Multiparametric MRI-Based Machine Learning Radiomics Prognostic Models for Multifocal Hepatocellular Carcinoma Beyond Milan Criteria: A Retrospective Study.

Purpose: To develop machine learning radiomics models for preoperative risk stratification of multifocal hepatocellular carcinoma (MHCC) beyond Milan criteria.

Methods: Patients with pathologically proven MHCC beyond Milan criteria between January 2015 and January 2019 were retrospectively included. Radiomic features were extracted from tumor, peritumor, and tumor-peritumor regions using multiparametric MRI (mpMRI).

Preoperative MRI and CA19-9 for predicting occult lymph node metastasis in small pancreatic ductal adenocarcinoma (≤ 2 cm).

Aim: Accurate prediction of occult lymph node metastasis (OLNM) in small pancreatic ductal adenocarcinoma (sPDAC) (≤ 2 cm) is crucial for curative management. This study aims to explore clinical and MRI features associated with OLNM in sPDAC and their pathological and prognostic implications.

Materials And Methods: This retrospective study included 135 patients with pathologically confirmed sPDAC who underwent surgery between September 2014 and September 2023.

Enhancing the intraoperative identification of high-grade patterns in invasive lung adenocarcinoma via radiomics.

Background: High-grade patterns (HGPs) are important for surgical decision-making in patients with invasive lung adenocarcinoma (IAC), but the sensitivity of intraoperative frozen section (FS) is not high. Radiomics has the potential to improve the sensitivity of intraoperative detection. The purpose of the present study was to evaluate the value of combining radiomics with FS analysis for predicting HGPs in patients with clinical T1 (cT1) IAC.

CT features predict tumour invasion of adrenal pheochromocytoma: a retrospective observational study.

Objective: To investigate the predictive value of the CT features of adrenal pheochromocytoma (PCC) for invasive behaviour.

Methods: From November 2009 to December 2021 at Zhongshan Hospital Affiliated with Fudan University, the clinical and CT data of 148 patients with 163 lesions confirmed by surgery and pathology were retrospectively analysed. The cases were divided into an invasive group and a noninvasive group on the basis of the surgical and pathological results; 27 lesions in 26 patients were classified into the invasive group, whereas 136 lesions in 122 patients were classified into the noninvasive group.

Performance of conventional MRI and endoscopy in assessing complete tumor response following immunotherapy-based neoadjuvant therapy for rectal cancer.

Purpose: Endoscopy and MRI are essential tools for assessing treatment response in locally advanced rectal cancer (LARC). However, their accuracy in identifying pathological complete response (pCR; ie, ypT0N0) following immunotherapy-based neoadjuvant chemoradiotherapy (iNCRT) remains uncertain. This study evaluates the performance of endoscopy and MRI in reflecting ypT0 status and assesses MRI efficacy for lymph node metastasis in LARC following iNCRT.

Diagnostic performances of adding transition and hepatobiliary phase to washout in gadoxetic acid-enhanced MRI for subcentimeter hepatocellular carcinoma.

Objective: To compare the diagnostic performances of washout (WO) criteria confined to portal venous phase (PVP), extended to transition phase (TP) or hepatobiliary phase (HBP) for subcentimeter hepatocellular carcinoma (HCC) using gadoxetic acid-enhanced MRI.

Materials And Methods: Two hundred patients (mean age, 53.4 ± 10.

Comparison of pilot tone-triggered and electrocardiogram-triggered cardiac magnetic resonance imaging: a prospective clinical feasibility study.

Background: Electrocardiogram (ECG)-triggered cardiovascular magnetic resonance (CMR) can be challenging in patients with ECG unreliability. Pilot tone (PT)-triggered CMR may offer a reliable alternative.

Purpose: To evaluate the feasibility of PT-triggered CMR and compare its performance with ECG-triggered imaging across various sequences in patients with common cardiovascular diseases.

Sagittal FOCUS-MUSE Diffusion-weighted Imaging MRI Improves the Accuracy of Rectal Cancer Location: A Prospective Observational Study.

Rationale And Objectives: Precise preoperative location on MRI is critical for rectal cancer management. This study aimed to evaluate whether integrating sagittal FOCUS-MUSE diffusion-weighted imaging (SDWI) sequence into MRI would improve the accuracy of the distance from tumor's inferior boundary to the anal verge (DTAV) measurements.

Methods: Consecutive 96 biopsy-confirmed rectal cancer patients underwent preoperative rigid rectoscopy (RRS), PET/CT, and rectal MRI (with/without SDWI) within one month.

MRI-based predictive model with obesity metabolic phenotype for postoperative survival in HBV-related hepatocellular carcinoma.

Purpose: Obesity metabolic phenotypes may influence survival outcomes in hepatocellular carcinoma (HCC) patients. This study aimed to develop an MRI-based model for postoperative survival prediction in HBV-related HCC patients, focusing on obesity metabolic phenotypes.

Methods: A retrospective cohort of 381 HBV-related HCC patients (312 males; mean age 55.

Impact of steatotic liver disease on hepatitis B-related hepatocellular carcinoma: MRI manifestation and prognostic potential.

Objectives: To investigate the impact of steatotic liver disease (SLD) on hepatitis B virus (HBV) related hepatocellular carcinoma (HCC) in clinical and MRI manifestations and prognostic potential.

Methods: Four hundred and forty-one HBV-related HCC patients were retrospectively enrolled (mean age 55.5 years ±10.

Multimodal Imaging of Mediastinal Epithelioid Hemangioendothelioma: Two Case Reports.

Introduction: Epithelioid Hemangioendothelioma (EHE) is a rare vascular neoplasm that typically occurs in the bone, soft tissue, liver, and lung but rarely in the mediastinum. Multimodal imaging of EHE is poorly understood, often leading to misdiagnosis as other mediastinal tumors.

Case Presentation: Two female cases with incidental mediastinal masses were retrospectively analysed, focusing on multimodal presentations.

Magnetic resonance imaging features of intrahepatic bile duct adenoma: a 10-year retrospective study.

Background: Intrahepatic bile duct adenoma (BDA) is a rare tumor with limited understanding of its magnetic resonance imaging (MRI) features and clinical characteristics. This study aimed to analyze the MRI characteristics of BDA.

Methods: This retrospective study analyzed MRI findings and clinical profiles of 33 patients diagnosed with bile duct adenomas (BDA) at Zhongshan Hospital Fudan University from January 2014 to January 2024.

Deep learning reconstruction combined with contrast-enhancement boost in dual-low dose CT pulmonary angiography: a two-center prospective trial.

Purpose: To investigate whether the deep learning reconstruction (DLR) combined with contrast-enhancement-boost (CE-boost) technique can improve the diagnostic quality of CT pulmonary angiography (CTPA) at low radiation and contrast doses, compared with routine CTPA using hybrid iterative reconstruction (HIR).

Materials And Methods: This prospective two-center study included 130 patients who underwent CTPA for suspected pulmonary embolism. Patients were randomly divided into two groups: the routine CTPA group, reconstructed using HIR; and the dual-low dose CTPA group, reconstructed using HIR and DLR, additionally combined with the CE-boost to generate HIR-boost and DLR-boost images.

Evaluation of free-breathing, non-ECG-triggered magnetic resonance T1 mapping derived from multitasking imaging at 3.0 T in patients with ischaemic and non-ischaemic cardiomyopathy.

Objective: To evaluate the image quality of the free-breathing, non-ECG-multitasking T1 mapping and to compare T1 values, lesion area, and ROC curve with those derived from the traditional MOLLI sequence in ischaemic and non-ischaemic cardiomyopathy.

Methods: In vitro, T1 values from CMR multitasking and MOLLI images were compared in 4 phantoms. In vivo studies included 108 patients (38 ischaemic cardiomyopathy, 70 non-ischaemic cardiomyopathy) and 31 healthy volunteers.

Deep learning empowered gadolinium-free contrast-enhanced abbreviated MRI for diagnosing hepatocellular carcinoma.

Background & Aims: By reducing some magnetic resonance imaging (MRI) sequences, abbreviated MRI (aMRI) has shown extensive promise for detecting hepatocellular carcinoma (HCC). We aim to develop deep learning (DL)-based gadolinium-free contrast-enhanced (CE) aMRI protocols (DL-aMRI) for detecting HCC.

Methods: In total, 1,769 patients (913 with HCC) were retrospectively included from three institutions for training, testing, and external validation.

Development and validation of a CT-based nomogram to preoperative prediction of pancreatic neuroendocrine tumors (pNETs) grade.

Background/purpose: It is challenging to determine the pancreatic neuroendocrine tumors (pNETs) malignancy grade noninvasively. We aim to establish a CT - based diagnostic nomogram to predict the tumor grade of pNETs.

Methods: The patients with pathologically confirmed pNETs were recruited in two centers between January 2009 and November 2020.

Development and validation of ADC-based nomogram model for predicting the prognostic factors in preoperative clinical early-stage cervical cancer patients.

Purpose: To investigate the feasibility of ADC-based nomogram models for predicting cervical cancer (CC) subtype, lymphovascular space invasion (LVSI) and lymph node metastases (LNM) status in preoperative clinical early-stage CC patients.

Materials And Methods: A total of 535 CC patients from three independent centers [center A (n = 251) for model training, and centers B (n = 193) and C (n = 91) for external validation] were included. Volumetric ADC histogram metrics (volume, minADC, meanADC, maxADC, skewness, kurtosis, entropy, P10_ADC, P25_ADC, P50_ADC, P75_ADC, and P90_ADC) derived the whole-tumor were calculated.

Quantitative assessment and risk stratification of random acute pulmonary embolism cases using a deep learning model based on computed tomography pulmonary angiography images.

Background: Computed tomography pulmonary angiography (CTPA) is the gold standard for the diagnosis of pulmonary embolism (PE). The semi-quantitative clot burden scoring based on imaging is related to the risk stratification and prognosis of acute PE, but it cannot be widely applied in the clinic due to the difficulty of calculation. This study developed a high-quality VB-Net deep learning (DL) model combined with Transformer, which can detect PE from images and automatically calculate the clot burden score (CBS).

Image quality, diagnostic performance of reduced-dose abdominal CT with artificial intelligence model-based iterative reconstruction for colorectal liver metastasis: a prospective cohort study.

Background: The optimization of regularization strategies in computed tomography (CT) iterative reconstruction may allow for a reduced dose (RD) without compromising image quality, thus the diagnostic ability of RD imaging must be considered, especially for low-contrast lesions. In this study, we evaluated the image quality and diagnostic performance of 50% RD CT for low-contrast colorectal liver metastasis (CRLM) with artificial intelligence model-based iterative reconstruction (AIIR) and standard-dose (SD) CT with hybrid iterative reconstruction (HIR).

Methods: In this prospective study, consecutive participants with pathologically proven colorectal cancer and suspected liver metastases who underwent portal venous phase CT scans both at SD and RD between June and November 2022 were included.

Contrast-enhanced MRI-based intratumoral heterogeneity assessment for predicting lymph node metastasis in resectable pancreatic ductal adenocarcinoma.

Objectives: To develop and validate a contrast-enhanced MRI-based intratumoral heterogeneity (ITH) model for predicting lymph node (LN) metastasis in resectable pancreatic ductal adenocarcinoma (PDAC).

Methods: Lesions were encoded into different habitats based on enhancement ratios at arterial, venous, and delayed phases of contrast-enhanced MRI. Habitat models on enhanced ratio mapping and single sequences, radiomic models, and clinical models were developed for evaluating LN metastasis.

Correlation of MRI characteristics with KRAS mutation status in pancreatic ductal adenocarcinoma.

Purpose: To investigate MRI features associated with KRAS mutation status in PDAC and their clinical implications.

Materials And Methods: In our study, 1474 patients pathologically confirmed PDAC patients between January 2016 and December 2023 were evaluated. Patients with genetic testing (KRAS mutation status) and MRI examination were enrolled and grouped as KRAS-mutated PDAC and non-KRAS-mutated PDAC.

Assessment of intrahepatic cholangiocarcinoma with LI-RADS in the high-risk population: MRI diagnosis and postoperative survival.

Background: The precise impact of LI-RADS-defined risk factors on the diagnosis and prognosis of intrahepatic cholangiocarcinoma (iCCA) remains unclear.

Objective: To assess the value of LI-RADS categories and features for iCCA diagnosis, focusing on the diagnostic and prognostic implications of LI-RADS-defined risk factors.

Methods: Totally 214 high risk patients, including 107 surgically-confirmed solitary iCCAs and 107 hepatocellular carcinomas (HCC) from two centers were retrospectively enrolled.