Artificial Intelligence

Artificial intelligence (AI) is becoming a crucial component of healthcare to help augment physicians and make them more efficient. In medical imaging, it is helping radiologists more efficiently manage PACS worklists, enable structured reporting, auto detect injuries and diseases, and to pull in relevant prior exams and patient data. In cardiology, AI is helping automate tasks and measurements on imaging and in reporting systems, guides novice echo users to improve imaging and accuracy, and can risk stratify patients. AI includes deep learning algorithms, machine learning, computer-aided detection (CAD) systems, and convolutional neural networks. 

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Ultrafast MRI protocol reduces scan time by 10 minutes for cervical imaging

Experts involved in the study suggested that the protocol could open doors leading to greater utilization of MRI in the future. 

Impella Heart Pump Abiomed RECOVER IV RCT cardiogenic shock

Regulatory Roundup: FDA clears AI model for RV/LV ratios, approves calcium-blocking TAVR valve and much more

Read our review of some of the biggest FDA-related stories that have hit cardiology in the last month, including news from Viz.ai, Edwards Lifesciences, Abiomed and Medtronic. 

Self-supervised AI ‘reads’ radiology reports to speed algorithm development

A machine learning system has come along that needs no human labeling of data for training yet matches radiologists at classifying diseases on chest X-rays—including some that the model was not specifically taught to detect.

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Might AI automation improve peer review?

With the software’s help, the ratio of CTs requiring radiologist review to missed findings identified was 10:1, experts shared, adding that without the help of AI that ratio would be at least 66:1. 

A study published this week in the Journal of the American College of Cardiology (JACC): Cardiovascular Imaging shows artificial intelligence (AI) algorithms can more rapidly and objectively determine calcium scores in computed tomographic (CT) and positron emission tomographic (PET) images than physicians.[1] The AI also performed well when the images were obtained from very-low-radiation CT attenuation scans. https://doi.org/10.1016/j.jcmg.2022.06.006

Artificial intelligence can objectively determine cardiac calcium scores faster than doctors

A new study shows artificial intelligence (AI) algorithms can more rapidly and objectively determine calcium scores in CT and PET/CT images than physicians.

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Deep learning reconstruction levels playing field between 1.5T and 3T MRI exams

Denoising using deep learning techniques can boost the performance of 1.5T MR brain imaging, resulting in quality comparable or superior to 3T imaging. 

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AI identifies pancreatic cancer frequently missed on CT

Specifically, the computer-aided detection (CAD) tool is capable of identifying lesions that are less than 2 cm.

Improving MRI reconstructions by combining traditional techniques with new ML tools

“We found that if you tune the classical methods, they can perform very well,” an expert involved in the research said.

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