Tissue-matched analysis of MRI evaluating the tumor infiltrating lymphocytes in hepatocellular carcinoma.

Tumor-infiltrating lymphocytes (TILs) play critical roles in the tumor microenvironment and immunotherapy response. This study aims to explore the feasibility of multi-parametric magnetic resonance imaging (MRI) in evaluating TILs and to develop an evaluation model that considers spatial heterogeneity. Multi-parametric MRI was performed on hepatocellular carcinoma (HCC) mice (N = 28).

Multiomics reveals microbial metabolites as key actors in intestinal fibrosis in Crohn's disease.

Intestinal fibrosis is the primary cause of disability in patients with Crohn's disease (CD), yet effective therapeutic strategies are currently lacking. Here, we report a multiomics analysis of gut microbiota and fecal/blood metabolites of 278 CD patients and 28 healthy controls, identifying characteristic alterations in gut microbiota (e.g.

Predicting One-year Recurrence of HCC based on Gadoxetic Acid-enhanced MRI by Machine Learning Models.

Objective: Accurate prediction of recurrence risk after resction in patients with Hepatocellular Carcinoma (HCC) may help to individualize therapy strategies. This study aimed to develop machine learning models based on preoperative clinical factors and multiparameter Magnetic Resonance Imaging (MRI) characteristics to predict the 1-year recurrence after HCC resection.

Methods: Eighty-two patients with single HCC who underwent surgery were retrospectively analyzed.

Prediction of immunocyte infiltration and prognosis in postoperative hepatitis B virus-related hepatocellular carcinoma patients using magnetic resonance imaging.

Background: The immune microenvironment (IME) is closely associated with prognosis and therapeutic response of hepatitis B virus-related hepatocellular carcinoma (HBV-HCC). Multi-parametric magnetic resonance imaging (MRI) enables non-invasive assessment of IME and predicts prognosis in HBV-HCC. We aimed to construct an MRI prediction model of the immunocyte-infiltration subtypes and explore its prognostic significance.

Dual-energy CT improves differentiation of non-hypervascular pancreatic neuroendocrine neoplasms from CA 19-9-negative pancreatic ductal adenocarcinomas.

Purpose: To evaluate the utility of dual-energy CT (DECT) in differentiating non-hypervascular pancreatic neuroendocrine neoplasms (PNENs) from pancreatic ductal adenocarcinomas (PDACs) with negative carbohydrate antigen 19-9 (CA 19-9).

Methods: This retrospective study included 26 and 39 patients with pathologically confirmed non-hypervascular PNENs and CA 19-9-negative PDACs, respectively, who underwent contrast-enhanced DECT before treatment between June 2019 and December 2021. The clinical, conventional CT qualitative, conventional CT quantitative, and DECT quantitative parameters of the two groups were compared using univariate analysis and selected by least absolute shrinkage and selection operator regression (LASSO) analysis.

A radiomics-based interpretable model to predict the pathological grade of pancreatic neuroendocrine tumors.

Objectives: To develop a computed tomography (CT) radiomics-based interpretable machine learning (ML) model to predict the pathological grade of pancreatic neuroendocrine tumors (pNETs) in a non-invasive manner.

Methods: Patients with pNETs who underwent contrast-enhanced abdominal CT between 2010 and 2022 were included in this retrospective study. Radiomics features were extracted, and five radiomics-based ML models, namely logistic regression (LR), random forest (RF), support vector machine (SVM), XGBoost, and GaussianNB, were developed.

Harnessing dual-energy CT for glycogen quantification: a phantom analysis.

Background: Non-invasive glycogen quantification could provide crucial information on biological processes for glycogen storage disorder. Using dual-energy computed tomography (DECT), this study aimed to assess the viability of quantifying glycogen content .

Methods: A fast kilovolt-peak switching DECT was used to scan a phantom containing 33 cylinders with different proportions of glycogen and iodine mixture at varying doses.

Clinical outcome is distinct between radiological stricture and endoscopic stricture in ileal Crohn's disease.

Objectives: Differences in clinical adverse outcomes (CAO) based on different intestinal stricturing definitions in Crohn's disease (CD) are poorly documented. This study aims to compare CAO between radiological strictures (RS) and endoscopic strictures (ES) in ileal CD and explore the significance of upstream dilatation in RS.

Methods: This retrospective double-center study included 199 patients (derivation cohort, n = 157; validation cohort, n = 42) with bowel strictures who simultaneously underwent endoscopic and radiologic examinations.

Evaluation of Hypoxia in Hepatocellular Carcinoma Using Quantitative MRI: Significances, Challenges, and Advances.

This review aimed to perform a scoping review of promising MRI methods in assessing tumor hypoxia in hepatocellular carcinoma (HCC). The hypoxic microenvironment and upregulated hypoxic metabolism in HCC are determining factors of poor prognosis, increased metastatic potential, and resistance to chemotherapy and radiotherapy. Assessing hypoxia in HCC is essential for personalized therapy and predicting prognoses.

Multi-frequency magnetic resonance elastography of the pancreas: measurement reproducibility and variance among healthy volunteers.

Background: Patients with chronic pancreatitis often have irreversible pancreatic insufficiency before a clinical diagnosis. Pancreatic cancer is a fatal malignant tumor in the advanced stages. Patients having high risk of pancreatic diseases must be screened early to obtain better outcomes using new imaging modalities.

Non-invasive diagnosis strategy of hepatocellular carcinoma in low-risk population.

Aims: With prevalence of hepatocellular carcinoma (HCC) in low-risk population (LRP), establishing a non-invasive diagnostic strategy becomes increasingly urgent to spare unnecessary biopsies in this population. The purposes of this study were to find characterisics of HCC and to establish a proper non-invasive method to diagnose HCC in LRP.

Methods: A total of 681 patients in LRP (defined as the population without cirrhosis, chronic HBV infection or HCC history) were collected from 2 institutions.

Tumor fibrosis correlates with the survival of patients with pancreatic adenocarcinoma and is predictable using clinicoradiological features.

Objectives: To evaluate the prognostic value of fibrosis for patients with pancreatic adenocarcinoma (PDAC) and preoperatively predict fibrosis using clinicoradiological features. Tumor fibrosis plays an important role in the chemoresistance of PDAC. However, the prognostic value of tumor fibrosis remains contradiction and accurate prediction of tumor fibrosis is required.

A Transfer Learning Radiomics Nomogram for Preoperative Prediction of Borrmann Type IV Gastric Cancer From Primary Gastric Lymphoma.

Objective: This study aims to differentiate preoperative Borrmann type IV gastric cancer (GC) from primary gastric lymphoma (PGL) by transfer learning radiomics nomogram (TLRN) with whole slide images of GC as source domain data.

Materials And Methods: This study retrospectively enrolled 438 patients with histopathologic diagnoses of Borrmann type IV GC and PGL. They received CT examinations from three hospitals.

Prediction of Early Treatment Response to Initial Conventional Transarterial Chemoembolization Therapy for Hepatocellular Carcinoma by Machine-Learning Model Based on Computed Tomography.

Purpose: The treatment response to initial conventional transarterial chemoembolization (cTACE) is essential for the prognosis of patients with hepatocellular carcinoma (HCC). This study explored and verified the feasibility of machine-learning models based on clinical data and contrast-enhanced computed tomography (CT) image findings to predict early responses of HCC patients after initial cTACE treatment.

Patients And Methods: Overall, 110 consecutive unresectable HCC patients who were treated with cTACE for the first time were retrospectively enrolled.

Preoperative Prediction of Cytokeratin 19 Expression for Hepatocellular Carcinoma with Deep Learning Radiomics Based on Gadoxetic Acid-Enhanced Magnetic Resonance Imaging.

Purpose: Cytokeratin 19 (CK19) expression is a proven independent prognostic predictor of hepatocellular carcinoma (HCC). This study aimed to develop and validate the performance of a deep learning radiomics (DLR) model for CK19 identification in HCC based on preoperative gadoxetic acid-enhanced magnetic resonance imaging (MRI).

Patients And Methods: A total of 141 surgically confirmed HCCs with preoperative gadoxetic acid-enhanced MRI from two institutions were included.

Predicting the recurrence risk of pancreatic neuroendocrine neoplasms after radical resection using deep learning radiomics with preoperative computed tomography images.

Background: To establish and validate a prediction model for pancreatic neuroendocrine neoplasms (pNENs) recurrence after radical surgery with preoperative computed tomography (CT) images.

Methods: We retrospectively collected data from 74 patients with pathologically confirmed pNENs (internal group: 56 patients, Hospital I; external validation group: 18 patients, Hospital II). Using the internal group, models were trained with CT findings evaluated by radiologists, radiomics, and deep learning radiomics (DLR) to predict 5-year pNEN recurrence.

Regional liver function analysis with gadoxetic acid-enhanced MRI and virtual hepatectomy: prediction of postoperative short-term outcomes for HCC.

Objectives: To explore the role of quantitative regional liver function assessed by preoperative gadoxetic acid-enhanced MRI with computer-aided virtual hepatectomy to predict short-term outcomes after major hepatectomy for HCC.

Methods: We retrospectively reviewed the records of 133 consecutive patients with HCC who underwent preoperative gadoxetic acid-enhanced MRI and indocyanine green (ICG) test. Forty-five patients received open major hepatectomy.

A Case of a Huge Inferior Vena Cava Leiomyosarcoma: Precise Preoperative Evaluation with Gadobutrol-Enhanced MRI.

Background: Leiomyosarcoma of the inferior vena cava (IVC) is a rare malignant tumour with poor prognosis. Surgical resection is the first line of treatment to achieve the best possible outcome. However, precise preoperative evaluation is essential to guide therapeutic decisions.

Hepatocellular carcinoma with hilar bile duct tumor thrombus versus hilar Cholangiocarcinoma on enhanced computed tomography: a diagnostic challenge.

Background: Hepatocellular carcinoma (HCC) with hilar bile duct tumor thrombus (HBDTT) often mimic hilar cholangiocarcinoma (hilar CC). The purpose of this study is to analyze the Computed Tomography (CT) characteristics of HCC with HBDTT and to identify imaging features to aid its differentiation from hilar CC on enhanced CT.

Methods: We retrospectively identified 58 cases with pathologically proved HCC with HBDTT between 2011 and 2018.

Imaging biomarkers for well and moderate hepatocellular carcinoma: preoperative magnetic resonance image and histopathological correlation.

Background: Our aim of the study is to investigate the feasibility of preoperative prediction for hepatocellular carcinoma (HCC) histological grading using gadoxetic acid-enhanced magnetic resonance imaging (MRI).

Methods: This study included one hundred and fifty-six patients with solitary HCC. Preoperative gadoxetic acid-enhanced MRI findings were retrospectively analyzed.