Liver volume in the cirrhotic patient: does size matter?

Impact of CT-determined low kidney volume on renal function decline: a propensity score-matched analysis

OBJECTIVES

To investigate the relationship between low kidney volume and subsequent estimated glomerular filtration rate (eGFR) decline in eGFR category G2 (60-89 mL/min/1.73 m2) population.

METHODS

In this retrospective study, we evaluated 5531 individuals with eGFR category G2 who underwent medical checkups at our institution between November 2006 and October 2017. Exclusion criteria were absent for follow-up visit, missing data, prior renal surgery, current renal disease under treatment, large renal masses, and horseshoe kidney. We developed a 3D U-net-based automated system for renal volumetry on CT images. Participants were grouped by sex-specific kidney volume deviations set at mean minus one standard deviation. After 1:1 propensity score matching, we obtained 397 pairs of individuals in the low kidney volume (LKV) and control groups. The primary endpoint was progression of eGFR categories within 5 years, assessed using Cox regression analysis.

RESULTS

This study included 3220 individuals (mean age, 60.0 ± 9.7 years; men, n = 2209). The kidney volume was 404.6 ± 67.1 and 376.8 ± 68.0 cm3 in men and women, respectively. The low kidney volume (LKV) cutoff was 337.5 and 308.8 cm3 for men and women, respectively. LKV was a significant risk factor for the endpoint with an adjusted hazard ratio of 1.64 (95% confidence interval: 1.09-2.45; p = 0.02).

CONCLUSION

Low kidney volume may adversely affect subsequent eGFR maintenance; hence, the use of imaging metrics may help predict eGFR decline.

CRITICAL RELEVANCE STATEMENT

Low kidney volume is a significant predictor of reduced kidney function over time; thus, kidney volume measurements could aid in early identification of individuals at risk for declining kidney health.

KEY POINTS

• This study explores how kidney volume affects subsequent kidney function maintenance. • Low kidney volume was associated with estimated glomerular filtration rate decreases. • Low kidney volume is a prognostic indicator of estimated glomerular filtration rate decline.

CBCT-based three-dimensional dual-phase vascular image fusion: a novel technique for interventional real-time TIPS guidance

BACKGROUND

Due to the invisibility of the portal vein (PV), how to puncture the PV accurately and safely in transjugular intrahepatic portosystemic shunt (TIPS) creation remains a challenge of the procedure.

OBJECTIVES

We aimed to provide the first evaluation of the safety, feasibility, and efficiency of cone beam computed tomography (CBCT)-based three-dimensional (3D) dual-phase vascular image fusion for interventional real-time guided PV puncture during TIPS procedures.

MATERIALS AND METHODS

From January 2021 to May 2021, 13 patients undergoing TIPS were prospectively enrolled in this study. Images of the hepatic artery (HA) and PV in 3D were acquired and overlaid on interventional fluoroscopy images in a dual-phase display mode for real-time PV puncture guidance. The number of PV puncture attempts, puncture time, overlaid image accuracy, dose area product, fluoroscopy time, and interventional complications were recorded.

RESULTS

Portal vein puncture guided by CBCT-based 3D dual-phase vascular image fusion was successfully performed on 92.3% (12/13) patients. The mean number of PV puncture attempts was 1.8 ± 0.7 (1-3). The mean puncture time and fluoroscopy time was 3.5 ± 1.2 (2-6) min and 25.1 ± 9.4 (15-45) min, respectively. The mean dose area product was 39.49 ± 7.88 (28.81-52.87) mGym2. The error between the reference position of the fusion image and the interventional PV angiography image was less than 0.5 cm. No interventional complication was observed.

CONCLUSION

Our results show that 3D dual-phase vascular image fusion might be a safe and feasible technique for interventional real-time guided PV puncture during TIPS. This novel technique might help to reduce the number of PV puncture attempts and the puncture time as well as lower the risks of interventional complications.

Comparative analysis of radiomics and deep-learning algorithms for survival prediction in hepatocellular carcinoma

To examine the comparative robustness of computed tomography (CT)-based conventional radiomics and deep-learning convolutional neural networks (CNN) to predict overall survival (OS) in HCC patients. Retrospectively, 114 HCC patients with pretherapeutic CT of the liver were randomized into a development (n = 85) and a validation (n = 29) cohort, including patients of all tumor stages and several applied therapies. In addition to clinical parameters, image annotations of the liver parenchyma and of tumor findings on CT were available. Cox-regression based on radiomics features and CNN models were established and combined with clinical parameters to predict OS. Model performance was assessed using the concordance index (C-index). Log-rank tests were used to test model-based patient stratification into high/low-risk groups. The clinical Cox-regression model achieved the best validation performance for OS (C-index [95% confidence interval (CI)] 0.74 [0.57-0.86]) with a significant difference between the risk groups (p = 0.03). In image analysis, the CNN models (lowest C-index [CI] 0.63 [0.39-0.83]; highest C-index [CI] 0.71 [0.49-0.88]) were superior to the corresponding radiomics models (lowest C-index [CI] 0.51 [0.30-0.73]; highest C-index [CI] 0.66 [0.48-0.79]). A significant risk stratification was not possible (p > 0.05). Under clinical conditions, CNN-algorithms demonstrate superior prognostic potential to predict OS in HCC patients compared to conventional radiomics approaches and could therefore provide important information in the clinical setting, especially when clinical data is limited.

Inducible overexpression of a FAM3C/ILEI transgene has pleiotropic effects with shortened life span, liver fibrosis and anemia in mice

FAM3C/ILEI is an important factor in epithelial-to-mesenchymal transition (EMT) induction, tumor progression and metastasis. Overexpressed in many cancers, elevated ILEI levels and secretion correlate with poor patient survival. Although ILEI's causative role in invasive tumor growth and metastasis has been demonstrated in several cellular tumor models, there are no available transgenic mice to study these effects in the context of a complex organism. Here, we describe the generation and initial characterization of a Tet-ON inducible Fam3c/ILEI transgenic mouse strain. We find that ubiquitous induction of ILEI overexpression (R26-ILEIind) at weaning age leads to a shortened lifespan, reduced body weight and microcytic hypochromic anemia. The anemia was reversible at a young age within a week upon withdrawal of ILEI induction. Vav1-driven overexpression of the ILEIind transgene in all hematopoietic cells (Vav-ILEIind) did not render mice anemic or lower overall fitness, demonstrating that no intrinsic mechanisms of erythroid development were dysregulated by ILEI and that hematopoietic ILEI hyperfunction did not contribute to death. Reduced serum iron levels of R26-ILEIind mice were indicative for a malfunction in iron uptake or homeostasis. Accordingly, the liver, the main organ of iron metabolism, was severely affected in moribund ILEI overexpressing mice: increased alanine transaminase and aspartate aminotransferase levels indicated liver dysfunction, the liver was reduced in size, showed increased apoptosis, reduced cellular iron content, and had a fibrotic phenotype. These data indicate that high ILEI expression in the liver might reduce hepatoprotection and induce liver fibrosis, which leads to liver dysfunction, disturbed iron metabolism and eventually to death. Overall, we show here that the novel Tet-ON inducible Fam3c/ILEI transgenic mouse strain allows tissue specific timely controlled overexpression of ILEI and thus, will serve as a versatile tool to model the effect of elevated ILEI expression in diverse tissue entities and disease conditions, including cancer.

Pre-operative CT scan helps predict outcome after liver transplantation for acute-on-chronic grade 3 liver failure

OBJECTIVES

The aim of this study was to identify the prognostic value of pre-operative imaging to predict post-transplantation survival in critically ill cirrhotic patients with severe acute-on-chronic liver failure (ACLF).

METHODS

Patients with grade 3 ACLF who underwent liver transplantation between January 2010 and January 2020 and with available contrast-enhanced abdominal computed tomography (CT) performed less than 3 months before LT were retrospectively included (n = 82). Primary endpoint was 1-year mortality. Imaging parameters (sarcopenia, liver morphology and volumetry, and signs of portal hypertension) were screened and tested to build a prognostic score.

RESULTS

In the multivariate analysis, three independent CT-derived prognostic factors were found: splenomegaly (p = 0.021; HR = 5.6 (1.29-24.1)), liver atrophy (p = 0.05; HR = 2.93 (1.01-10.64)), and vena cava diameter ratio (p < 0.0001; HR = 12.7 (3.4-92)). A simple prognostic score was proposed, based on the presence of splenomegaly (5 points), liver atrophy (5 points), and vena cava diameter ratio < 0.2 (12 points). A cutoff at 10 points distinguished a high-risk group (score > 10) from a low-risk group (score ≤ 10) with 1-year survival of 27% vs. 67% respectively (p < 0.001). It was found to be an independent predictive factor in association with the Transplantation for ACLF3 Model (TAM) score.

CONCLUSION

Pre-transplantation contrast-enhanced abdominal CT has a significant impact on selection of patients in ACLF3 in order to predict 1-year survival after LT.

KEY POINTS

• Splenomegaly, liver atrophy, and vena cava diameter ratio are independent CT-derived prognostic factors after transplantation for severe acute-on-chronic liver failure. • A simple CT-based prognostic score is an independent predictive factor, complementary to clinical and biological parameters. • The use of the CT-derived score allows stratification based on 1-year mortality for patients with otherwise uncertain prognosis with clinical and biological parameters alone.

Genetic architecture of 11 organ traits derived from abdominal MRI using deep learning

Cardiometabolic diseases are an increasing global health burden. While socioeconomic, environmental, behavioural, and genetic risk factors have been identified, a better understanding of the underlying mechanisms is required to develop more effective interventions. Magnetic resonance imaging (MRI) has been used to assess organ health, but biobank-scale studies are still in their infancy. Using over 38,000 abdominal MRI scans in the UK Biobank, we used deep learning to quantify volume, fat, and iron in seven organs and tissues, and demonstrate that imaging-derived phenotypes reflect health status. We show that these traits have a substantial heritable component (8-44%) and identify 93 independent genome-wide significant associations, including four associations with liver traits that have not previously been reported. Our work demonstrates the tractability of deep learning to systematically quantify health parameters from high-throughput MRI across a range of organs and tissues, and use the largest-ever study of its kind to generate new insights into the genetic architecture of these traits.

The Association between the Platelet Count and Liver Volume in Compensated Cirrhosis Patients after the Eradication of Hepatitis C virus by Direct-acting Antivirals

Objective Although most patients who obtain a sustained virological response (SVR) show an improved liver function, some show decreased platelet counts after the eradication of hepatitis C virus (HCV). The aim of this retrospective study was to clarify the association of the liver and spleen volumes with the platelet count after SVR achieved by direct-acting antiviral (DAA) treatment. Methods This study enrolled 36 consecutive patients treated by DAAs who obtained an SVR between September 2014 and December 2018. The liver and spleen volumes were derived from computed tomography scans obtained at pretreatment, SVR, and 48 weeks after SVR. No patient developed hepatocellular carcinoma during this study. Results Compared with pretreatment, the median aspartate aminotransferase, alanine aminotransferase, albumin serum levels, and platelet counts were significantly improved at SVR and 48 weeks after SVR. The liver/spleen volumes per body weight had decreased significantly from 22.5/4.2 mL/kg at baseline to 21.1/3.6 mL/kg at 48 weeks after SVR. The change in the liver volume was associated with the change in the platelet count, and the change in the spleen volume was negatively associated with the change in the serum albumin level. A multivariate analysis identified the change in the liver volume (≥95%, odds ratio 76.9, p=0.005) as the factor associated with improvement in the platelet count at 48 weeks after SVR. The patients with an increased liver volume at 48 weeks after SVR showed an increased platelet count. Conclusion Both the liver and spleen volume decreased significantly after the eradication of HCV. The patients with a re-increased liver volume showed a rapid increase in the platelet count.

Liver volume index predicts the risk of esophageal variceal hemorrhage in cirrhotic patients on propranolol prophylaxis

BACKGROUND/AIMS

Non-selective β-blockers (NSBBs) are used for primary prevention of esophageal variceal hemorrhage (VH) in patients with portal hypertension, but a significant number of patients develop VH while on NSBB therapy. In this study, we sought to determine whether liver volume can predict the risk of primary prophylaxis failure in cirrhotic patients on NSBB therapy.

METHODS

A retrospective cohort of 309 patients on prophylactic propranolol was analyzed. Liver volume was measured in portal venous phase images of multidetector computed tomography. Predictors of VH were assessed using a Cox proportional hazards model with competing-risks analysis. A nomogram was developed for estimation of the risk of primary prophylaxis failure.

RESULTS

During a median follow-up of 36 months, 37 patients on propranolol developed VH. Liver volume index, the ratio of measured-to-expected liver volume, was an independent predictor of VH (adjusted hazard ratio [HR], 2.70; 95% confidence interval [CI], 1.37 to 5.33; p = 0.004) as were the presence of large varices and the absence of ascites. A nomogram-based volume score of > 0.6 was predictive of prophylaxis failure (HR, 7.54; 95% CI, 2.88 to 19.73; p < 0.001). Time-dependent receiver operating characteristic curve analysis revealed that a nomogram-based risk score had significantly better discriminatory power than the North Italian Endoscopy Club index in predicting prophylaxis failure at 6 and 8 years.

CONCLUSION

Liver volume index is an independent predictor of first VH and a nomogram-based volume score stratifies the VH risk in cirrhotic patients on propranolol prophylaxis.

Does providing routine liver volume assessment add value when performing CT surveillance in cirrhotic patients?

BACKGROUND

The measurement of liver volume (LV) is considered to be an effective prognosticator for postoperative liver failure in patients undergoing hepatectomy. It is unclear whether LV can be used to predict mortality in cirrhotic patients.

METHODS

We enrolled 584 consecutive cirrhotic patients who underwent computerized topography (CT) of the abdomen for hepatocellular carcinoma surveillance and 50 age, gender, race, and BMI-matched controls without liver disease. Total LV (TLV), functional LV (FLV), and segmental liver volume (in cm³) were measured from CT imaging. Cirrhotic subjects were followed until death, liver transplantation, or study closure date of July 31, 2016. The survival data were assessed with log-rank statistics and independent predictors of survival were performed using Cox hazards model.

RESULTS

Cirrhotic subjects had significantly lower TLV, FLV, and segmental (all except for segments 1, 6, 7) volume when compared to controls. Subjects presenting with hepatic encephalopathy had significantly lower TLV and FLV than those without HE (p = 0.002). During the median follow-up of 1145 days, 112 (19%) subjects were transplanted and 131 (23%) died. TLV and FLV for those who survived were significantly higher than those who were transplanted or dead (TLV:1740 vs. 1529 vs. 1486, FLV 1691 vs. 1487 vs. 1444, p < 0.0001). In the Cox regression model, age, MELD score, TLV, or FLV were independent predictors of mortality.

CONCLUSION

Baseline liver volume is an independent predictor of mortality in subjects with cirrhosis. Therefore, it may be useful to provide these data while performing routine surveillance CT scan as an important added value. Further studies are needed to validate these findings and to better understand their clinical utility.

Predictors of Radiation-Induced Liver Disease in Eastern and Western Patients With Hepatocellular Carcinoma Undergoing Proton Beam Therapy

PURPOSE

To identify predictors of radiation-induced liver disease (RILD) in patients with hepatocellular carcinoma (HCC) treated with proton beam therapy (PBT).

METHODS

This multicenter study included 136 patients with HCC (eastern, n = 102; western, n = 34) without evidence of intrahepatic tumor progression after PBT. The RILD was defined as ascites with alkaline-phosphatase abnormality, grade ≥3 hepatic toxicity, or Child-Pugh score worsening by ≥2 within 4 months after PBT completion. The proton doses were converted to equivalent doses in 2-GyE fractions. The unirradiated liver volume (ULV) was defined as the absolute liver volume (LV) receiving <1 GyE; the standard liver volume (SLV) was calculated using body surface area. Possible correlations of clinicodosimetric parameters with RILD were examined.

RESULTS

The mean pretreatment LV was 85% of SLV, and patients with a history of hepatectomy (P < .001) or hepatitis B virus infection (P = .035) had significantly smaller LV/SLV. Nineteen (14%) patients developed RILD. Multivariate logistic regression analysis identified ULV/SLV (P = .001), gross tumor volume (P = .001), and Child-Pugh classification (P = .002) as independent RILD predictors, and mean liver dose and target-delivered dose were not associated with RILD occurrence. A "volume-response" relationship between ULV/SLV and RILD was consistently observed in both eastern and western cohorts. In Child-Pugh class-A patients whose ULV/SLV were ≥50%, 49.9%-40%, 39.9%-30% and <30%, the RILD incidences were 0%, 6%, 16%, and 39% (P < .001), respectively. For the Child-Pugh class-B group, the RILD incidences in patients with ≥60%, 59.9%-40%, and <40% of ULV/SLV were 0%, 14%, and 83% (P = .006), respectively.

CONCLUSIONS

The ULV/SLV, not mean liver dose, independently predicts RILD in patients with HCC undergoing PBT. The relative and absolute contraindications for Child-Pugh class-A patient's ULV/SLV are <50% and <30%, and <60% and <40% for Child-Pugh class-B patients, respectively. Our results indicate that the likelihood of hepatic complications for PBT is dictated by similar metrics as that for surgery.

Combination of Active Transfer Learning and Natural Language Processing to Improve Liver Volumetry Using Surrogate Metrics with Deep Learning

PURPOSE

To determine if weakly supervised learning with surrogate metrics and active transfer learning can hasten clinical deployment of deep learning models.

MATERIALS AND METHODS

By leveraging Liver Tumor Segmentation (LiTS) challenge 2017 public data (n = 131 studies), natural language processing of reports, and an active learning method, a model was trained to segment livers on 239 retrospectively collected portal venous phase abdominal CT studies obtained between January 1, 2014, and December 31, 2016. Absolute volume differences between predicted and originally reported liver volumes were used to guide active learning and assess accuracy. Overall survival based on liver volumes predicted by this model (n = 34 patients) versus radiology reports and Model for End-Stage Liver Disease with sodium (MELD-Na) scores was assessed. Differences in absolute liver volume were compared by using the paired Student t test, Bland-Altman analysis, and intraclass correlation; survival analysis was performed with the Kaplan-Meier method and a Mantel-Cox test.

RESULTS

Data from patients with poor liver volume prediction (n = 10) with a model trained only with publicly available data were incorporated into an active learning method that trained a new model (LiTS data plus over- and underestimated active learning cases [LiTS-OU]) that performed significantly better on a held-out institutional test set (absolute volume difference of 231 vs 176 mL, P = .0005). In overall survival analysis, predicted liver volumes using the best active learning-trained model (LiTS-OU) were at least comparable with liver volumes extracted from radiology reports and MELD-Na scores in predicting survival.

CONCLUSION

Active transfer learning using surrogate metrics facilitated deployment of deep learning models for clinically meaningful liver segmentation at a major liver transplant center.© RSNA, 2019Supplemental material is available for this article.

Clearing the Confusion over Hepatic Encephalopathy After TIPS Creation: Incidence, Prognostic Factors, and Clinical Outcomes

PURPOSE

To assess the incidence, prognostic factors, and clinical outcomes of hepatic encephalopathy (HE) after transjugular intrahepatic portosystemic shunt (TIPS) creation.

MATERIALS AND METHODS

In this single-institution retrospective study, 191 patients (m:f = 114:77, median age 54 years, median Model for End-Stage Liver Disease or MELD score 14) who underwent TIPS creation between 1999 and 2013 were studied. Medical record review was used to identify demographic characteristics, liver disease, procedure, and outcome data. Post-TIPS HE within 30 days was defined by new mental status changes and was graded according to the West Haven classification system. The influence of data parameters on HE occurrence and 90-day mortality was assessed using binary logistic regression.

RESULTS

TIPS was successfully created with hemodynamic success in 99 % of cases. Median final PSG was 7 mmHg. HE incidence within 30 days was 42 % (81/191; 22 % de novo, 12 % stable, and 8 % worsening). Degrees of HE included grade 1 (46 %), grade 2 (29 %), grade 3 (18 %), and grade 4 (7 %). Medical therapy typically addressed HE, and shunt reduction was necessary in only three cases. MELD score (P = 0.020) and age (P = 0.009) were significantly associated with HE development on multivariate analysis. Occurrence of de novo HE post-TIPS did not associate with 90-day mortality (P = 0.400), in contrast to worsening HE (P < 0.001).

CONCLUSIONS

The incidence of post-TIPS HE is non-trivial, but symptoms are typically mild and medically managed. HE rates are higher in older patients and those with worse liver function and should be contemplated when counseling on expected TIPS outcomes and post-procedure course.

Retrospective analysis of liver cirrhosis influence on heart walls thickness

OBJECTIVE

Cirrhotic cardiomyopathy is a chronic cardiac dysfunction in patients with liver cirrhosis. It is mostly characterized by impaired cardiac function, but some myocardial anatomical changes have also been described. The aim of this study was to assess the influence of liver cirrhosis on heart wall thickness changes in a retrospective pathological analysis of cirrhotic patients without hypertension.

MATERIALS AND METHODS

Statistical analysis of 11,860 autopsy protocols drawn up between 1981 and 2002 in the Department of Pathology Medical University of Warsaw was done.

RESULTS

Liver cirrhosis was confirmed by autopsy in 802 patients (6.7%); in 697 patients, hypertension was excluded. Analysis of heart wall thickness showed pathological changes in 53.2% of patients - left ventricular thickening in 9.3%, right ventricular thinning in 31.0%, and both in 12.9%. In clinical assessment, the cause of death in 25.8% of patients was cardiocirculatory failure, significantly more in the group with selective left ventricular thickening. It was the most common cause of death among them. Vascular changes in the upper gastrointestinal tract, liver enlargement and hepatic coma were also significantly related to the heart wall thickness changes occurrence.

CONCLUSIONS

Based on statistical analysis of autopsy material, we concluded that liver cirrhosis can lead to heart wall thickness changes (left ventricular thickening and/or right ventricular thinning). We revealed that patients with selective left ventricular thickening had significantly more cardiac related causes of death. In clinical practice, treatment of cirrhotic cardiomyopathy requires specialized diagnostics and appropriate cardiological procedures involving the participation of a hepatologist, especially in the group of patients with selective left ventricular hypertrophy.