Ramesh Paudyal1, Linda Chen2, Jung Hun Oh1, Kaveh Zakeri2, Vaios Hatzoglou3, Chiaojung Jillian Tsai2, Nancy Lee2, and Amita Shukla-Dave1,3
1Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States, 2Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States, 3Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
1Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States, 2Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States, 3Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
Quantitative
imaging metrics derived from NG-IVIM DW- and FXR DCE-MRI could predict the patients with LRF in NPC using the cumulative incidence analysis .
Figure 4. Cumulative
incidence analysis for pretreatment apparent diffusion coefficient, ADC (mm2/s),
true diffusion coefficient, D (mm2/s), perfusion fraction, f, volume transfer
constant, Ktrans (min-1), the volume fraction of
extravascular extracellular, ve, and mean lifetime of intracellular
water protons, τi (sec). Gray’s
test revealed a significant difference for ADC, D, and f (P <0.05), and a
borderline significance for τi (sec) (P=0.098).
Figure 3. Left:
Representative histogram plot of true diffusion coefficient, D, and kurtosis
coefficient, K), in patients with and without LRF of nasopharyngeal cancer
(Figure 2). D values spread out towards higher in a patient without LRF than
compared to with LRF. In contrast, K values spread to a higher value in a
patient with LRF than without LRF. Right: Ktrans values spread out
towards higher in a patient without LRF as compared to with LRF. In contrast, τi values spread to
higher in a patient with LRF as compared without LRF.
