Cardiovascular diseases remain one of the leading causes of mortality and morbidity worldwide. They are responsible for almost 31 percent of all deaths. India is also struggling with rising number of cardiovascular diseases with the number of people dying from diseases going up every year. In 1990, the number of deaths was 2.26 million which increased to 4.77 million by 2020.
While cardiovascular diseases pose a challenge across the globe, yet, amidst these grim statistics, a glimmer of hope shines through the intersection of cutting-edge technology and medical expertise. Recent years have witnessed several advancements in the field of cardiac imaging, giving radiologists higher-quality images that enable quicker and more accurate interpretations.
Additionally, the growing use of three-dimensional (3D) visualisations, such as 3D-printed models, virtual reality (VR), and mixed reality (MR), have increased the diagnostic value of standard cardiac imaging tests, such as computed tomography (CT), magnetic resonance imaging (MRI), echocardiography, and nuclear medicine technologies, including positron emission tomography (PET) and PET-CT. Additionally, the extensive use of CT-derived fractional flow reserve (FFR-CT), artificial intelligence (AI), machine learning (ML), and deep learning (DL) has further expanded the applications of cardiac imaging modalities by providing more accurate or personalised medicine and providing both anatomical and physiological assessment of cardiovascular disease, primarily assisting in improving diagnostic assessment of coronary artery lesions.
Echocardiography
Echocardiography creates images of the heart using sound waves. Since the images are created in real time, we can view the current state of the heart. Doctors that need to diagnose heart problems will find this to be very helpful. Echocardiography aids physicians in the diagnosis of various cardiac conditions, including birth defects and abnormalities with the heart valves.
Echocardiography is used to monitor patients and track the health of their hearts over time. This helps in creating a personalised treatment strategy for each patient.
Computed Tomography (CT)
Coronary computed tomography angiography (CCTA) is a non-invasive 3D imaging test that identifies plaque and blockages or narrowing (stenosis) of the coronary arteries. The CCTA is a way to detect cardiac diseases in people who are at high risk like those with a family history
Calcium Scoring is performed using non-contrast CT which helps to quantify calcified plaque in your arteries. A Calcium Scoring of 0 that is great signalling your arteries are clear, while a score below 100 is generally considered less risk. A score more than 400 signals a high risk of cardiovascular disease.
Magnetic Resonance Imaging (MRI)
MRI employs magnetic fields and radio waves to reveal intricate images of the heart. It detects congenital abnormalities and arrhythmias and excels at identifying cardiac muscle damage, such as the scars left by heart attacks. By offering deep learning solutions for image capture, reconstruction, and analysis, artificial intelligence (AI) is further transforming the area of medical imaging, and specifically Cardiovascular Magnetic Resonance (CMR), ultimately helping clinical decision-making.
Nuclear imaging techniques use tracers to assess the risk of coronary artery disease and what happens following a heart attack. They also help us understand heart failure and cardiomyopathy.
Furthermore, integrating AI and ML into imaging workflows improves the accuracy and efficiency of diagnosis. Automated imaging data processing improves diagnosis consistency and cuts down on interpretation time, which is particularly helpful in high-volume clinical settings.
Future developments in cardiac imaging are expected to be fuelled by continuing research and advances in technology. The capabilities of cardiac imaging will continue to improve by the creation of ultra-high-resolution imaging devices, innovative contrast agents, and increasingly complex AI algorithms.