Journal highlights

Despite evidence that breast imaging specialists outperform general radiologists, about 70% of screening mammograms are interpreted by generalists due to specialist shortages. AI-supported workflows may help address variability and standardize screening mammography performance.

In a new Radiology article, Matthew McCabe, PhD, DeepHealth in Somerville, MA, and colleagues evaluated whether a multistage AI-driven workflow could improve screening performance of generalists and specialists.

The prospective study included 60 generalists and 35 fellowship-trained specialists who interpreted 577,742 mammograms. The AI workflow incorporated a computer-aided detection and diagnosis tool that routed AI-identified suspicious examinations not initially recalled for additional expert review.

With AI, generalists’ cancer detection rate increased from 3.76 to 4.99 cancers per 1,000 mammograms, and positive predictive value increased from 3.38% to 3.89% despite a higher recall rate (9.06% to 10.40%). Specialists’ detection rates were unchanged, and generalists using AI performed similarly to specialists using AI.

“The benefit of improved positive predictive value of recalls indicates a favorable shift in the screening process despite the observed increase in recall rate,” the authors conclude.

Read the full article, “Closing the Performance Gap between Generalists and Breast Imaging Specialists Using a Nationally Deployed AI Workflow for Screening Mammography.” 

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Imaging Clues of Early Pancreatic Cancer

Pancreatic cancer is often diagnosed at an advanced stage and carries a poor prognosis, making earlier detection critical to improve outcomes.

In an article published in RadioGraphics, Shintaro Kano, MD, University of Tokyo, and colleagues provide a comprehensive overview of the clinical implications, diagnostic workup and imaging findings of early pancreatic cancer, with histopathologic correlation to support personalized surveillance.

The authors defined early pancreatic cancer as high-grade dysplastic precursor lesions and invasive carcinomas measuring 2 cm or smaller that remain confined to the pancreas. Direct imaging findings include a solid lesion or an enhancing mural nodule within a cystic lesion. Equally important are indirect findings, such as focal pancreatic parenchymal atrophy, focal faint parenchymal enhancement, main pancreatic duct strictures and focal side-branch dilatation or retention cysts. Notably, these subtle changes may precede visible tumor development by months to years, providing a valuable window for intervention.

“Radiologists should recognize subtle imaging features that may precede overt tumor development, aiding effective multidisciplinary decision making and timely management,” the authors write.

Read the full article, “Early Pancreatic Cancer: Clinical Implications, Workup, and Imaging Findings with Histopathologic Correlation for Personalized Surveillance," and the invited commentary, "Early Detection of Pancreatic Cancer: Are We Up for the Challenge?” This article is also available for CME on EdCentral. 

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Diffusion MRI Offers Insight into Myocardial Microstructure

Diffusion-weighted imaging (DWI) is an MRI technique that is widely used to characterize tissue structure, but technical challenges have limited its use in cardiac MRI.
Despite advances in motion compensation techniques, high-performance gradient systems and other acquisition strategies, there are no recent reviews of the clinical applications of cardiac diffusion imaging.

In a new Radiology: Cardiothoracic Imaging study, Neel Vora, MBBS, Cleveland Clinic, and colleagues conducted a comprehensive review to characterize the extent, clinical applications, heterogeneity and emerging trends of cardiac diffusion imaging in in vivo human studies.

The review included 55 studies, most commonly evaluating hypertrophic cardiomyopathy and ischemic heart disease. DWI showed high sensitivity (83.1%–97%) and specificity (90%–100%) for detecting acute myocardial infarction. Cardiac diffusion tensor imaging metrics, including mean diffusivity and fractional anisotropy, identified microstructural abnormalities in hypertrophic cardiomyopathy and ischemic heart disease.

“Diffusion imaging techniques show potential for characterizing myocardial microstructure and pathology, but variability in methodology and limited clinical validation currently constrain broader clinical adoption,” the authors conclude.

Read the full article, “Clinical Applications of Cardiac Diffusion MRI: A Scoping Review.”

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