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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AI model could open doors for greater access to obstetric ultrasound

Experts have developed an artificial intelligence model that can estimate gestational age with accuracy that rivals that of formally trained sonographers completing fetal biometry scans. 

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Abbreviated breast MRI deemed an attractive screening option—sometimes

AB-MRI is a cost-effective means of screening women with dense breast tissue for breast cancer—as long as the per-exam costs don’t top 82% of what would have been spent to perform full-protocol breast MRI.

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.

An example of COVID vaccine caused axillary adenopathy. The woman has a family history of breast cancer, but this lesion, seen on breast ultrasound, tested negative in an RSNA study.

Experts suggest new follow-up imaging protocols for vaccine-related lymphadenopathy

New research shows that persistent lymph node swelling observed on imaging can persist beyond 12 weeks post-vaccination for up to 50% of women.

Stratifying patients by risk of poor outcomes could reduce overtreatment of lung cancer

Researchers are using radiomics to narrow patient cohorts down to those who are at the greatest risk of poor lung cancer outcomes.

Ischemic stroke CT imaging. Images courtesy of RSNA

Stroke care still lags among certain Medicare populations

Despite increases of 250% for CTA and 428% for CTP, researchers observed lower rates of neuroimaging utilization among rural residents, older individuals (80 years and above), women and Black patients.

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AI spots pancreatic cancer in its earliest stages

Experts involved in the study suggest their findings could eventually be used to detect pancreatic cancer in its earliest stages when patients are most likely to respond to interventions favorably.

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.