Free-Breathing 3D Liver Perfusion Quantification Using a Dual-Input Two-Compartment Model

Abstract

The purpose of this study is to test the feasibility of applying a dual-input two-compartment liver perfusion model to patients with different pathologies. A total of 7 healthy subjects and 11 patients with focal liver lesions, including 6 patients with metastatic adenocarcinoma and 5 with hepatocellular carcinoma (HCC), were examined. Liver perfusion values were measured from both focal liver lesions and cirrhotic tissues (from the 5 HCC patients). Compared to results from volunteer livers, significantly higher arterial fraction, fractional volume of the interstitial space, and lower permeability-surface area product were observed for metastatic lesions, and significantly higher arterial fraction and lower vascular transit time were observed for HCCs (P < 0.05). Significantly lower arterial fraction and higher vascular transit time, fractional volume of the vascular space, and fractional volume of the interstitial space were observed for metastases in comparison to HCCs (P < 0.05). For cirrhotic livers, a significantly lower total perfusion, lower fractional volume of the vascular space, higher fractional volume of the interstitial space, and lower permeability-surface area product were noted in comparison to volunteer livers (P < 0.05). Our findings support the possibility of using this model with 3D free-breathing acquisitions for lesion and diffuse liver disease characterization.

Current Imaging Diagnosis of Hepatocellular Carcinoma

“…Wash-in, wash-out, and PEI can be used to differentiate hemangiomas from malignant liver lesions (HCCs and metastases) ( Table 7 , [ 105 ]). Using a variety of dual input perfusion models, several authors have reported a higher arterial fraction (comparable to HAF or HPI) and hepatic arterial blood flow, as well as a lower portal-venous flow and distribution volume (v e ) in HCC lesions compared to surrounding liver parenchyma [ 90 , 92 , 93 , 107 ]. Permeability-related parameters like K trans and K ep seem to be more dependent on the characteristics of the employed pharmacokinetic model, and as such, might contribute less to HCC diagnosis [ 92 ].…”

“…However, Chen et al demonstrated a significant correlation between these parameters and tumor proliferation status, histological grade, and microvascular density, which suggests that permeability parameters might offer insights into HCC prognosis [ 169 ]. In addition, arterial fraction, MTT, and BV seem to differ between HCC lesions, colorectal liver metastases, and hemangiomas and might aid in the differential diagnosis of focal liver lesions ( Table 7 , [ 107 , 108 , 169 ]).…”

Accelerated brain tumor dynamic contrast‐enhanced MRI using Adaptive Pharmaco‐Kinetic Model Constrained method

“…This makes APKMC quite generalizable to DCE-MRI reconstruction of other body parts by using appropriate PK models, such as the Dual-Input Two-Compartment Model for liver DCE-MRI. 35 In addition, a more precise, but also more complex PK model, which fits the data better, or the combination of several PK models, can be used to improve the reconstruction performance without greatly increasing the computational burden of optimization algorithm. For the image reconstruction part of APKMC, other priori knowledge such as the sparsity of coefficients matrix U can be exploited to obtain additional performance gains.…”

“…Another advantage of APKMC is that the Patlak model used in our method can be easily replaced by any other PK models without the need to tune regularization parameters because the choice of PK model is only related to the construction process of PK model‐based dictionary. This makes APKMC quite generalizable to DCE‐MRI reconstruction of other body parts by using appropriate PK models, such as the Dual‐Input Two‐Compartment Model for liver DCE‐MRI 35 . In addition, a more precise, but also more complex PK model, which fits the data better, or the combination of several PK models, can be used to improve the reconstruction performance without greatly increasing the computational burden of optimization algorithm.…”

Quantitative magnetic resonance imaging for focal liver lesions: bridging the gap between research and clinical practice

“…44,45 Studies have shown that both HCC and liiver metastases and HCC can be differentiated using perfusion and permeability parameters extracted from perfusion MR sequences. 46,47 Similarly, authors reported on ability of distribution volume and perfusion to differentiate liver metastases from neuroendocrine tumors according to their enhancement pattern (i.e., hypo or hyperenhanced). 48 In cirrhotic patients, most studies have focued on the differentiation between benign dysplastic nodules and HCC.…”