Comparison of prognostic accuracy of HCC staging systems in patients undergoing TACE.

Purpose: To compare the prognostic power of commonly used staging systems of hepatocellular carcinoma (HCC) for predicting overall survival after transarterial chemoembolization (TACE).

Materials And Methods: This retrospective single center study included patients with HCC who underwent TACE between 2008 and 2019 in a single tertiary care center. After initial screening of 408 consecutive patients, 317 patients with HCC treated with conventional or drug-eluting beads-TACE were included.

Artificial intelligence in liver cancer - new tools for research and patient management.

Liver cancer has high incidence and mortality globally. Artificial intelligence (AI) has advanced rapidly, influencing cancer care. AI systems are already approved for clinical use in some tumour types (for example, colorectal cancer screening).

Automated graded prognostic assessment for patients with hepatocellular carcinoma using machine learning.

Background: Accurate mortality risk quantification is crucial for the management of hepatocellular carcinoma (HCC); however, most scoring systems are subjective.

Purpose: To develop and independently validate a machine learning mortality risk quantification method for HCC patients using standard-of-care clinical data and liver radiomics on baseline magnetic resonance imaging (MRI).

Methods: This retrospective study included all patients with multiphasic contrast-enhanced MRI at the time of diagnosis treated at our institution.

Automated MRI liver segmentation for anatomical segmentation, liver volumetry, and the extraction of radiomics.

Objectives: To develop and evaluate a deep convolutional neural network (DCNN) for automated liver segmentation, volumetry, and radiomic feature extraction on contrast-enhanced portal venous phase magnetic resonance imaging (MRI).

Materials And Methods: This retrospective study included hepatocellular carcinoma patients from an institutional database with portal venous MRI. After manual segmentation, the data was randomly split into independent training, validation, and internal testing sets.

Spectral top-down recovery of latent tree models.

Modeling the distribution of high-dimensional data by a latent tree graphical model is a prevalent approach in multiple scientific domains. A common task is to infer the underlying tree structure, given only observations of its terminal nodes. Many algorithms for tree recovery are computationally intensive, which limits their applicability to trees of moderate size.

Advancing diagnosis and management of liver disease in adults through exome sequencing.

Background: Whole-exome sequencing (WES) is an effective tool for diagnosis in patients who remain undiagnosed despite a comprehensive clinical work-up. While WES is being used increasingly in pediatrics and oncology, it remains underutilized in non-oncological adult medicine, including in patients with liver disease, in part based on the faulty premise that adults are unlikely to harbor rare genetic variants with large effect size. Here, we aim to assess the burden of rare genetic variants underlying liver disease in adults at two major tertiary referral academic medical centers.

Adherence to Tumor Board Recommendations in the Treatment of Patients with Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) is a heterogeneous disease that typically arises in the setting of chronic liver disease, making treatment selection complex. Multidisciplinary liver tumor boards (MDLTB) have been shown to improve outcomes in patients with HCC. However, in many cases, patients evaluated by MDLTBs ultimately do not receive the board's recommended treatment.

Holistic management of hepatocellular carcinoma: The hepatologist's comprehensive playbook.

Hepatocellular carcinoma (HCC) is a common complication in patients with chronic liver disease and leads to significant morbidity and mortality. Liver disease and liver cancer are preventable by mitigating and managing common risk factors, including chronic hepatitis B and C infection, alcohol use, diabetes, obesity and other components of the metabolic syndrome. The management of patients with HCC requires treatment of the malignancy and adequate control of the underlying liver disease, as preserving liver function is critical for successful cancer treatment and may have a relevant prognostic role independent of HCC management.

Immune checkpoint inhibitors in malignancies after liver transplantation: A systematic review and pooled analysis.

Background And Aims: Treatment of de novo malignancies and recurrent hepatocellular carcinoma with immune checkpoint inhibitors (ICI) in liver transplant recipients (LT) is an attractive strategy that is infrequently pursued because of the lack of strong evidence regarding their safety and efficacy. In this systematic review with pooled analysis, we aimed to assess safety and efficacy of ICI therapy following LT.

Methods: We performed a systematic search of case reports and series published until January 2022.

Super-resolution multi-reference alignment.

We study super-resolution multi-reference alignment, the problem of estimating a signal from many circularly shifted, down-sampled and noisy observations. We focus on the low SNR regime, and show that a signal in is uniquely determined when the number of samples per observation is of the order of the square root of the signal's length ( ). Phrased more informally, one can square the resolution.

Optimization of the BCLC Staging System for Locoregional Therapy for Hepatocellular Carcinoma by Using Quantitative Tumor Burden Imaging Biomarkers at MRI.

Background Patients with intermediate- and advanced-stage hepatocellular carcinoma (HCC) represent a highly heterogeneous patient collective with substantial differences in overall survival. Purpose To evaluate enhancing tumor volume (ETV) and enhancing tumor burden (ETB) as new criteria within the Barcelona Clinic Liver Cancer (BCLC) staging system for optimized allocation of patients with intermediate- and advanced-stage HCC to undergo transarterial chemoembolization (TACE). Materials and Methods In this retrospective study, 682 patients with HCC who underwent conventional TACE or TACE with drug-eluting beads from January 2000 to December 2014 were evaluated.

Diabetes medications and risk of HCC.

Type 2 diabetes mellitus is a recognized risk factor for HCC in patients with liver disease, independent from the etiology of their liver disease. Hence, prevention and treatment of type 2 diabetes mellitus and its underlying cause, insulin resistance, should be considered a treatment target for patients with liver disease. The drug armamentarium for diabetes is wide and consists of agents with insulin-sensitizing activity, agents that stimulate insulin secretion, insulin itself, and agents that reduce gastrointestinal and urinary glucose absorption.

Improved performance and consistency of deep learning 3D liver segmentation with heterogeneous cancer stages in magnetic resonance imaging.

Purpose: Accurate liver segmentation is key for volumetry assessment to guide treatment decisions. Moreover, it is an important pre-processing step for cancer detection algorithms. Liver segmentation can be especially challenging in patients with cancer-related tissue changes and shape deformation.

The Spectral Underpinning of word2vec.

Word2vec introduced by Mikolov et al. is a word embedding method that is widely used in natural language processing. Despite its success and frequent use, a strong theoretical justification is still lacking.

Spectral neighbor joining for reconstruction of latent tree Models.

A common assumption in multiple scientific applications is that the distribution of observed data can be modeled by a latent tree graphical model. An important example is phylogenetics, where the tree models the evolutionary lineages of a set of observed organisms. Given a set of independent realizations of the random variables at the leaves of the tree, a key challenge is to infer the underlying tree topology.

Detection of differentially abundant cell subpopulations in scRNA-seq data.

Comprehensive and accurate comparisons of transcriptomic distributions of cells from samples taken from two different biological states, such as healthy versus diseased individuals, are an emerging challenge in single-cell RNA sequencing (scRNA-seq) analysis. Current methods for detecting differentially abundant (DA) subpopulations between samples rely heavily on initial clustering of all cells in both samples. Often, this clustering step is inadequate since the DA subpopulations may not align with a clear cluster structure, and important differences between the two biological states can be missed.

Reliable prediction of survival in advanced-stage hepatocellular carcinoma treated with sorafenib: comparing 1D and 3D quantitative tumor response criteria on MRI.

Objectives: To compare 1D and 3D quantitative tumor response criteria applied to DCE-MRI in patients with advanced-stage HCC undergoing sorafenib therapy to predict overall survival (OS) early during treatment.

Methods: This retrospective analysis included 29 patients with advanced-stage HCC who received sorafenib for at least 60 days. All patients underwent baseline and follow-up DCE-MRI at 81.

Randomized near-neighbor graphs, giant components and applications in data science.

If we pick random points uniformly in [0, 1] and connect each point to its log -nearest neighbors, where ≥ 2 is the dimension and is a constant depending on the dimension, then it is well known that the graph is connected with high probability. We prove that it suffices to connect every point to log log points chosen randomly among its log -nearest neighbors to ensure a giant component of size - () with high probability. This construction yields a much sparser random graph with ~ log log instead of ~ log edges that has comparable connectivity properties.

Health related quality of life in chronic liver diseases.

Background & Aims: The impact of chronic liver diseases (CLDs) on health-related quality of life (HRQoL) is relevant to understand the burden of these conditions and inform decision-making processes related to their care. Studies simultaneously comparing the HRQoL of patients affected by the major CLDs to that of the general population are still lacking and are the subject of this study.

Methods: Using the EQ-5D-3L questionnaire, we analysed and compared HRQoL data from 2962 Italian patients affected by CLDs and forming a representative sample of the general Italian population (6800 individuals).