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000135948 1001_ $$0P:(DE-He78)d2d971750bce6217eb90fff9b01e61f9$$aBickelhaupt, Sebastian$$b0$$eFirst author
000135948 245__ $$aRadiomics Based on Adapted Diffusion Kurtosis Imaging Helps to Clarify Most Mammographic Findings Suspicious for Cancer.
000135948 260__ $$aOak Brook, Ill.$$bSoc.$$c2018
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000135948 520__ $$aPurpose To evaluate a radiomics model of Breast Imaging Reporting and Data System (BI-RADS) 4 and 5 breast lesions extracted from breast-tissue-optimized kurtosis magnetic resonance (MR) imaging for lesion characterization by using a sensitivity threshold similar to that of biopsy. Materials and Methods This institutional study included 222 women at two independent study sites (site 1: training set of 95 patients; mean age ± standard deviation, 58.6 years ± 6.6; 61 malignant and 34 benign lesions; site 2: independent test set of 127 patients; mean age, 58.2 years ± 6.8; 61 malignant and 66 benign lesions). All women presented with a finding suspicious for cancer at x-ray mammography (BI-RADS 4 or 5) and an indication for biopsy. Before biopsy, diffusion-weighted MR imaging (b values, 0-1500 sec/mm2) was performed by using 1.5-T imagers from different MR imaging vendors. Lesions were segmented and voxel-based kurtosis fitting adapted to account for fat signal contamination was performed. A radiomics feature model was developed by using a random forest regressor. The fixed model was tested on an independent test set. Conventional interpretations of MR imaging were also assessed for comparison. Results The radiomics feature model reduced false-positive results from 66 to 20 (specificity 70.0% [46 of 66]) at the predefined sensitivity of greater than 98.0% [60 of 61] in the independent test set, with BI-RADS 4a and 4b lesions benefiting from the analysis (specificity 74.0%, [37 of 50]; 60.0% [nine of 15]) and BI-RADS 5 lesions showing no added benefit. The model significantly improved specificity compared with the median apparent diffusion coefficient (P < .001) and apparent kurtosis coefficient (P = .02) alone. Conventional reading of dynamic contrast material-enhanced MR imaging provided sensitivity of 91.8% (56 of 61) and a specificity of 74.2% (49 of 66). Accounting for fat signal intensity during fitting significantly improved the area under the curve of the model (P = .001). Conclusion A radiomics model based on kurtosis diffusion-weighted imaging performed by using MR imaging machines from different vendors allowed for reliable differentiation between malignant and benign breast lesions in both a training and an independent test data set. © RSNA, 2018 Online supplemental material is available for this article.
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000135948 7001_ $$0P:(DE-HGF)0$$aJaeger, Paul Ferdinand$$b1
000135948 7001_ $$0P:(DE-He78)b709e6df1ec6b63e5ffad4c8131f6f4d$$aLaun, Frederik$$b2
000135948 7001_ $$0P:(DE-HGF)0$$aLederer, Wolfgang$$b3
000135948 7001_ $$aDaniel, Heidi$$b4
000135948 7001_ $$0P:(DE-He78)59dfdd0ee0a7f0db81535f0781a3a6d6$$aKuder, Tristan Anselm$$b5
000135948 7001_ $$aWuesthof, Lorenz$$b6
000135948 7001_ $$0P:(DE-He78)c6e31fb8f19e185e254174554a0cccfc$$aPaech, Daniel$$b7
000135948 7001_ $$0P:(DE-He78)ea098e4d78abeb63afaf8c25ec6d6d93$$aBonekamp, David$$b8
000135948 7001_ $$0P:(DE-He78)77588f5b9413339755a66e739d316c7d$$aRadbruch, Alexander$$b9
000135948 7001_ $$0P:(DE-He78)3e76653311420a51a5faeb80363bd73e$$aDelorme, Stefan$$b10
000135948 7001_ $$0P:(DE-He78)3d04c8fee58c9ab71f62ff80d06b6fec$$aSchlemmer, Heinz-Peter$$b11
000135948 7001_ $$aSteudle, Franziska Hildegard$$b12
000135948 7001_ $$0P:(DE-He78)33c74005e1ce56f7025c4f6be15321b3$$aMaier-Hein, Klaus$$b13$$eLast author
000135948 773__ $$0PERI:(DE-600)2010588-5$$a10.1148/radiol.2017170273$$gVol. 287, no. 3, p. 761 - 770$$n3$$p761 - 770$$tRadiology$$v287$$x1527-1315$$y2018
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