Pulmonary embolism

Pulmonary embolism (PE) is the third leading cardiovascular cause of death after heart attacks and stroke. PE is caused by blood clots in the pulmonary arteries. These are often caused by clots from the venous system, including thrombus from trauma, surgery or deep vein thrombosis (DVT). Treatment has traditionally been systemic use of thrombolytic drugs to dissolve the clot. But in cases there is a massive, life-threatening PE, or chronic clot burden that have remained in a vessel for an extended period of time, mechanical thrombectomy and ultrasound-assisted catheter-directed thrombolysis (USCDT) is being used as more targeted and aggressive treatments.

AI is revolutionizing radiology workflow and patient care
In the rapidly evolving healthcare landscape, artificial intelligence (AI) is making significant strides in improving radiology workflow and patient care coordination. Nicholas Galante, MD, medical director of informatics at Radiology Associates of North Texas, recently discussed how technology from Viz.ai is transforming his radiology practice, enhancing efficiency, and ultimately benefiting patient outcomes.
Use of CTPA for suspected pulmonary embolism in pregnancy surges 156% at 2 hospitals
Despite the marked increase, there was no corresponding uptick in either positive PE readings or pregnancies, experts detailed.
How CT creates barrier to treating pulmonary embolism patients in cheaper outpatient settings
Rather than being discharged, low-risk PE patients often receive unnecessary additional services and overnight stays, experts wrote in JAMA.
AI dramatically reduces radiologists’ rate of missed incidental pulmonary embolism on routine CT
The commercial software also reduced the median detection and notification time for incidental PE in flagged scans from “several days” down to just 1 hour.
Pulmonary embolism AI cleared
A Silicon Valley AI shop has been OK’d by the FDA to market software that automatically flags suspected pulmonary embolisms (PEs) and immediately notifies physicians.

AI is revolutionizing radiology workflow and patient care

Sponsored by Viz.ai

In the rapidly evolving healthcare landscape, artificial intelligence (AI) is making significant strides in improving radiology workflow and patient care coordination. Nicholas Galante, MD, medical director of informatics at Radiology Associates of North Texas, recently discussed how technology from Viz.ai is transforming his radiology practice, enhancing efficiency, and ultimately benefiting patient outcomes.

Use of CTPA for suspected pulmonary embolism in pregnancy surges 156% at 2 hospitals

Despite the marked increase, there was no corresponding uptick in either positive PE readings or pregnancies, experts detailed.

How CT creates barrier to treating pulmonary embolism patients in cheaper outpatient settings

Rather than being discharged, low-risk PE patients often receive unnecessary additional services and overnight stays, experts wrote in JAMA.

artificial intelligence AI deep learning ChatGPT OpenAI Microsoft Google

AI dramatically reduces radiologists’ rate of missed incidental pulmonary embolism on routine CT

The commercial software also reduced the median detection and notification time for incidental PE in flagged scans from “several days” down to just 1 hour.

Pulmonary embolism AI cleared

A Silicon Valley AI shop has been OK’d by the FDA to market software that automatically flags suspected pulmonary embolisms (PEs) and immediately notifies physicians.

Imaging shows COVID vaccines effective at warding off pulmonary embolism

Researchers have found the condition significantly less among patients who received at least two doses of a COVID vaccine.

New pulmonary embolism approach could substantially reduce imaging overuse

The pretest probability score produced false-negative rates below 1% and dropped imaging use by about 20%, according to a new JAMA Cardiology study.

AI spots dozens of missed incidental pulmonary embolism diagnoses at one hospital

The investigation was retrospective, but Duke scientists believe their algorithm could potentially aid radiologists in spotting near-misses in their work.

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