Abstract #1193

Predicting tumor aggressiveness in papillary thyroid cancers using multiparametric quantitative imaging metrics

Ramesh Paudyal¹, Jung Hun Oh¹, Vaios Hatzoglou², Andre L. Moreira ³, Ashok shaha⁴, R. Michael Tuttle⁵, and Amita Shukla-Dave^1,2

¹Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States, ²Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States, ³Pathology, NYU Langone Medical Center, New York, NY, United States, ⁴Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, United States, ⁵Medicine, Memorial Sloan Kettering Cancer Center, New, NY, United States

Accurate risk stratification and predicting tumor aggressiveness is critically important for the management of papillary thyroid cancer. The results from the present study predict tumor aggressiveness in papillary thyroid cancer using noninvasive multi-parametric MRI (i.e. non-Gaussian intravoxel incoherent motion (NG-IVIM) diffusion weighted (DW) and dynamic contrast-enhanced (DCE)-MRI). The surrogate biomarkers of tumor vascularity (K^trans) and tumor cellularity (D) were negatively correlated. The kurtosis coefficient (K) reflecting tissue microstructure showed a moderate and significant correlation with the contrast agent leakage space (v_e). DWI and DCE-MRI derived metrics can predict tumor aggressiveness in PTC.

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