Hepatitis C virus (HCV) is the main agent of post-transfusion chronic hepatitis and liver fibrosi s[11]. The highest incidence of HCV infection in the world is in Egypt [12], which makes a need for different laboratory and radiological methods to asses liver injury [13].
In the last few years, Fibroscan was considered as a fast, safe, and reproducible procedure to assess liver stiffness to predict liver fibrosis stag e[14,15,16].
However, Fibroscan cannot be used in obese patients, ascites, and narrow intercostal spaces [17].
Diffusion-weighted imaging enables qualitative and quantitative assessment of tissue diffusivity. Random motion of water molecules in the liver can be quantified by calculation of the apparent diffusion coefficient (ADC). The ADC of livers with moderate or advanced fibrosis and cirrhosis has been reported to be lower than that of normal livers or livers with mild fibrosis across multiple studies [18].
DWI is a crucial sequence in the MR abdomen, but the lack of standardization of DWI acquisition techniques is a major limitation of more broad and uniform use of ADC measurements as a quantitative biomarker. The variability in reported ADC values is further complicated by the use of different b values and acquisition methods based on breath-hold, free-breathing, or respiratory triggered techniques, which can affect ADC quantification and that should have influenced all of the abdominal organs scanned, including not only the liver, but also the spleen, pancreas, kidney, and paraspinal muscle. So, in our study as well as previous studies, we assume that normalization using a reference organ would not be affected by different respiratory motion compensation techniques [19].
Many researchers have tried to evaluate the impact of the apparent diffusion coefficient (ADC) measurements in the assessment of liver diseases. Many studies show that the cirrhotic livers are of lower ADC values than the healthy livers [20]. This is consistent with our study as we also demonstrated a linear negative correlation between liver ADC value and fibrosis stages (r = − 0.63). We also found that the mean liver ADC value in patients with hepatic fibrosis was significantly lower than that of volunteers (1.47 × 10−3 mm2/s vs 1.65 × 10−3 mm2/s, p = 0.04) [21, 22].
In another study done by Sandrasegaran et al. [23], ADC was able to differentiate cirrhotic from the non-cirrhotic liver with lower ADC values of the former; however, in that study, ADC could not categorize liver fibrosis in different stages; this is also confirmed by Razek et al. [24]. Earlier study done by Do et al. [25] concluded that liver ADC failed to distinguish individual stages of fibrosis, except between stages 0 and 4 mm; these results are the same to ours.
The variability in reported ADC values is further complicated using different b values and acquisition methods based on breath-hold, free-breathing, or respiratory triggered techniques, which can affect ADC quantification [26, 27]. For example, in our study, mean liver ADC (b = 800) for the control group was 1.65 ± 0.44 × 10−3 mm2/s and nADC liver 1.87 ± 0.50, while in a recent study done by Shin et al. [28], the mean liver ADCs for the control group (F0) was 1.389 × 10−3 mm2/s, and nADC liver was 1.977.
In the study carried out by Kim et al. [29], there was no difference between spleen ADCs values between diseased and volunteers’ individuals. This supports our results as there was no significant difference between spleen ADC values among patients in comparison to control (1 ± 0.33 × 10−3 mm2/s vs 0.85 ± 1.61 × 10−3 mm2/s, p = 0.24); also, there was no significant difference in the spleen ADC between different stages of fibrosis (r = 0.105; p = 0.866).
Pervious results of Do et al. [25] showed that area under ROC curve values of nADC were higher than liver ADC values. AUC of nADC ≥ F2 stages was 0.864 with sensitivity and specificity of 90% and 77% respectively while ADC values were 0.655 with sensitivity and specificity of 61% and 61% respectively (p = 0.013); AUC of nADC ≥ F3 stages was 0.805 with sensitivity and specificity of 96% and 71% respectively while ADC values were 0.689 with sensitivity and specificity of 56% and 71% respectively (p = 0.015), and nADC AUC for F4 stage was 0.935 with sensitivity and specificity of 95% and 66% respectively while ADC AUC was 0.720 with sensitivity and specificity of 76% and 60% respectively (p = 0.185).
While our study reveals close results, there was a statistically significant difference between area under the receiver operating characteristic curve (AUC) of normalized liver ADC and ADC for all comparison’s subsets except for diagnosis of cirrhosis (stage 4). nADC AUC was 0.878 for detection of ≥ F2 stages with sensitivity and specificity of 87% and 80% respectively while ADC value was 0.548 with sensitivity and specificity of 62% and 72% respectively (p = 0.021); nADC AUC for ≥ F3 stages was 0.891 with sensitivity and specificity of 88.7% and 80% respectively while ADC values were 0.603 with sensitivity and specificity of 72% and 72% respectively (p = 0.023), and F4 stage nADC AUC was 0.879 with sensitivity and specificity of 90% and 80% respectively, while ADC values were 0.648 with sensitivity and specificity of 80% and 72% respectively (p = 0.054). We acknowledge some limitations in current study as small number of subjects enrolled in this study and the lack of biopsy.