Quantification of Hemodynamic Changes in Chronic Liver Disease: Correlation of Perfusion-CT Data with Histopathologic Staging of Fibrosis

SIRT3/6: an amazing challenge and opportunity in the fight against fibrosis and aging

Fibrosis is a typical aging-related pathological process involving almost all organs, including the heart, kidney, liver, lung, and skin. Fibrogenesis is a highly orchestrated process defined by sequences of cellular response and molecular signals mechanisms underlying the disease. In pathophysiologic conditions associated with organ fibrosis, a variety of injurious stimuli such as metabolic disorders, epigenetic changes, and aging may induce the progression of fibrosis. Sirtuins protein is a kind of deacetylase which can regulate cell metabolism and participate in a variety of cell physiological functions. In this review, we outline our current understanding of common principles of fibrogenic mechanisms and the functional role of SIRT3/6 in aging-related fibrosis. In addition, sequences of novel protective strategies have been identified directly or indirectly according to these mechanisms. Here, we highlight the role and biological function of SIRT3/6 focus on aging fibrosis, as well as their inhibitors and activators as novel preventative or therapeutic interventions for aging-related tissue fibrosis.

Conventional and artificial intelligence-based computed tomography and magnetic resonance imaging quantitative techniques for non-invasive liver fibrosis staging

Chronic liver disease (CLD) ultimately develops into liver fibrosis and cirrhosis and is a major public health problem globally. The assessment of liver fibrosis is important for patients with CLD for prognostication, treatment decisions, and surveillance. Liver biopsies are traditionally performed to determine the stage of liver fibrosis. However, the risks of complications and technical limitations restrict their application to screening and sequential monitoring in clinical practice. CT and MRI are essential for evaluating cirrhosis-associated complications in patients with CLD, and several non-invasive methods based on them have been proposed. Artificial intelligence (AI) techniques have also been applied to stage liver fibrosis. This review aimed to explore the values of conventional and AI-based CT and MRI quantitative techniques for non-invasive liver fibrosis staging and summarized their diagnostic performance, advantages, and limitations.

Noninvasive staging of liver fibrosis: review of current quantitative CT and MRI-based techniques

Liver fibrosis features excessive protein accumulation in the liver interstitial space resulting from repeated tissue injury due to chronic liver disease. Liver fibrosis eventually proceeds to cirrhosis and associated complications. So, early diagnosis and staging of liver fibrosis are of vital importance for clinical treatment. Liver biopsy remains the gold standard for the diagnosing and staging of fibrosis, but it is suboptimal due to various limitations. Recently, efforts have been made to migrate toward noninvasive techniques for assessing liver fibrosis. CT is relatively easy to perform, relatively standardized for different scanners, and does not require additional hardware in liver fibrosis staging. MRI is frequently performed to characterize indeterminate liver lesions. Because it does not use ionizing radiation and features high image contrast, its role has increased in the staging of liver fibrosis. More recently, several studies on liver fibrosis staging using deep learning algorithms in CT or MRI have been proposed and have shown meaningful results. In this review, we summarize the basic concept, diagnostic performance, and advantages and limitations of each technique to noninvasively stage liver fibrosis.

CT hepatic arterial perfusion index does not allow stratification of the degree of esophageal varices and bleeding risk in cirrhotic patients in Child-Pugh classes A and B

Purpose

To evaluate if the hepatic arterial perfusion index (HPI) in liver parenchyma of cirrhotic patients can serve as a surrogate parameter for stratifying the degree of esophageal varices and related bleeding risks.

Methods

CT image data of sixty-six patients (59 men; mean age 68 years ± 10 years) with liver cirrhosis (Child–Pugh class A (35/66, 53%), B (25/66, 38%), and C (6/66, 9%) who underwent perfusion CT (PCT) for hepatocellular carcinoma (HCC) screening between April 2010 and January 2019 were retrospectively identified. HPI, a parameter calculated by a commercially available CT liver perfusion analysis software that is based on the double maximum slope model, using time attenuation curve to determine perfusion, was correlated with the degree of esophageal varices diagnosed at endoscopy and the number of bleeding events.

Results

Eta correlation coefficient for HPI/presence of esophageal varices was very weak (0.083). Spearman-Rho for HPI/grading of esophageal varices was very weak (0.037 (p = 0.804)). Kendall-Tau-b for HPI/grading of esophageal varices was very weak (0.027 (p = 0.807)). ANOVA and Bonferroni post-hoc-tests showed no significant difference of HPI between different grades of esophageal varices (F (3, 62) = 1.676, p = 0.186). Eta correlation coefficient for HPI/bleeding event was very weak (0.126).

Conclusion

The stratification of the degree of esophageal varices and the related bleeding risk by correlation with the HPI as a surrogate parameter for portal venous hypertension was not possible for patients with liver cirrhosis in Child–Pugh class A and B.

Graphic abstract

Hemodynamic Alteration in the Liver in Acute Hepatitis: A Quantitative Evaluation Using Computed Tomographic Perfusion

BACKGROUND/AIM

We aimed to elucidate the hemodynamic alterations in the liver of patients with acute hepatitis (AH) using computed tomography perfusion imaging.

PATIENTS AND METHODS

For 14 patients with AH and nine patients with no disease (ND group), we compared the mean arterial blood flow (AF), portal blood flow (PF) and perfusion index (%) [PI=AF/(AF+PF) ×100] of the right and left liver lobes and investigated their relationship with clinical factors.

RESULTS

The mean PI of the right lobe in the AH group (30.5±10.0%) was significantly higher than that in the ND group (20.8±9.7%) (p=0.031). For all patients of the AH and ND groups, the PI of the right lobe was increased as the prothrombin time decreased (R=-0.56, p=0.006) and as the prothrombin time-international normalized ratio increased (R=0.48, p=0.02).

CONCLUSION

The PI of the right liver lobe may increase in AH and may be a predictive parameter for the severity of hepatic failure.

Usefulness of diffusion derived vessel density computed from a simplified IVIM imaging protocol: An experimental study with rat biliary duct blockage induced liver fibrosis

OBJECTIVES

Liver vessel density can be evaluated by DDVD (diffusion derived vessel density): DDVD_(b0b1) = Sb0/ROIarea0 - Sb1/ROIarea1, where Sb0 and Sb1 refer to the liver signal when b is 0 or 1 s/mm². Sb1 and ROIarea1 may be replaced by other b-values. With a rat biliary duct ligation (BDL) model, this study assesses the usefulness of liver DDVD computed from a simplified IVIM imaging protocol using b = 25 and b = 50 to replace b = 1 s/mm², alone and in combination with other IVIM parameters.

METHODS

Male Sprague-Dawley rats were used. The rat number was 5, 5, 5, and 3 respectively, for the timepoints of 7, 14, 21, 28 days post-BDL surgery. 12 rats had partial biliary duct recanalization performed after the rats had BDL for 7 days and then again followed-up for a mean of 14 days. Liver diffusion MRIs were acquired at 3.0 T with a b-value distribution of 0, 25, 50, 75, 100, 150, 300, 700, 1000 s/mm². DDVD_mean (control rats n = 6) was the mean of DDVD_(b0b25) and DDVD_(b0b50). IVIM fitting started from b = 0 s/mm² with segmented fitting and a threshold b of 50 s/mm² (n = 5 for control rats). Three 3-D spaces were constructed using a combination of the four diffusion parameters.

RESULTS

The control rats and BDL rats (n = 18) had a liver DDVD_mean of 84.0 ± 26.2 and 44.7 ± 14.4 au/pixel (p < 0.001). All 3-D spaces totally separated healthy livers and all fibrotic livers (n = 30, BDL rats and recanalization rats). The mean relative distance between healthy liver cluster and fibrotic liver cluster was 0.331 for PF, D_slow, and D_fast; 0.381 for PF, D_fast, and DDVD_mean; and 0.384 for PF, D_slow, and DDVD_mean.

CONCLUSION

A combination of PF, D_slow, and D_fast allows total separation of healthy livers and fibrotic livers and the integration of DDVD improved the separation.

Non-invasive assessment of cirrhosis using multiphasic dual-energy CT iodine maps: correlation with model for end-stage liver disease score

PURPOSE

To determine whether multiphasic dual-energy (DE) CT iodine quantitation correlates with the severity of chronic liver disease.

METHODS

We retrospectively included 40 cirrhotic and 28 non-cirrhotic patients who underwent a multiphasic liver protocol DECT. All three phases (arterial, portal venous (PVP), and equilibrium) were performed in DE mode. Iodine (I) values (mg I/ml) were obtained by placing regions of interest in the liver, aorta, common hepatic artery, and portal vein (PV). Iodine slopes (λ) were calculated as follows: (I_equilibrium-I_arterial)/time and (I_equilibrium-I_PVP)/time. Spearman correlations between λ and MELD scores were evaluated, and the area under the curve of the receiver operating characteristic (AUROC) was calculated to distinguish cirrhotic and non-cirrhotic patients.

RESULTS

Cirrhotic and non-cirrhotic patients had significantly different λ_{equilibrium-arterial} [IQR] for the caudate (λ = 2.08 [1.39-2.98] vs 1.46 [0.76-1.93], P = 0.007), left (λ = 2.05 [1.50-2.76] vs 1.51 [0.59-1.90], P = 0.002) and right lobes (λ = 1.72 [1.12-2.50] vs 1.13 [0.41-0.43], P = 0.003) and for the PV (λ = 3.15 [2.20-5.00] vs 2.29 [0.85-2.71], P = 0.001). λ_{equilibrium-PVP} were significantly different for the right (λ = 0.11 [- 0.45-1.03] vs - 0.44 [- 0.83-0.12], P = 0.045) and left lobe (λ = 0.30 [- 0.25-0.98] vs - 0.10 [- 0.35-0.24], P = 0.001). Significant positive correlations were found between MELD scores and λ_{equilibrium-arterial} for the caudate lobe (ρ = 0.34, P = 0.004) and λ_{equilibrium-PVP} for the caudate (ρ = 0.26, P = 0.028) and right lobe (ρ = 0.33, P = 0.007). AUROC in distinguishing cirrhotic and non-cirrhotic patients were 0.72 (P = 0.002), 0.71 (P = 0.003), and 0.75 (P = 0.001) using λ_{equilibrium-arterial} for the left lobe, right lobe, and PV, respectively. The λ_{equilibrium-PVP} AUROC of the right lobe was 0.73 (P = 0.001).

CONCLUSION

Multiphasic DECT iodine quantitation over time is significantly different between cirrhotic and non-cirrhotic patients, correlates with the MELD score, and it could potentially serve as a non-invasive measure of cirrhosis and disease severity with acceptable diagnostic accuracy.

Liver segmental volume and attenuation ratio (LSVAR) on portal venous CT scans improves the detection of clinically significant liver fibrosis compared to liver segmental volume ratio (LSVR)

Background

The aim of this proof-of-concept study was to show that the liver segmental volume and attenuation ratio (LSVAR) improves the detection of significant liver fibrosis on portal venous CT scans by adding the liver vein to cava attenuation (LVCA) to the liver segmental volume ratio (LSVR).

Material and methods

Patients who underwent portal venous phase abdominal CT scans and MR elastography (reference standard) within 3 months between 02/2016 and 05/2017 were included. The LSVAR was calculated on portal venous CT scans as LSVR*LVCA, while the LSVR represented the volume ratio between Couinaud segments I-III and IV-VIII, and the LVCA represented the density of the liver veins compared to the density in the vena cava. The LSVAR and LSVR were compared between patients with and without significantly elevated liver stiffness (based on a cutoff value of 3.5 kPa) using the Mann–Whitney U test and ROC curve analysis.

Results

The LSVR and LSVAR allowed significant differentiation between patients with (n = 19) and without (n = 122) significantly elevated liver stiffness (p < 0.001). However, the LSVAR showed a higher area under the curve (AUC = 0.96) than the LSVR (AUC = 0.74). The optimal cutoff value was 0.34 for the LSVR, which detected clinically increased liver stiffness with a sensitivity of 53% and a specificity of 88%. With a cutoff value of 0.67 for the LSVAR, the sensitivity increased to 95% while maintaining a specificity of 89%.

Conclusion

The LSVAR improves the detection of significant liver fibrosis on portal venous CT scans compared to the LSVR.

Liver CT perfusion: which is the relevant delay that reduces radiation dose and maintains diagnostic accuracy?

OBJECTIVES

High radiation dose during CT perfusion (CTp) studies contributes to prevent CTp application in daily clinical practice. This work evaluates the consequences of scan delay on perfusion parameters and provides guidelines to help reducing the radiation dose by choosing the most appropriate delay.

METHODS

Fifty-nine patients (34 men, 25 women; mean age 68 ± 12) with colorectal cancer, without underlying liver disease, underwent liver CTp, with the acquisition starting simultaneously with iodinated contrast agent injection. Blood flow (BF) and hepatic perfusion index (HPI) were computed on the acquired examinations and compared with those of the same examinations when a variable scan delay (τ) is introduced. Dose length product, CT dose index, and effective dose were also computed on original and delayed examinations.

RESULTS

Altogether, three groups of delays (τ ≤ 4 s, 5 s ≤ τ ≤ 9 s, τ ≥ 10 s) were identified, yielding increasing radiation dose saving (RDS) (RDS ≤ 9.5%, 11.9% ≤ RDS ≤ 21.4%, RDS ≥ 23.8%) and decreasing perfusion accuracy (high (τ ≤ 4 s), medium (5 s ≤ τ ≤ 9 s), low (τ ≥ 10 s)). In particular, single-input and arterial BF and HPI were more insensitive to delay as regards the absolute variations (only 1 ml/min/100 g and 1%, respectively, for τ ≤ 9 s), than portal and total BF.

CONCLUSION

Using delays lower than 4 s does not change perfusion accuracy and conveys unnecessary dose to patients. Conversely, starting the acquisition 9 s after contrast agent injection yields a RDS of about 21%, with no significant losses in perfusion accuracy.

KEY POINTS

• Scan delays lower than 4 s do not alter perfusion accuracy and deliver an unnecessary radiation dose to patients. • Radiation dose delivered to patients can be reduced by 21.4% by introducing a 9-s scan delay, while keeping accurate perfusion values. • Using scan delays higher than 10 s, some perfusion parameters (portal and total BF) were inaccurate.

Intravoxel incoherent motion derived liver perfusion/diffusion readouts can be reliable biomarker for the detection of viral hepatitis B induced liver fibrosis

BACKGROUND

Recent two studies reported that intravoxel incoherent motion (IVIM) analysis can separate healthy livers and viral hepatitis B (VHB) induced liver fibrosis. However, in these two studies the starting b value for bi-exponential decay analysis was b =10 and 15 s/mm2 respectively. The current study has two primary aims. The first is to further confirm the diagnostic value of IVIM in detecting liver fibrosis. The second is to test whether by sampling very low b value densely, then b =0 s/mm2 image could be included to improve IVIM's diagnostic performance.

METHODS

This was a prospective study with data acquired at the Third Xiangya Hospital of Central South University, Changsha, China. Healthy volunteers and patients suspected of VHB induced liver fibrosis with liver biopsy performed, as well as hepatocellular carcinoma patients scheduled for surgery, were recruited. All the hepatocellular carcinoma patients had liver fibrosis. After exclusions based on pre-defined criteria for image data quality, for IVIM analysis this study included 20 healthy volunteers; 4 chronic VHB patients with biopsy showing no liver fibrosis; 11 stage-1 liver fibrosis patients, 10 stage-2 liver fibrosis patients, 2 stage-3 liver fibrosis patients, and 5 stage-4 liver fibrosis patients. In the liver fibrosis patients, 1, 19, and 8 cases had inflammation grade-0, grade-1, and grade-2 respectively. The reference IVIM bi-exponential decay curve fitting analysis was segmented fitting performed with b =2 s/mm2 image as the starting point and a threshold-b of 60 s/mm2. This reference fitting method was compared with threshold-b of 40 s/mm2, full fitting, fitting starting from b =0, 5, and 10 s/mm2 respectively. The potential correlation between IVIM readouts and liver function was assessed for the liver fibrosis patients.

RESULTS

Based on the smaller coefficient of variation (CoV) for the volunteer group and the smaller patient/volunteer ratios [= (mean measurement for patient groups)/(mean measurement for healthy volunteers)], the comparison of fitting methods favored the reference approach starting from b =2 s/mm2 with a threshold-b of 60 s/mm2. The IVIM measures of four patients without liver fibrosis resembled those of healthy subjects. PF offered the best diagnostic value for separating healthy livers and fibrotic livers, and a threshold of PF =0.1406 separated all fibrotic livers and healthy livers with an exception of one hepatocellular carcinoma patient (fibrosis grade-2/inflammation grade-2). The correlation between fibrosis grading and inflammation grading was weakly positive; while compared with fibrotic livers with inflammation grade-1, fibrotic livers with inflammation grade-2 showed a trend of higher Dfast. A weak correlation is shown with lower PF and lower Dfast associated with lower total protein, lower albumin; higher alanine transaminase, higher aspartate transaminase; higher total bilirubin, and higher direct bilirubin.

CONCLUSIONS

Segmented-fitting with threshold-b =60 s/mm2 and starting from non-zero very low b value outperforms other methods. IVIM has high sensitivity in detecting liver fibrosis, and PF and Dfast have potential correlation with serum liver function biomarkers. IVIM measures and liver fibrosis grading are not in a linear relationship.