Technical noteAssessment of hepatocellular carcinoma using apparent diffusion coefficient and diffusion kurtosis indices: preliminary experience in fresh liver explants☆
Introduction
Diffusion-weighted imaging (DWI) has shown potential for improved hepatocellular carcinoma (HCC) detection [1], [2], prediction of HCC aggressiveness [3], [4] and evaluation of HCC response following transarterial chemoembolization (TACE) [5], [6]. However, other studies have provided less promising data regarding the role of DWI for HCC assessment [7], [8], [9]. One limitation of standard DWI is that apparent diffusion coefficients (ADCs) are calculated using a monoexponential analysis, which assumes Gaussian behavior of water diffusion. Diffusion kurtosis imaging (DKI) is an advanced DWI model that quantifies non-Gaussian behavior of diffusion and provides both a corrected ADC as well as the excess kurtosis of tissue, a measure of the extent to which tissue diffusion deviates from a Gaussian pattern [10]. It is believed that the DKI model is more sensitive to tissue microstructural complexity than is standard DWI [11], [12]. DKI has been shown to better predict grade of gliomas [13] and to provide a better fit of diffusion data for head-and-neck cancers [14] than the standard monoexponential DWI model.
It is possible that DKI may also have value for assessment of HCC. However, performance of DKI in the liver is challenging given the need to acquire higher b-values with DKI than are used for standard DWI. The difficulty of such a technique within the liver relates to short T2 relaxation times of liver parenchyma [15] that limit signal-to-noise ratio (SNR) at high b-values. In addition, obtaining good image quality for high b-value images in the liver can be difficult given respiratory motion artifact. These challenges can be addressed ex vivo, given higher SNR achievable through longer scan times than are feasible in a clinical setting, as well as absence of respiratory motion. While ex vivo tissue properties and associated MR metrics may differ from the in vivo case, the study of ex vivo specimens may still provide valuable intuition regarding the information content of DKI metrics in HCC. Therefore, the aim of this study was to perform ex vivo evaluation of the utility of DKI for the assessment of HCC, including treatment response, using fresh liver explants.
Section snippets
Subjects
This prospective HIPAA-compliant study was approved by our Institutional Review Board. Twelve patients (mean age 56.9±11.7 years, range 29–78 years; 10 men, 2 women) with known HCC who underwent liver transplantation (LT) between 10/1/2009 and 5/1/2011 were included. All patients provided written informed consent prior to LT. Etiologies of liver disease were as follows: hepatitis C (n= 6), hepatitis B (n= 3), alcohol use (n= 2), and both hepatitis B and C (n= 1). Nine patients had undergone
Lesions
Sixteen HCCs in 12 patients were included (9 patients with 1 lesion, 2 patients with 2 lesions and 1 patient with 3 lesions). The lesions had mean size of 2.1±1.2 cm (range 0.9–4.5 cm). One HCC had a small component of intermixed cholangiocarcinoma, histologically constituting less than 10% of the lesion.
Summary of kurtosis metrics
Fig. 1 shows results for a representative case. This figure demonstrates better fit of signal intensity data derived from the total-lesion ROI for this case using the non-Gaussian kurtosis
Discussion
In this study, we used fresh liver explants to demonstrate feasibility of DKI for assessment of HCC. DKI employs an extended b-value range to model non-Gaussian diffusion behavior. This model is intended to provide greater sensitivity to tissue microstructural complexity. K ranged from 0.56 to 2.38 in our series, indicative of intermediate to substantial non-Gaussian diffusion of HCC. There was substantial deviation of D, a corrected ADC value accounting for non-Gaussian diffusion, from ADC
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Grant support: none.