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New research suggests the capability of a mammography-based deep learning model to identify women at high risk of breast cancer led to more than triple the cancer detection rate on breast MRI in comparison to traditional risk assessment tools.

In the third episode of a three-part podcast, Anand Narayan, M.D., Ph.D., and Amy Patel, M.D., discuss the challenges of expanded breast cancer screening amid a backdrop of radiologist shortages and ever-increasing volume on radiology worklists.

For cT1 renal masses < 4 cm and renal masses < 2 cm, the PET/CT agent 89Zr-DFO-girentuximab had respective sensitivity rates of approximately 85 percent and 96.7 percent for diagnosing clear cell renal cell carcinoma, according to research recently presented at the European Association of Nuclear Medicine (EANM) 2023 Congress.

In the second episode of a three-part podcast, Anand Narayan, M.D., Ph.D., and Amy Patel, M.D., discuss recent studies published by the Journal of the American Medical Association (JAMA) that suggested moving to more of a risk-adapted model for mammography screening.

The use of automated detection of large vessel occlusion on computed tomography (CT) through artificial intelligence (AI) software reportedly led to an 11.2-minute reduction in triage time from the completion of imaging to initiation of endovascular therapy, according to newly published research.

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