Quantification of Liver Surface Nodularity at CT: Utility for Detection of Portal Hypertension

Prediction of portal venous pressure in living donor liver transplantation: A retrospective study

Liver transplantation is the definitive treatment for advanced liver cirrhosis with portal hypertension. In Japan, the scarcity of deceased donors leads to reliance on living donors, often resulting in smaller grafts. Managing portal venous pressure (PVP) is critical to prevent fatal posttransplant complications. This study explored the possibility of predicting intraoperative PVP. We analyzed 475 living donor liver transplant cases from 2006 to 2023, excluding those with acute liver failure or prior splenectomy or splenic artery embolization. Patients were divided into a training group (n = 425) and a test group (n = 50). We evaluated the correlation between preoperative factors and PVP at laparotomy to predict PVP at laparotomy and closure. The predictive model was validated with the test group data. PVP at laparotomy could be predicted using correlated preoperative factors: prothrombin time ( p < 0.001), predicted splenic volume ( p < 0.001), and presence of a portosystemic shunt ( p = 0.002), as follows: predicted PVP at laparotomy (mm Hg)=25.818 - 0.077 × (prothrombin time [%]) + 0.004 × (predicted splenic volume [mL]) - 2.067 × (1: with a portosystemic shunt) ( p < 0.001; R = 0.346). In addition, PVP at closure could be predicted using correlated operative factors, including measured PVP at laparotomy, as follows: predicted PVP at closure (mm Hg)=14.268 + 0.149 × (measured PVP at laparotomy [mm Hg]) - 0.040 × (GV/SLV [%]) - 0.862 × (1: splenectomy [if yes]) - 3.511 × (1: splenic artery ligation without splenectomy [if yes]) ( p < 0.001; R = 0.339). This study demonstrated the feasibility of predicting intraoperative PVP using preoperative factors in patients with decompensated cirrhosis undergoing liver transplant. This predictive approach could refine surgical planning, potentially improving patient outcomes.

Non-invasive assessment of portal hypertension: Liver stiffness and beyond

Portal hypertension (PH) leads to life-threatening clinical manifestations such as bleeding from gastro-oesophageal varices, ascites and its complications, and portosystemic encephalopathy. It can develop because of advanced chronic liver disease (ACLD) or due to rarer causes such as vascular liver disease. Reference standard methods to assess PH in ACLD include the measurement of hepatic venous pressure gradient and endoscopy, which have limitations due to their high resource utilisation and invasiveness. Non-invasive tests (NITs) have entered clinical practice and allow invasive procedures to be reserved for patients with indeterminate findings on NITs or for specific clinical questions. In this review, we present an update on the role of NITs, and in particular ultrasound elastography, to diagnose PH in ACLD and vascular liver disease, and to stratify the risk of liver-related events. We also provide insights into the open research questions and design of studies in this field.

Liver segmental volumes and their relationship with 5-year prognostication

PURPOSE

This study aimed to analyze the predictive value of caudate to right lobe ratio (CRL-R) and liver segmental volume ratio (LSVR) for chronic liver disease (CLD) on routine abdominal CT scans and their association with 5-year decompensation- and transplant-free survival.

METHOD

This retrospective study included 108 patients without CLD and 98 patients with biopsy-proven CLD. All patients underwent abdominal CT scans between 03/2015 and 08/2017. Patients with CLD were divided into three groups: early CLD (F0-F2; eCLD; n = 40), advanced CLD (F3-F4; aCLD; n = 20), and aCLD with clinically significant portal hypertension (aCLDPH; n = 38). CRL-R and LSVR were compared between groups using Kruskal-Wallis test and ROC analysis to determine cutoff-values. 5-year decompensation- and transplant-free survival were assessed by Kaplan-Meier curve analysis.

RESULTS

CRL-R and LSVR were significantly different between all groups (p < 0.001). A CRL-R cutoff-value of > 0.99 predicted aCLD with a sensitivity of 69% and a specificity of 80% (AUC = 0.75, p < 0.001), while LSVR > 0.37 had a sensitivity of 67% and a specificity of 84% (AUC = 0.80, p < 0.001). CLD-patients with both CRL-R > 0.99 and LSVR > 0.37 had a significantly lower probability of 5-year decompensation-free survival (31%) as well as lower probability of 5-year transplant-free survival (41%) than those with a CRL-R < 0.99 and/or LSVR < 0.37 (70%, 62%, p = 0.006, p = 0.038).

CONCLUSION

CRL-R and LSVR showed a high predictive value for CLD on routine abdominal CT scans. In patients with CLD, both CRL-R and LSVR may be combined and are associated with 5-year decompensation-free and transplant-free survival.

Fully Automated and Explainable Measurement of Liver Surface Nodularity in CT: Utility for Staging Hepatic Fibrosis

RATIONALE AND OBJECTIVES

In the United States, cirrhosis was the 12th leading cause of death in 2016. Despite end-stage cirrhosis being irreversible, earlier stages of hepatic fibrosis can be reversed via early diagnosis and intervention. The objective is to investigate the utility of a fully automated technique to measure liver surface nodularity (LSN) for staging hepatic fibrosis (stages F0-F4).

MATERIALS AND METHODS

In this retrospective study, a dataset consisting of patients with multiple etiologies of liver disease collected at Institution-A (METAVIR F0-F4, 2000-2016) was used. The LSN was automatically measured in contrast-enhanced CT volumes and compared against scores from a manual tool. Area under the receiver operating characteristics curve (AUC) was used to distinguish between clinically significant fibrosis (≥ F2), advanced fibrosis (≥F3), and end-stage cirrhosis (F4).

RESULTS

The study sample had 480 patients (304 men, 176 women, mean age, 49±9). Automatically derived LSN scores progressively increased with the fibrosis stage: F0 (1.64 [mean]±1.13 [standard deviation]), F1 (2.16±2.39), F2 (2.17±2.55), F3 (2.23±2.52), and F4 (4.21±2.94). For discriminating significant fibrosis (≥F2), advanced fibrosis (≥F3), and cirrhosis (F4), the automated tool achieved ROC AUCs of 73.9%, 82.5%, and 87.8% respectively. The sensitivity and specificity for significant fibrosis (nodularity threshold 1.51) was 85.2% and 73.3%, advanced fibrosis (nodularity threshold 1.73) was 84.2% and 79.5%, and cirrhosis (nodularity threshold 2.18) was 86.5% and 79.5%. Statistical tests revealed that the automated LSN scores distinguished patients with advanced fibrosis (p<.001) and cirrhosis (p<.001).

CONCLUSION

The fully automated LSN measurement retained its predictive power for distinguishing between advanced fibrosis and cirrhosis. The clinical impact is that the fully automated LSN measurement may be useful for early interventions and population-based studies. It can automatically predict the fibrosis stage in ∼45 s in comparison to the ∼2 min needed to manually measure the LSN in a CT volume.

Quantitative Edge Analysis Can Differentiate Pancreatic Carcinoma from Normal Pancreatic Parenchyma

This study aimed to introduce specific image feature analysis, focusing on pancreatic margins, and to provide a quantitative measure of edge irregularity, evidencing correlations with the presence/absence of pancreatic adenocarcinoma. We selected 50 patients (36 men, 14 women; mean age 63.7 years) who underwent Multi-detector computed tomography (MDCT) for the staging of pancreatic adenocarcinoma of the tail of the pancreas. Computer-assisted quantitative edge analysis was performed on the border fragments in MDCT images of neoplastic and healthy glandular parenchyma, from which we obtained the root mean square deviation SD of the actual border from the average boundary line. The SD values relative to healthy and neoplastic borders were compared using a paired t-test. A significant SD difference was observed between healthy and neoplastic borders. A threshold SD value was also found, enabling the differentiation of adenocarcinoma with 96% specificity and sensitivity. We introduced a quantitative measure of boundary irregularity, which correlates with the presence/absence of pancreatic adenocarcinoma. Quantitative edge analysis can be promptly performed on select border fragments in MDCT images, providing a useful supporting tool for diagnostics and a possible starting point for machine learning recognition based on lower-dimensional feature space.

The Negative Impact of Sarcopenia on Hepatocellular Carcinoma Treatment Outcomes

INTRODUCTION

Hepatocellular carcinoma (HCC) represents a major global health concern, characterized by evolving etiological patterns and a range of treatment options. Among various prognostic factors, sarcopenia, characterized by loss of skeletal muscle mass, strength, and function, has emerged as a pivotal contributor to HCC outcomes. Focusing on liver transplantation, surgical resection, locoregional treatments, and systemic therapies, this review aims to analyze the impact of sarcopenia on HCC treatment outcomes, shedding light on an underexplored subject in the pursuit of more personalized management.

METHODS

A comprehensive literature review was conducted by searching peer-reviewed articles on sarcopenia and treatment outcomes in patients with HCC from inception up to October 2023.

RESULTS

Sarcopenia was found to be prevalent among HCC patients, exhibiting different occurrence, possibly attributable to diverse diagnostic criteria. Notably, despite variations in studies utilizing skeletal muscle indices, sarcopenia independently correlated with lower overall survival (OS), recurrence-free survival (RFS), and progression-free survival (PFS) across surgical (both transplantation and resection), locoregional, and systemic therapies, including tyrosine-kinase inhibitors (TKIs) and immune-checkpoint inhibitors (ICIs). Moreover, a link between sarcopenia and increased rate and severity of adverse events, particularly in surgery and TKIs recipients, and larger tumor size at diagnosis was observed. While baseline sarcopenia negatively influenced treatment outcomes, alterations in muscle mass post-treatment emerged as primary determinants of reduced OS.

CONCLUSIONS

Sarcopenia, either present before or after HCC treatment, negatively correlates with response to it, across all etiologies and therapeutic strategies. Although only a few studies have evaluated the impact of supervised physical activity training on muscle mass and OS after HCC treatment, it is crucial to evaluate the presence of sarcopenia before treatment initiation, to better stratify patients' prognosis, thus performing a more tailored approach, and identify therapies able to restore muscle mass in HCC patients. Conversely, the impact of sarcopenia on HCC recurrence and extrahepatic spread remains inadequately explored.

Obliteration of portal venules contributes to portal hypertension in biliary cirrhosis

The effects of the obliteration of portal venules (OPV) in cirrhotic portal hypertension are poorly understood. To investigate its contribution to portal hypertension in biliary cirrhosis and its underlying mechanism, we evaluated OPV using two-dimensional (2D) histopathology in liver explants from patients with biliary atresia (BA, n = 63), primary biliary cholangitis (PBC, n = 18), and hepatitis B-related cirrhosis (Hep-B-cirrhosis, n = 35). Then, three-dimensional (3D) OPV was measured by X-ray phase-contrast CT in two parallel models in rats following bile duct ligation (BDL) or carbon tetrachloride (CCl4) administration, representing biliary cirrhosis and post-necrotic cirrhosis, respectively. The portal pressure was also measured in the two models. Finally, the effects of proliferative bile ducts on OPV were investigated. We found that OPV was significantly more frequent in patients with biliary cirrhosis, including BA (78.57 ± 16.45%) and PBC (60.00 ± 17.15%), than that in Hep-B-cirrhotic patients (29.43 ± 14.94%, p < 0.001). OPV occurred earlier, evidenced by the paired liver biopsy at a Kasai procedure (KP), and was irreversible even after a successful KP in the patients with BA. OPV was also significantly more frequent in the BDL models than in the CCl4 models, as shown by 2D and 3D quantitative analysis. Portal pressure was significantly higher in the BDL model than that in the CCl4 model. With the proliferation of bile ducts, portal venules were compressed and irreversibly occluded, contributing to the earlier and higher portal pressure in biliary cirrhosis. OPV, as a pre-sinusoidal component, plays a key role in the pathogenesis of portal hypertension in biliary cirrhosis. The proliferated bile ducts and ductules gradually take up the 'territory' originally attributed to portal venules and compress the portal venules, which may lead to OPV in biliary cirrhosis. © 2024 The Pathological Society of Great Britain and Ireland.

Prediction of Hepatic Encephalopathy After Transjugular Intrahepatic Portosystemic Shunt Based on CT Radiomic Features of Visceral Adipose Tissue

RATIONALE AND OBJECTIVES

To evaluate the performance and clinical utility of CT radiomic features of visceral adipose tissue (VAT) in the prediction of hepatic encephalopathy (HE) after transjugular intrahepatic portosystemic shunt (TIPS).

MATERIALS AND METHODS

This multi-center study was retrospectively designed. Patients with cirrhosis who underwent TIPS were recruited from January 2015 to December 2020. Pre-TIPS contrast-enhanced CT images were collected for VAT segmentation and radiomic feature extraction. Least absolute shrinkage and selection operator regression with ten-fold cross-validation was performed to reduce dimension. Logistic regression with regularization, support vector machine, and random forest were used for model construction.

RESULTS

A total of 130 patients (90 men; mean age, 54 ± 11 years) were finally enrolled. The cohort was split into 85 patients for the training set (58 men; mean age, 53 ± 12 years) with 19 HE, 21 patients for the internal test set (17 men; mean age, 53 ± 11 years) with 5 HE, and 24 patients for the external test set (15 men; mean age, 55 ± 11 years). Ten radiomic features and C-reactive protein constituted radiomic-clinical models with the best performance. The average area under the receiver operating characteristic curve is 0.97 in the training set and 0.84 in the test sets. For a fixed sensitivity of 0.90, the specificity and negative predictive value of the model is 0.63 and 1.00, respectively; while for a fixed specificity of 0.90, the sensitivity and positive predictive value is 0.60 and 0.75, respectively.

CONCLUSION

Machine learning models based on CT radiomic features extracted from VAT can predict post-TIPS HE with satisfactory performance.

CLINICAL RELEVANCE STATEMENT

Our machine learning models based on CT radiomic features of visceral adipose tissue in patients with cirrhosis may assist in predicting hepatic encephalopathy after transjugular intrahepatic portosystemic shunt, indicating its potential in patient selection and clinical decision-making.

KEY POINTS

Radiomics of visceral adipose tissue provide great help in predicting hepatic encephalopathy after transjugular intrahepatic portosystemic shunt. The clinical-radiomic models showed satisfactory performance with an average area under the receiver operating characteristic curve of 0.84. The model can hypothetically provide 90% sensitivity and 100% negative predictive value for guiding patients who are considering transjugular intrahepatic portosystemic shunt.

Liver surface nodularity and ascites are associated with mortality risk in acute alcohol-associated hepatitis

BACKGROUND

Acute alcohol-associated hepatitis (AH) is associated with high mortality. CT-derived liver surface nodularity (LSN) is a robust prognostic biomarker in other chronic liver diseases. The aim of this study was to determine relationships between LSN, disease severity, and mortality in AH.

METHODS

Adults hospitalized with AH from January 2016 to March 2020 were included if an abdominal CT was performed between 8 weeks prior to 72 h after hospitalization. LSN was measured using quantitative methods (Liver Surface Nodularity Software version 0.88, Birmingham, AL, USA). Cox proportional hazards models, logistic regression and AUROC analysis were used to examine relationships between LSN and 180-day transplant-free survival.

RESULTS

Of 386 patients hospitalized with AH during the study period, 230 had CT scans performed, and 205 met inclusion criteria. Mean transplant-free survival was 127 days (95% CI 118-137). Within each cohort, patients were grouped into low [LSN-LOW, N = 109 (53.2%)] and high [LSN-HIGH, N = 96 (46.8%)] LSN strata based on an optimal cutoff of 2.86 derived from unadjusted ROC curves. Patients with high LSN had features of portal hypertension, which included encephalopathy [53 (55.2%) vs. 43 (39.4%), p = 0.017], ascites on CT [81 (84.4%) vs. 69 (63.3%), p = 0.001] and portosystemic shunts [78 (81.2%) vs. 69 (63.3%), p = 0.003]. High LSN, ascites and MELD were independently associated with lower likelihood of 180-day transplant-free survival, and inclusion of a score assigning 1 point each for high LSN or ascites on CT (AHRADS score) to MELD enhanced diagnostic accuracy of AUROC for 180-day survival compared to MELD alone [AUROC 0.782 (95% CI 0.719-0.845) vs. 0.735 (0.667-0.802), p = 0.023].

CONCLUSIONS

CT-derived factors that include LSN and ascites are radiographic biomarkers associated with 180-day transplant-free survival in alcohol-associated hepatitis.

Portal hypertension and variceal bleeding in patients with liver cancer: Evidence gaps for prevention and management

BACKGROUND AND AIMS

Portal hypertension (PHT) and HCC are 2 major complications of cirrhosis that often coexist in the same patient and impact the prognosis, especially in patients with acute variceal bleeding. In this review, we aim to discuss the best strategy for PHT screening and primary prophylaxis, as well as the management of acute variceal bleeding, to improve the management of PHT in HCC patients.

RESULTS

Recent therapeutic advances observed in the management of HCC, notably through the advent of immunotherapy, have led to a clear improvement in the survival of patients. The prevention of complications related to underlying cirrhosis, such as PHT and acute variceal bleeding, is now part of the management of HCC patients. The Baveno VII conference recently redefined screening and prophylaxis in patients with cirrhosis. However, data regarding the applicability of these criteria in patients with HCC have been sparse. From our point of view, the Baveno criteria are not appropriate to exclude high-risk esophageal varices (EV) in HCC patients, and endoscopy should be performed except in HCC patients with a liver stiffness measurement (LSM) ≥25 kPa, who should benefit from nonselective beta-blockers (NSSBs) without performing endoscopy. We are also in favor of using NSBBs as primary prophylaxis in patients with EV regardless of the size and with gastric varices since these patients display clinically significant PHT.

CONCLUSIONS

Appropriate evaluation and treatment of PHT remain major issues in improving the outcomes of HCC patients. Many questions remain unanswered, opening the field to many areas of research.

Methods for assessing portal hypertension

Many researchers and clinicians have taken the value of hepatic venous pressure gradient (HVPG) as an essential prognostic factor in subjects with chronic liver diseases. HVPG ≥ 10 mmHg indicates the presence of clinically significant portal hypertension, the main predictor of the risk of variceal bleeding, hepatic decompensation, and mortality. However, HVPG measurement is invasive and requires high expertise, so its routine use outside tertiary care centers or clinical trials is limited. Clinically significant portal hypertension also might be detected using non-invasive options such as ultrasonography, elastography, magnetic resonance imaging, and indices derived from laboratory parameters. Our review aims to present the feasibility and applicability of HVPG in modern clinical practice in patients with liver cirrhosis, including invasive and non-invasive methods, based on literary sources from the MEDLINE database.

Current status of preoperative risk assessment for posthepatectomy liver failure in patients with hepatocellular carcinoma

Liver resection is an effective therapeutic option for patients with hepatocellular carcinoma. However, posthepatectomy liver failure (PHLF) remains a major cause of hepatectomy-related mortality, and the accurate prediction of PHLF based on preoperative assessment of liver functional reserve is a critical issue. The definition of PHLF proposed by the International Study Group for Liver Surgery has gained acceptance as a standard grading criterion. Liver function can be estimated using a variety of parameters, including routine blood biochemical examinations, clinical scoring systems, dynamic liver function tests, liver stiffness and fibrosis markers, and imaging studies. The Child-Pugh score and model for end-stage liver disease scores are conventionally used for estimating liver decompensation, although the alternatively developed albumin-bilirubin score shows superior performance for predicting hepatic dysfunction. Indocyanine green clearance, a dynamic liver function test mostly used in Japan and other Asian countries, serves as a quantitative estimation of liver function reserve and helps determine indications for surgical procedures according to the estimated risk of PHLF. In an attempt to improve predictive accuracy, specific evaluation of liver fibrosis and portal hypertension has gained popularity, including liver stiffness measurements using ultrasonography or magnetic resonance elastography, as well as noninvasive fibrosis markers. Imaging modalities, including Tc-99m-labeled galactosyl serum albumin scintigraphy and gadolinium-enhanced magnetic resonance imaging, are used for preoperative evaluation in combination with liver volume. This review aims to provide an overview of the usefulness of current options for the preoperative assessment of liver function in predicting PHLF.

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.

Quantitative computed tomography‐based approaches for noninvasive diagnosis of portal hypertension in patients with cirrhosis

Noninvasive diagnosis of portal hypertension in patients with cirrhosis can be achieved using different methods, including laboratory tests and imaging. The Baveno VII consensus suggested that liver stiffness measurements and platelet counts were sufficient for assessing the presence of clinically significant portal hypertension. However, computed tomography (CT) is frequently performed in patients with cirrhosis, and numerous studies have established the possibility of an opportunistic noninvasive diagnosis of portal hypertension using CT. These studies have utilized radiomics, volumetric changes in the liver and spleen, quantitative assessment of liver surface nodularity, and more advanced techniques based on computational fluid dynamics. This review summarizes the main original studies related to the quantitative CT‐based noninvasive diagnosis of portal hypertension.

Detecting liver cirrhosis in computed tomography scans using clinically-inspired and radiomic features

Hepatic cirrhosis is an increasing cause of mortality in developed countries-it is the pathological sequela of chronic liver diseases, and the final liver fibrosis stage. Since cirrhosis evolves from the asymptomatic phase, it is of paramount importance to detect it as quickly as possible, because entering the symptomatic phase commonly leads to hospitalization and can be fatal. Understanding the state of the liver based on the abdominal computed tomography (CT) scans is tedious, user-dependent and lacks reproducibility. We tackle these issues and propose an end-to-end and reproducible approach for detecting cirrhosis from CT. It benefits from the introduced clinically-inspired features that reflect the patient's characteristics which are often investigated by experienced radiologists during the screening process. Such features are coupled with the radiomic ones extracted from the liver, and from the suggested region of interest which captures the liver's boundary. The rigorous experiments, performed over two heterogeneous clinical datasets (two cohorts of 241 and 32 patients) revealed that extracting radiomic features from the liver's rectified contour is pivotal to enhance the classification abilities of the supervised learners. Also, capturing clinically-inspired image features significantly improved the performance of such models, and the proposed features were consistently selected as the important ones. Finally, we showed that selecting the most discriminative features leads to the Pareto-optimal models with enhanced feature-level interpretability, as the number of features was dramatically reduced (280×) from thousands to tens.

Towards optimal deep fusion of imaging and clinical data via a model-based description of fusion quality

BACKGROUND

Due to intrinsic differences in data formatting, data structure, and underlying semantic information, the integration of imaging data with clinical data can be non-trivial. Optimal integration requires robust data fusion, that is, the process of integrating multiple data sources to produce more useful information than captured by individual data sources. Here, we introduce the concept of fusion quality for deep learning problems involving imaging and clinical data. We first provide a general theoretical framework and numerical validation of our technique. To demonstrate real-world applicability, we then apply our technique to optimize the fusion of CT imaging and hepatic blood markers to estimate portal venous hypertension, which is linked to prognosis in patients with cirrhosis of the liver.

PURPOSE

To develop a measurement method of optimal data fusion quality deep learning problems utilizing both imaging data and clinical data.

METHODS

Our approach is based on modeling the fully connected layer (FCL) of a convolutional neural network (CNN) as a potential function, whose distribution takes the form of the classical Gibbs measure. The features of the FCL are then modeled as random variables governed by state functions, which are interpreted as the different data sources to be fused. The probability density of each source, relative to the probability density of the FCL, represents a quantitative measure of source-bias. To minimize this source-bias and optimize CNN performance, we implement a vector-growing encoding scheme called positional encoding, where low-dimensional clinical data are transcribed into a rich feature space that complements high-dimensional imaging features. We first provide a numerical validation of our approach based on simulated Gaussian processes. We then applied our approach to patient data, where we optimized the fusion of CT images with blood markers to predict portal venous hypertension in patients with cirrhosis of the liver. This patient study was based on a modified ResNet-152 model that incorporates both images and blood markers as input. These two data sources were processed in parallel, fused into a single FCL, and optimized based on our fusion quality framework.

RESULTS

Numerical validation of our approach confirmed that the probability density function of a fused feature space converges to a source-specific probability density function when source data are improperly fused. Our numerical results demonstrate that this phenomenon can be quantified as a measure of fusion quality. On patient data, the fused model consisting of both imaging data and positionally encoded blood markers at the theoretically optimal fusion quality metric achieved an AUC of 0.74 and an accuracy of 0.71. This model was statistically better than the imaging-only model (AUC = 0.60; accuracy = 0.62), the blood marker-only model (AUC = 0.58; accuracy = 0.60), and a variety of purposely sub-optimized fusion models (AUC = 0.61-0.70; accuracy = 0.58-0.69).

CONCLUSIONS

We introduced the concept of data fusion quality for multi-source deep learning problems involving both imaging and clinical data. We provided a theoretical framework, numerical validation, and real-world application in abdominal radiology. Our data suggests that CT imaging and hepatic blood markers provide complementary diagnostic information when appropriately fused.

Bibliometric-analysis visualization and review of non-invasive methods for monitoring and managing the portal hypertension

Background

Portal hypertension monitoring is important throughout the natural course of cirrhosis. Hepatic venous pressure gradient (HVPG), regarded as the golden standard, is limited by invasiveness and technical difficulties. Portal hypertension is increasingly being assessed non-invasively, and hematological indices, imaging data, and statistical or computational models are studied to surrogate HVPG. This paper discusses the existing non-invasive methods based on measurement principles and reviews the methodological developments in the last 20 years.

Methods

First, we used VOSviewer to learn the architecture of this field. The publications about the non-invasive assessment of portal hypertension were retrieved from the Web of Science Core Collection (WoSCC). VOSviewer 1.6.17.0 was used to analyze and visualize these publications, including the annual trend, the study hotspots, the significant articles, authors, journals, and organizations in this field. Next, according to the cluster analysis result of the keywords, we further retrieved and classified the related studies to discuss.

Results

A total of 1,088 articles or review articles about our topic were retrieved from WoSCC. From 2000 to 2022, the number of publications is generally growing. “World Journal of Gastroenterology” published the most articles (n = 43), while “Journal of Hepatology” had the highest citations. “Liver fibrosis” published in 2005 was the most influential manuscript. Among the 20,558 cited references of 1,088 retrieved manuscripts, the most cited was a study on liver stiffness measurement from 2007. The highest-yielding country was the United States, followed by China and Italy. “Berzigotti, Annalisa” was the most prolific author and had the most cooperation partners. Four study directions emerged from the keyword clustering: (1) the evaluation based on fibrosis; (2) the evaluation based on hemodynamic factors; (3) the evaluation through elastography; and (4) the evaluation of variceal bleeding.

Conclusion

The non-invasive assessment of portal hypertension is mainly based on two principles: fibrosis and hemodynamics. Liver fibrosis is the major initiator of cirrhotic PH, while hemodynamic factors reflect secondary alteration of splanchnic blood flow. Blood tests, US (including DUS and CEUS), CT, and magnetic resonance imaging (MRI) support the non-invasive assessment of PH by providing both hemodynamic and fibrotic information. Elastography, mainly USE, is the most important method of PH monitoring.

Contrast-enhanced CT and liver surface nodularity for the diagnosis of porto-sinusoidal vascular disorder: A case-control study

BACKGROUND AND AIMS

Porto-sinusoidal vascular disorder (PSVD) is a rare and commonly overlooked cause of portal hypertension. The interest of CT analysis, including quantification of liver surface nodularity (LSN) for PSVD diagnosis has not been established. This study aimed at assessing the performance of LSN and CT features for a PSVD diagnosis in patients with signs of portal hypertension.

APPROACH AND RESULTS

This retrospective case-control study included a learning cohort consisting of 50 patients with histologically proven PSVD, according to VALDIG criteria, and 100 control patients with histologically proven cirrhosis, matched on ascites. All patients and controls had at least one sign of portal hypertension and CT available within 1 year of liver biopsy. Principal component analysis of CT features separated patients with PSVD from patients with cirrhosis. Patients with PSVD had lower median LSN than those with cirrhosis (2.4 vs. 3.1, p < 0.001). Multivariate analysis identified LSN < 2.5 and normal-sized or enlarged segment IV as independently associated with PSVD. Combination of these two features had a specificity of 90% for PSVD and a diagnostic accuracy of 84%. Even better results were obtained in an independent multicenter validation cohort including 53 patients with PSVD and 106 control patients with cirrhosis (specificity 94%, diagnostic accuracy 87%).

CONCLUSIONS

This study that included a total of 103 patients with PSVD and 206 patients with cirrhosis demonstrates that LSN < 2.5 combined with normal-sized or enlarged segment IV strongly suggests PSVD in patients with signs of portal hypertension.

Management of Portal Hypertension

Portal hypertension is the cause of the clinical complications associated with cirrhosis. The primary complications of portal hypertension are ascites, acute variceal bleed, and hepatic encephalopathy. Hepatic venous pressure gradient measurement remains the gold standard test for diagnosing cirrhosis-related portal hypertension. Hepatic venous pressure gradient more than 10 mmHg is associated with an increased risk of complications and is termed clinically significant portal hypertension (CSPH). Clinical, laboratory, and imaging methods can also aid in diagnosing CSPH non-invasively. Recently, deep learning methods have been demonstrated to diagnose CSPH effectively. The management of portal hypertension is always individualized and is dependent on the etiology, the availability of therapies, and the degree of portal hypertension complications. In this review, we discuss the diagnosis and management of cirrhosis-related portal hypertension in detail. Also, we highlight the history of portal hypertension and future research areas in portal hypertension.

Network Meta-Analysis: Noninvasive Imaging Modalities for Identifying Clinically Significant Portal Hypertension

BACKGROUND

Although measurement of the hepatic venous pressure gradient (HVPG) is the current reference standard for obtaining portal venous pressures, several noninvasive imaging-based modalities have been proposed as alternatives.

AIMS

We performed a systematic review and meta-analysis to compare the diagnostic accuracy of noninvasive imaging approaches for identifying clinically significant portal hypertension (CSPH).

METHODS

Two independent reviewers conducted a literature search of PubMed, SCOPUS, and the Cochrane Library from inception until January 5, 2021. The following imaging modalities were compared to HVPG: computed tomography (CT), magnetic resonance imaging (MRI), magnetic resonance elastography, ultrasound, transient elastography (TE), shear wave elastography (SWE), acoustic radiation force impulse (ARFI) imaging, contrast-enhanced ultrasound (CEUS), and subharmonic-aided pressure estimation (SHAPE). Sensitivity, specificity, diagnostic odds ratio (DOR), and area under the curve (AUC) for summary receiver operating characteristic were calculated using both frequentist random effects and Bayesian network meta-analytic approaches.

RESULTS

We analyzed 45 studies of 5678 patients. A broad overlapping confidence interval (CI) of DOR was observed among different imaging modalities: ARFI (30.5; 95% CI 12.7-73.3), CEUS and SHAPE (21.1; 95% CI 6.4-69.8), TE of liver stiffness (21.1; 95% CI 13.3-33.5), CT and MRI (13.7; 95% CI 7.40-25.4), SWE of liver stiffness (10.5; 95% CI 5.2-21.1), and ultrasound (9.5; 95% CI 4.9-18.4). The AUC of all imaging methods exceeded 0.8, indicating very good performance. At a cutoff of 80% specificity, TE, CEUS, and SHAPE exceeded 80% sensitivity.

CONCLUSION

Overall, noninvasive imaging modalities perform well for identifying CSPH. Clinicians should consider these noninvasive and cost-efficient tests when diagnosing CSPH.

Conventional and artificial intelligence-based imaging for biomarker discovery in chronic liver disease

Chronic liver diseases, resulting from chronic injuries of various causes, lead to cirrhosis with life-threatening complications including liver failure, portal hypertension, hepatocellular carcinoma. A key unmet medical need is robust non-invasive biomarkers to predict patient outcome, stratify patients for risk of disease progression and monitor response to emerging therapies. Quantitative imaging biomarkers have already been developed, for instance, liver elastography for staging fibrosis or proton density fat fraction on magnetic resonance imaging for liver steatosis. Yet, major improvements, in the field of image acquisition and analysis, are still required to be able to accurately characterize the liver parenchyma, monitor its changes and predict any pejorative evolution across disease progression. Artificial intelligence has the potential to augment the exploitation of massive multi-parametric data to extract valuable information and achieve precision medicine. Machine learning algorithms have been developed to assess non-invasively certain histological characteristics of chronic liver diseases, including fibrosis and steatosis. Although still at an early stage of development, artificial intelligence-based imaging biomarkers provide novel opportunities to predict the risk of progression from early-stage chronic liver diseases toward cirrhosis-related complications, with the ultimate perspective of precision medicine. This review provides an overview of emerging quantitative imaging techniques and the application of artificial intelligence for biomarker discovery in chronic liver disease.

The Value of Liver and Spleen Stiffness for Evaluation of Portal Hypertension in Compensated Cirrhosis

Patients with compensated advanced chronic liver disease who develop clinically significant portal hypertension (CSPH) are at high risk for hepatic decompensation and mortality if left untreated. Liver biopsy and hepatic venous pressure gradient (HVPG) measurements are the current gold standard procedures for determining fibrosis severity and diagnosing CSPH, respectively; however, both are invasive, limiting their use in clinical practice and larger trials of novel agents. As such, there is an unmet clinical need for reliable, validated, noninvasive measures to detect CSPH and to further assess portal hypertension (PH) severity. Alterations in the biomechanical properties of the liver or spleen in patients with cirrhosis can be quantified by tissue elastography, which examines the elastic behavior of tissue after a force has been applied. A variety of methods are available, including magnetic resonance elastography, shear-wave elastography, and the most thoroughly investigated measure, vibration-controlled transient elastography. Liver stiffness (LS) and spleen stiffness (SS) measurements offer valuable alternatives to detect and monitor CSPH. Both LS and SS correlate well with HVPG, with thresholds of LS >20-25 kPa and SS >40-45 kPa indicating a high likelihood of CSPH. Because SS is a direct and dynamic surrogate of portal pressure, it has the potential to monitor PH severity and assess PH improvement as a surrogate marker for clinical outcomes. Importantly, SS seems to be superior to LS for monitoring treatment response in clinical trials focusing on reducing PH.

Multiinstitutional Evaluation of the Liver Surface Nodularity Score on CT for Staging Liver Fibrosis and Predicting Liver-Related Events in Patients With Hepatitis C

BACKGROUND. In single-institution multireader studies, the liver surface nodularity (LSN) score accurately detects advanced liver fibrosis and cirrhosis and predicts liver decompensation in patients with chronic liver disease (CLD) from hepatitis C virus (HCV). OBJECTIVE. The purpose of this study was to assess the diagnostic performance of the LSN score alone and in combination with the (FIB-4; fibrosis index based on four factors) to detect advanced fibrosis and cirrhosis and to predict future liver-related events in a multiinstitutional cohort of patients with CLD from HCV. METHODS. This retrospective study included 40 consecutive patients, from each of five academic medical centers, with CLD from HCV who underwent nontargeted liver biopsy within 6 months before or after abdominal CT. Clinical data were recorded in a secure web-based database. A single central reader measured LSN scores using software. Diagnostic performance for detecting liver fibrosis stage was determined. Multivariable models were constructed to predict baseline liver decompensation and future liver-related events. RESULTS. After exclusions, the study included 191 patients (67 women, 124 men; mean age, 54 years) with fibrosis stages of F0-F1 (n = 37), F2 (n = 44), F3 (n = 46), and F4 (n = 64). Mean LSN score increased with higher stages (F0-F1, 2.26 ± 0.44; F2, 2.35 ± 0.37; F3, 2.42 ± 0.38; F4, 3.19 ± 0.89; p < .001). The AUC of LSN score alone was 0.87 for detecting advanced fibrosis (≥ F3) and 0.89 for detecting cirrhosis (F4), increasing to 0.92 and 0.94, respectively, when combined with FIB-4 scores (both p = .005). Combined scores at optimal cutoff points yielded sensitivity of 75% and specificity of 82% for advanced fibrosis, and sensitivity of 84% and specificity of 85% for cirrhosis. In multivariable models, LSN score was the strongest predictor of baseline liver decompensation (odds ratio, 14.28 per 1-unit increase; p < .001) and future liver-related events (hazard ratio, 2.87 per 1-unit increase; p = .03). CONCLUSION. In a multiinstitutional cohort of patients with CLD from HCV, LSN score alone and in combination with FIB-4 score exhibited strong diagnostic performance in detecting advanced fibrosis and cirrhosis. LSN score also predicted future liver-related events. CLINICAL IMPACT. The LSN score warrants a role in clinical practice as a quantitative marker for detecting advanced liver fibrosis, compensated cirrhosis, and decompensated cirrhosis and for predicting future liver-related events in patients with CLD from HCV.

Performance of non-invasive biomarkers compared with invasive methods for risk prediction of posthepatectomy liver failure in hepatocellular carcinoma

BACKGROUND

Posthepatectomy liver failure (PHLF) is a rare but dreaded complication. The aim was to test whether a combination of non-invasive biomarkers (NIBs) and CT data could predict the risk of PHLF in patients who underwent resection of hepatocellular carcinoma (HCC).

METHODS

Patients with HCC who had liver resection between 2012 and 2020 were included. A relevant combination of NIBs (NIB model) to model PHLF risk was identified using a doubly robust estimator (inverse probability weighting combined with logistic regression). The adjustment variables were body surface area, ASA fitness grade, male sex, future liver remnant (FLR) ratio, difficulty of liver resection, and blood loss. The reference invasive biomarker (IB) model comprised a combination of pathological analysis of the underlying liver and hepatic venous pressure gradient (HVPG) measurement. Various NIB and IB models for prediction of PHLF were fitted and compared. NIB model performances were validated externally. Areas under the curve (AUCs) were corrected using bootstrapping.

RESULTS

Overall 323 patients were included. The doubly robust estimator showed that hepatitis C infection (odds ratio (OR) 4.33, 95 per cent c.i. 1.29 to 9.20; P = 0.001), MELD score (OR 1.26, 1.04 to 1.66; P = 0.001), fibrosis-4 score (OR 1.36, 1.06 to 1.85; P = 0.001), liver surface nodularity score (OR 1.55, 1.28 to 4.29; P = 0.031), and FLR volume ratio (OR 0.99, 0.97 to 1.00; P = 0.014) were associated with PHLF. Their combination (NIB model) was fitted externally (2-centre cohort, 165 patients) to model PHLF risk (AUC 0.867). Among 129 of 323 patients who underwent preoperative HVPG measurement, NIB and IB models had similar performances (AUC 0.753 versus 0.732; P = 0.940). A well calibrated nomogram was drawn based on the NIB model (AUC 0.740). The risk of grade B/C PHLF could be ruled out in patients with a cumulative score of less than 160 points.

CONCLUSION

The NIB model provides reliable preoperative evaluation with performance at least similar to that of invasive methods for PHLF risk prediction.

Liver surface nodularity on non-contrast MRI identifies advanced fibrosis in patients with NAFLD

OBJECTIVES

To evaluate the diagnostic performance of liver surface nodularity (LSN) for the assessment of advanced fibrosis in patients with non-alcoholic fatty liver disease (NAFLD).

METHODS

We retrospectively analysed patients with pathologically proven NAFLD who underwent liver MRI. Demographic, clinical, and laboratory data (including FIB-4 scores) were gathered. The SAF score was used to assess NAFLD. MRI-proton density fat fraction (PDFF) and LSN were determined on pre-contrast MR sequences. ROC curve analysis was performed to evaluate the diagnostic performance of MRI-LSN for the diagnosis of advanced (F3-F4) liver fibrosis.

RESULTS

The final population included 142 patients. Sixty-seven (47%) patients had non-alcoholic steatohepatitis (NASH), and 52 (37%) had advanced fibrosis. The median MRI-PDFF increased with the grades of steatosis: 8.1%, 18.1%, and 31% in S1, S2, and S3 patients, respectively (p < 0.001). The area under the ROC curve (AUC) of MRI-LSN ≥ 2.50 was 0.838 (95%CI 0.767-0.894, sensitivity 67.3%, specificity 88.9%, positive and negative predictive values 77.8% and 82.5%, respectively) for the diagnosis of advanced fibrosis. Combining FIB-4 and MRI-LSN correctly classified 103/142 (73%) patients. This was validated in an external cohort of 75 patients.

CONCLUSIONS

MRI-LSN has good diagnostic performance in diagnosis of advanced fibrosis in NAFLD patients. A combination of FIB-4 and MRI-LSN derived from pre-contrast MRI could be helpful to detect advanced fibrosis.

KEY POINTS

• MRI-LSN ≥ 2.5 was accurate for the diagnosis of advanced hepatic fibrosis in NAFLD patients. • The combination of FIB-4 and MRI-LSN improved the detection of advanced fibrosis. • MRI-LSN can be easily derived by unenhanced MRI sequences that are routinely acquired.

Noncontrast-enhanced MRI-based Noninvasive Score for Portal Hypertension (CHESS1802): An International Multicenter Study

BACKGROUND AND AIMS

This study aimed to determine the performance of the non-invasive score using noncontrast-enhanced MRI (CHESS-DIS score) for detecting portal hypertension in cirrhosis.

METHODS

In this international multicenter, diagnostic study (ClinicalTrials.gov, NCT03766880), patients with cirrhosis who had hepatic venous pressure gradient (HVPG) measurement and noncontrast-enhanced MRI were prospectively recruited from four university hospitals in China (n=4) and Turkey (n=1) between December 2018 and April 2019. A cohort of patients was retrospectively recruited from a university hospital in Italy between March 2015 and November 2017. After segmentation of the liver on fat-suppressed T1-weighted MRI maps, CHESS-DIS score was calculated automatically by an in-house developed code based on the quantification of liver surface nodularity.

RESULTS

A total of 149 patients were included, of which 124 were from four Chinese hospitals (training cohort) and 25 were from two international hospitals (validation cohort). A positive correlation between CHESS-DIS score and HVPG was found with the correlation coefficients of 0.36 (p<0.0001) and 0.55 (p<0.01) for the training and validation cohorts, respectively. The area under the receiver operating characteristic curve of CHESS-DIS score in detection of clinically significant portal hypertension (CSPH) was 0.81 and 0.9 in the training and validation cohorts, respectively. The intraclass correlation coefficients for assessing the inter- and intra-observer agreement were 0.846 and 0.841, respectively.

CONCLUSIONS

A non-invasive score using noncontrast-enhanced MRI was developed and proved to be significantly correlated with invasive HVPG. Besides, this score could be used to detect CSPH in patients with cirrhosis.

Noninvasive assessment of clinically significant portal hypertension using ΔT1 of the liver and spleen and ECV of the spleen on routine Gd-EOB-DTPA liver MRI

PURPOSE

To analyze the predictive value of ΔT1 of the liver and spleen as well as the extracellular volume fraction (ECV) of the spleen as noninvasive biomarkers for the determination of clinically significant portal hypertension (CSPH) on routine Gd-EOB-DTPA liver MRI.

METHOD

195 consecutive patients with known or suspected chronic liver disease from 9/2018 to 7/2019 with Gd-EOB-DTPA liver MRI and abdominal T1 mapping were retrospectively included. Based on the presence of splenomegaly with thrombocytopenia, ascites and portosystemic collaterals, the patients were divided into noCSPH (n = 113), compensated CSPH (cCSPH, ≥1 finding without ascites; n = 55) and decompensated CSPH (dCSPH, ascites ± other findings; n = 27). T1 times were measured in the liver, spleen and abdominal aorta in the unenhanced and contrast-enhanced T1 maps. Native T1 times and ΔT1 of the liver and spleen as well as ECV of the spleen were compared between groups using the Kruskal-Wallis test with Dunn's post hoc test. Furthermore, cutoff values for group differentiation were calculated using ROC analysis with Youden's index.

RESULTS

ΔT1 of the liver was significantly lower in patients with cCSPH and dCSPH (p < 0.001) compared to patients with noCSPH. In the ROC analyses for differentiation between noCSPH and CSPH (cCSPH + dCSPH), a cutoff of < 0.67 for ΔT1 of the liver (AUC = 0.79) performed better than ΔT1 (AUC = 0.69) and ECV (AUC = 0.63) of the spleen with cutoffs of > 0.29 and > 41.9, respectively.

CONCLUSION

ΔT1 of the liver and spleen in addition to ECV of the spleen allow for determination of CSPH on routine Gd-EOB-DTPA liver MRI.

EASL Clinical Practice Guidelines on non-invasive tests for evaluation of liver disease severity and prognosis - 2021 update

Non-invasive tests are increasingly being used to improve the diagnosis and prognostication of chronic liver diseases across aetiologies. Herein, we provide the latest update to the EASL Clinical Practice Guidelines on the use of non-invasive tests for the evaluation of liver disease severity and prognosis, focusing on the topics for which relevant evidence has been published in the last 5 years.

Combining hepatic surface nodularity and serum tests better predicts hepatic fibrosis stages in chronic liver disease

PURPOSE

Hepatic surface nodularity quantified on CT images has shown promising results in staging hepatic fibrosis in chronic hepatitis C. The aim of this study was to evaluate hepatic surface nodularity, serum fibrosis indices, and a linear combination of them for staging fibrosis in chronic liver disease, mainly chronic hepatitis B.

METHODS

We developed a semiautomated software quantifying hepatic surface nodularity on CT images. Hepatic surface nodularity and serum fibrosis indices were assessed in the development group of 125 patients to generate 3 linear models combining hepatic surface nodularity with the aspartate aminotransferase to platelet ratio index, fibrosis-4 index, or platelet count in reference to the METAVIR scoring system. The models were validated in 183 patients.

RESULTS

Hepatic surface nodularity and serum fibrosis indices all significantly correlated with fibrosis stages. For binary classifications into cirrhosis (F4), advanced fibrosis (≥ F3), and significant fibrosis (≥ F2), hepatic surface nodularity was significantly different across categories. The areas under the curve (AUCs) of the best model were 0.901, 0.872, and 0.794 for cirrhosis, advanced fibrosis, and significant fibrosis, respectively, higher than serum fibrosis indices alone (0.797-0.802, 0.799-0.818, and 0.761-0.773). In the validation group, the same model likewise showed higher AUCs (0.872, 0.831, and 0.850) compared to serum fibrosis indices (0.722-0.776, 0.692-0.768, and 0.695-0.769; p < 0.001 for F4).

CONCLUSION

Hepatic surface nodularity combined with serum blood test could be a practical method to predict cirrhosis, advanced fibrosis, and significant fibrosis in chronic liver disease patients, providing higher accuracy than using serum fibrosis indices alone.

Predicting the stages of liver fibrosis with multiphase CT radiomics based on volumetric features

PURPOSES

To develop and externally validate a multiphase computed tomography (CT)-based machine learning (ML) model for staging liver fibrosis (LF) by using whole liver slices.

MATERIALS AND METHODS

The development dataset comprised 232 patients with pathological analysis for LF, and the test dataset comprised 100 patients from an independent outside institution. Feature extraction was performed based on the precontrast (PCP), arterial (AP), portal vein (PVP) phase, and three-phase CT images. CatBoost was utilized for ML model investigation by using the features with good reproducibility. The diagnostic performance of ML models based on each single- and three-phase CT image was compared with that of radiologists' interpretations, the aminotransferase-to-platelet ratio index, and the fibrosis index based on four factors (FIB-4) by using the receiver operating characteristic curve with the area under the curve (AUC) value.

RESULTS

Although the ML model based on three-phase CT image (AUC = 0.65-0.80) achieved higher AUC value than that based on PCP (AUC = 0.56-0.69) and PVP (AUC = 0.51-0.74) in predicting various stage of LF, significant difference was not found. The best CT-based ML model (AUC = 0.65-0.80) outperformed the FIB-4 in differentiating advanced LF and cirrhosis and radiologists' interpretation (AUC = 0.50-0.76) in the diagnosis of significant and advanced LF.

CONCLUSION

All PCP, PVP, and three-phase CT-based ML models can be an acceptable in assessing LF, and the performance of the PCP-based ML model is comparable to that of the enhanced CT image-based ML model.

Noninvasive Detection of Clinically Significant Portal Hypertension in Compensated Advanced Chronic Liver Disease

Patients with compensated advanced chronic liver disease have different prognoses depending on the presence of portal hypertension. Current non-invasive diagnostic methods allow identification of clinically significant portal hypertension. Portosystemic collaterals on imaging or liver stiffness of more than 20 to 25 kPa by using transient elastography identifies patients with clinically significant portal hypertension. Patients with liver stiffness of less than 20 kPa and platelet count of greater than 150 g/L can avoid endoscopy. This rule could be expanded using spleen stiffness. Methods to risk stratify for portal hypertension in compensated advanced chronic liver disease and successfully treated chronic hepatitis C and B are subject of research.

Quantification of Pancreas Surface Lobularity on CT: A Feasibility Study in the Normal Pancreas

Objective

To assess the feasibility and reproducibility of pancreatic surface lobularity (PSL) quantification derived from abdominal computed tomography (CT) in a population of patients free from pancreatic disease.

Materials and Methods

This retrospective study included 265 patients free from pancreatic disease who underwent contrast-enhanced abdominal CT between 2017 and 2019. A maximum of 11 individual PSL measurements were performed by two abdominal radiologists (head [5 measurements], body, and tail [3 measurements each]) using dedicated software. The influence of age, body mass index (BMI), and sex on PSL was assessed using the Pearson correlation and repeated measurements. Inter-reader agreement was assessed using the intraclass correlation coefficient (ICC) and Bland Altman (BA) plots.

Results

CT images of 15 (6%) patients could not be analyzed. A total of 2750 measurements were performed in the remaining 250 patients (143 male [57%], mean age 45 years [range, 18–91]), and 2237 (81%) values were obtained in the head 951/1250 (76%), body 609/750 (81%), and tail 677/750 (90%). The mean ± standard deviation PSL was 6.53 ± 1.37. The mean PSL was significantly higher in male than in female (6.89 ± 1.30 vs. 6.06 ± 1.31, respectively, p < 0.001). PSL gradually increased with age (r = 0.32, p < 0.001) and BMI (r = 0.32, p < 0.001). Inter-reader agreement was excellent (ICC 0.82 [95% confidence interval 0.72–0.85], with a BA bias of 0.30 and 95% limits of agreement of −1.29 and 1.89).

Conclusion

CT-based PSL quantification is feasible with a high success rate and inter-reader agreement in subjects free from pancreatic disease. Significant variations were observed according to sex, age, and BMI. This study provides a reference for future studies.

Assessment of Liver Fibrosis Stage Using Integrative Analysis of Hepatic Heterogeneity and Nodularity in Routine MRI with FIB-4 Index as Reference Standard

Image-based quantitative methods for liver heterogeneity (L_Het) and nodularity (L_Nod) provide helpful information for evaluating liver fibrosis; however, their combinations are not fully understood in liver diseases. We developed an integrated software for assessing L_Het and L_Nod and compared L_Het and L_Nod according to fibrosis stages in chronic liver disease (CLD). Overall, 111 CLD patients and 16 subjects with suspected liver disease who underwent liver biopsy were enrolled. The procedures for quantifying L_Het and L_Nod were bias correction, contour detection, liver segmentation, and L_Het and L_Nod measurements. L_Het and L_Nod scores among fibrosis stages (F0–F3) were compared using ANOVA with Tukey’s test. Diagnostic accuracy was determined by calculating the area under the receiver operating characteristics (AUROC) curve. The mean L_Het scores of F0, F1, F2, and F3 were 3.49 ± 0.34, 5.52 ± 0.88, 6.80 ± 0.97, and 7.56 ± 1.79, respectively (p < 0.001). The mean L_Nod scores of F0, F1, F2, and F3 were 0.84 ± 0.06, 0.91 ± 0.04, 1.09 ± 0.08, and 1.15 ± 0.14, respectively (p < 0.001). The combined L_Het × L_Nod scores of F0, F1, F2, and F3 were 2.96 ± 0.46, 5.01 ± 0.91, 7.30 ± 0.89, and 8.48 ± 1.34, respectively (p < 0.001). The AUROCs of L_Het, L_Nod, and L_Het × L_Nod for differentiating F1 vs. F2 and F2 vs. F3 were 0.845, 0.958, and 0.954; and 0.619, 0.689, and 0.761, respectively. The combination of L_Het and L_Nod scores derived from routine MR images allows better differential diagnosis of fibrosis subgroups in CLD.

Liver surface nodularity: a novel predictor of post-hepatectomy liver failure in patients with colorectal liver metastases following chemotherapy

OBJECTIVES

The goal of this study was to assess the relationship between liver surface nodularity (LSN), chemotherapy-associated liver injury (CALI), and clinically relevant post-hepatectomy liver failure (CR-PHLF) (i.e., ≥ grade B) in patients undergoing hepatectomy for colorectal liver metastases (CLM).

METHODS

Preoperative CT scans of patients who underwent chemotherapy followed by hepatectomy for CLM between 2010 and 2017 were retrospectively analyzed. LSN was measured using semi-automated CT software CT images in patients who had available preoperative CT scans within 6 weeks before hepatectomy, and was computed based on the means of one to 10 measurements by two abdominal radiologists consensually. The association of LSN, CALI, and CR-PHLF was analyzed.

RESULTS

Two hundred fifty-six patients were analyzed (149 men and 107 women; overall median age, 61 [range, 29-88 years]). A total of 26 patients (10.2%) developed CR-PHLF. The optimal LSN cut-off value for detecting CR-PHLF was 2.5, as determined by receiver operative characteristic analysis (p < 0.001). LSN ≥ 2.5 was associated with prolonged chemotherapy (> 6 cycles, p = 0.018), but not with CALIs. After propensity score matching, LSN remained significantly associated with CR-PHLF (p = 0.031). Furthermore, multivariate analysis identified LSN ≥ 2.50 and future liver remnant (FLR) < 30% as significant preoperative predictors of CR-PHLF in 102 patients undergoing major hepatectomy. LSN ≥ 2.50 was more frequent in patients undergoing major hepatectomy despite FLR ≥ 30% (p = 0.008).

CONCLUSION

LSN quantified on CT is an independent surrogate of CR-PHLF in patients who undergo chemotherapy followed by hepatectomy for CLM and may provide a valuable additional tool in the preoperative assessment of these patients.

KEY POINTS

• LSN was not associated with chemotherapy- associated liver injury but high LSN (defined ≥ 2.5) was associated with prolonged chemotherapy (> 6 cycles). • High LSN was an independent predictor of clinically relevant postoperative liver failure in patients undergoing hepatectomy for CRLM. • LSN ≥ 2.50 was more frequent in patients with PHLF after major hepatectomy despite a future liver remnant ≥ 30%.

Computed Tomography-Derived Liver Surface Nodularity and Sarcopenia as Prognostic Factors in Patients with Resectable Metabolic Syndrome-Related Hepatocellular Carcinoma

OBJECTIVE

The aim of this study was to assess the prognostic value of liver surface nodularity (LSN) and sarcopenia from preoperative computed tomography (CT) in patients with resectable metabolic syndrome (MS)-related hepatocellular carcinoma (HCC).

METHODS

Patients with MS undergoing hepatectomy for HCC between 2006 and 2018 at a single center were retrospectively analyzed. LSN and sarcopenia were assessed on preoperative CT scans, and their association with severe (Clavien-Dindo grade 3-5) postoperative complications was analyzed on multivariate analysis. The influence of LSN and sarcopenia on overall survival (OS) and recurrence-free survival (RFS) was assessed.

RESULTS

Overall, 110 patients (92 men [84%], mean 67.7 ± 7.7 years of age) were analyzed. Severe postoperative complications occurred in 34/110 (31%) patients. Patients with severe complications had a significantly higher LSN score (area under the receiver operating characteristic curve 0.68 ± 0.05, optimal cut-off > 2.50) and were more frequently sarcopenic (47% vs. 13% without major complications, p < 0.001). Multivariate analysis identified sarcopenia (odds ratio [OR] 6.51, 95% confidence interval [CI] 2.08-20.39; p < 0.001), LSN > 2.50 (OR 7.05, 95% CI 2.13-23.35; p < 0.001), and preoperative portal vein embolization (PVE; OR 6.06, 95% CI 1.71-21.48; p = 0.005) as independent predictors of severe complications. LSN and sarcopenia had no influence on OS. Stratification according to a combination of LSN > 2.50 and sarcopenia predicted the risk of severe postoperative complications from 7% (no sarcopenia and LSN ≤2.50) to 71% (sarcopenia and LSN > 2.50; p < 0.001), as well as RFS from 61 months (95% CI 40-82) to 17 months (95% CI 9-25; p = 0.033). Results remained significant in 52 patients without advanced fibrosis.

CONCLUSIONS

The combination of LSN and sarcopenia derived from routine preoperative CT seems to help predict severe postoperative complications and stratification of RFS in patients with MS and resectable HCC.

Noninvasive imaging assessment of portal hypertension

Portal hypertension (PH) is a spectrum of complications of chronic liver disease (CLD) and cirrhosis, with manifestations including ascites, gastroesophageal varices, splenomegaly, hypersplenism, hepatic hydrothorax, hepatorenal syndrome, hepatopulmonary syndrome and portopulmonary hypertension. PH can vary in severity and is diagnosed via invasive hepatic venous pressure gradient measurement (HVPG), which is considered the reference standard. Accurate diagnosis of PH and assessment of severity are highly relevant as patients with clinically significant portal hypertension (CSPH) are at higher risk for developing acute variceal bleeding and mortality. In this review, we discuss current and upcoming noninvasive imaging methods for diagnosis and assessment of severity of PH.

Similar performance of liver stiffness measurement and liver surface nodularity for the detection of portal hypertension in patients with hepatocellular carcinoma

BACKGROUND & AIMS

We compare the performance of liver surface nodularity (LSN) and liver stiffness measurements (LSM) using transient elastography (TE) for the detection of clinically significant portal hypertension (CSPH) in patients with cirrhosis and hepatocellular carcinoma (HCC).

METHODS

All patients with cirrhosis and HCC who underwent computed tomography, LSM and hepatic venous pressure gradient (HVPG) measurements within 30 days between 2015 and 2018 were included. The estimation of CSPH by LSN and LSM, and the LSM-spleen-size-to-platelet ratio score (LSPS) were evaluated and compared.

RESULTS

In total, 140 patients were included (109 men [78%], mean age 63 ± 9 years old), including 39 (28%) with CSPH. LSN measurements were valid in 130 patients (93%) and significantly correlated with HVPG (r = 0.68; p <0.001). Patients with CSPH had higher LSN measurements compared with those without [3.1 ± 0.4 vs. 2.5 ± 0.3, p <0.001; area under the receiver operating characteristic (AUROC): 0.87 ± 0.31]. LSM and LSPS were valid in 132 patients (94%) and significantly correlated with HVPG (r = 0.75, p <0.001; AUROC 0.87 ± 0.04 and r = 0.68, p <0.001; AUROC 0.851 ± 0.04, respectively). There was no significant difference in the diagnostic performance between LSN and LSM-LSPS (DeLong, p = 0.28, 0.37, and 0.65, respectively) in patients with both valid tests (n = 122). LSN <2.50 had a 100% negative predictive value for CSPH. A 2-step algorithm combining LSN and LSPS for the diagnosis of CSPH classified 108/140 patients (77%) with an 8% error.

CONCLUSIONS

The diagnostic performance and feasibility of LSN measurements were similar to those of LSM for the detection of CSPH in patients with compensated cirrhosis and HCC. Combining LSN and LSPS accurately detected CSPH in >75% of patients. Such a combination could be useful in centres where the HVPG measurement is unavailable.

LAY SUMMARY

The diagnostic performance and feasibility of liver surface nodularity was similar to that of liver stiffness measurement (LSM) for the detection of clinically significant portal hypertension in patients with compensated cirrhosis. Thus, liver surface nodularity could be an option for the preoperative detection of clinically significant portal hypertension in patients with hepatocellular carcinoma. Combining liver surface nodularity with LSM-spleen-size-to-platelet ratio score resulted in the accurate detection of clinically significant portal hypertension in >75% of patients, thus limiting the need for HVPG measurements.

Staging of Liver Fibrosis by Means of Semiautomatic Measurement of Liver Surface Nodularity in MRI

OBJECTIVE. The purposes of this study were to evaluate the accuracy of a semiautomatic method of measuring liver surface nodularity (LSN) on contrast-enhanced MR images and to compare the LSN score with pathologic fibrosis stage. MATERIALS AND METHODS. This retrospective study included patients who had undergone gadoxetate disodium-enhanced liver MRI 6 months before or after histopathologic investigation including percutaneous parenchymal biopsy and surgical biopsy for staging of chronic liver disease between January 2010 and December 2018. Semiautomated LSN quantification software was developed to measure LSN at MRI. Aspartate aminotransferase to platelet ratio index and fibrosis-4 index were derived from serum laboratory test results. The reference standard for staging of liver fibrosis was Metavir score. The accuracy of LSN score for staging of liver fibrosis was evaluated with AUC, and the optimal cutoff value was calculated by Youden index. Spearman correlation coefficient was used for correlation analysis. RESULTS. The study included 132 patients (93 men, 39 women). LSN score was evaluated without technical failure. There was high correlation between LSN score and Metavir score (Spearman ρ = 0.713, p < 0.001). The AUCs of LSN score for distinguishing Metavir score were 0.93 for F0-F1 versus F2-F4 (95% CI, 0.88-0.97; p < 0.001), 0.98 for F0-F2 vs F3-F4 (95% CI, 0.95-1.00; p < 0.001), and 0.83 for F0-F3 versus F4 (95% CI, 0.76-0.90; p < 0.001). The optimal cutoff value for differentiating F0-F2 from F3-F4 was 0.850 with 100% sensitivity and 85.4% specificity. CONCLUSION. LSN score calculated semiautomatically from MR images of the liver has high accuracy and correlates directly with the pathologic fibrosis stage.

CT-based liver surface nodularity for the detection of clinically significant portal hypertension: defining measurement quality criteria

PURPOSE

To establish measurement quality criteria for the noninvasive assessment of clinically significant portal hypertension (CSPH) in patients with cirrhosis using CT-based liver surface nodularity (LSN) measurements.

METHODS

Seventy-four consecutive patients with cirrhosis (mean 62 ± 13 years), including 30 with CSPH (41%), underwent CT and hepatic venous pressure gradient measurements. Three independent readers performed 15 LSN measurements/patient using dedicated software. LSN was computed based on the median and means of one to 15 measurements. Accuracy for diagnosing CSPH was assessed using receiver operating characteristic (ROC) curve analysis. Variability was assessed by the intra-class correlation coefficient (ICC) and the Bland-Altman plot (BA). Quality criteria were identified to maximize the accuracy of LSN and minimize variability.

RESULTS

The area under the (AU) ROCs of mean and median LSN measurements based on one to 15 measurements ranged from 0.79 ± 0.05 to 0.91 ± 0.04 and 0.86 ± 0.04 to 0.91 ± 0.03, respectively, with no difference on pair-wise comparisons (all p > 0.05). AUROCs of LSN increased from one to eight and leveled off between eight and 15 measurements. Inter- and intra-reader variability decreased from one to 15 measurements, with only slight improvement after more than eight measurements. Intra- and inter-observer agreements were excellent with eight measurements (ICC = 0.90 [95%CI 0.84-0.94], and ICC = 0.93 [95%CI 0.89-0.95], respectively), and variability for intra-observer and inter-observer agreement was low (BA bias 4.2% (95% limits of agreement [LoA] [- 15.3; + 23.7%]) and 4.8% LoA [ - 17.5; + 27.1%], respectively).

CONCLUSIONS

CT-based LSN measurement is highly reproducible and accurate. We suggest using at least 8 valid measurements to determine the mean LSN value for the detection of CSPH.

New frontiers in liver resection for hepatocellular carcinoma

Liver resection is one of the main curative options for early hepatocellular carcinoma (HCC) in patients with cirrhosis and is the treatment of choice in non-cirrhotic patients. However, careful patient selection is required to balance the risk of postoperative liver failure and the potential benefit on long-term outcomes. In the last decades, improved surgical techniques and perioperative management, as well as better patient selection, have enabled the indications for liver resection to be expanded. In this review, we aim to describe the main indications for liver resection in the management of HCC, its role compared to percutaneous ablation and liver transplantation in the therapeutic algorithm, as well as the recent advances in liver surgery that could be used to improve the prognosis of patients with HCC.

Relevance of liver surface nodularity for preoperative risk assessment in patients with resectable hepatocellular carcinoma

BACKGROUND

Quantification of liver surface nodularity (LSN) on routine preoperative CT images allows detection of cirrhosis and clinically significant portal hypertension. This study aimed to assess the relevance of LSN in preoperative assessment of operative risks for patients with resectable hepatocellular carcinoma (HCC).

METHODS

All patients undergoing hepatectomy for HCC between 2012 and 2017 were analysed retrospectively. LSN was assessed at the liver-fat interface on the left liver lobe on preoperative CT images. The feasibility of LSN quantification was assessed. The association between LSN and outcomes (severe complications and posthepatectomy liver failure (PHLF)) was evaluated by multivariable analysis and after propensity score matching.

RESULTS

Among 210 patients, LSN measurement was successful in 187 (89·0 per cent). Among these, the median LSN score was 2·42 (i.q.r. 2·21-2·66) and 52·9 per cent had severe fibrosis, including 33·7 per cent with cirrhosis. LSN score increased with hepatic venous pressure gradient (P = 0·048), severity of steatosis (P = 0·011) and fibrosis grade (P = 0·001). LSN score was independently associated with severe complications (odds ratio (OR) 5·25; P = 0·006) and PHLF (OR 6·78; P = 0·003). After matching with respect to model for end-stage liver disease, aspartate aminotransferase-to-platelet ratio index and fibrosis-4 score, patients with a LSN score of 2·63 or higher retained an increased risk of PHLF (OR 5·81; P = 0·018). In the subgroup of patients without severe fibrosis, LSN was accurate in predicting severe complications (P = 0·005). Patients with (P = 0·039) or without (P = 0·018) severe fibrosis with increased LSN score had a higher comprehensive complication index score. Among patients with cirrhosis who had clinically significant portal hypertension, a LSN value below 2·63 ruled out the risk of PHLF.

CONCLUSION

LSN measurement represents a practical tool that may allow improvement in the preoperative evaluation and management of patients with HCC.

Performance of liver surface nodularity quantification for the diagnosis of portal hypertension in patients with cirrhosis: comparison between MRI with hepatobiliary phase sequences and CT

PURPOSE

To assess and compare the performance of liver surface nodularity (LSN) quantification using Gd-BOPTA-enhanced MRI and contrast-enhanced CT for the diagnosis of clinically significant portal hypertension (CSPH) in patients with cirrhosis.

METHODS

This retrospective study included 30 patients with compensated histologically proven cirrhosis who underwent hepatic venous pressure gradient (HVPG), abdominal CT and Gd-BOPTA-MRI within a 60-day interval during pre-surgery workup for hepatocellular carcinoma (HCC) between January 2016 and August 2018. LSN score was derived from CT portal venous phase (PVP), axial T2- and T1-weighted PVP and hepatobiliary phase (HBP). Accuracy for the detection of CSPH was evaluated for each set of images by ROC curve analysis. Intra-observer, inter-observer and inter-method reproducibilities were assessed by the intraclass correlation coefficient (ICC) and coefficient of variation (CV).

RESULTS

Thirty patients were analysed (23 men [77%], mean age 60 ± 11 years old), including 15 (50%) with CSPH. All CT- and MRI-derived LSN quantifications were correlated to HVPG (CT-PVP: r = 0.63, p = 0.001, AUROC = 0.908 ± 0.06; T1-w-PVP: r = 0.43, p = 0.028, AUROC = 0.876 ± 0.07; T1-w-HBP: r = 0.50, p = 0.012, AUROC = 0.823 ± 0.08; T2-w: r = 0.51, p = 0.007, AUROC = 0.801 ± 0.09). There was no significant difference in AUROC pairwise comparisons (p = 0.12-0.88). Patients with CSPH had higher LSN than those without (CT-PVP: 3.2 ± 0.6 vs 2.4 ± 0.5, p < 0.001; T1-w-PVP: 2.7 ± 0.4 vs 2.2 ± 0.4, p = 0.002; T1-w-HBP: 3.0 ± 0.6 vs 2.3 ± 0.3, p < 0.001; T2-w: 3.0 ± 0.6 vs 2.2 ± 0.3, p = 0.001) and 86%, 82%, 85% and 82% of patients were correctly classified, respectively. Reproducibility of inter-image set comparisons was excellent (ICC = 0.84-0.96 and CV = 8.3-14.2%).

CONCLUSION

The diagnostic performance of MRI-based LSN for detecting CSPH is strong and similar to that of CT-based LSN.

Establishment and assessment of the hepatic venous pressure gradient using biofluid mechanics (HVPGBFM): protocol for a prospective, randomised, non-controlled, multicentre study

INTRODUCTION

Portal hypertension (PH) is a severe disease with a poor outcome. Hepatic venous pressure gradient (HVPG), the current gold standard to detect PH, is available only in few hospitals due to its invasiveness and technical difficulty. This study aimed to establish and assess a novel model to calculate HVPG based on biofluid mechanics.

METHODS AND ANALYSIS

This is a prospective, randomised, non-controlled, multicentre trial. A total of 248 patients will be recruited in this study, and each patient will undergo CT, blood tests, Doppler ultrasound and HVPG measurement. The study consists of two independent and consecutive cohorts: original cohort (124 patients) and validation cohort (124 patients). The researchers will establish and improve the HVPG using biofluid mechanics (HVPG_BFM)model in the original cohort and assess the model in the validation cohort.

ETHICS AND DISSEMINATION

The study was approved by the Scientific Research Projects Approval Determination of Independent Ethics Committee of Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine (approval number 2017-430 T326). Study findings will be disseminated through peer-reviewed publications and conference presentations.

TRIAL REGISTRATION NUMBER

NCT03470389.

Diagnostic accuracy of non-invasive methods detecting clinically significant portal hypertension in liver cirrhosis: a systematic review and meta-analysis

INTRODUCTION

We attempted to investigate non-invasive techniques and their diagnostic performances for evaluating clinically significant portal hypertension.

EVIDENCE ACQUISITION

The systematic search was performed on PubMed, Embase, Scopus, and Web of Science TM core index databases before 13 December 2018 restricted to English language and human studies.

EVIDENCE SYNTHESIS

Thirty-two studies were included, with total populations of 3,987. The overall pooled analysis was performed by bivariate random effect model, which revealed significantly higher sensitivity and specificity of 77.1% (95% confidence interval, 76.8-78.5%) and 80.1% (95% confidence interval, 78.2-81.9%), respectively; positive likelihood ratio (3.67), negative likelihood ratio (0.26); and diagnostic odd ratio (16.24). Additionally, the area under curve exhibited significant diagnostic accuracy of 0.871. However, notable heterogeneity existed in between studies (I2=87.1%), therefore, further subgroup analysis was performed. It demonstrated ultrasonography, elastography, biomarker, and computed tomography scan had a significant overall summary sensitivity (specificity) of 89.6% (78.9%), 81.7% (83.2%), 72.2% (76.8%), and 77.2% (81.2%), respectively. Moreover, the areas under curve values were significantly higher in elastography (0.906), followed by computed tomography scan (0.847), biomarker (0.825), and ultrasonography (0.803).

CONCLUSIONS

In future, non-invasive techniques could be the future choice of investigations for screening and diagnosis of clinically significant portal hypertension in cirrhosis. However, standardization of diagnostic indices and their cut-off values in each non-invasive method needs to be addressed.

Portal pressure monitoring-state-of-the-art and future perspective

Portal hypertension is a serious symptom of chronic liver diseases, which can lead to many critical complications, such as the formation of varices related to upper digestive bleeding, ascites, infection, hepatic encephalopathy, renal failure, and even death. As a result, portal pressure monitoring has important prognostic and clinical implications. The hepatic venous pressure gradient measurement, a gold-standard method applied to monitor portal pressure, is invasive and only available in experienced centers. Over the past decade, noninvasive methods aimed at monitoring the portal pressure have been increasingly investigated, including serum markers, radiological features, ultrasound elastography, doppler and contrast-enhanced ultrasonography. In this study, we focused on both invasive and noninvasive methods for portal pressure monitoring and explored their roles in clinical setting. The advantages and limitations of various techniques for future research are also discussed.

Current Imaging Techniques for Noninvasive Staging of Hepatic Fibrosis

OBJECTIVE. The purpose of this article is to discuss quantitative methods of CT, MRI, and ultrasound (US) for noninvasive staging of hepatic fibrosis. Hepatic fibrosis is the hallmark of chronic liver disease (CLD), and staging by random liver biopsy is invasive and prone to sampling errors and subjectivity. Several noninvasive quantitative imaging methods are under development or in clinical use. The accuracy, precision, technical aspects, advantages, and disadvantages of each method are discussed. CONCLUSION. The most promising methods are the liver surface nodularity score using CT and measurement of liver stiffness using MR elastography or US elastography.