Prostate cancer tumor grade differentiation with dynamic contrast-enhancedMR imaging in the rat: Comparison of macromolecular and small-molecular contrast media - Preliminary experience
A. Gossmann et al., Prostate cancer tumor grade differentiation with dynamic contrast-enhancedMR imaging in the rat: Comparison of macromolecular and small-molecular contrast media - Preliminary experience, RADIOLOGY, 213(1), 1999, pp. 265-272
Citations number
45
Categorie Soggetti
Radiology ,Nuclear Medicine & Imaging","Medical Research Diagnosis & Treatment
PURPOSE: To differentiate prostate cancers of different histopathologic gra
des with dynamic gadolinium-enhanced magnetic resonance (MR) imaging. Resul
ts with a conventional small-molecular contrast medium (CM) were compared t
o those with a prototypic macromolecular CM.
MATERIALS AND METHODS: High- and low-grade tumors, sublines of the Dunning
R3327 rat prostate cancer line, were subcutaneously implanted into the flan
ks of 12 male Copenhagen rats. Dynamic contrast material-enhanced MR imagin
g was performed with small-molecular CM and macromolecular CM at an interva
l of 1 day. Microvascular permeability, as estimated with the endothelial t
ransfer coefficient, and fractional plasma volume were calculated for each
tumor and each CM by means of a two-compartmental, bidirectional kinetic mo
del.
RESULTS: Mean endothelial transfer coefficient values for both macromolecul
ar CM and small-molecular CM were significantly different between the two t
umor sublines: (P =.0004 and P = 01, respectively). For the high- and low-g
rade tumors, no overlap of values was seen with macromolecular CM, but a br
oad overlap was seen with small-molecular CM despite a significant differen
ce in mean values.
CONCLUSION: Dynamic contrast-enhanced MR imaging permits differentiation of
histopathologic prostatic tumor types. Quantitative microvascular permeabi
lity characteristics estimated from macromolecular CM-enhanced data were:si
gnificantly superior to those derived from small-molecular CM-enhanced data
.