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A Simultaneous Non-contrast Angiography and intraPlaque hemorrhage (SNAP) MR imaging technique was proposed to detect both luminal stenosis and hemorrhage in atherosclerosis patients in a single scan. 13patients with diagnosed carotid atherosclerotic plaque were recruited after informed consent. All scans were performed on a 3T MR imaging system with SNAP, 2D time-of-flight (TOF) and magnetization-prepared 3D rapid acquisition gradient echo (MP-RAGE) sequences. The SNAPsequence utilized a phase sensitive acquisition, and was designed toprovide positive signals corresponding to intraplaque hemorrhage (IPH) and negative signals corresponding to lumen. SNAP images were compared to TOF images to validate lumen area measurements using linear mixed models and the intraclass correlation coefficient (ICC). IPHidentification accuracy was evaluated by comparing to MP-RAGE images using Cohen’s Kappa. Diagnostic quality SNAP images were generatedfrom all subjects. Quantitatively, the lumen area measurements by SNAP were strongly correlated (ICC=0.96, p<0.001) with those measuredby TOF. For IPH detection, strong agreement (&#954;=0.82, p<0.001)was also identified between SNAP and MP-RAGE images. The SNAP technique was proposed and validated to reliably detect in a single acquisition both luminal size and intraplaque hemorrhage in the patients with carotid atherosclerosis.

Purpose: To evaluate the effect of different b-values on intravoxelincoherent motion (IVIM) and diffusion parameters for prostate cancer detection. Materials and methods: Thirty three patients (mean age of 61.6 years, mean serum PSA of 10 ng/dl) undergoing endorectal coil MRI of the prostate underwent multiparametric imaging includingdiffusion weighted (DW) imaging with five b-values (0, 188, 375, 563and 750 s/mm2), T2 weighting and dynamic contrast enhanced MRI. Diffusion coefficients were obtained from a simple mono-exponential fitusing different non-zero b-values. A simplified IVIM model was used to generate perfusion fractions, by combining both the measured and the extrapolated diffusion data at a b-value of zero. Correlationswere made with the results of DCE-MRI using an extended Tofts pharmacokinetic model. Pathologic correlation was obtained by precisely targeting the needle via a fused MRI-Transrectal Ultrasound (MR-TRUS)image-guided biopsy system. Results: Diffusion coefficients differentiated tumors from normal tissues in the prostate using all possible combinations of non-zero b-values; however, perfusion fractionsdemonstrated large variations depending on the choice of b-values.Exclusion of the highest b-value of 750 (s/mm2) led to better correlations of perfusion fraction with DCE-MRI and predicted the presenceof cancer independent of diffusion. Conclusions: Estimates of perfusion fraction using IVIM obtained on DW-MRI correlate with DCE-MRIparameters and are predictive for cancer in MRI of the prostate. Perfusion fraction therefore represents another independent parameterto help differentiate prostate cancers from surrounding benign tissue using multiparametric MRI