Meet Dr. Kan Liu, MD, Cardiology Researcher | WashU Department of Medicine posted on the topic | LinkedIn (2024)

Breaking New Ground: Microscopic Heart Vessels Imaged in Super-Resolution for the First TimeRecent research from Imperial College London has captured microscopic heart vessels in super-resolution imaging, offering unprecedented clarity. This achievement marks a milestone in cardiovascular research, providing insights that could significantly improve our understanding of heart diseases.Key Findings:Advanced Imaging Technology: The research utilized pioneering super-resolution imaging technology, capable of visualizing intricate details of heart microvasculature previously unobserved.Impact on Research: This clarity could accelerate the development of new treatments, allowing scientists to identify abnormalities and disease progression more precisely.Potential Applications: It opens doors to future studies on vascular disorders and enhances early diagnosis capabilities by revealing the earliest stages of cardiovascular disease.Implications:This breakthrough in imaging technology enables researchers to explore new dimensions of heart health. The clearer understanding of vascular conditions could influence both treatment and preventive strategies. With continued advancements, personalized medicine for cardiovascular diseases is within reach.This post was written with the help of ChatGPT.#CardiovascularResearch #MedicalImaging #SuperResolution #HealthcareInnovation #ScientificBreakthrough

3

Coronary Imaging and Physiology

Coronary Imaging and Physiology

We are delighted to share some recent publications by our teams at RPN:1) Deep brain stimulation in Parkinson's disease: A scientometric and bibliometric analysis, trends, and research hotspots.https://lnkd.in/gHsGSkWjTirth Dave, Shankhaneel Ghosh, Rahul Jena, Vivek Sanker2) Exploring the Role of Orexin-A Neuropeptide in Parkinson's Disease: A Systematic Review and Meta-Analysishttps://lnkd.in/gzZizcKR@Yash Chandani, Shankhaneel Ghosh, Aravind Gandhi P, Muhammad Aaqib Shamim3) Zavegepant for Acute Treatment of Migraine: A Systematic Review and Meta-analysis of Randomized Controlled Trialshttps://lnkd.in/gVhCCCVaMainak Bardhan, Tirth Dave, Aman Bhonsale, Muhammad Aaqib Shamim, @dilip suresh, Poorvikha Gowda, Bishal Dhakal

14

Revolutionizing Early Detection: Researchers from UCL and Moorfields Eye Hospital have identified markers that can detect Parkinson's disease in patients an average of seven years before clinical symptoms appear.AI-Powered Insights: This groundbreaking discovery was made possible through the use of artificial intelligence (AI) to analyze eye scans, revealing subtle markers of Parkinson's disease.Retinal Imaging for Parkinson's Diagnosis: The study identified thinner retinal layers associated with an increased risk of Parkinson's disease. Further studies are needed to explore the mechanism and diagnostic potential of retinal imaging for Parkinson's.Scalability: Optical coherence tomography (OCT) scans, used in this research, are scalable, non-invasive, cost-effective, and quicker than traditional brain scans, making them a promising tool for predictive analysis.Multiple Health Conditions: Eye scans have previously unveiled signs of other neurodegenerative conditions, cardiovascular issues, and diabetes, making them a valuable tool for early diagnosis.Study Published in Neurology®: [DOI: https://lnkd.in/eQnAkzg3]Image source-euronews.net#Retina #aiapplications #parkinsonsdisease #biomedicalengineering #interdisciplinary #ophthalmology

1

💡 At last, some outstanding news! Our new paper entitled "Exploring the disruptions of the neurophysiological organization in Alzheimer’s disease: An integrative approach" has been recently published (albeit it's actual publication date is June 2024) in Computer Methods and Programs in Biomedicine!🎖 Highlights:• Neurophysiological disruptions are assessed by the relationships of M/EEG features.• Association networks are able to represent this neurophysiological organization.• Graph properties derived from association networks showed alterations in AD.• Local activation metrics play a critical role in maintaining network stability.• High degree of replication has been obtained using both M/EEG signals.Check this out by just clicking in here: https://lnkd.in/dJNJHbmy#Alzheimersdisease #Magnetoencephalography #Electroencephalography #Neurophysiologicalorganization #Associationnetworks#Networkanalysis

23

4 Comments

For the Neurophysiology: Exploring Basic Research & Clinical Consequences webinar series this fall, don't miss Drs. Esra Neufeld (@sparc.science) & Max Haberbusch exploring closed-loop #cardiacrhythm control restoration in #hearttransplant patients from model development to #insilico regulatory evidence for safety & efficacy trials. Wednesday, Oct.18th, 8AM PT, 11AM ET, 5PM CET #VNS #cardiotwitter #computationalmodeling https://bit.ly/3sfA2iVThe webinar will discuss: 1. Hybrid electromagnetic (EM-)electrophysiological modeling of neural interfaces, including model-based stimulation selectivity optimization and neural sensing information content maximization; 2. A comprehensive model of cardiovascular regulation and its experimental validation; and 3. Integration of these independently developed neural interface and cardiovascular regulation models, along with a generic closed-loop control framework.It will end with a view on the ongoing research on model-based intelligent control and in silico regulatory evidence and trials for safety and efficacy assessment.The American Physiological Society (APS), Society for Neuroscience (SfN), Federation of European Neuroscience Societies - FENS, AMERICAN AUTONOMIC SOCIETY (AAS), and InsideScientific | A Scientist.com Company are pleased to announce this joint webinar series covering late-breaking research, novel discovery, fundamental principles, and research innovation in the field of neuroscience and related disease models. Join us on October 18 to hear about research hosted on the SPARC Portal.

8

1 Comment

📃Scientific paper: Sensitive and reproducible MEG resting-state metrics of functional connectivity in Alzheimer’s diseaseAbstract:Background Analysis of functional brain networks in Alzheimer’s disease (AD) has been hampered by a lack of reproducible, yet valid metrics of functional connectivity (FC).This study aimed to assess both the sensitivity and reproducibility of the corrected amplitude envelope correlation (AEC-c) and phase lag index (PLI), two metrics of FC that are insensitive to the effects of volume conduction and field spread, in two separate cohorts of patients with dementia due to AD versus healthy elderly controls.Methods Subjects with a clinical diagnosis of AD dementia with biomarker proof, and a control group of subjective cognitive decline (SCD), underwent two 5-min resting-state MEG recordings.Data consisted of a test (AD = 28; SCD = 29) and validation (AD = 29; SCD = 27) cohort.Time-series were estimated for 90 regions of interest (ROIs) in the automated anatomical labelling (AAL) atlas.For each of five canonical frequency bands, the AEC-c and PLI were calculated between all 90 ROIs, and connections were averaged per ROI.General linear models were constructed to compare the global FC differences between the groups, assess the reproducibility, and evaluate the effects of age and relative power.Reproducibility of the regional FC differences was assessed using the Mann-Whitney U tests, with correction for multiple testing using the false discovery rate (FDR).Results The AEC-c showed significantly and reproducibly lower global FC for the AD group compared to SCD, in t... Discover the rest of the scientific article on es/iode ➡️https://etcse.fr/fvKU #alzheimer #science #health

💡 A revolutionary #MRI technique has been introduced: a #noninvasive method to gauge varied molecular iron scenarios in the brain. This novel quantitative MRI aims for a more precision-based approach. Iron balance or homeostasis in the brain is essential for holistic health. Any deviations in these levels can indicate a slew of conditions, including cancer and neurodegenerative diseases. In fact, unlike traditional MRI, which primarily produces images for visual evaluation, #quantitativeMRI focuses on obtaining numerical data that can be used for objective analysis and comparisons. In quantitative MRI, specific imaging sequences and techniques are used to measure parameters such as tissue density, water content, relaxation times, diffusion rates, and more. Talking about MRI and precision medicine, I can't help but add that #machinelearning can be used in several ways to enhance the quantitative analysis of MRI data, including quantitative MRI. Some examples are as follows: ✅ Automatically segment MRI images, separating different tissues and regions of interest.✅ Classify different tissues based on their MRI signal characteristics.✅ Extract a wide range of quantitative features, such as texture, shape, and intensity features.✅ Assist in diagnosing diseases.✅ Assist in tailoring treatment plans to individual patients. How do you envision the future of MRI techniques, especially with the integration of machine learning? #ML #MRItechnology #neuroimaging

15

5 Comments

🫀💡Utilizing AI for advanced predictive cardiac care! Collaboration between researchers and physicians from Cedars-Sinai Medical Center, University of California, Stanford University, and the Veterans Affairs health networks in California to explore applying deep learning to electrocardiograms (ECGs) toward early detection of atrial fibrillation (AFib). “This research allows for better identification of a hidden heart condition and informs the best way to develop algorithms that are equitable and generalizable to all patients.” - Dr. David Ouyang, MD, Senior Author & Cardiologist at the Smidt Heart Institute at Cedars-Sinai Full Article in JAMA Cardiology - https://lnkd.in/e88ds-KU #afib#aihealthcare#medicalinnovation#cardiology#deeplearningThe Mullings Group Cardiovascular Business

7

1 Comment