Automated Fast Prediction of Bone Mineral Density From Low-dose Computed Tomography.

Background: Low-dose chest CT (LDCT) is commonly employed for the early screening of lung cancer. However, it has rarely been utilized in the assessment of volumetric bone mineral density (vBMD) and the diagnosis of osteoporosis (OP).

Purpose: This study investigated the feasibility of using deep learning to establish a system for vBMD prediction and OP classification based on LDCT scans.

A novel hybrid deep learning framework based on biplanar X-ray radiography images for bone density prediction and classification.

Unlabelled: This study utilized deep learning for bone mineral density (BMD) prediction and classification using biplanar X-ray radiography (BPX) images from Huashan Hospital Medical Checkup Center. Results showed high accuracy and strong correlation with quantitative computed tomography (QCT) results. The proposed models offer potential for screening patients at a high risk of osteoporosis and reducing unnecessary radiation and costs.

Geriatric nutritional risk index has a prognostic value for recovery outcomes in elderly patients with brain abscess.

Background: The Geriatric Nutritional Risk Index (GNRI) is a straightforward and objective tool for nutritional screening in older patients and has been demonstrated to possess prognostic predictive value in several diseases. Nonetheless, there is a lack of research on the nutritional risk associated with brain abscess in the older. This study aimed to evaluate the prevalence of nutritional risk among these patients by GNRI and to investigate its potential prognostic value for clinical outcomes.

An automated hybrid approach via deep learning and radiomics focused on the midbrain and substantia nigra to detect early-stage Parkinson's disease.

Objectives: The altered neuromelanin in substantia nigra pars compacta (SNpc) is a valuable biomarker in the detection of early-stage Parkinson's disease (EPD). Diagnosis via visual inspection or single radiomics based method is challenging. Thus, we proposed a novel hybrid model that integrates radiomics and deep learning methodologies to automatically detect EPD based on neuromelanin-sensitive MRI, namely short-echo-time Magnitude (setMag) reconstructed from quantitative susceptibility mapping (QSM).

Altered whole-brain functional network in patients with frontal low-grade gliomas: a resting-state functional MRI study.

Purpose: Gliomas are the most common primary brain tumor. Currently, topological alterations of whole-brain functional network caused by gliomas are not fully understood. The work here clarified the topological reorganization of the functional network in patients with unilateral frontal low-grade gliomas (LGGs).

Combination of Conventional EVD and Ommaya Drainage for Intraventricular Hemorrhage (IVH).

Background: The effect of Ommaya reservoirs on the clinical outcomes of patients with intraventricular hemorrhage (IVH) remains unclear.

Objective: We aimed to determine the effect of combining the Ommaya reservoir and external ventricular drainage (EVD) therapy on IVH and explore better clinical indicators for Ommaya implantation.

Methods: A retrospective analysis was conducted on patients diagnosed with IVH who received EVD-Ommaya drainage between January 2013 and March 2021.

Quantitative collateral score for the prediction of clinical outcomes in stroke patients: Better than visual grading.

Objectives: To identify preoperative prognostic factors for acute ischemic stroke (AIS) patients receiving mechanical thrombectomy (MT) and compare the performance of quantitative collateral score (qCS) and visual collateral score (vCS) in outcome prediction.

Methods: Fifty-five patients with AIS receiving MT were retrospectively enrolled. qCS was defined as the percentage of the volume of collaterals of both hemispheres.

Agreement of three CT perfusion software packages in patients with acute ischemic stroke: A comparison with RAPID.

Purpose: To compare ischemic core volume (ICV) and penumbra volume (PV) measured by MIStar, F-STROKE, and Syngo.via with that measured by RAPID in acute ischemic stroke (AIS), and their concordance in selecting patients for endovascular thrombectomy (EVT).

Methods: Computed tomography perfusion (CTP) data were processed with four software packages.

Functionalized PEG-PLA nanoparticles for brain targeted delivery of ketoconazole contribute to pregnane X receptor overexpressing in drug-resistant epilepsy.

Objective: To develop a functionalized PEG-PLA nanoparticle system containing ketoconazole (KCZ) to overcome the overactivity of pregnane X receptor (PXR) for the treatment of drug-resistant epilepsy (DRE).

Significance: KCZ was developed as a therapy strategy for DRE limited by its lethal hepatotoxicity and minute brain concentration. KCZ-incorporated nanoparticles modified with angiopep-2 (NPs/KCZ) could reduce adverse effects of KCZ and achieve epileptic foci-targeted drug delivery.

Radiomics for the detection of microvascular invasion in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common primary liver cancer, accounting for about 90% of liver cancer cases. It is currently the fifth most common cancer in the world and the third leading cause of cancer-related mortality. Moreover, recurrence of HCC is common.

Neuroplasticity of Glioma Patients: Brain Structure and Topological Network.

Glioma is the most common primary malignant brain tumor in adults. It accounts for about 75% of such tumors and occurs more commonly in men. The incidence rate has been increasing in the past 30 years.

Salvianolic acid B decreases interleukin-1β-induced colitis recurrence in mice.

Background: Degree of mucosal recovery is an important indicator for evaluating the therapeutic effects of drugs in treatment of inflammatory bowel disease (IBD). Increasing evidences has proved that tight junction (TJ) barrier dysfunction is one of the pathological mechanisms of IBD. The aim of this study was to observe whether enhancement of TJ can decrease colitis recurrence.