A Protocol for Body MRI/CT and Extraction of Imaging-Derived Phenotypes (IDPs) from the China Phenobank Project.

Currently, standard protocols for body imaging and corresponding image processing pipelines in population-based cohort studies are unavailable, limiting the applications of body imaging. Based on the China Phenobank Project (CHPP), the present study described a body imaging protocol for multiple organs, including cardiac structures, liver, spleen, pancreas, kidneys, lung, prostate, and uterus, and the corresponding image processing pipelines promoted its development. Briefly, the body imaging protocol comprised a 40-min cardiac magnetic resonance imaging (MRI) scan, a 5-min computed tomography (CT) scan, a 20-min abdominal MRI scan, and a 10-min pelvic MRI scan.

Denoising of volumetric magnetic resonance imaging using multi-channel three-dimensional convolutional neural network with applications on fast spin echo acquisitions.

Background: Three-dimensional (3D) magnetic resonance imaging (MRI) can be acquired with a high spatial resolution with flexibility being reformatted into arbitrary planes, but at the cost of reduced signal-to-noise ratio. Deep-learning methods are promising for denoising in MRI. However, the existing 3D denoising convolutional neural networks (CNNs) rely on either a multi-channel two-dimensional (2D) network or a single-channel 3D network with limited ability to extract high dimensional features.

Indirect Shear Wave Excitation for Brain Magnetic Resonance Elastography With Minimal Cerebral Blood Flow Alteration.

Unlabelled: Magnetic resonance elastography (MRE) of brain relies on inducing and measuring shear waves in the brain. However, studies have shown vibration could induce changes in cerebral blood flow (CBF), which has a modulation effect and can affect the biomechanical properties measured.

Objective: This work demonstrates the initial prototype of the indirect excitation method, which can generate shear waves in the brain with minimal changes in CBF.

Viscoelastic parameters derived from multifrequency MR elastography for depicting hepatic fibrosis and inflammation in chronic viral hepatitis.

Objectives: The capability of MR elastography (MRE) to differentiate fibrosis and inflammation, and to provide precise diagnoses is crucial, whereas the coexistence of fibrosis and inflammation may obscure the diagnostic accuracy.

Methods: In this retrospective study, from June 2020 to December 2022, chronic viral hepatitis patients who underwent multifrequency MRE (mMRE) were included in, and further divided into, training and validation cohorts. The hepatic viscoelastic parameters [shear wave speed (c) and loss angle (φ) of the complex shear modulus] were obtained from mMRE.

A Comparative Study of Three Systems for Liver Magnetic Resonance Elastography.

Background: Different MR elastography (MRE) systems may produce different stiffness measurements, making direct comparison difficult in multi-center investigations.

Purpose: To assess the repeatability and reproducibility of liver stiffness measured by three typical MRE systems.

Study Type: Prospective.

Three-Dimensional Multifrequency MR Elastography for Microvascular Invasion and Prognosis Assessment in Hepatocellular Carcinoma.

Background: Pretreatment identification of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is important when selecting treatment strategies.

Purpose: To improve models for predicting MVI and recurrence-free survival (RFS) by developing nomograms containing three-dimensional (3D) MR elastography (MRE).

Study Type: Prospective.

Three-dimensional multifrequency magnetic resonance elastography improves preoperative assessment of proliferative hepatocellular carcinoma.

Background: To investigate the viscoelastic signatures of proliferative hepatocellular carcinoma (HCC) using three-dimensional (3D) magnetic resonance elastography (MRE).

Methods: This prospective study included 121 patients with 124 HCCs as training cohort, and validation cohort included 33 HCCs. They all underwent preoperative conventional magnetic resonance imaging (MRI) and tomoelastography based on 3D multifrequency MRE.

Clinic-radiomics model using liver magnetic resonance imaging helps predict chronicity of drug-induced liver injury.

Background And Aims: Some drug-induced liver injury (DILI) cases may become chronic, even after drug withdrawal. Radiomics can predict liver disease progression. We established and validated a predictive model incorporating the clinical characteristics and radiomics features for predicting chronic DILI.

MR Elastography With Optimization-Based Phase Unwrapping and Traveling Wave Expansion-Based Neural Network (TWENN).

Magnetic Resonance Elastography (MRE) can characterize biomechanical properties of soft tissue for disease diagnosis and treatment planning. However, complicated wavefields acquired from MRE coupled with noise pose challenges for accurate displacement extraction and modulus estimation. Using optimization-based displacement extraction and Traveling Wave Expansion-based Neural Network (TWENN) modulus estimation, we propose a new pipeline for processing MRE images.

Multi-channel GAN-based calibration-free diffusion-weighted liver imaging with simultaneous coil sensitivity estimation and reconstruction.

Introduction: Diffusion-weighted imaging (DWI) with parallel reconstruction may suffer from a mismatch between the coil calibration scan and imaging scan due to motions, especially for abdominal imaging.

Methods: This study aimed to construct an iterative multichannel generative adversarial network (iMCGAN)-based framework for simultaneous sensitivity map estimation and calibration-free image reconstruction. The study included 106 healthy volunteers and 10 patients with tumors.

Reduced tumor stiffness quantified by tomoelastography as a predicative marker for glypican-3-positive hepatocellular carcinoma.

Background: Glypican-3 (GPC3) expression is investigated as a promising target for tumor-specific immunotherapy of hepatocellular carcinoma (HCC). This study aims to determine whether GPC3 alters the viscoelastic properties of HCC and whether tomoelastography, a multifrequency magnetic resonance elastography (MRE) technique, is sensitive to it.

Methods: Ninety-five participants (mean age, 58 ± 1 years; 78 men and 17 women) with 100 pathologically confirmed HCC lesions were enrolled in this prospective study from July 2020 to August 2021.

Noninvasive Assessment of Liver Fibrosis and Inflammation in Chronic Hepatitis B: A Dual-task Convolutional Neural Network (DtCNN) Model Based on Ultrasound Shear Wave Elastography.

Background And Aims: Liver stiffness (LS) measured by shear wave elastography (SWE) is often influenced by hepatic inflammation. The aim was to develop a dual-task convolutional neural network (DtCNN) model for the simultaneous staging of liver fibrosis and inflammation activity using 2D-SWE.

Methods: A total of 532 patients with chronic hepatitis B (CHB) were included to develop and validate the DtCNN model.

Correlation analysis of structural and biomechanical properties of hepatocellular carcinoma tissue.

It is known that biomechanical and structural properties of tumor tissues are potential biomarkers for the diagnosis and prognosis of tumors such as Hepatocellular carcinoma (HCC). Although there are many studies on the characterization of biomechanical properties of HCC at the cellular level, limited information is known from in vitro studies. Here, tissue samples from 14 patients diagnosed with HCC were analyzed.

Added Value of Viscoelasticity for MRI-Based Prediction of Ki-67 Expression of Hepatocellular Carcinoma Using a Deep Learning Combined Radiomics (DLCR) Model.

This study aimed to explore the added value of viscoelasticity measured by magnetic resonance elastography (MRE) in the prediction of Ki-67 expression in hepatocellular carcinoma (HCC) using a deep learning combined radiomics (DLCR) model. This retrospective study included 108 histopathology-proven HCC patients (93 males; age, 59.6 ± 11.

Tomoelastography based on multifrequency MR elastography predicts liver function reserve in patients with hepatocellular carcinoma: a prospective study.

Background: Estimating liver function reserve is essential for preoperative surgical planning and predicting post-hepatectomy complications in patients with hepatocellular carcinoma (HCC). We investigated hepatic viscoelasticity quantified by tomoelastography, a multifrequency magnetic resonance elastography technique, to predict liver function reserve.

Methods: One hundred fifty-six patients with suspected HCC (mean age, 60 ± 1 years; 131 men) underwent preoperative tomoelastography examination between July 2020 and August 2021.

COVID-19 vaccines in patients with decompensated cirrhosis: a retrospective cohort on safety data and risk factors associated with unvaccinated status.

Background: Safety data reported from the large-scale clinical trials of the coronavirus disease 2019 (COVID-19) vaccine are extremely limited in patients with decompensated cirrhosis. The vaccination campaign in this specific population could be difficult due to uncertainty about the adverse events following vaccination. We aimed to assessed the COVID-19 vaccination rate, factors associated with unvaccinated status, and the adverse events following vaccination in patients with decompensated cirrhosis.

A new visual quantitative assessment of ultrasound attenuation parameters for the mild liver steatosis.

Background: Controlled attenuation parameter (CAP) without the guidance of the grey scale sonogram was a classic method in the quantitative evaluation of liver steatosis, it is recommended by international guidelines. Our study aimed to compare the diagnostic efficiency of a new real-time visual liver steatosis analysis (LiSA) versus CAP in chronic hepatitis B patients with liver steatosis.

Methods: Patients were enrolled who underwent liver biopsy and received both LiSA (Hepatus, Mindray, probe LFP5-1U/s, China) and CAP (FibroScan502, Echosens, probe M, France) measurement simultaneously in our hospital from November 2018 to December 2019.

Fast magnetic resonance elastography with multiphase radial encoding and harmonic motion sparsity based reconstruction.

. To achieve fast magnetic resonance elastography (MRE) at a low frequency for better shear modulus estimation of the brain..

Assessment of Vascular Network Connectivity of Hepatocellular Carcinoma Using Graph-Based Approach.

Background: The angiogenesis of liver cancer is a key condition for its growth, invasion, and metastasis. This study aims to investigate vascular network connectivity of hepatocellular carcinoma (HCC) using graph-based approach.

Methods: Orthotopic HCC xenograft models (n=10) and the healthy controls (n=10) were established.

An electromagnetic actuator for brain magnetic resonance elastography with high frequency accuracy.

Our goal is to design, test and verify an electromagnetic actuator for brain magnetic resonance elastography (MRE). We proposed a grappler-shaped design that can transmit stable vibrations into the brain. To validate its performance, simulations were carried out to ensure the electromagnetic field generated by the actuator did not interfere with the B field.

Differentiation of Hepatocellular Carcinoma from Hepatic Hemangioma and Focal Nodular Hyperplasia using Computed Tomographic Spectral Imaging.

Background And Aims: Hepatocellular carcinoma (HCC) is the most common primary hepatic malignancy. This study was designed to investigate the value of computed tomography (CT) spectral imaging in differentiating HCC from hepatic hemangioma (HH) and focal nodular hyperplasia (FNH).

Methods: This was a retrospective study of 51 patients who underwent spectral multiple-phase CT at 40-140 keV during the arterial phase (AP) and portal venous phase (PP).

Diagnostic Performance of Shear Wave Elastography in the Noninvasive Evaluation of Liver Inflammation of Chronic Hepatitis B Patients.

In the current study, we sought to delineate the elastographic characteristics and further compare the diagnostic performance of various shear wave elastography modalities in hepatitis B virus patients whose liver fibrosis stage was less than F2 by liver biopsy. We retrospectively studied the clinical and imaging data of chronic hepatitis B virus patients who underwent liver biopsy at our hospital between January 2017 and October 2017. Totally, 102 patients were eligible for the study.

Feasibility of automatic detection of small hepatocellular carcinoma (≤2 cm) in cirrhotic liver based on pattern matching and deep learning.

Early detection of hepatocellular carcinoma (HCC) is crucial for clinical management. Current studies have reported large HCC detections using automatic algorithms, but there is a lack of research on automatic detection of small HCCs (sHCCs). This study is to investigate the feasibility of automatic detection of sHCC (≤2 cm) based on pattern matching and deep learning (PM-DL) model.