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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