Personalized Prediction of Glioma Growth Using Bayesian Inference Introduction Glioblastoma is the most aggressive type of primary brain tumor, characterized by highly invasive tumor cells that spread to surrounding tissues. Conventional medical imaging techniques cannot precisely identify these diffuse tumor boundaries, leading to suboptimal clini...
Globally, the most common and deadly malignant brain tumor is glioblastoma (Glioblastoma, GBM). In recent years, research has continuously attempted to predict the overall survival time (OS) of GBM patients using machine learning techniques based on preoperative single-modality or multi-modality imaging phenotypes. Although these machine learning m...
Study of Mathematical Models for Tumor Growth – Exploring Glioma Extension Using Longitudinal Magnetic Resonance Imaging A recent article published in the IEEE Transactions on Biomedical Engineering presents a systematic study on the mathematical modeling and growth patterns of gliomas (glioma). This research was conducted by Birkan Tunç, David A. ...
Near-Infrared Window II Fluorescence Imaging-Guided Surgery Prolongs Progression-Free Survival for High-Grade Glioma Patients Research Background High-grade glioma (HGG) is the most common malignant primary tumor in the central nervous system, with glioblastoma (GBM) having the worst prognosis. To improve the treatment outcomes for GBM patients, in...
Clinical Validation Study on the Application of Cell-Free DNA Fragment Analysis in Enhancing Early Detection of Lung Cancer Background Lung cancer is one of the leading types of cancer threatening the health of both men and women globally. Over 125,000 people die from lung cancer in the United States each year, and globally, the number is close to ...
Cerebrospinal Fluid Proteomics Study for Diagnosis and Prediction of Alzheimer’s Disease Background and Research Objectives Alzheimer’s disease (AD) is a neurodegenerative disease that leads to memory loss and cognitive decline, and currently, there is no effective cure globally. Traditionally, the pathological features of AD include β-amyloid (Aβ)...
Functional Connectivity Across the Brain and Temporally Enhanced Non-neuronal Low-Frequency Oscillation (SLFO) Blood Flow Signal Based on Functional Magnetic Resonance Imaging Scans In the field of neuroscience, a core question is how the brain’s connectivity reconfigures over time to support adaptive functional changes. These dynamically changing ...
Breakthrough in Long-term Live Subcellular Imaging: Study of Confocal Scanning Light-Field Microscopy Research Background Long-term live cell dynamic observation is indispensable in studying physiological pathological processes such as immune response and brain function, requiring high spatiotemporal resolution and low phototoxicity. Existing confo...
Academic News Report on Multidimensional Cross-Frequency Coupling Analysis in EEG/MEG Data In recent years, with the advancement of neuroscience and medical imaging technology, researchers’ exploration of brain functional connectivity has become increasingly in-depth. This report will introduce a scientific research paper on multi-dimensional cross...
Scientific Report Background Introduction Perception and neuronal processing of sensory information are largely influenced by prior expectations. Perception is not merely passive reception, but an active inferential process by combining existing sensory information with prior information based on past experience and current context. The combination...