
Lamenting a lack of control over imaging requests from referring clinicians, this author suggests that a more collaborative approach between referrers and radiologists may facilitate more efficient use of imaging.

In a recent video interview, David Ouyang, M.D., shared insights from two recent studies he co-authored on the use of artificial intelligence (AI) to improve initial assessment of left ventricular ejection fraction (LVEF) on echocardiography and ascertain cardiac risks associated with changes in the left ventricle sphericity index seen on magnetic resonance imaging (MRI).

Lamenting a lack of control over imaging requests from referring clinicians, this author suggests that a more collaborative approach between referrers and radiologists may facilitate more efficient use of imaging.

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The BD Prevue™ II Peripheral Vascular Access System reportedly offers real-time needle depth markers that may reduce multiple needlestick attempts and allow easier placement of intravenous (IV) access in high-risk patients.

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Based on a review of 3,495 echocardiographic studies to evaluate left ventricular ejection fraction (LVEF), researchers found that cardiologists changed initial artificial intelligence (AI) assessment 16.8 percent of the time and initial sonographer assessment 27.2 percent of the time.

The artificial intelligence (AI) powered Auto B-line Counter, which reportedly produces a B-line count from a six-second ultrasound clip, may facilitate more expedient and consistent assessment of abnormal lung function.

Emerging research shows the adjunctive use of automated breast ultrasound with mammography has similar sensitivity for breast cancer detection as adjunctive handheld ultrasound but may offer reduced false-positive rates in women with dense breasts.

Smart-CKD, an ultrasound-derived, computer-aided diagnosis (CAD) tool, demonstrated an area under the curve of 81 percent and an 83 percent sensitivity rate in a validation cohort for differentiating between mild and moderate to severe fibrosis in patients with chronic kidney disease.

Findings from three randomized trials of ultrasound renal denervation revealed a significant reduction in daytime ambulatory systolic blood pressure in patients with varying levels of hypertension.

Catch up on the top AI-related news and research in radiology over the past month.

The TE Air reportedly combines enhanced point-of-care ultrasound imaging with an array of practical benefits for radiologists.

When you are asked about your occupation, how do you respond?

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The HERA W10 Elite ultrasound platform provides enhanced visualization features and artificial intelligence (AI)-aided measurement capabilities.

Employing an artificial intelligence (AI)-powered scoring system, LVivo IQS reportedly provides real-time assessment of the quality of cardiac ultrasound images.

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In what is reportedly the first Food and Drug Administration (FDA) 510(k) clearance for the use of artificial intelligence (AI) for musculoskeletal ultrasound, the model provides automated measurements of tendons in the knee, ankle, and foot.

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Review the case study and test your knowledge to make the correct diagnosis.

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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.

CAAS Qardia 2.0, an updated version of the CAAS Qardia echocardiography software platform, reportedly incorporates artificial intelligence (AI)-enabled workflows, and provides enhanced imaging and analysis of key cardiac measures.

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 new prospective study, an emerging deep learning model, which incorporates parametric mapping with quantitative ultrasound to estimate liver fat fraction, demonstrated a 90 percent sensitivity rate and a 91 percent specificity rate for diagnosing hepatic steatosis in patients with non-alcoholic fatty liver disease (NAFLD).