Mammography

In a new survey that examined perceptions of breast cancer risk among more than 1,800 women who had a recent mammogram, 65 percent noted that being overweight or obese was a greater risk factor than breast density, and over a quarter of those interviewed noted they were not aware that they could reduce their breast cancer risk.

Catch up on the top radiology content of the past week.

Noting the significant administrative fees for the Independent Dispute Resolution (IDR) process of the No Surprises Act and onerous restrictions that have led to a nearly “non-existent” use of batching of disputed claims in radiology, the American College of Radiology (ACR) has sent formal recommendations to the United States Departments of Health and Human Services, Labor, and Treasury for addressing these issues.

Emerging research suggests combined artificial intelligence (AI) assessment of digital mammography and automated 3D breast ultrasound provides enhanced detection of breast cancer in women with dense breasts and may be a viable alternative in areas where radiologists are scarce.

In a provocative new article, radiology researchers discuss the impact of social determinants of health (SDoH) upon access to care and patient outcomes, and present strategies within the realms of radiology education, research, clinical care, and innovation that may help mitigate health-care disparities.

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While breast cancer imaging guidelines recommend annual screening for five years after treatment for ductal carcinoma in situ (DCIS), a new study of over 12,000 women found that only 52 percent had consistent surveillance screening with researchers noting disproportionately lower follow-up imaging rates for Black and Hispanic women.

For system errors and failures in radiology, are we prone to a satisfaction of search that prevents us from addressing deeper issues?

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In a recent interview from the Radiological Society of North America (RSNA) conference, Mary Yamashita, M.D. discussed a variety of findings from a survey of over 8,000 women about breast density awareness, challenges with current breast density notification after mammography exams, and the ongoing need to educate patients as well as referring providers on breast density awareness.

Catch up on the most well-read mammography articles from 2022.

Catch up on the most well-viewed video interviews from Diagnostic Imaging in 2022.

Touching on a variety of topics in radiology, here are the top five most well-read articles from Diagnostic Imaging in 2022.

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Catch up on the top AI-related news and research of the past month.

The artificial intelligence (AI) software Saige-Density™ reportedly provides automated assessment of breast density during mammography exams.

Catch up on the top radiology content of the past week.

In a recent video interview, Susan Holley, MD discussed key findings from a large retrospective longitudinal study, presented at the recent Radiological Society of North America (RSNA) conference, which found that an emerging artificial intelligence (AI) model was over 24 percent more consistent than radiologist assessment of breast density.

An emerging artificial intelligence algorithm, developed to estimate volumetric breast density from 3D-reconstructed digital breast tomosynthesis images, could potentially facilitate individual risk assessments for breast cancer.

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In a study of over 800 women with breast cancer, researchers found that African-American women had a higher rate of ductal carcinoma in situ (DCIS) and were less likely to have irregular masses in screening exams in comparison to non-Latina White women.

The ebbs and flows of worklists in radiology require equal parts productivity and preservation.

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In a recently published article, researchers from Yale University discuss the pros and cons of current FDA regulations as they apply to the clearance and use of adjunctive artificial intelligence (AI) software with conventional breast cancer screening modalities such as mammography.

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In a new study involving 198 contrast-enhanced mammography exams in 104 women with breast implants, researchers noted that only one patient had a complication.

Is due consideration of patient history, demographics, and previous imaging essential or a cheater’s crutch when assessing new imaging?

Catch up on the top radiology content of the past week.

In separate test sets of Israeli women and United States women who had either ductal carcinoma in situ or invasive breast cancer, emerging artificial intelligence (AI) algorithms achieved an area under the curve (AOC) of 88 percent and 80 percent, respectively, for malignancy detection.

Rads will always have to deal with forces outside of their control, but it’s how we address those forces that makes us the type of radiologist we can be proud of.