Machine learning model for preoperative classification of stromal subtypes in salivary gland pleomorphic adenoma based on ultrasound histogram analysis.

Objectives: Accurate preoperative discrimination of salivary gland pleomorphic adenoma (SPA) stromal subtypes is essential for therapeutic plannings. We aimed to establish and test machine learning (ML) models for classification of stromal subtypes in SPA based on ultrasound histogram analysis.

Methods: A total of 256 SPA patients were enrolled in the study and categorized into two groups: stroma-low and stroma-high.

Contrast-enhanced ultrasound (CEUS) and shear wave elastography (SWE) features for characterizing serous microcystic adenomas (SMAs): In comparison to pancreatic neuroendocrine tumors (pNETs).

Objectives: Serous microcystic adenoma (SMA), a primary benign pancreatic tumor which can be clinically followed-up instead of undergoing surgery, are sometimes mis-distinguished as pancreatic neuroendocrine tumor (pNET) in regular preoperative imaging examinations. This study aimed to analyze preoperative contrast-enhanced ultrasound (CEUS) and shear wave elastography (SWE) features of SMAs in comparison to pNETs.

Material And Methods: In this retrospective study, patients with imaging-diagnosed pancreatic lesions were screened between October 2020 to October 2022 (ethical approval No.

A multi-parameter intrahepatic cholangiocarcinoma scoring system based on modified contrast-enhanced ultrasound LI-RADS M criteria for differentiating intrahepatic cholangiocarcinoma from hepatocellular carcinoma.

Purpose: To develop a multi-parameter intrahepatic cholangiocarcinoma (ICC) scoring system and compare its diagnostic performance with contrast-enhanced ultrasound (CEUS) liver imaging reporting and data system M (LR-M) criteria for differentiating ICC from hepatocellular carcinoma (HCC).

Methods: This retrospective study enrolled 62 high-risk patients with ICCs and 62 high-risk patients with matched HCCs between January 2022 and December 2022 from two institutions. The CEUS LR-M criteria was modified by adjusting the early wash-out onset (within 45 s) and the marked wash-out (within 3 min).

Differential diagnosis between pancreatic solid pseudopapillary tumors and pancreatic neuroendocrine tumors based on contrast enhanced ultrasound imaging features.

Purposes: To evaluate the application of contrast enhanced ultrasound (CEUS) in preoperatively differential diagnosis between pancreatic solid pseudopapillary tumors (SPTs) and pancreatic neuroendocrine tumors (pNETs).

Patients And Methods: This retrospective study was approved by Institutional Review Board. Patients with surgical resection and histopathological diagnosis as SPTs and pNETs were included.

Pancreatic neuroendocrine tumor: prediction of tumor grades by radiomics models based on ultrasound images.

Objective: We aimed to investigate whether the radiomics analysis based on B-mode ultrasound (BMUS) images could predict histopathological tumor grades in pancreatic neuroendocrine tumors (pNETs).

Methods: A total of 64 patients with surgery and histopathologically confirmed pNETs were retrospectively included (34 male and 30 female, mean age 52.4 ± 12.

Clinical Application of High-Frame-Rate Vector Flow Imaging in Evaluation of Carotid Atherosclerotic Stenosis.

Objective: This study seeks to evaluate the value of the high-frame-rate vector flow imaging technique in assessing the hemodynamic changes of carotid atherosclerotic stenosis in aging people (>60 years old).

Methods: Aging patients diagnosed with carotid atherosclerotic stenosis who underwent carotid high-frame-rate vector flow imaging examination were prospectively enrolled. A Mindray Resona7s ultrasound machine equipped with high-frame-rate vector flow function was used for ultrasound evaluation.

Prediction of Pathological Grades of Pancreatic Neuroendocrine Tumors Based on Dynamic Contrast-Enhanced Ultrasound Quantitative Analysis.

Objective: To investigate whether the dynamic contrast-enhanced ultrasound (DCE-US) analysis and quantitative parameters could be helpful for predicting histopathologic grades of pancreatic neuroendocrine tumors (pNETs). Methods: This retrospective study conducted a comprehensive review of the CEUS database between March 2017 and November 2021 in Zhongshan Hospital, Fudan University. Ultrasound examinations were performed by an ACUSON Sequioa unit equipped with a 3.