resonance Imaging 01/2012; 35(5):1077-88. · 2.70 Impact Factor