Purpose:To develop a multi-parametric model suitable for prospectively identifying prostate cancer in peripheral zone (PZ) using magnetic resonance imaging (MRI).
Materials and Methods:Twenty-five radical prostatectomy patients (median age, 63 years; range, 44 -72 years) had T2-weighted, diffusion-weighted imaging (DWI), T2-mapping, and dynamic contrast-enhanced (DCE) MRI at 1.5 Tesla (T) with endorectal coil to yield parameters apparent diffusion coefficient (ADC), T2, volume transfer constant (K trans ) and extravascular extracellular volume fraction (v e ). Whole-mount histology was generated from surgical specimens and PZ tumors delineated. Thirty-eight tumor outlines, one per tumor, and pathologically normal PZ regions were transferred to MR images. Receiver operating characteristic (ROC) curves were generated using all identified normal and tumor voxels.Step-wise logistic-regression modeling was performed, testing changes in deviance for significance. Areas under the ROC curves (A z ) were used to evaluate and compare performance. .719], which was significantly higher than A z,T2 , A z,Ktrans , and A z,ve (P Ͻ 0.002). A z,LR-3p tended to be greater than A z,ADC , however, this result was not statistically significant (P ϭ 0.090).
Conclusion:Using logistic regression, an objective model capable of mapping PZ tumor with reasonable performance can be constructed.