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Abstract #1979

Comparison of Tissue Homogeneity Tracer Kinetics Models on Pixel-By-Pixel DCE MRI Data in Breast Tumors

Dennis Lai Hong Cheong1, 2, Thian Chor Ng1, 3, Bo Zhang1, 4, Bingwen Zheng1, Eugene Mun Wai Ong3, Soo Chin Lee5, 6

1Clinical Imaging Research Center, A*STAR & National University of Singapore, Singapore, Singapore; 2Neuroradiology Department, National Neuroscience Institute, 308433, Singapore; 3Department of Radiology, National University of Singapore, 119074, Singapore; 4Quantitative Image Processing Group, SBIC/A*STAR, 138671, Singapore; 5Department of Haematology-Oncology, National University Health System, 119074, Singapore; 6Cancer Science Institute, 117456, Singapore

Pixel-by-pixel concentration time curves from a breast tumor were extracted and analyzed by two compartmental models (Tofts model and extended Tofts model), and two distributed parameter models (adiabatic approximation to tissue homogeneity model and two-compartment axially distributed parameter model). All models are able to fit the data although distributed parameter models have slightly better fittings. Parameters Ktrans and ve and impulse residue functions of the models were being compared. In pixel-by-pixel analysis of DCE MRI data in tumors, our preliminary data suggests that distributed parameter models are better than compartmental models by having better fittings and more stable parameter values.