Meeting Banner
Abstract #4788

Prostate Cancer Diffusion Signal Analysis: Combination of Multiple Fit Parameters Improves Tissue Discrimination

Stephan E. Maier1,2, Thiele Kobus3, Andriy Fedorov1, Fredrik Langkilde2, Ruth Dunne1, Robert V. Mulkern4, and Clare M. Tempany1

1Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States, 2Radiology, Sahlgrenska Academy, Gothenburg University, Gothenburg, Sweden, 3Department of Radiology and Nuclear Medcine, Radbound University Medical Center, Netherlands, 4Radiology, Children's Hospital, Harvard Medical School, Boston, MA, United States

Diffusion signals over an extended b-factor range 0-3500 s/mm2 were measured with an endorectal coil at 3 Tesla in 56 prostate cancer patients. For each pixel, signal decay fits were computed assuming biexponential, kurtosis, stretched exponential and gamma distribution diffusion signal models. The potential of individual parameters and linear parameter combinations to differentiate normal from cancerous tissue was evaluated with ROC analysis. For the kurtosis and stretched exponential models, single parameters yield the highest AUCs, whereas for the biexponential and gamma distribution models, only combinations of parameters produce the comparably high AUCs.

This abstract and the presentation materials are available to members only; a login is required.

Join Here