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 classifies lung cancer slides with similar accuracy as pathologists

The researchers believe their algorithm could help pathologists classify the histologic patterns of lung adenocarcinoma—the most common form of the disease—and potentially lead to more accurate staging.

Imaging groups collaborate on ethics in AI draft document

The American College of Radiology (ACR) is asking for comments to be submitted by April 15.

Google, Verily develop AI algorithm to detect diabetic eye disease from imaging exams

Google and its sister company Verily announced on Monday, Feb. 25, the development of an AI-based algorithm that can screen eye imaging exams for diabetic retinopathy and diabetic macular edema—two of the leading causes of preventable blindness in adults with diabetes, according to a recent report by CNBC.  

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AI detects schizophrenia from fMRIs with 87% accuracy

A new AI-based software called the Ensemble Algorithm with Multiple Parcellations for Schizophrenia Prediction, or EMPaSchiz, can identify schizophrenia on fMRI scans with 87 percent accuracy, according to a recent report by AI in Healthcare.  

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How AI can help ‘see beyond’ breast density, provide more individualized patient care

Mammography is an essential screening and diagnostic tool for the detection of breast cancer and the assessment of breast density. But, according to Victoria L. Mango, MD, a breast radiologist at Memorial Sloan Kettering Cancer Center in New York City, AI can help breast imagers and physicians see beyond basic breast density information provided by mammographic images and improve clinical management overall.

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Machine learning model may save women from unnecessary breast surgery

Researchers have created a machine learning model that identified 98 percent of malignant atypical ductal hyperplasia (ADH) lesions prior to surgery, according to a single-center study published in JCO Clinical Cancer Informatics. The approach saved 16 percent of women from unnecessary surgery.

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Microsoft, Philips release new augmented reality application for image-guided procedures

Royal Philips and Microsoft recently unveiled their latest technological collaboration for the "operating room of the future," which combines Philips’ Azurion image-guided therapy platform and Microsoft’s newly released HoloLens 2 holographic augmented reality (AR) headset to help create novel AR applications for image-guided minimally invasive therapy. 

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4 areas AI must excel in to improve women’s imaging

For AI to become clinically feasible in women’s imaging, it must excel in the areas of performance, time, workflow and cost, according to an opinion piece published online in the American Journal of Roentgenology.  

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Around the web

Cardiovascular Business
Positron partners with Upbeat Cardiology Solutions to improve cardiac PET/CT access

Positron, a New York-based nuclear imaging company, will now provide Upbeat Cardiology Solutions with advanced PET/CT systems and services. 

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.