Improved hepatic arterial fraction estimation using cardiac output correction of arterial input functions for liver DCE MRI

Abstract

Liver dynamic contrast enhanced (DCE) MRI pharmacokinetic modelling could be useful in the assessment of diffuse liver disease and focal liver lesions, but is compromised by errors in arterial input function (AIF) sampling. In this study, we apply cardiac output correction to arterial input functions (AIFs) for liver DCE MRI and investigate the effect on dual-input single compartment hepatic perfusion parameter estimation and reproducibility.Thirteen healthy volunteers (28.7 ± 1.94 years, seven males) underwent liver DCE MRI and cardiac output measurement using aortic root phase contrast MRI (PCMRI), with reproducibility (n = 9) measured at 7 d. Cardiac output AIF correction was undertaken by constraining the first pass AIF enhancement curve using the indicator-dilution principle. Hepatic perfusion parameters with and without cardiac output AIF correction were compared and 7 d reproducibility assessed.Differences between cardiac output corrected and uncorrected liver DCE MRI portal venous (PV) perfusion (p = 0.066), total liver blood flow (TLBF) (p = 0.101), hepatic arterial (HA) fraction (p = 0.895), mean transit time (MTT) (p = 0.646), distribution volume (DV) (p = 0.890) were not significantly different. Seven day corrected HA fraction reproducibility was improved (mean difference 0.3%, Bland–Altman 95% limits-of-agreement (BA95%LoA) ±27.9%, coefficient of variation (CoV) 61.4% versus 9.3%, ±35.5%, 81.7% respectively without correction). Seven day uncorrected PV perfusion was also improved (mean difference 9.3 ml min−1/100 g, BA95%LoA ±506.1 ml min−1/100 g, CoV 64.1% versus 0.9 ml min−1/100 g, ±562.8 ml min−1/100 g, 65.1% respectively with correction) as was uncorrected TLBF (mean difference 43.8 ml min−1/100 g, BA95%LoA ±586.7 ml min−1/ 100 g, CoV 58.3% versus 13.3 ml min−1/100 g, ±661.5 ml min−1/100 g, 60.9% respectively with correction). Reproducibility of uncorrected MTT was similar (uncorrected mean difference 2.4 s, BA95%LoA ±26.7 s, CoV 60.8% uncorrected versus 3.7 s, ±27.8 s, 62.0% respectively with correction), as was and DV (uncorrected mean difference 14.1%, BA95%LoA ±48.2%, CoV 24.7% versus 10.3%, ±46.0%, 23.9% respectively with correction).Cardiac output AIF correction does not significantly affect the estimation of hepatic perfusion parameters but demonstrates improvements in normal volunteer 7 d HA fraction reproducibility, but deterioration in PV perfusion and TLBF reproducibility. Improved HA fraction reproducibility maybe important as arterialisation of liver perfusion is increased in chronic liver disease and within malignant liver lesions.

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

“…Of the 30 perfusion property measurements made by both the curve fitting and dictionary matching methods in Table 1, zero ROIs showed statistically significant differences, indicating that both methods perform comparably. The mean AF measurement of the three healthy liver subjects ranged from 19-28%, which is within the expected range for normal liver tissue 22 . The mean AF measurements for all of the metastatic and hepatocellular carcinoma tumors were comparatively very high (over 90% in all cases), which is consistent with the fact that these tumors are known to induce arterial angiogenesis 23 .…”

Dynamic contrast‑enhanced MRI differentiates hepatocellular carcinoma from hepatic metastasis of rectal cancer by extracting pharmacokinetic parameters and radiomic features

“…In the present study, the K trans value of HCC was higher compared with that of HRMC, indicating that HCC exhibited a higher level of infiltration and permeability compared with those of HRMC on the vascular surface, which may be used for the differential diagnosis of the two lesions. The IAUC value, which was represented by the AUC of the time-concentration curve of the contrast agent, refers to the estimated value of the concentration of the contrast agent in the lesion (9). The degree of enhancement varies for lesions with different etiologies, and the IAUC value may be used to identify lesions with different properties (19,21).…”

“…The endothelial transfer constant (K trans ) reflects the microvascular changes in the lesion area, and the K trans value in the tumor area is markedly increased compared with that in normal tissue, which may be used to observe the vascular permeability changes of the liver and tumor tissues (8). The initial area under the gadolinium concentration curve during the first 60 sec (IAUC) is a semi-quantitative parameter that represents the contrast agent concentration in the lesion during the first 60 sec (9). Hepatic perfusion index (HPI) refers to the hepatic artery blood supply fraction related to the portal vein as a reference standard; lesions with different pathogeneses have different HPI values (10).…”

“…Hepatic perfusion index (HPI) refers to the hepatic artery blood supply fraction related to the portal vein as a reference standard; lesions with different pathogeneses have different HPI values (10). Previous studies have demonstrated that quantified pharmacokinetic parameters, such as K trans , IAUC and HPI, derived from DCE-MRI exhibit high potential in assessing liver tumors (7)(8)(9)(10).…”

Towards Improved Pharmacokinetic Models for the Analysis of Transporter-Mediated Hepatic Disposition of Drug Molecules with Positron Emission Tomography

“…Thus, considering only AIF as a source of radioactivity to a liver PK model might not be accurate. Since direct blood sampling from the PV is not feasible in humans, several previous modeling approaches have applied image-derived PV blood curves (34–36). However, this approach is prone to imaging artifacts such as partial volume effects or respiratory motion, which are challenging to correct for and which may affect the accuracy of the model-derived parameter estimates (37).…”