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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FDA approves PET imaging agent to fight Parkinson’s

The go-ahead was granted to the Feinstein Institutes for Medical Research to use Fluorodopa F-18 injections in patients with suspected Parkinson’s syndromes.

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How AI could limit gadolinium use when treating MS

Deep learning (DL) can predict and enhance MS lesions on unenhanced MRI scans, according to a new study published in Radiology

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Radiologists call for government action amid glaring deficiencies across UK emergency imaging

Underfunding and a lack of resources have led to significant problems imaging severely injured patients in trauma centers across the UK's health system. The Royal College of Radiologists has called on the government to address the issues.

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AI algorithm can spot LVEF from 15 seconds of ECG data

An AI algorithm that reportedly helps physicians identify reduced left ventricular ejection fraction (LVEF) received Breakthrough Device designation from the FDA on Dec. 18.

AI algorithm optimizes CCTA image quality

Deep learning can improve the quality of coronary CT angiography (CCTA) images, according to a new study published in Academic Radiology.

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‘One stop’ CT perfusion requires less contrast, radiation dose than CCTA

The new approach offers more comprehensive information with no loss of image quality, and may alter the care landscape for patients with coronary artery disease.

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Prediction time: How will AI impact radiology in another 10-15 years?

AI continues to evolve at a rapid pace, with new algorithms and solutions being developed all the time. What kind of long-term impact could these technologies have on patient care?

PET/CT roots out early lung cancer subtypes, may help personalize treatment

Combining fluorodeoxyglucose PET with high-resolution CT can help predict subtypes of early lung adenocarcinoma—a form of cancer that is on the rise.