Fetal cardiac MRI and congenital heart defects; Survival tips for early radiology practice; Plus, Risk-based prioritization models for mammography during crises.
Welcome to Diagnostic Imaging’s Weekly Scan. I’m senior editor Whitney Palmer.
Before we get out our featured interview with Dr. Diana Miglioretti about a risk-based model designed to help providers prioritize which women to bring in for mammograms during a crisis, such as the COVID-19 pandemic, here are the top stories of the week.
Fetal cardiovascular MRI can be useful in providing information about congenital heart defects when echocardiography results are unclear, said a group of researchers in JAMA Network Open. Although echocardiography is typically the tool of choice to catch these defects in utero, sometimes the acoustic window isn’t sufficient, leading to indeterminate images. In these cases, fetal CMR can provide useful details in 84 percent of cases, potentially impacting choices for mode of delivery, early postnatal care planning, and parental counseling. To determine how well fetal CMR performs, the team examined results from 31 fetuses with an average gestational age of 36 weeks between January 2017 and June 2020. Alongside that additional diagnostic information, the team determined the extra data bolstered parental counseling in 68 percent of cases.
Being a new radiologist can be difficult. You have to learn the ropes of your new practice, get to know your colleagues, and figure out how to handle the daily workload. It can be overwhelming – and, frankly, residency doesn’t necessary give you the skills you need navigate it all successfully. In an attempt to help you, a group of radiology experts from The Netherlands published a list of 10 survival tips this week in the Journal of the American College of Radiology. They touched on finances, insurance, continuing medical education, setting boundaries, avoiding burnout, and more. Not only can these tips help the new radiologist, but they can also be good suggestions for how residency programs can improve how they prepare providers for the realities of clinical practice.
And, finally this week, Diagnostic Imaging spoke with Dr. Diana Miglioretti, chief of biostatistics at the University of California-Davis School of Medicine, about the risk-based model she and her colleagues created. It is designed to help providers prioritize which women to bring in for screening mammography during times of crisis when resources and capacity are limited, such as during the COVID-19 pandemic. Here’s what she had to say about the impact of using such as model.
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Mammography Study Suggests DBT-Based AI May Help Reduce Disparities with Breast Cancer Screening
December 13th 2024New research suggests that AI-powered assessment of digital breast tomosynthesis (DBT) for short-term breast cancer risk may help address racial disparities with detection and shortcomings of traditional mammography in women with dense breasts.