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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AI mammography, prostate imaging algorithms cleared for market

The FDA has OK’d two subsidiaries of Los Angeles-based RadNet to sell medical AI software—one product for diagnosing breast cancer, the other for streamlining MRI prostate reporting workflows. 

breast cancer screening mammography

Malignant architectural distortion ably diagnosed on breast imaging by human-AI combo

Combining ensemble AI models with reads from breast radiologists of mixed experience levels can help health systems consistently diagnose malignant architectural distortion on mammography.

Academic surveyors find 56% of consumers anticipate better healthcare through AI

More than 40% of Americans are generally OK with the thought of AI reading their chest x-rays. Moreover, some 12.3% are very comfortable with the prospect.

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10 notable regulatory approvals of diagnostic devices over the past 30 days

Along with radiology-specific software and products, the list may include newly greenlit offerings for use in other settings that are increasingly important to multidisciplinary care.

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Most imaging AI algorithms perform unimpressively in external validation exercises

Some 81% of the models—70 of 86 DL algorithms reported in 83 separate studies—diminished at least somewhat in diagnostic accuracy compared with their accuracy on internal datasets.

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Deep learning and rads comprise an ‘efficient pipeline’ for detecting, classifying thyroid nodules

Competing to classify thyroid nodules on ultrasound images as either malignant or benign, three deep learning models have essentially drawn a tie with four radiologists.

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AI looking handy with 3D abdominal ultrasound

Mayo Clinic researchers have demonstrated a deep learning model that can automatically segment kidneys and measure total kidney volumes using only 3D ultrasound images.

AI aids coma prognostics, potentially averting withdrawal of care

Deep learning has bested experienced neurosurgeons at predicting poor outcomes, including mortality, among patients admitted comatose with severe traumatic brain injuries.

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Around the web

Health Imaging
Nearly $800,000 settlement offered to family of man who died during MRI exam

The patient, who was being cared for in the ICU, was not accompanied or monitored by nursing staff during his exam, despite being sedated.

Cardiovascular Business
Global shortage of nuclear imaging isotopes may be over

The nuclear imaging isotope shortage of molybdenum-99 may be over now that the sidelined reactor is restarting. ASNC's president says PET and new SPECT technologies helped cardiac imaging labs better weather the storm.

Cardiovascular Business
‘A huge win’: CMS significantly increases Medicare payments for cardiac CT

CMS has more than doubled the CCTA payment rate from $175 to $357.13. The move, expected to have a significant impact on the utilization of cardiac CT, received immediate praise from imaging specialists.