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Abstract #0607

3D Texture Analysis of DCE-MRI Pharmacokinetic Parametric Maps for Early Prediction of Breast Cancer Therapy Response

Guillaume Thibault 1 , Alina Tudorica 1 , Aneela Afzal 1 , Stephen Y-C Chui 1 , Arpana Naik 1 , Megan L Troxell 1 , Kathleen A Kemmer 1 , Karen Y Oh 1 , Nicole Roy 1 , Megan L Holtorf 1 , Wei Huang 1 , and Xubo Song 1

1 Oregon Health & Science University, Portland, OR, United States

Twenty-eight women with locally advanced breast cancer who underwent neoadjuvant chemotherapy (NACT) consented to research DCE-MRI studies before, during, and after NACT. The DCE-MRI data were subjected to both Standard and Shutter-Speed model (SM and SSM) pharmacokinetic (PK) analyses to generate pixel-by-pixel parametric maps. Three texture analysis methods were employed to extract triple features from the maps and their changes after one NACT cycle were correlated with residual cancer burden (RCB) measured by pathology analysis of post-NACT resection specimens. Texture feature changes in several PK parametric maps provided good early prediction of therapy response, with the SSM maps the most frequently used in feature extraction with good early prediction of response.

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