Week in Review: ACP and breast cancer screening | Nassau MRI story gets weirder

It’s been an interesting week here at AuntMinnie.com. Our top story was a MinnieCast with Carolyn Crandall, MD, of the University of California, Los Angeles, who discussed the American College of Physicians’ (ACP) newly released guidance regarding breast cancer screening. Click here for the full interview with Crandall.

Readers also showed significant interest in the latest Invisible Force podcast episode, during which hosts Toby Gilk and John Posh discussed the “real confusion” about the MRI provider involved in a fatal accident that occurred in July of last year.

Got Coke? Third on our most-clicked list of articles for the week was a case study conducted by Florida researchers that reported the CT imaging-confirmed efficacy of using Classic Coca-Cola to dissolve fecalomas.

Fourth up was coverage of a study reporting that routine measurements of the brain found on MR or PET imaging could help identify which older adults are likely to gain cognitive protection from a structured, intensive lifestyle program. In fifth place was an article regarding delays women face in having abnormal mammograms evaluated — an effect that appears to be due in part to the COVID-19 pandemic.

See below for the full list of our top stories of the week:

1. Women’s Imaging MinnieCast, Episode 7: What to know about the ACP’s breast cancer screening guidance

2. Podcast: The story just got weirder in Nassau Open MRI fatality

3. CT reveals new use for Coca-Cola: Dissolving massive fecalomas

4. Brain MRI, PET may predict who gains most from lifestyle interventions

5. Women face more diagnostic delays after abnormal mammograms

6. Radiologists land on low end of industry research money, study finds

7. FAPI-PET superior to FDG-PET in liver cancer

8. Opinion: Radiologists must be proactive to protect helium supply

9. Ultrasound O-RADS categorizes borderline ovarian tumors

10. Musculoskeletal strain affects majority of radiologists

11. New x-ray dataset helps clinicians develop pathology detection AI