Dual-input Single-compartment Model Research Articles

Contrast-enhanced magnetic resonance imaging perfusion can predict microvascular invasion in patients with hepatocellular carcinoma (between 1 and 5cm).

To evaluate the role of perfusion parameters with MR imaging of the liver in diagnosing MVI in hepatocellular carcinoma (HCC) (between 1 and 5cm). This retrospective study was approved by the institutional review board. In 80 patients with 43 MVI( +) and 42 MVI( -) HCC, whole-liver perfusion MR imaging with Cartesian k-space undersampling and compressed sensing reconstruction was performed after injection of 0.1mmol/kg gadopentetate dimeglumine. Parameters derived from a dual-input single-compartment model of arterial flow (Fa), portal venous flow (Fp), total blood flow (Ft = Fa + Fp), arterial fraction (ART), distribution volume (DV), and mean transit time (MTT) were measured. The significant parameters between the two groups were included to correlate with the presence of MVI at simple and multiple regression analysis. In MVI-positive HCC, Fp was significantly higher than in MVI-negative HCC, whereas the reverse was seen for ART (p < 0.001). Tumor size (β = 1.2, p = 0.004; odds ratio, 3.20; 95% CI 1.45, 7.06), Fp (β = 1.1, p = 0.004; odds ratio, 3.09; 95% CI 1.42, 6.72), and ART (β = - 3.1, p = 0.001; odds ratio, 12.13; 95% CI 2.85, 51.49) were independent risk factors for MVI. The AUC value of the combination of all three metrics was 0.931 (95% CI 0.855, 0.975), with sensitivity of 97.6% and specificity of 76.2%. The combination of Fp, ART, and tumor size demonstrated a higher diagnostic accuracy compared with each parameter used individually when evaluating MVI in HCC (between 1 and 5cm).

Quantifying Perfusion Properties with DCE-MRI Using a Dictionary Matching Approach

Perfusion properties can be estimated from pharmacokinetic models applied to DCE-MRI data using curve fitting algorithms; however, these suffer from drawbacks including the local minimum problem and substantial computational time. Here, a dictionary matching approach is proposed as an alternative. Curve fitting and dictionary matching were applied to simulated data using the dual-input single-compartment model with known perfusion property values and 5 in vivo DCE-MRI datasets. In simulation at SNR 60 dB, the dictionary estimate had a mean percent error of 0.4–1.0% for arterial fraction, 0.5–1.4% for distribution volume, and 0.0% for mean transit time. The curve fitting estimate had a mean percent error of 1.1–2.1% for arterial fraction, 0.5–1.3% for distribution volume, and 0.2–1.8% for mean transit time. In vivo, dictionary matching and curve fitting showed no statistically significant differences in any of the perfusion property measurements in any of the 10 ROIs between the methods. In vivo, the dictionary method performed over 140-fold faster than curve fitting, obtaining whole volume perfusion maps in just over 10 s. This study establishes the feasibility of using a dictionary matching approach as a new and faster way of estimating perfusion properties from pharmacokinetic models in DCE-MRI.

Impact of temporal resolution and motion correction for dynamic contrast-enhanced MRI of the liver using an accelerated golden-angle radial sequence

This paper presents a prospective study evaluating the impact on image quality and quantitative dynamic contrast-enhanced (DCE)-MRI perfusion parameters when varying the number of respiratory motion states when using an eXtra-Dimensional Golden-Angle Radial Sparse Parallel (XD-GRASP) MRI sequence. DCE acquisition was performed using a 3D stack-of-stars gradient-echo golden-angle radial acquisition in free-breathing with 100 spokes per motion state and temporal resolution of 6 s/volume, and using a non-rigid motion compensation to align different motion states. Parametric analysis was conducted using a dual-input single-compartment model. Nonparametric analysis was performed on the time-intensity curves. A total of 22 hepatocellular carcinomas (size: 11–52 mm) were evaluated. XD-GRASP reconstructed with increasing number of spokes for each motion state increased the signal-to-noise ratio (SNR) (p < 0.05) but decreased temporal resolution (0.04 volume/s vs 0.17 volume/s for one motion state) (p < 0.05). A visual scoring by an experienced radiologist show no change between increasing number of motion states with same number of spokes using the Likert score. The normalized maximum intensity time ratio, peak enhancement ratio and tumor arterial fraction increased with decreasing number of motion states (p < 0.05) while the transfer constant from the portal venous plasma to the surrounding tissue significantly decreased (p < 0.05). These same perfusion parameters show a significant difference in case of tumor displacement more than 1 cm (p < 0.05) whereas in the opposite case there was no significant variation. While a higher number of motion states and higher number of spokes improves SNR, the resulting lower temporal resolution can influence quantitative parameters that capture rapid signal changes. Finally, fewer displacement compensation is advantageous with lower number of motion state due to the higher temporal resolution. XD-GRASP can be used to perform quantitative perfusion measures in the liver, but the number of motion states may significantly alter some quantitative parameters.

Dynamic contrast-enhanced MRI to assess hepatocellular carcinoma response to Transarterial chemoembolization using LI-RADS criteria: A pilot study

PurposeTo identify quantitative dynamic contrast-enhanced (DCE)-MRI perfusion parameters indicating tumor response of hepatocellular carcinoma (HCC) to transarterial chemoembolization (TACE). Materials and methodsThis prospective pilot study was approved by our institutional review board; written and informed consent was obtained for each participant. Patients underwent DCE-MRI examinations before and after TACE. A variable flip-angle unenhanced 3D mDixon sequence was performed for T1 mapping. A dynamic 4D mDixon sequence was performed after contrast injection for assessing dynamic signal enhancement. Nonparametric analysis was conducted on the time-intensity curves. Parametric analysis was performed on the time-concentration curves using a dual-input single-compartment model. Treatment response according to Liver Reporting and Data System (LI-RADS) v2018 was used as the reference standard. The comparisons within groups (before vs. after treatment) and between groups (nonviable vs. equivocal or viable tumor) were performed using nonparametric bootstrap taking into account the clustering effect of lesions in patients. ResultsTwenty-eight patients with 52 HCCs (size: 10–104 mm) were evaluated. For nonviable tumors (n = 27), time to peak increased from 62.5 ± 18.2 s before to 83.3 ± 12.8 s after treatment (P< 0.01). For equivocal or viable tumors (n = 25), time to peak and mean transit time significantly increased (from 54.4 ± 24.1 s to 69.5 ± 18.9 s, P < 0.01 and from 14.2 ± 11.8 s to 33.9 ± 36.8 s, P= 0.01, respectively) and the transfer constant from the extracellular and extravascular space to the central vein significantly decreased from 14.8 ± 14.1 to 8.1 ± 9.1 s−1 after treatment (P= 0.01). ConclusionThis prospective pilot DCE-MRI study showed that time to peak significantly changed after TACE treatment for both groups (nonviable tumors and equivocal or viable tumors). In our cohort, several perfusion parameters may provide an objective marker for differentiation of treatment response after TACE in HCC patients.

Quantitative perfusion imaging of neoplastic liver lesions: A multi-institution study

We describe multi-institutional experience using free-breathing, 3D Spiral GRAPPA-based quantitative perfusion MRI in characterizing neoplastic liver masses. 45 patients (age: 48–72 years) were prospectively recruited at University Hospitals, Cleveland, USA on a 3 Tesla (T) MRI, and at Zhongshan Hospital, Shanghai, China on a 1.5 T MRI. Contrast-enhanced volumetric T1-weighted images were acquired and a dual-input single-compartment model used to derive arterial fraction (AF), distribution volume (DV) and mean transit time (MTT) for the lesions and normal parenchyma. The measurements were compared using two-tailed Student’s t-test, with Bonferroni correction applied for multiple-comparison testing. 28 hepatocellular carcinoma (HCC) and 17 metastatic lesions were evaluated. No significant difference was noted in perfusion parameters of normal liver parenchyma and neoplastic masses at two centers (p = 0.62 for AF, 0.015 for DV, 0.42 for MTT for HCC, p = 0.13 for AF, 0.97 for DV, 0.78 for MTT for metastases). There was statistically significant difference in AF, DV, and MTT of metastases and AF and DV of HCC compared to normal liver parenchyma (p < 0.5/9 = 0.0055). A statistically significant difference was noted in the MTT of metastases compared to hepatocellular carcinoma (p < 0.001*10-5). In conclusion, 3D Spiral-GRAPPA enabled quantitative free-breathing perfusion MRI exam provides robust perfusion parameters.

Vastly accelerated linear least-squares fitting with numerical optimization for dual-input delay-compensated quantitative liver perfusion mapping.

To propose an efficient algorithm to perform dual input compartment modeling for generating perfusion maps in the liver. We implemented whole field-of-view linear least squares (LLS) to fit a delay-compensated dual-input single-compartment model to very high temporal resolution (four frames per second) contrast-enhanced 3D liver data, to calculate kinetic parameter maps. Using simulated data and experimental data in healthy subjects and patients, whole-field LLS was compared with the conventional voxel-wise nonlinear least-squares (NLLS) approach in terms of accuracy, performance, and computation time. Simulations showed good agreement between LLS and NLLS for a range of kinetic parameters. The whole-field LLS method allowed generating liver perfusion maps approximately 160-fold faster than voxel-wise NLLS, while obtaining similar perfusion parameters. Delay-compensated dual-input liver perfusion analysis using whole-field LLS allows generating perfusion maps with a considerable speedup compared with conventional voxel-wise NLLS fitting. Magn Reson Med 79:2415-2421, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Intravoxel incoherent motion diffusion-weighted imaging of hepatocellular carcinoma: Is there a correlation with flow and perfusion metrics obtained with dynamic contrast-enhanced MRI?

To assess the correlation between intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) metrics in hepatocellular carcinoma (HCC) and liver parenchyma. Twenty-five patients with HCC (M/F 23/2, mean age 58 years) underwent abdominal MRI at 1.5 or 3.0T, including IVIM-DWI (with 16 b-values) and DCE-MRI (3D FLASH sequence, mean temporal resolution of 2.3 sec). IVIM-DWI parameters (pseudodiffusion coefficient, D*, diffusion coefficient, D, and perfusion fraction, PF) were quantified in HCC lesions and liver parenchyma using a Bayesian fitting algorithm. DCE-MRI parameters (arterial flow, Fa , portal flow, Fp , total flow, Ft , mean transit time, MTT, distribution volume, DV, and arterial fraction, ART) were quantified using a dual-input single-compartment model. Correlations between IVIM-DWI and DCE-MRI parameters were assessed using a Spearman correlation test. Thirty-three HCC lesions (average size 5.0 ± 3.6 cm) were analyzed. D, D*, and PF were all significantly lower in HCC vs. liver (P < 0.05). Significantly higher Fa and ART and lower Fp were observed in HCC vs. liver (P < 0.001). Significant moderate to strong negative correlations were observed between ART and D* (r = -0.443, P = 0.028), ART and PF (r = -0.536, P = 0.006), ART and PFxD* (r = -0.655, P < 0.001), Fa and PF (r = 0.455, P = 0.023), and Fa and PFxD* (r = -0.475, P = 0.018) in liver parenchyma. There was no significant correlation between IVIM-DWI and DCE-MRI metrics in HCC lesions. IVIM-DWI and DCE-MRI provide nonredundant information in HCC, while they correlate in liver parenchyma. These findings may be secondary to predominant portal inflow in the liver and tortuous vasculature and tissue heterogeneity in tumors. J. MAGN. RESON. IMAGING 2016;44:856-864.

Free-breathing liver perfusion imaging using 3-dimensional through-time spiral generalized autocalibrating partially parallel acquisition acceleration.

The goal of this study was to develop free-breathing high-spatiotemporal resolution dynamic contrast-enhanced liver magnetic resonance imaging using non-Cartesian parallel imaging acceleration, and quantitative liver perfusion mapping. This study was approved by the local institutional review board and written informed consent was obtained from all participants. Ten healthy subjects and 5 patients were scanned on a Siemens 3-T Skyra scanner. A stack-of-spirals trajectory was undersampled in-plane with a reduction factor of 6 and reconstructed using 3-dimensional (3D) through-time non-Cartesian generalized autocalibrating partially parallel acquisition. High-resolution 3D images were acquired with a true temporal resolution of 1.6 to 1.9 seconds while the subjects were breathing freely. A dual-input single-compartment model was used to retrieve liver perfusion parameters from dynamic contrast-enhanced magnetic resonance imaging data, which were coregistered using an algorithm designed to reduce the effects of dynamic contrast changes on registration. Image quality evaluation was performed on spiral images and conventional images from 5 healthy subjects. Images with a spatial resolution of 1.9 × 1.9 × 3 mm3 were obtained with whole-liver coverage. With an imaging speed of better than 2 s/vol, free-breathing scans were achieved and dynamic changes in enhancement were captured. The overall image quality of free-breathing spiral images was slightly lower than that of conventional long breath-hold Cartesian images, but it provided clinically acceptable or better image quality. The free-breathing 3D images were registered with almost no residual motion in liver tissue. After the registration, quantitative whole-liver 3D perfusion maps were obtained and the perfusion parameters are all in good agreement with the literature. This high-spatiotemporal resolution free-breathing 3D liver imaging technique allows voxelwise quantification of liver perfusion.

Hepatic necro-inflammation and elevated liver enzymes: Evaluation with MRI perfusion imaging with gadoxetic acid in chronic hepatitis patients

To evaluate liver necro-inflammation and function by using gadoxetic acid-enhanced dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), with histological analysis as the reference standard. Seventy-nine subjects (21 healthy subjects; 58 chronic hepatitis patients) who received gadoxetic acid-enhanced DCE-MRI were divided into three subgroups: no (A0, n = 31), mild (A1, n = 27), and moderate-severe (A2-A3, n = 21) activities. Two DCE-MRI models were measured: (1) a dual-input single-compartment model to obtain absolute arterial, portal venous, and total blood flow, arterial fraction (ART), distribution volume, and mean transit time; (2) a curve analysis method to obtain peak, slope, and AUC (area under curve). The serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels also obtained. Statistical testing included Kruskal-Wallis tests for continuous data, Pearson's correlation tests, and multiple linear regression analyses. Hepatic necro-inflammatory activity grades were significantly correlated with fibrotic stages, serum ALT level, ART and AUC. ART was helpful to predict the mild activity (≤ A1 versus >A1; Az = 0.728), whereas AUC could differentiate no activity from any activity (A0 versus >A0; Az = 0.703). Peak, slope and AUC were all associated with AST and ALT (p < 0.05). Gadoxetic acid-enhanced DCE-MRI parameters may be used to evaluate the severity of hepatic necro-inflammation and function.

Hepatocellular Carcinoma: Perfusion Quantification With Dynamic Contrast-Enhanced MRI

The objective of our study was to report our initial experience with dynamic contrast-enhanced MRI (DCE-MRI) for perfusion quantification of hepatocellular carcinoma (HCC) and surrounding liver. DCE-MRI of the liver was prospectively performed on 31 patients with HCC (male-female ratio, 26:5; mean age, 61 years; age range, 41-83 years). A dynamic coronal 3D FLASH sequence was performed at 1.5 T before and after injection of gadolinium-based contrast agent with an average temporal resolution of 3.8 seconds. Regions of interest were drawn on the abdominal aorta, portal vein, liver parenchyma, and HCC lesions by two observers in consensus. Time-activity curves were analyzed using a dual-input single-compartment model. The following perfusion parameters were obtained: arterial flow, portal venous flow, arterial fraction, distribution volume, and mean transit time (MTT). Thirty-three HCCs (mean size, 3.9 cm; range, 1.1-12.6 cm) were evaluated in 26 patients. When compared with liver parenchyma, HCC showed significantly higher arterial hepatic blood flow and arterial fraction (p < 0.0001) and significantly lower distribution volume and portal venous hepatic blood flow (p < 0.0001-0.023), with no difference in MTT. Untreated HCCs (n = 16) had a higher arterial fraction and lower portal venous hepatic blood flow value than chemoembolized HCCs (n = 17, p < 0.04). DCE-MRI can be used to quantify perfusion metrics of HCC and liver parenchyma and to assess perfusion changes after HCC chemoembolization.

An empirical mathematical model applied to quantitative evaluation of thioacetamide-induced acute liver injury in rats by use of dynamic contrast-enhanced computed tomography

Our purpose in this study was to apply an empirical mathematical model (EMM) to the quantitative evaluation of thioacetamide (TAA)-induced acute liver injury in rats by use of dynamic contrast-enhanced computed tomography (DCE-CT), and to investigate its usefulness in comparison with a dual-input, single-compartment model. The rats in the TAA-treated group were injected intravenously with 140 mg/kg body weight (n = 10) or 280 mg/kg body weight (n = 10) of TAA, whereas those in the control group (n = 10) were injected with saline instead of TAA. The DCE-CT studies were performed 2 days after injection of TAA or saline by use of a 4-detector row CT. The upper limit of the time-density curve (A), the rates of contrast uptake (α) and washout (β), the parameter related to the slope of early uptake (q), the area under the curve (AUC), the time to the maximum enhancement (T (max)), the maximum enhancement (C (Lmax)), and the elimination half-life of the contrast agent (T (1/2)) were calculated by use of the EMM. Serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT) were also measured. Both α and q decreased significantly in the rats of the TAA-treated group compared to those in the control group, whereas T (max) and T (1/2) increased significantly. The values of α, q, AUC, and T (max) were significantly correlated with both AST and ALT. Our results suggest that the EMM is useful for quantitative evaluation of TAA-induced acute liver injury and can be used as an alternative to the dual-input single-compartment model, especially when the vascular input functions cannot be obtained.

GPU-accelerated voxelwise hepatic perfusion quantification

Voxelwise quantification of hepatic perfusion parameters from dynamic contrast enhanced (DCE) imaging greatly contributes to assessment of liver function in response to radiation therapy. However, the efficiency of the estimation of hepatic perfusion parameters voxel-by-voxel in the whole liver using a dual-input single-compartment model requires substantial improvement for routine clinical applications. In this paper, we utilize the parallel computation power of a graphics processing unit (GPU) to accelerate the computation, while maintaining the same accuracy as the conventional method. Using compute unified device architecture-GPU, the hepatic perfusion computations over multiple voxels are run across the GPU blocks concurrently but independently. At each voxel, nonlinear least-squares fitting the time series of the liver DCE data to the compartmental model is distributed to multiple threads in a block, and the computations of different time points are performed simultaneously and synchronically. An efficient fast Fourier transform in a block is also developed for the convolution computation in the model. The GPU computations of the voxel-by-voxel hepatic perfusion images are compared with ones by the CPU using the simulated DCE data and the experimental DCE MR images from patients. The computation speed is improved by 30 times using a NVIDIA Tesla C2050 GPU compared to a 2.67 GHz Intel Xeon CPU processor. To obtain liver perfusion maps with 626 400 voxels in a patient's liver, it takes 0.9 min with the GPU-accelerated voxelwise computation, compared to 110 min with the CPU, while both methods result in perfusion parameters differences less than 10−6. The method will be useful for generating liver perfusion images in clinical settings.

Correction of arterial input function in dynamic contrast‐enhanced MRI of the liver

To develop a postprocessing method to correct saturation of arterial input function (AIF) in T1-weighted dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for quantification of hepatic perfusion. The saturated AIF is corrected by parameterizing the first pass of the AIF as a smooth function with a single peak and minimizing a least-squares error in fitting the liver DCE-MRI data to a dual-input single-compartment model. Sensitivities of the method to the degree of saturation in the AIF first-pass peak and the image contrast-to-noise ratio were assessed. The method was also evaluated by correlating portal venous perfusion with an independent overall liver function measurement. The proposed method corrects the distorted AIF with a saturation ratio up to 0.45. The corrected AIF improved hepatic arterial perfusion by -23.4% and portal venous perfusion by 26.9% in a study of 12 patients with liver cancers. The correlation between the mean voxelwise portal venous perfusion and overall liver function measurement was improved by using the corrected AIFs (R(2) = 0.67) compared with the saturated AIFs (R(2) = 0.39). The method is robust for correcting AIF distortion and has the potential to improve quantification of hepatic perfusion for assessment of liver tissue response to treatment in patients with hepatic cancers.

Neuroendocrine Tumor Liver Metastases: Use of Dynamic Contrast-enhanced MR Imaging to Monitor and Predict Radiolabeled Octreotide Therapy Response

To evaluate dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging for monitoring and assessing treatment response in patients with neuroendocrine liver metastases treated using yttrium 90 ((90)Y)-labeled octreotide ((90)Y-DOTATOC). The study was approved by the local research and ethics committee and patient informed consent was obtained. Twenty patients with liver metastases from neuroendocrine tumors underwent T1-weighted DCE MR imaging of the liver before and at 2 months after intravenous (90)Y-DOTATOC treatment. Regions of interest were drawn around target lesions, as well as along liver outlines for each patient. A dual-input single-compartment model was used to compute parameters including fractional distribution volume and the arterial flow fraction. Pre- and posttreatment values were compared using Wilcoxon signed rank test. Treatment response was defined as showing a greater than 50% reduction in the nadir chromogranin A level within the 1st year after treatment. Pretreatment values of responders and nonresponders were compared using the Mann-Whitney test. A two-tailed P value of .008 or less, which accounts for multiple testing, was considered to indicate a significant difference. In responders, tumor and whole liver distribution volume significantly increased after treatment (median tumor distribution volume, 0.182 vs 0.244; median whole liver distribution volume, 0.175 vs 0.207; P = .008). The pretreatment whole liver distribution volume was significantly lower in responders (median, 0.175 vs 0.248; P = .003), while pretreatment tumor arterial flow fraction was significantly higher in responders (median, 1.000 vs 0.7 ± 1, P = .006). DCE MR imaging may be used to monitor the effects of peptide receptor radiolabeled targeted therapy in patients with neuroendocrine tumors liver metastases; a lower pretreatment distribution volume and high arterial flow fraction was associated with a better response to treatment.

Dynamic contrast-enhanced magnetic resonance imaging with Gd-EOB-DTPA for the evaluation of liver fibrosis in chronic hepatitis patients

To develop a non-invasive MRI method for evaluation of liver fibrosis, with histological analysis as the reference standard. The study protocol was approved by the Institutional Review Board for Human Studies of our hospital, and written informed consent was obtained from all subjects. Seventy-nine subjects who received dynamic contrast-enhanced MRI (DCE-MRI) with Gd-EOB-DTPA were divided into three subgroups according to Metavir score: no fibrosis (n = 30), mild fibrosis (n = 34), and advanced fibrosis (n = 15). The DCE-MRI parameters were measured using two models: (1) dual-input single-compartment model for arterial blood flow (F (a)), portal venous blood flow, total liver blood flow, arterial fraction (ART), distribution volume, and mean transit time; and (2) curve analysis model for Peak, Slope, and AUC. Statistical analysis was performed with Student's t-test and the nonparametric Kruskal-Wallis test. Slope and AUC were two best perfusion parameters to predict the severity of liver fibrosis (>F2 vs. ≦F2). Four significantly different variables were found between non-fibrotic versus mild-fibrotic subgroups: F (a), ART, Slope, and AUC; the best predictor for mild fibrosis was F (a) (AUROC:0.701). DCE-MRI with Gd-EOB-DTPA is a noninvasive imaging, by which multiple perfusion parameters can be measured to evaluate the severity of liver fibrosis.

Usefulness of a dual-input single-compartment model for quantitative evaluation of thioacetamide-induced acute liver injury in rats using dynamic contrast-enhanced computed tomography

We undertook this study to investigate the usefulness of a dual-input single-compartment model for evaluating thioacetamide (TAA)-induced acute liver injury in rats by use of dynamic contrast-enhanced computed tomography (DCE-CT). The rats in the TAA-treated group were injected intravenously with 140 mg/kg (n = 10) or 280 mg/kg (n = 10) of TAA, whereas those in the control group (n = 10) were injected with saline. The rate constants for the transfer of the contrast agent from the hepatic artery to the liver (K(1a)), from the portal vein to the liver (K(1p)), and from the liver to the blood (k₂), as well as liver perfusion (LP), the arterial fraction of LP (AFLP), distribution volume (DV), and mean transmit time (MTT) were estimated with use of the dual-input single-compartment model. Serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT) were also measured. K(1p), k₂, and LP decreased significantly in the TAA-treated group compared to those in the control group, whereas K(1a), AFLP, DV, and MTT increased significantly. The above parameters except for K (1a) were significantly correlated with both AST and ALT. We concluded that DCE-CT using the dual-input single-compartment model is useful for quantitative evaluation of TAA-induced acute liver injury.

CT hepatic perfusion measurement: Comparison of three analytic methods

ObjectivesTo compare the efficacy of three analytic methods, maximum slope (MS), dual-input single-compartment model (CM) and deconvolution (DC), for CT measurements of hepatic perfusion and assess the effects of extra-hepatic systemic factors. Materials and methodsEighty-eight patients who were suspected of having metastatic liver tumors underwent hepatic CT perfusion. The scans were performed at the hepatic hilum 7–77s after administration of contrast material. Hepatic arterial and portal perfusions (HAP and HPP, ml/min/100ml) and arterial perfusion fraction (APF, %) were calculated with the three methods, followed by correlation assessment. Partial correlation analysis was used to assess the effects on hepatic perfusion values by various factors such as age, sex, risk of cardiovascular diseases, arrival time of contrast material at abdominal aorta, transit time from abdominal aorta to hepatic parenchyma, and liver dysfunction. ResultsMean HAP of MS was significantly higher than DC. HPP of CM was significantly higher than MS and CM, and HPP of MS was significantly higher than DC. There was no significant difference in APF. HAP and APF showed significant and moderate correlations among the methods. HPP showed significant and moderate correlations between CM and DC, and poor correlation between MS and CM or DC. All methods showed weak correlations between HAP or APF and age or sex. Finally, MS showed weak correlations between HAP or HPP and arrival time or cardiovascular risks. ConclusionsHepatic perfusion values arrived at with the three methods are not interchangeable. CM and DC are less susceptible to extra-hepatic systemic factors.

Hepatic computed tomography perfusion: comparison of maximum slope and dual-input single-compartment methods

The aim of the study was to compare two analytical methods-maximum slope (MS) and the dualinput single-compartment model (CM)-in computed tomography (CT) measurements of hepatic perfusion and to assess the effects of extrahepatic systemic factors. A total of 109 patients underwent hepatic CT perfusion. The scans were conducted at the hepatic hilum 7-77 s after administration of contrast material. Hepatic arterial perfusion (HAP) and portal perfusion (HPP) (ml/min/100 ml) and the arterial perfusion fraction (APF, %) were calculated with the two methods, followed by correlation assessment. Partial correlation analysis was used to assess the effects on hepatic perfusion values by various factors, including age, sex, risk of cardiovascular disease, compensation for respiratory misregistration, arrival time of contrast material at the abdominal aorta, transit time from abdominal aorta to hepatic parenchyma, and liver dysfunction. The mean HAPs, HPPs, and APFs were, respectively, 31.4, 104.2, and 23.9 for MS and 27.1, 141.3, and 22.1 for CM. HAP and APF showed significant (P<0.0001) and moderate correlation (γ=0.417 and 0.548) and HPP showed poor correlation (γ=0.172) between the two methods. While MS showed weak correlations (γ=-0.39 to 0.34; P<0.001 to <0.02) between multiple extrahepatic factors and perfusion values, CM showed weak correlation only between the patients' sex and HAP (γ=0.31, P=0.001). Hepatic perfusion values estimated by the two methods are not interchangeable. CM is less susceptible to extrahepatic systemic factors.

Timing bolus dynamic contrast‐enhanced (DCE) MRI assessment of hepatic perfusion: Initial experience

To assess whether dynamic contrast-enhanced (DCE) MRI timing bolus data from routine clinical examinations can be postprocessed to obtain hepatic perfusion parameters for diagnosing cirrhosis. We retrospectively identified 57 patients (22 with cirrhosis and 35 without cirrhosis) who underwent abdominal MRI, which included a low-dose (2 mL gadodiamide) timing bolus using a volumetric spoiled gradient echo T1-weighted sequence through the abdomen. Using a dual-input single-compartment model, the following perfusion parameters were measured: arterial, portal, and total blood flow; arterial fraction; mean transit time; and distribution volume. Those parameters were compared between patients with and without cirrhosis using t-tests. Receiver operating characteristic (ROC) curve analysis was used to identify the perfusion parameters that can best predict the presence of cirrhosis. The hepatic arterial fraction, arterial flow, and distribution volume in patients with cirrhosis (27.7 +/- 8.3%, 44.8 +/- 14.1 mL/minute/100 g, and 16.3 +/- 4.5%, respectively) were significantly higher than those without cirrhosis (18.7 +/- 4.4%, 28.5 +/- 11.7 mL/minute/100 g, and 14.0 +/- 4.2%, respectively; P < 0.05 for all). ROC analysis showed arterial fraction as the best predictor of cirrhosis, with sensitivity of 73% and specificity of 86%. Timing bolus DCE MR images from routine examinations can be postprocessed to yield potentially useful hepatic perfusion parameters.

Error analysis of the quantification of hepatic perfusion using a dual-input single-compartment model

We performed an error analysis of the quantification of liver perfusion from dynamic contrast-enhanced computed tomography (DCE-CT) data using a dual-input single-compartment model for various disease severities, based on computer simulations. In the simulations, the time-density curves (TDCs) in the liver were generated from an actually measured arterial input function using a theoretical equation describing the kinetic behavior of the contrast agent (CA) in the liver. The rate constants for the transfer of CA from the hepatic artery to the liver (K1a), from the portal vein to the liver (K1p), and from the liver to the plasma (k2) were estimated from simulated TDCs with various plasma volumes (V0s). To investigate the effect of the shapes of input functions, the original arterial and portal-venous input functions were stretched in the time direction by factors of 2, 3 and 4 (stretching factors). The above parameters were estimated with the linear least-squares (LLSQ) and nonlinear least-squares (NLSQ) methods, and the root mean square errors (RMSEs) between the true and estimated values were calculated. Sensitivity and identifiability analyses were also performed. The RMSE of V0 was the smallest, followed by those of K1a, k2 and K1p in an increasing order. The RMSEs of K1a, K1p and k2 increased with increasing V0, while that of V0 tended to decrease. The stretching factor also affected parameter estimation in both methods. The LLSQ method estimated the above parameters faster and with smaller variations than the NLSQ method. Sensitivity analysis showed that the magnitude of the sensitivity function of V0 was the greatest, followed by those of K1a, K1p and k2 in a decreasing order, while the variance of V0 obtained from the covariance matrices was the smallest, followed by those of K1a, K1p and k2 in an increasing order. The magnitude of the sensitivity function and the variance increased and decreased, respectively, with increasing disease severity and decreased and increased, respectively, with increasing stretching factor except for V0. Identifiability analysis showed that the identifiability between K1p and k2 was lower than that between K1a and k2 or between K1a and K1p. In conclusion, this study will be useful for understanding the accuracy and reliability of the quantitative measurement of liver perfusion using a dual-input single-compartment model and DCE-CT data.