Turning the Operating Room into a Mixed-Reality Environment: A Prospective Clinical Investigation for Cerebral Aneurysm Clipping

Turning the Operating Room into a Mixed-Reality Environment: A Prospective Clinical Investigation for Cerebral Aneurysm Clipping

Transforming the Operating Room into a Mixed Reality Environment: A Prospective Clinical Study on Aneurysm Clipping The surgical treatment of cerebral aneurysms is a highly complex and delicate process in neurosurgery. Researchers continue to explore new technologies and methods to improve surgical outcomes. In recent years, the development of Mixe...

A Novel Stratification Scheme Combined with Internal Arteries in CT Imaging for Guiding Postoperative Adjuvant Transarterial Chemoembolization in Hepatocellular Carcinoma: A Retrospective Cohort Study

Retrospective Cohort Study on Innovative Stratification Scheme Based on Postoperative Combined CT Imaging to Guide Postoperative Adjuvant Transarterial Chemoembolization for Hepatocellular Carcinoma Background Hepatocellular carcinoma (HCC) is the sixth most common cancer globally and the fourth leading cause of cancer-related deaths. For HCC, live...

Distribution of Coronal Plane Alignment of the Knee Classification in Chinese Osteoarthritic and Healthy Population: A Retrospective Cross-sectional Observational Study

A Retrospective Cross-Sectional Observational Study on the Distribution of Coronal Plane Alignment Classifications in Chinese Osteoarthritic and Healthy Populations Research Background Neutral mechanical alignment (MA) of the knee is considered the cornerstone of successful and durable total knee arthroplasty (TKA). However, the existence of “const...

Artificial Intelligence-Based Classification of Breast Lesion from Contrast Enhanced Mammography: A Multicenter Study

Multi-center Study on Artificial Intelligence-based Classification of Breast Lesions In the field of breast cancer, early diagnosis is crucial for improving treatment efficacy and survival rate. Breast cancer can be mainly divided into two categories: in situ carcinoma and invasive carcinoma, which have significant differences in treatment strategi...

Radiomics-based Prediction of Local Control in Patients with Brain Metastases Following Postoperative Stereotactic Radiotherapy

Application of Radiomics in Predicting Local Control in Postoperative Stereotactic Radiotherapy for Brain Metastasis Patients Academic Background Brain Metastases (BMs) are the most common malignant brain tumors, far surpassing primary brain tumors like gliomas in incidence. Recent medical guidelines recommend surgical treatment for patients with s...

Leptomeningeal Metastases in IDH-Wildtype Glioblastomas Revisited: Comprehensive Analysis of Incidence, Risk Factors, and Prognosis Based on Post-Contrast FLAIR

Comprehensive Analysis of Leptomeningeal Metastasis in IDH Wild-Type Glioblastoma In this article published in the journal “Neuro-Oncology,” the research team starting in 2024 delves into the incidence, risk factors, and prognosis of leptomeningeal metastases (LM) in patients with isocitrate dehydrogenase (IDH) wild-type glioblastoma. This study wa...

Raman-Based Machine Learning Platform Reveals Unique Metabolic Differences Between IDHmut and IDHwt Glioma

Study on Metabolic Differences between IDH Mutant and Wild-type Glioma Cells Using Raman Spectroscopy and Machine Learning Platform Background Introduction In the diagnosis and treatment of gliomas, formalin-fixed, paraffin-embedded (FFPE) tissue sections are commonly used. However, due to background noise interference from the embedding medium, th...

Diffusion-based Deep Learning Method for Augmenting Ultrastructural Imaging and Volume Electron Microscopy

Diffusion-based Deep Learning Method for Augmenting Ultrastructural Imaging and Volume Electron Microscopy

Enhancing Super-Resolution Imaging and Volume Electron Microscopy with Deep Learning Algorithms Based on Diffusion Models Background Introduction Electron Microscopy (EM) as a high-resolution imaging tool has made significant breakthroughs in cell biology. Traditional EM techniques are primarily used for two-dimensional imaging, and although they h...

Injectable Ultrasonic Sensor for Wireless Monitoring of Intracranial Signals

Injectable Ultrasonic Sensor for Wireless Monitoring of Intracranial Signals

Wireless Injectable Ultrasound Sensor for Intracranial Signal Monitoring Background Introduction Direct and accurate monitoring of intracranial physiological conditions is extremely important for injury classification, prognosis assessment, and disease prevention. However, traditional wired clinical devices, such as percutaneous leads, although per...

A Novel CNN-Based Image Segmentation Pipeline for Individualized Feline Spinal Cord Stimulation Modeling

Automated Spinal Cord Segmentation Pipeline Based on Convolutional Neural Network (CNN) for Individualized Cat Spinal Cord Stimulation Modeling Background and Research Motivation Spinal cord stimulation (SCS) is a widely used treatment method for chronic pain management. In recent years, it has also been used to modulate neural activity, aiming to ...