Leveraging AI for Second Opinions: Detecting Early Indicators of Cardiovascular Disease
Leveraging AI for Second Opinions: Detecting Early Indicators of Cardiovascular Disease
Leveraging AI for Second Opinions: Detecting Early Indicators of Cardiovascular Disease
The Potential of AI in Early Detection
The most common form of diagnostic "quality control" is a patient-initiated second opinion. In one study, 38% of patients sought a second opinion because they had doubts about the diagnosis or treatment, and 19% did so due to dissatisfaction with communication. Imagine if AI could assist in identifying chronic conditions before symptoms even appear. What if, when seeking a diagnosis for one ailment, AI could also highlight opportunistic findings related to other chronic conditions that the patient wasn’t aware of?
The Power of AI Insights
The enormous volume of digital data, or "big data," generated by an aging population and the increasing demand for imaging, provides significant opportunities for AI application in radiology. Radiology has become a leader in integrating AI into medical practice due to the screening and detection capabilities AI offers, especially in the early identification and intervention of chronic diseases.
Today, the medical field benefits from a vast collection of data, algorithms, and analytics. AI can rapidly analyze this data, identify patterns, and provide insights that are crucial for informed decision-making.
Contrary to the belief that machines operate without oversight, AI platforms used for medical purposes must meet strict precision standards to be certified. Additionally, all AI-generated insights must be approved by a qualified physician.
When to Trust AI
If you're skeptical about AI-generated second opinions, consider AI as another tool in the radiologist’s diagnostic toolbox. Think of it as a second pair of eyes, enhancing the radiologist’s ability to detect and measure findings, rather than replacing their judgment.
Some researchers suggest that when an AI-driven diagnosis contradicts a physician’s initial diagnosis, a second physician should be consulted to verify the findings. This approach allows patients to "trust but verify," relying on AI when it supports initial findings and seeking further confirmation when it conflicts.
Matters of the Heart
Let’s explore how AI can help prevent one of the deadliest forms of chronic diseases: cardiovascular disease (CVD). Nearly half of all U.S. adults have some form of CVD, making it difficult to find anyone untouched by this disease. The U.S. spends $225 billion annually on CVD, yet it remains the leading cause of death domestically and globally. CVD is often called a "silent killer" because many people are unaware they have it until they experience a major cardiac event, such as a stroke or heart attack. The healthcare system often reacts to these events rather than proactively preventing them.
Proactive efforts, such as obtaining a coronary artery calcium (CAC) scoring CT scan, can help assess the risk of future cardiovascular events. CAC scores are the most reliable predictor of a patient's risk for cardiovascular events. However, radiologists typically do not evaluate CAC levels on standard chest CT scans unless specifically requested.
Taking AI to Heart
New AI solutions can now assess CAC levels and provide radiologists and cardiologists with the data needed to detect heart disease, such as coronary artery disease (CAD), before it’s too late. AI algorithms have significantly enhanced personalized healthcare by detecting and forecasting disorders through deep learning and machine learning.
In an ideal scenario, radiologists would proactively measure CAC levels during routine chest CT scans, ensuring comprehensive reports that include critical information about coronary artery calcium. By incorporating these findings into the report, with recommendations for further clinical action, radiologists empower physicians to make informed decisions about patient care, increasing the likelihood of follow-up and improved outcomes.
However, we are not there yet. Radiologists focus on the clinical indications, and while they strive to provide complete reports, chronic findings are often overlooked. This is where AI can support radiologists by offering data-driven insights and predictive analytics, enabling more informed decisions.
Harnessing the Power of AI: From Reactive to Proactive
Vitamu AI’s cardiac solution is an AI software designed to evaluate calcified plaques in the coronary arteries on non-ECG gated chest CT scans, which may indicate the risk of coronary artery disease. By leveraging routine CT scans, Vitamu AI integrates seamlessly into a radiologist’s workflow, providing clear visual identifications of CAC levels. This proactive use of AI maximizes existing imaging data to assess the risk of coronary artery disease, potentially prompting clinicians to take steps to reduce the risk of heart attacks or strokes.
The software can identify patients with signs of coronary artery disease, promoting appropriate risk assessment, preventative care, and follow-up treatment, shifting CVD care from reactive to proactive.
AI in Action: A Real-Life Example
Consider a potential patient case from a U.S. institution. A patient arrived at the Emergency Room with chest and back pain. The ER physician ordered blood tests, an EKG, and a CT scan. The CT scan was reported as 'normal,' apart from a vertebral compression fracture that could explain the back pain. However, the patient’s CAC, visible on the CT scan, went unnoticed. Fortunately, the Vitamu AI technology, which measures coronary artery calcium on non-contrast chest CTs, flagged the high CAC levels. The cardiology team was alerted, and the patient was started on appropriate medication, followed by a complete cardiac workup that led to coronary artery stenting.
This case highlights the often "silent" reality of CVD. With AI, CAC levels could be detected before symptoms manifest, enabling earlier intervention.
The Power of Data-Backed Trust in Cardiac Insights: Vitamu AI Proven Results
Vitamu AI’s cardiac software was retrospectively tested on 549 cases in a clinical setting at a Michigan hospital. The results were reviewed by the lead cardiologists, who compared the AI findings with human assessments. In 49% of cases, Vitamu AI classified CAC as moderate or severe. Physicians agreed with the AI findings in 83% of moderate cases and 92% of severe cases, with an overall agreement rate of 89%.
Most importantly, when Vitamu AI detected moderate or severe CAC, approximately 65% of those cases had no prior diagnosis of CAD. In one year, 3,710 patients with medium or high CAC levels were identified without a previous diagnosis, demonstrating the life-saving potential of AI.
Conclusion: Be Proactive with AI
An ounce of prevention is worth a pound of cure. Take the AI leap and get a second opinion on your chest CT scan with Vitamu AI. Identify and measure coronary artery calcium to assess your cardiovascular risk and potentially prevent future illness.
The Potential of AI in Early Detection
The most common form of diagnostic "quality control" is a patient-initiated second opinion. In one study, 38% of patients sought a second opinion because they had doubts about the diagnosis or treatment, and 19% did so due to dissatisfaction with communication. Imagine if AI could assist in identifying chronic conditions before symptoms even appear. What if, when seeking a diagnosis for one ailment, AI could also highlight opportunistic findings related to other chronic conditions that the patient wasn’t aware of?
The Power of AI Insights
The enormous volume of digital data, or "big data," generated by an aging population and the increasing demand for imaging, provides significant opportunities for AI application in radiology. Radiology has become a leader in integrating AI into medical practice due to the screening and detection capabilities AI offers, especially in the early identification and intervention of chronic diseases.
Today, the medical field benefits from a vast collection of data, algorithms, and analytics. AI can rapidly analyze this data, identify patterns, and provide insights that are crucial for informed decision-making.
Contrary to the belief that machines operate without oversight, AI platforms used for medical purposes must meet strict precision standards to be certified. Additionally, all AI-generated insights must be approved by a qualified physician.
When to Trust AI
If you're skeptical about AI-generated second opinions, consider AI as another tool in the radiologist’s diagnostic toolbox. Think of it as a second pair of eyes, enhancing the radiologist’s ability to detect and measure findings, rather than replacing their judgment.
Some researchers suggest that when an AI-driven diagnosis contradicts a physician’s initial diagnosis, a second physician should be consulted to verify the findings. This approach allows patients to "trust but verify," relying on AI when it supports initial findings and seeking further confirmation when it conflicts.
Matters of the Heart
Let’s explore how AI can help prevent one of the deadliest forms of chronic diseases: cardiovascular disease (CVD). Nearly half of all U.S. adults have some form of CVD, making it difficult to find anyone untouched by this disease. The U.S. spends $225 billion annually on CVD, yet it remains the leading cause of death domestically and globally. CVD is often called a "silent killer" because many people are unaware they have it until they experience a major cardiac event, such as a stroke or heart attack. The healthcare system often reacts to these events rather than proactively preventing them.
Proactive efforts, such as obtaining a coronary artery calcium (CAC) scoring CT scan, can help assess the risk of future cardiovascular events. CAC scores are the most reliable predictor of a patient's risk for cardiovascular events. However, radiologists typically do not evaluate CAC levels on standard chest CT scans unless specifically requested.
Taking AI to Heart
New AI solutions can now assess CAC levels and provide radiologists and cardiologists with the data needed to detect heart disease, such as coronary artery disease (CAD), before it’s too late. AI algorithms have significantly enhanced personalized healthcare by detecting and forecasting disorders through deep learning and machine learning.
In an ideal scenario, radiologists would proactively measure CAC levels during routine chest CT scans, ensuring comprehensive reports that include critical information about coronary artery calcium. By incorporating these findings into the report, with recommendations for further clinical action, radiologists empower physicians to make informed decisions about patient care, increasing the likelihood of follow-up and improved outcomes.
However, we are not there yet. Radiologists focus on the clinical indications, and while they strive to provide complete reports, chronic findings are often overlooked. This is where AI can support radiologists by offering data-driven insights and predictive analytics, enabling more informed decisions.
Harnessing the Power of AI: From Reactive to Proactive
Vitamu AI’s cardiac solution is an AI software designed to evaluate calcified plaques in the coronary arteries on non-ECG gated chest CT scans, which may indicate the risk of coronary artery disease. By leveraging routine CT scans, Vitamu AI integrates seamlessly into a radiologist’s workflow, providing clear visual identifications of CAC levels. This proactive use of AI maximizes existing imaging data to assess the risk of coronary artery disease, potentially prompting clinicians to take steps to reduce the risk of heart attacks or strokes.
The software can identify patients with signs of coronary artery disease, promoting appropriate risk assessment, preventative care, and follow-up treatment, shifting CVD care from reactive to proactive.
AI in Action: A Real-Life Example
Consider a potential patient case from a U.S. institution. A patient arrived at the Emergency Room with chest and back pain. The ER physician ordered blood tests, an EKG, and a CT scan. The CT scan was reported as 'normal,' apart from a vertebral compression fracture that could explain the back pain. However, the patient’s CAC, visible on the CT scan, went unnoticed. Fortunately, the Vitamu AI technology, which measures coronary artery calcium on non-contrast chest CTs, flagged the high CAC levels. The cardiology team was alerted, and the patient was started on appropriate medication, followed by a complete cardiac workup that led to coronary artery stenting.
This case highlights the often "silent" reality of CVD. With AI, CAC levels could be detected before symptoms manifest, enabling earlier intervention.
The Power of Data-Backed Trust in Cardiac Insights: Vitamu AI Proven Results
Vitamu AI’s cardiac software was retrospectively tested on 549 cases in a clinical setting at a Michigan hospital. The results were reviewed by the lead cardiologists, who compared the AI findings with human assessments. In 49% of cases, Vitamu AI classified CAC as moderate or severe. Physicians agreed with the AI findings in 83% of moderate cases and 92% of severe cases, with an overall agreement rate of 89%.
Most importantly, when Vitamu AI detected moderate or severe CAC, approximately 65% of those cases had no prior diagnosis of CAD. In one year, 3,710 patients with medium or high CAC levels were identified without a previous diagnosis, demonstrating the life-saving potential of AI.
Conclusion: Be Proactive with AI
An ounce of prevention is worth a pound of cure. Take the AI leap and get a second opinion on your chest CT scan with Vitamu AI. Identify and measure coronary artery calcium to assess your cardiovascular risk and potentially prevent future illness.