Dr. Manthan Mehta’s Post

Cardiology is changing, and for the better. Richard Chazal, MD, Medical Director of the Lee Health Heart Institute’s Center for Cardiovascular Quality, Technology & Innovation, describes how we are moving towards a new era that utilizes imaging, AI and personalized medicine to better assist physicians in diagnosing coronary artery disease. Watch the full video: https://lnkd.in/gRNGyPaT #YesCCT #Cardiology #AI

🧠 Yale researchers have unveiled a groundbreaking AI-based biomarker poised to transform how we detect and manage aortic stenosis, a condition affecting over 1.5 million Americans. 1️⃣🔸 Leveraging deep learning, the team developed the Digital AS Severity index (DASSi), capable of predicting progression to severe aortic stenosis by analyzing cardiac ultrasound videos. 🔍 2️⃣🔸With plans for a multi-randomized clinical trial, researchers aim to validate AI's role in diagnosing and predicting aortic stenosis, paving the way for personalized interventions and improved patient outcomes. 🌟 🔬 Dive deeper into this game-changing research in JAMA Cardiology, marking a pivotal moment in the intersection of AI and cardiovascular medicine. Let's see how this advanced redefine the fight against heart disease! 🫀 #AIHealthcare #CardiovascularInnovation

📢 Highly cited article! 🧠🩺 Explore the transformative role of Artificial Intelligence (AI) in detecting vulnerable carotid plaques—a key factor in preventing ischemic strokes. This comprehensive review covers: 1️⃣ Key concepts of AI in cardiovascular imaging. 2️⃣ How AI enhances ultrasound, CT, and MRI for plaque characterization. 3️⃣ Benefits and limitations of AI-based techniques in improving early detection and risk assessment. 🔑 Don't miss this essential read for advancing precision medicine in carotid atherosclerotic disease. Download now! 📄⬇️ https://lnkd.in/g8uJ5Ve7 #AIinHealthcare #CardiovascularImaging #StrokePrevention #CarotidPlaque #cardioMeded Luca Saba Rami Neemtallah francesca pitocco Laura Anna Leo Bobak Mosadegh Amr Idris, MD, FACC, FASNC Judith Bonnes Bilal Djemmal Dr. med. Verena Brandt Enrico Sfriso Landy Rodriguez Amaguay CardioVascular and Interventional Radiology (CVIR) Boston Scientific Cardiology

Stanford Health Care cardiologists are teaming with our Technology & Digital Solutions - Stanford Medicine group to integrate machine learning with chest computed tomography, or CT, scans to reimagine preventive cardiology. This ambitious project aims to detect arterial plaque, a significant indicator of heart disease, by using AI-supported algorithms to interpret existing medical imaging data — allowing patients the opportunity to start implementing preventive measures without needing invasive diagnostic procedures. https://bit.ly/3Kv3zea

🌟 𝗥𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝗶𝘇𝗶𝗻𝗴 𝗖𝗮𝗿𝗱𝗶𝗮𝗰 𝗛𝗲𝗮𝗹𝘁𝗵 𝗗𝗶𝗮𝗴𝗻𝗼𝘀𝘁𝗶𝗰𝘀 𝘄𝗶𝘁𝗵 𝗔𝗜: 𝗧𝗵𝗲 𝗦𝘁𝗼𝗿𝘆 𝗼𝗳 𝗖𝗮𝗿𝗶𝘀𝘁𝗼 𝗗𝗶𝗮𝗴𝗻𝗼𝘀𝘁𝗶𝗰𝘀 𝗮𝗻𝗱 𝗣𝗿𝗼𝗳𝗲𝘀𝘀𝗼𝗿 𝗞𝗲𝗶𝘁𝗵 𝗦𝗵𝗮𝗻𝗻𝗼𝗻 Professor Keith Channon is Co-founder and Chief Medical Officer at Caristo Diagnostics and Chair of Cardiovascular Medicine at the University of Oxford. I would llike to shed light on Caristo Diagnostics' AI-powered solution, a pioneering technology capable of detecting coronary inflammation in cardiac CT scans—a condition that traditional CT scans fail to identify. This innovation is particularly significant given that coronary inflammation is a major risk factor for heart attacks, which are not always preceded by visible coronary artery narrowing. Despite advancements in cardiac CT scans for detecting coronary artery disease, a significant gap remains in identifying patients at risk of heart attacks due to coronary inflammation. Professor Channon explains that while 80% of individuals undergoing cardiac CT scans for chest pain show no signs of coronary artery disease, studies reveal they die at twice the rate of those with positive scans, underscoring the hidden danger of coronary inflammation. Caristo's AI solution, highlighted at the American Heart Association conference, has been implemented in five NHS hospitals and has shown remarkable results in a study of 40,000 patients over ten years. The technology not only accurately reveals coronary inflammation but also predicts heart attacks years in advance, leading to adjusted treatment plans for 45% of the patients identified. The scientific journey behind this innovation is the initial discovery of how inflammation affects the fat tissue surrounding coronary arteries which led to the development of the Fat Attenuation Index (FAI) as a biomarker for inflammation. This journey underscores the role of AI in identifying new biomarkers and the transition from scientific discovery to a clinically applicable tool. Caristo Diagnostics has successfully commercialized this research through its product, Carry Hart, a cloud-based platform that provides a comprehensive analysis of coronary inflammation and plaque presence. This analysis includes a personalized risk score predicting the likelihood of a heart attack within the next eight years, offering a significant leap forward in personalized cardiac care. bit.ly/49EtnzK #ai #aritificialintelligence #aiinmedicine #innovation

The study emphasizes the potential of automated multiorgan CT in predicting diabetes and related cardiometabolic conditions. It highlights the importance of advanced imaging techniques for early detection and risk assessment. Key factors such as visceral fat, muscle area, liver fat fraction, and aortic calcification were found to be particularly effective in predicting diabetes and metabolic syndrome. The findings pave the way for using imaging technology in preventive healthcare and personalised medicine. There is no doubt that imaging will be a good source of information to strengthen the usage and accuracy in predictive models through AI. #medicalresearch #ctimaging #visceralfatindex #diabetesprediction

“Remote ECG access on a smart phone via the Viz.ai Cardio Suite, which enables access to dynamic ECG, echo, MRI, CT images and reports. It also enables automated detection on imaging to alert care teams for STEMI, hypertrophic cardiomyopathy, pulmonary embolism, aortic dissection and abdominal aortic aneurysm, and heart failure. Photo by Dave Fornell Cardiology continues to have the second largest number of clinical artificial intelligence (AI) algorithms cleared by the U.S. Food and Drug Administration, trailing only radiology. The FDA's latest update covers all AI approvals through May 2024. There are now 122 FDA-cleared AI algorithms specific to cardiology. This makes up 14% of the 882 clinical AI algorithms now on the U.S. market. “

Excited to share my final PhD project "Enhancing the diagnosis of functionally relevant coronary artery disease with #machinelearning" is now published in Nature Communications. In this collaboration between ETH Zürich and Universitätsspital Basel (USB), we show that 1. 🏥🤖 #DeepLearning (using stress test #ECG) and conventional ML models outperform cardiologists in predicting the presence of stress-induced functionally relevant coronary artery disease significantly. 2. 📉☢️ The use of ML could potentially reduce imaging procedures by 15–17% compared to the cardiologist’s judgement, leading to less #patients being unnecessarily exposed to radiation. 3. 🧮📈Combining #ClinicalJudgement with conventional ML and DL resulted in the highest predictive performance, showing the potential of #collaborativeML as a risk-stratification tool. Paper: https://lnkd.in/efvGHtEa Code: https://lnkd.in/eW_-3m8m Thanks to all coauthors and especially to Joan Walter, Bastian Rieck, Christian Müller, Karsten Borgwardt, and Nature Portfolio! #AIinHealthcare #MedicalDiagnostics #HealthTech #Cardiology #InnovationInMedicine #CAD #CoronaryArteryDisease AI in Healthcare

This is a major milestone in medical AI ! And I hope to see more of this in radiology !👇 A Taiwanese team achieved a major feat by conducting a randomized control trial, the gold standard in medical evaluation, to measure the impact of an AI-based ECG alarm on patient mortality – a rock-solid outcome ! The results speak for themselves: AI usage was associated with a remarkable 16% reduction in mortality 🤩 This is a major milestone for cardiology 🫀 While most AI evaluations in radiology focus on intermediate outcomes like diagnostic performance or report turnaround time, this cardiology study delves deeper, emphasizing the importance of assessing effects at patient-level and on hard outcomes such as mortality for widespread adoption of healthcare AI. It's easier to evaluate such effects for acute diseases, where outcomes manifest quickly, unlike diseases like cancer or neurodegenerative conditions. This study serves as a crucial reminder to prioritize bold, hard outcomes over intermediate ones in radiology research. Special thanks to Eric Topol, MD for highlighting this extraordinary study in his newsletter, and kudos to the dedicated research and clinical teams behind this groundbreaking work ! Find the study link in the comments below. #cardiology #AI #RCT #Radiology Illustration : Cardiologs website

Radiation exposure is a significant concern for those in interventional cardiology. The constant exposure to ionizing radiation puts both healthcare professionals and patients at risk, with potential long-term health issues like cancer and cataracts looming over them. But we strongly believe that AI is changing the game in that field. It can enhance diagnostic precision, enable early detection of heart diseases, and tailor treatment plans to individual patient needs. And by reducing the necessity for prolonged radiation exposure, AI ensures safer procedures for everyone involved. Think about a scenario where AI systems detect heart anomalies that traditional methods might miss. This early detection can lead to timely interventions, reducing the need for repeated, radiation-heavy imaging procedures. AI-driven technologies are continuously learning and improving, providing us with cutting-edge insights and techniques to better serve your patients. Embracing AI in cardiology is not just about adopting new technology; it's about committing to better patient care and reducing radiation risks. Systems like Omega's #SoteriaAI exemplify how AI can be seamlessly integrated into our practice, enhancing diagnostic accuracy while significantly lowering radiation exposure. Technology is advancing so why not adopt solutions that ensure safer, more efficient cardiac care? Learn more about SoteriaAI and other AI-driven solutions at omegamedicalimaging.com. #InterventionalCardiology #AngiographySystem #MedicalImaging