51. Influence of residual fat signal on diffusion kurtosis MRI of suspicious mammography findings
- Author
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Franziska König, Tristan Anselm Kuder, Heinz-Peter Schlemmer, Heidi Daniel, Wolfgang Lederer, Stefan Delorme, Frederik Bernd Laun, Anna Mlynarska-Bujny, Mark E. Ladd, and Sebastian Bickelhaupt
- Subjects
0301 basic medicine ,Adult ,lcsh:Medicine ,Signal-To-Noise Ratio ,Residual ,Article ,03 medical and health sciences ,0302 clinical medicine ,Breast cancer ,Medical research ,Image Interpretation, Computer-Assisted ,Image Processing, Computer-Assisted ,Medicine ,Mammography ,Humans ,ddc:610 ,Diffusion (business) ,lcsh:Science ,Diffusion Kurtosis Imaging ,Retrospective Studies ,Multidisciplinary ,Receiver operating characteristic ,medicine.diagnostic_test ,business.industry ,lcsh:R ,Area under the curve ,Middle Aged ,Signal on ,030104 developmental biology ,Diffusion Magnetic Resonance Imaging ,Adipose Tissue ,Kurtosis ,lcsh:Q ,Female ,business ,Nuclear medicine ,030217 neurology & neurosurgery - Abstract
Recent studies showed the potential of diffusion kurtosis imaging (DKI) as a tool for improved classification of suspicious breast lesions. However, in diffusion-weighted imaging of the female breast, sufficient fat suppression is one of the main factors determining the success. In this study, the data of 198 patients examined in two study centres was analysed using standard diffusion and kurtosis evaluation methods and three DKI fitting approaches accounting phenomenologically for fat-related signal contamination of the lesions. Receiver operating characteristic curve analysis showed the highest area under the curve (AUC) for the method including fat correction terms (AUC = 0.85, p p = 0.036) using a fat correction term for the first centre, while no significant difference with no adverse effects was observed for the second centre (AUC 0.89 vs. 0.90, p = 0.95). Contamination of the signal in breast lesions with unsuppressed fat causing a reduction of diagnostic performance of diffusion kurtosis imaging may potentially be counteracted by proposed adapted evaluation methods.
- Published
- 2020