Diagnostic evaluation of diffusion kurtosis imaging for prostate cancer: Detection in a biopsy population.

PURPOSE: To prospectively assess the feasibility of diffusional kurtosis (DK) imaging for distinguishing prostate cancer(PCa) from benign prostate hyperplasia (BPH) in comparison with standard diffusion-weighted (DW) imaging, as well as low-from high-grade malignant regions. MATERIALS AND METHODS: 147 consecutive patients with suspected PCa underwent multi-parametric 1.5-TMR. Diffusion kurtosis imaging was acquired with with 5 b values (0,600,800,1600,and 2400sec/mm2).Region of interest (ROI)-based measurements were performed on ADC, D, and K map by two radiologists. Data were analyzed by using mixed-model analysis of variance and receiver operating characteristic curves. Correlations among the three parameters (ADC,D and K) in all patients, and correlations between three parameters with the tumor Gleason score (GS) in PCa group were analyzed using Pearson's correlation coefficient in peripheral zone(PZ) and transiton zone(TZ). RESULTS: 58 patients were proved with PCa (9 GS 3 + 3[PZ/TZ = 4/5], 49 GS ≥ 7 [PZ/TZ = 26/23]), and 89 patients were with BPH. ADC,D and K were able to distinguish benignance from tumor tissue both in PZ and TZ(P＜0.01), but performed poorly in neither differentiating low-(GS 3 + 3) from high-grade (GS≥3 + 4) disease, nor GS(3 + 4) from GS(4 + 3).There was a weak correlation between the GS and ADC, D (PZ:ADC r=-0.113, D r=-0.139; TZ:ADC r=-0.104,D r=-0.103), while a moderate correlation between the GS and K(PZ:K r = 0.492; TZ:K r = 0.433, P＜0.01).K had significantly greater area under the curve for differentiating PCa from BHP than ADC both in PZ and TZ. CONCLUSION: DK model may add value in PCa detection and diagnosis, but none can differentiate low-from high-grade PCas (including GS=3+4 from GS=4+3).

Pancreatic ductal adenocarcinoma and chronic mass-forming pancreatitis: Differentiation with dual-energy MDCT in spectral imaging mode.

OBJECTIVE: To investigate the value of dual-energy MDCT in spectral imaging in the differential diagnosis of chronic mass-forming chronic pancreatitis (CMFP) and pancreatic ductal adenocarcinoma (PDAC) during the arterial phase (AP) and the pancreatic parenchymal phase (PP). MATERIALS AND METHODS: Thirty five consecutive patients with CMFP (n=15) or PDAC (n=20) underwent dual-energy MDCT in spectral imaging during AP and PP. Iodine concentrations were derived from iodine-based material-decomposition CT images and normalized to the iodine concentration in the aorta. The difference in iodine concentration between the AP and PP, contrast-to-noise ratio (CNR) and the slope K of the spectrum curve were calculated. RESULTS: Normalized iodine concentrations (NICs) in patients with CMFP differed significantly from those in patients with PDAC during two double phases (mean NIC, 0.26±0.04 mg/mL vs. 0.53±0.02 mg/mL, p=0.0001; 0.07±0.02 mg/mL vs. 0.28±0.04 mg/mL, p=0.0002, respectively). There were significant differences in the value of the slope K of the spectrum curve in two groups during AP and PP (K(CMFP)=3.27±0.70 vs. K(PDAC)=1.35±0.41, P=0.001, and K(CMFP)=3.70±0.17 vs. K(PDAC)=2.16±0.70, p=0.003, respectively). CNRs at low energy levels (40-70 keV) were higher than those at high energy levels (80-40 keV). CONCLUSION: Individual patient CNR-optimized energy level images and the NIC can be used to improve the sensitivity and the specificity for differentiating CMFP from PDAC by use of dual-energy MDCT in spectral imaging with fast tube voltage switching.

[Diagnostic value of mult-detector CT for papillary renal cell carcinoma and chromophobe renal cell carcinoma].

OBJECTIVE: To explore the significance of multi-detector CT (MDCT) in differential diagnosis of papillary renal cell carcinoma and chromophobe renal cell carcinoma. METHODS: Clinical data of forty-one cases of renal cancers confirmed pathologically were collected, including 21 cases of papillary renal cell carcinoma (PRCC) (14 type I, 7 type II) and 20 cases of chromophobe renal cell carcinoma (ChRCC). Their morphological and MDCT characteristics were retrospectively analyzed. Receiver operator characteristic curve (ROC) was used to analyze the value of MDCT in differential diagnosis of PRCC and ChRCC. Two senior radiologists analyzed the morphological and the dynamic enhancement characteristics of the images. The attenuation of the lesions and the adjacent renal parenchyma were measured. The morphological indexes were compared with chi-square test and the quantitative indexes were compared with independent sample T-test. Receiver operator characteristic curve (ROC) was used to analyze the sensitivity, specificity and accuracy of diagnosis of PRCC and ChRCC. RESULTS: Angioid enhancement and filled enhancement were more common in ChRCC than in PRCC, while delayed enhancement was more often seen in PRCC than in ChRCC. Calcification was more common in type I than type II PRCC. The enhancement value (ΔCT value) in corticomedullary phase was (29.08 ± 20.12) Hu for PRCC, significantly lower than the (48.29 ± 26.70) Hu for ChRCC (t = -2.611, P = 0.013). The ΔCT value of type I PRCC in corticomedullary phase was (26.36 ± 18.16) Hu, showing a significant difference from that of ChRCC (t = -2.666, P = 0.012). The lesion to kidney ratio (LKR) in corticomedullary phase was 0.44 ± 0.19 for PRCC and 0.58 ± 0.15 for ChRCC, with a significant difference between them (t = -2.587, P = 0.014). The LKR of type I PRCC in corticomedullary phase was 0.39 ± 0.15, showing a significant difference from that of ChRCC (t = -3.628, P = 0.001). The difference value (D-value) of the attenuation of lesion between corticomedullary and nephrographic phases was (-3.69 ± 8.90) Hu for PRCC and (8.39 ± 21.98) Hu for ChRCC, with a significant difference between them (t = -2.285, P = 0.031). The D-value of type I PRCC was (-4.55 ± 9.82) Hu, showing a significant difference from that of ChRCC (t = -2.323, P = 0.028). There was no significant difference between the ΔCT, LKR and D-value of the type II PRCC and ChRCC (P > 0.05 for all). The area under the curve (AUC) for ΔCT value, LKR value in corticomedullary phase, and D-value were 0.718, 0.751 and 0.668, respectively, and there were no significant differences among them (z values were 0.896, 0.683 and 0.559, respectively, and P values were 0.370, 0.495 and 0.576, respectively). Using 49.350 Hu as the cutoff value for ΔCT value in corticomedullary phase, resulted in a sensitivity, specificity and accuracy of 50.0%, 90.5% and 70.7%, respectively. Corresponding values were 65.0%, 81.0% and 73.2%, when using a cutoff value of 0.532 for LKR in corticomedullary phase, and were 60.0%, 76.2% and 68.3%, when using a D-value of 0.400 Hu. CONCLUSIONS: The ΔCT value, LKR value in corticomedullary phase, and the D-value are all useful indexes for the differentiation of PRCC and ChRCC.