The executive order seeks to promote continued innovation and growth with artificial intelligence (AI) while ensuring monitoring of AI models for safety, privacy, and equity.

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New research shows that pelvic MRI offers equivalent sensitivity but nearly 20 percent greater specificity than transvaginal ultrasound for the classification of adnexal lesions.

Could adjustments to quality assurance review facilitate improved teamwork between radiologists and referring clinicians?

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

In a study of over 375,000 people, researchers found that a high liver MRI proton density fat fraction was associated with an over 7.5-fold higher risk for non-alcoholic steatohepatitis, a 4.5-fold higher risk for malignancy, and a 3.8-fold elevated risk for cirrhosis of the liver.

Photon-counting computed tomography (PCCT) offers a number of salient advantages over conventional CT, including improved image resolution and contrast-to-noise ratio, enhanced denoising capability and inherent spectral sensitivity.

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

The update of the S-scan magnetic resonance imaging (MRI) system reportedly offers an improved ergonomic design, algorithms to enhance image quality and reduced scan times.

A 49-study meta-analysis revealed that MRI-based and CT-based radiomics models outperformed clinical models for predicting recurrence of hepatocellular carcinoma.

An emerging deep learning algorithm can reportedly triage 40 percent of no-change X-rays while providing 88 to 90 percent accuracy for detecting changes with X-rays obtained in the emergency department and intensive care unit at a tertiary referral hospital, according to recently published research.

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Emerging research findings suggest that a longer prostatic urethral length on MRI is associated with a 70 percent increased risk of grade >2 acute urinary toxicity after radiotherapy for prostate cancer.

The artificial intelligence (AI)-powered software VUNO Med-DeepBrain reportedly automates brain MRI segmentation and provides access to volumetric data on over 100 regions of the brain.

Is there a certain hypochondriasis that may lead some radiologists to pursue their own imaging, and would it change how aggressively they follow up incidentalomas on their own scans?

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

While ChatGPT has the potential to help streamline responses to imaging-related questions from patients, the authors of a new study found that a third of ChatGPT responses to unprompted questions on medical imaging were not “fully relevant.”

In a newly published literature review, researchers examined the benefits of diffusion-weighted imaging (DWI) magnetic resonance imaging (MRI) for breast cancer characterization and monitoring of neoadjuvant chemotherapy, current drawbacks that thwart wider adoption, and emerging techniques that may enhance the modality’s effectiveness.

In a multicenter cohort of patients with interstitial lung disease (ILD), a deep learning classification tool demonstrated an 81 percent sensitivity rate and a 77 percent specificity rate for predicting usual interstitial pneumonia on computed tomography (CT) scans.

Artificial intelligence (AI) software assigned high malignancy risk scores to mammography exams completed up to two years prior to breast cancer diagnosis in over 38 percent of screen-detected cancer cases and over 39 percent of interval cancer cases, according to newly published research.