The aim of the current study was to explore the value of tumor attenuation and quantitative analysis of perfusion parameters obtained from traditional tri-phasic CT scans in grading hepatocellular carcinoma (HCC). Totally 39 patients (42 lesion samples) with pathologically confirmed HCC who underwent tri-phasic CT scans were enrolled. HCC lesions were divided into non-poorly differentiated HCC (NP-HCC; n = 31) and poorly differentiated HCC (pHCC; n = 11). All lesions were divided into 5 groups according to the attenuation on different CT enhancement phase. The values of tumor attenuation on different scanning phases were measured. The following parameters were calculated: arterial enhancement fraction (AEF), portal venous supply coefficient (PVC), and hepatic arterial supply coefficient (HAC). The relationship of perfusion parameters with the histological grade of HCC was analyzed. Receiver operating characteristic curves were generated. No significant correlation was observed between the perfusion parameters and tumor grading. Only HAC showed a non-significant trend in different grades of HCC (pHCC < NP-HCC; P = .07). The pHCC cases had significantly decreased values of tumor attenuation on the unenhanced phase (TAu), tumor attenuation on the portal phase portal phase (TAp), and equilibrium phase (TAe) ( P < .01). The difference of tumor attenuation between the portal phase and the unenhanced phase (TAp-TAu) of the pHCC cases was decreased than that of the NP-HCC cases ( P < .01), whereas the difference of attenuation between the equilibrium phase and portal phase (TAe-TAp) was significantly higher in the pHCC cases than that in the NP-HCC cases ( P < .01). TAe-TAp had the highest area under the curve. The number of tumor enhancement pattern in Group 5 of HCCs with a diameter of 3 cm or more was significantly more than that of HCCs with a diameter of less than 3 cm or with other different enhancement patterns ( P < .01). Histological HCC grading cannot be predicted by the perfusion parameters derived from traditional tri-phasic CT scans, whereas the tumor attenuation on different phases and the tumor attenuation differences among different phases, especially the mean value of TAe-TAp, might be useful for non-invasive prediction on the degree of HCC differentiation.

We aim to gain further insight into identifying differential perfusion parameters and corresponding histogram parameters of intrahepatic mass-forming cholangiocarcinoma (IMCC) from hepatocellular carcinomas (HCCs) on triphasic computed tomography (CT) scans. 90 patients with pathologically confirmed HCCs (n = 54) and IMCCs (n = 36) who underwent triple-phase enhanced CT imaging were included. Quantitative analysis of CT images derived from triphasic CT scans were evaluated to generate liver perfusion and histogram parameters. The differential performances, including the area under the receiver operating characteristic curve (AUC), specificity, and sensitivity were assessed. The mean value, and all thepercentiles of the arterial enhancement fraction (AEF) were significantly higher in HCCs than in IMCCs. The difference in hepatic arterial blood supply perfusion (HAP) and AEF (ΔHAP = HAPtumor − HAPliver, ΔAEF = AEFtumor − AEFliver) for the mean perfusion parameters and all percentile parameters between tumor and peripheral normal liver were significantly higher in HCCs than in IMCCs. The relative AEF (rAEF = ΔAEF/AEFliver), including the mean value and all corresponding percentile parameters were statistically significant between HCCs and IMCCs. The 10th percentiles of the ΔAEF and rAEF had the highest AUC of 0.788 for differentiating IMCC from HCC, with sensitivities and specificities of 87.0%, 83.3%, and 61.8%, 64.7%, respectively. Among all parameters, the mean value of ∆AEF, the 75th percentiles of ∆AEF and rAEF, and the 25th percentile of HFtumor exhibited the highest sensitivities of 94.4%, while the 50th percentile of rAEF had the highest specificity of 82.4%. AEF (including ΔAEF and rAEF) and the corresponding histogram parameters derived from triphasic CT scans provided useful value and facilitated the accurate discrimination between IMCCs and HCCs.

This study is to investigate quantitative measures and heterogeneity of perfusion parameters in the differential diagnosis of hepatocellular carcinoma (HCC) and hemangioma.In total, 32 HCC and 44 hemangioma (types 1, 2, and 3) cases were included in this retrospective study. Hepatic artery coefficient (HAC), portal vein coefficient (PVC), and arterial enhancement fraction (AEF) were calculated. Tumor heterogeneity was analyzed. Perfusion parameters and corresponding percentiles were compared between the HCC and hemangioma (especially atypical hemangioma) cases, as well as between the substantial lesion part and surrounding normal tissue.The mean value, and the 10th, 50th, 75th, and 90th percentiles of PVC were significantly lower in the HCC cases than the types 1 and 2 hemangioma cases (P < .01). Moreover, the 90th percentile PVC in the HCC cases was also significantly lower than the type 3 hemangioma case (P < .01), while the mean value, and all the percentiles of AEF in the HCC cases were higher than the types 2 and 3 hemangioma cases (P < .01). The 10th percentile HAC in the HCC cases was higher than the type 2 hemangioma cases (P < .05). The mean value, and the 10th and 50th percentile HAC in the HCC cases were higher than the type 3 hemangioma case (P < .05). However, there was no statistically significant difference in HAC between the HCC and type 1 hemangioma cases (P > .05).Quantitative measurement of perfusion parameters and heterogeneity analysis show significance differences in the early detection and differential diagnosis of HCC and hemangioma cases, which might contribute to increasing the diagnostic accuracy.

CTVE can differentiate PV variations that cannot be identified accurately on MIP and VR.

Background: Pre-operative non-invasive histological evaluation of hepatocellular carcinoma (HCC) remains a challenge. Tumor perfusion is significantly associated with the development and aggressiveness of HCC. The purpose of the study was to evaluate the clinical value of quantitative liver perfusion parameters and corresponding histogram parameters derived from traditional triphasic enhanced computed tomography (CT) scans in predicting histological grade of HCC. Methods: Totally, 52 patients with HCC were enrolled in this retrospective study and underwent triple-phase enhanced CT imaging. The blood perfusion parameters were derived from triple-phase CT scans. The relationship of liver perfusion parameters and corresponding histogram parameters with the histological grade of HCC was analyzed. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal ability of the parameters to predict the tumor histological grade. Results: The variance of arterial enhancement fraction (AEF) was significantly higher in HCCs without poorly differentiated components (NP-HCCs) than in HCCs with poorly differentiated components (P-HCCs). The difference in hepatic blood flow (HF) between total tumor and total liver flow (ΔHF = HF tumor − HF liver ) and relative flow (rHF = ΔHF/HF liver ) were significantly higher in NP-HCCs than in P-HCCs. The difference in portal vein blood supply perfusion (PVP) between tumor and liver tissue (ΔPVP) and the ΔPVP/liver PVP ratio (rPVP) were significantly higher in patients with NP-HCCs than in patients with P-HCCs. The area under ROC (AUC) of ΔPVP and rPVP were both 0.697 with a high sensitivity of 84.2% and specificity of only 56.2%. The ΔHF and rHF had a higher specificity of 87.5% with an AUC of 0.681 and 0.673, respectively. The combination of rHF and rPVP showed the highest AUC of 0.732 with a sensitivity of 57.9% and specificity of 93.8%. The combined parameter of ΔHF and rPVP, rHF and rPVP had the highest positive predictive value of 0.903, and that of rPVP and ΔPVP had the highest negative predictive value of 0.781. Conclusion: Liver perfusion parameters and corresponding histogram parameters (including ΔHF, rHF, ΔPVP, rPVP, and AEF variance ) in patients with HCC derived from traditional triphasic CT scans may be helpful to non-invasively and pre-operatively predict the degree of the differentiation of HCC.