Abstract #4089
Improving Bladder Cancer Staging by using quantitative DCE-MRI with k-means clustering
Huyen T Nguyen 1 , Guang Jia 2 , Kamal S Pohar 3 , Amir Mortazavi 4 , Zarine K Shah 5 , Debra Zynger 6 , Lai Wei 7 , Xiangyu Yang 1 , Daniel Clark 1 , and Michael V Knopp 1
1
Wright Center of Innovation in Biomedical
Imaging, Department of Radiology, The Ohio State
University, Columbus, Ohio, United States,
2
Department
of Physics and Astronomy, Louisiana State University,
Baton Rouge, Louisiana, United States,
3
Deparment
of Urology, The Ohio State University, Columbus, Ohio,
United States,
4
Deparment
of Internal Medicine, The Ohio State University,
Columbus, Ohio, United States,
5
Deparment
of Radiology, The Ohio State University, Columbus, Ohio,
United States,
6
Deparment
of Pathology, The Ohio State University, Columbus, Ohio,
United States,
7
Center
for Biostatistics, The Ohio State University, Columbus,
Ohio, United States
This study is to evaluate the value of k-means
clustering of DCE-MRI pharmacokinetic parameters in T
staging of bladder tumors. k-means clustering was
performed on the non-dimensionalized Amp and kep values
of all twenty-four patients in the study to determine
three cluster centers. The volume fractions (VFs) of
three clusters were correlated with the tumor stage.
Significant difference in the VF of cluster 2 was found
between T1/lower vs. T2, T1/lower vs. T3, and T3 vs. T4.
The differences in all three cluster VFs were also
statistically significant. Fat-invasive tumors had
significantly higher VFs of cluster 1 and 3 and a
significantly lower VF of cluster 2 than did
non-fat-invasive tumors. The VF of cluster 2 had
area-under-the-curve (AUC) value of 0.83 in the
differentiation of fat-invasive from non-fat-invasive
tumors. k-means clustering of DCE-MRI pharmacokinetic
parameters can be a useful tool for the quantitative
assessment of T stages to improve the accuracy of the T
staging of bladder cancer.
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