Medical Imaging

Physicians utilize medical imaging to see inside the body to diagnose and treat patients. This includes computed tomography (CT), magnetic resonance imaging (MRI), X-ray, ultrasound, fluoroscopy, angiography,  and the nuclear imaging modalities of PET and SPECT. 

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Prostate AI cleared for U.S. sales

A medical AI startup in Omaha, Neb., has received the FDA’s blessing to market software for diagnosing prostate cancer on MRI scans.

Breathing issues, language barriers swell MRI scan times

MRI technologists serving patients who have difficulty understanding English may need to budget additional scanner time—especially when image quality largely depends on patients’ compliance with breathing instructions.

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These CT findings increase risk of thromboembolic events for patients with COVID pneumonia

Authors of the new paper noted that radiologists should be highly suspicious of pulmonary embolism and DVT when they encounter these findings on chest CT exams of COVID patients.

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Following inspection failures, 2 mammography centers have 2 different outcomes

The FDA’s Center for Devices and Radiological Health (CDRH) has updated the status of two previously disaccredited mammography operations, rehabilitating the reputation of one while showing the other in limbo.

What works—and what doesn’t—for chipping away at CT overutilization in the ED

The presence of any or all of four factors can help ensure appropriate CT utilization in emergency settings: established diagnostic pathways, alternative test availability, involvement of specialists and feedback from referrers.

father of #MRI, Raymond Damadian

'Father of MRI' dies at 86

The science community lost a man who pioneered one of medical imaging’s most important developments when Raymond Vahan Damadian passed away August 3. 

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EHR tracking system significantly improves diagnostic timelines for liver cancer patients

Implementing an EHR cancer tracking system to review radiology reports for abnormal findings resulted in patients at one Veterans Affairs Hospital receiving their cancer diagnosis and treatment months earlier than those who were imaged before the system was put into place.

Less experienced radiologists benefit from deep learning models when scouting for intracranial aneurysms

Deep learning models can increase reader accuracy while simultaneously decreasing interpretation times when evaluating imaging for intracranial aneurysms.