Jeffrey SorensonAIUtilization is the new innovation in healthcare enterprise AIEnterprise artificial intelligence (AI) has shown tremendous promise in the field of radiology, specifically around assistive intelligence. But what can be done to improve confidence in its use? Jeff Sorenson explains.February 1, 2021Page 1 of 1Top StoriesMolecular ImagingWhole-body PET shows how naloxone blocks opioidsPET imaging has shown for the first time how the opioid overdose treatment naloxone blocks neuroreceptors throughout the body.Womens ImagingKomen rails against proposed federal cuts to women's health programCTCT muscle metrics could help screen for sarcopeniaWomens ImagingCancer incidence on rise in younger people, womenAssociationsFinancial shock waves strike close to radiology researchers
![Images depict axial MRI scans in a 50-year-old premenopausal female patient with biopsy-proven 12-mm invasive lobular cancer in the lower outer quadrant of the left breast. Upper images are subtracted dynamic contrast-enhanced (DCE) MRI scans from the first and second postcontrast acquisitions. Lower images are ultrafast MRI scans obtained within 24 hours after the DCE study (four consecutive subtracted dynamic frames from time points [T] 6–9). There is marked background parenchymal enhancement (BPE) on the DCE MRI scans. Thus, the known cancer (arrow) is barely visible; it exhibits only slightly stronger enhancement than the normal fibroglandular tissue, which results in low conspicuity. At ultrafast MRI there is less BPE, and still the cancer is barely visible because it starts to enhance simultaneously with the BPE. The conspicuity of the cancer is even reduced compared with the DCE series. Both of the readers missed this cancer on both the DCE and ultrafast MRI scans.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2025/05/2025-05-06-rsna-ultrafast-dce-mri-breast.Gzvq76udFr.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
