Search

Purpose To investigate relaxation along a fictitious field (RAFF) and continuous wave (cw) T1ρ imaging of prostate cancer (PCa) in the terms of repeatability, PCa detection, and characterization. Methods Thirty-six patients (PSA 11.6 ± 7.6 ng/mL, mean ± standard deviation) with histologically confirmed PCa underwent two repeated 3T MR examinations using surface array coils before prostatectomy. Relaxation along fictitious field, cw T1ρ, and T2 relaxation times (TRAFF, T1ρcw, T2) were measured and averaged over regions of interest placed in PCa, normal peripheral zone (PZ), and normal central gland (CG) positioned using whole-mount prostatectomy sections and anatomical T2-weighted images. Receiver operating characteristic curve analysis with area under the curve (AUC) was calculated to distinguish PCa from PZ/CG and PCa with Gleason score (GS) of 3+3 from GS of 3+4/≥ 3+4. Results TRAFF and T1ρcw relaxation times were repeatable with coefficients of repeatability as a percentage of median value in the range of 7.8-23.2%. AUC (mean, 95% confidence interval) in the differentiation of PCa with GS of 3+3 from PCa with CS of ≥ 3+4 were 0.88 (0.72-0.99), 0.69 (0.46-0.90), and 0.68 (0.45-0.88), for TRAFF, T1ρcw, and T2, respectively. Conclusion In quantitative region of interest based analysis, TRAFF outperformed T1ρcw and T2 in PCa detection and characterization.

Purpose To evaluate monoexponential, stretched exponential, kurtosis, and biexponential models for diffusion-weighted imaging (DWI) of normal prostate and prostate cancer (PCa), using b-values up to 2000 s/mm2, in terms of fitting quality and repeatability. Methods Eight healthy volunteers and 16 PCa patients underwent a total of four repeated 3T DWI examinations using 16 and 12 b-values, respectively. The highest b-value was 2000 s/mm2. The normalized mean signal intensities of regions of interest, placed in normal tissue and PCa using anatomical images and prostatectomy sections, were fitted using the four models. The fitting quality was evaluated using Akaike information criteria and F-ratio. Repeatability of the fitted parameters was evaluated using intraclass correlation coefficient ICC(3,1). Results The biexponential model provided the best fit to normal prostate and PCa DWI data. The parameters of the monoexponential, kurtosis, and stretched exponential (with the exception of the α parameter) models had higher ICC(3,1) values compared with the biexponential model. The kurtosis model provided a better fit to DWI data of normal prostate and PCa than the monoexponential model, whereas these models had comparable reliability and repeatability based on ICC(3,1) values. Conclusion Considering the model fit and repeatability, the kurtosis model seems to be the preferred model for characterization of normal prostate and PCa DWI using b-values up to 2000 s/mm2. Magn Reson Med 73:1988–1998, 2015. © 2014 Wiley Periodicals, Inc.

Purpose To find the diagnostic accuracy of 3T multiparametric magnetic resonance imaging (mpMRI) and mpMRI targeted transrectal ultrasound (TRUS)-guided biopsy using visual coregistration (TB) in patients with elevated prostate-specific antigen (PSA), normal digital rectal examination, and no previous biopsy. Materials and Methods Fifty-five patients at two institutions underwent mpMRI, consisting of anatomical T2-weighted imaging (T2W), diffusion-weighted imaging (DWI), proton magnetic resonance spectroscopy (1H-MRS), and dynamic contrast-enhanced MRI (DCE-MRI), followed by TB in addition to 12 core systematic TRUS-guided biopsy (SB). Histopathological scorings of biopsy (n = 38) and prostatectomy (n = 17) specimens were used as the reference standard for calculation of diagnostic accuracy values. Clinically significant prostate cancer (SPCa) was defined as 3 mm core length of Gleason score 3+3 or any Gleason grade 4. Results The sensitivity, specificity, accuracy, and area under the curve (AUC) values for the detection of SPCa on the sextant level for T2W+DWI+1H-MRS+DCE-MRI were 72%, 89%, 85%, and 0.81, respectively. The corresponding values for T2wi+DWI were 61%, 96%, 87%, and 0.79, respectively. The overall PCa detection rate per core in 53 patients was 21% (138 of 648 cores) for SB and 43% (33 of 77 cores) for TB (P

The expression of glucose transporter genes (GLUTI-4) was studied in 20 head-and-neck tumors of 18 patients. All tumors--16 of which were squamous-cell carcinomas (SCC)--expressed GLUT1 and/or GLUT3 mRNA, while detectable levels of GLUT2 or GLUT4 mRNA were not observed. The signals for GLUT1 and GLUT3 mRNAs varied markedly throughout the SCC tumor population but no clear relationship with the grade of differentiation was found. The high GLUT expression observed in some tumors was not associated with amplification or rearrangement of the corresponding genes. Immunohistochemistry of 5 SCCs showed that GLUT1 protein was located in tumor-cell membranes in relation to the level of mRNA expression. We conclude that both GLUT1 and GLUT3 are involved in basal glucose uptake of extracranial head-and-neck tumors. The increased expression of these high-affinity GLUT isoforms may be related to the growth maintenance of cancer tissue in cases of limited supply of substrate e.g., in poorly vascularized tumor areas.

Thirteen patients with malignant head and neck tumors were studied before they were treated with (18F) fluorodeoxyglucose (FDG) imaging and DNA flow cytometry (FCM). The nuclear DNA content and the percentage of proliferative cells (S + G2/M) were compared with the FDG uptake; FDG was retained in the primary tumor and/or neck metastasis in all patients. The accumulation of FDG did not correlate with histologic grade of the tumors, but there was a clear correlation (r = 0.86, P less than 0.001) between the proportion of the cells in S + G2/M phases of the cell cycle and the intensity of FDG accumulation. The uptake of FDG by the tumor also correlated with the percentage of S-phase cells (r = 0.82, P less than 0.001). The result suggests that enhanced glucose metabolism, measured by FDG uptake, is associated with the proliferative activity of the tumor. Thus, imaging with FDG may offer a new method to assess the aggressiveness of human cancer growth in vivo.