Technology

A model combining deep learning features and clinical variables demonstrated a 30 percent higher AUC than a clinical model for detecting DCIS and invasive ductal carcinoma from suspicious microcalcifications on mammography, according to a new study.

Over 26 percent of AI-detected future breast cancers and interval breast cancers missed by radiologists were invasive cancers, according to newly published research involving over 42,000 women who had 2D screening mammography.

Reportedly the only point-of-care ultrasound system that can estimate liver stiffness and attenuation that correlate to MRI-PDFF, Velacur One also may facilitate higher reimbursement than non-imaging elastography.

Incorporating technology from Siemens Healthineers’ Magnetom Skyra Fit system, the Invision 3T Recharge Operating Suite offers AI-powrred protocols and automated image reconstruction capabilities.

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

A deep learning multimodal model that incorporates MRI features offered nearly double the sensitivity for predicting post-prostatectomy biochemical recurrence of prostate cancer in comparison to the traditional CAPRA-S scoring system.

While a CT-based deep learning model demonstrated a 91 percent AUC for predicting lung cancer risk within one year, researchers noted other mixed results in a new study involving over 18,000 individuals.

Combining sub-second load times and AI-automated features, the PET/CT Viewer Mode and Mammography Viewer Mode may help address bottlenecks in nuclear medicine imaging and mammography workflows.

Offering an 87 percent sensitivity for clinically significant prostate cancer (csPCa), the deep learning model demonstrated an 86 percent AUC for predicting > PI-RADS 3 lesions on prostate MRI.

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

The addition of two new AI-enabled models for the latest version of the NeuroQuant Brain Tumor software facilitates automated tracking of the progression of brain tumors and meningiomas.

In a retrospective review of screening digital breast tomosynthesis (DBT) exams for over 200 women with interval breast cancers, researchers found that AI provided accurate localization of cancers in 32.6 percent of the cases.

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

The newly launched Definium Pace Select ET X-ray platform reportedly provides increased automation and advanced image processing.

Catch up on the latest MRI studies, AI innovations, and expert insights on abbreviated breast MRI with our Weekly Scan.

The use of adjunctive bpMRI-based AI led to 10 percent and greater increases in lesion-level PPV for csPCa and PCa with a threshold of PI-RADS > 3.

The dual FDA clearances for the Accuro 3S point-of-care ultrasound device and the SpineNav-AI machine learning-based software may enhance precision and safety with ultrasound-guided neuraxial procedures.

Noting a 7.4 percent incidence of motion artifacts on brain MRI scans for suspected stroke patients, the authors of a new study found that motion artifacts can reduce radiologist and AI accuracy for detecting hemorrhagic lesions.

In external validation findings from a 29-study meta-analysis, MRI-based AI had a pooled AUC of 85 percent for preoperative prediction for microvascular invasion in patients with hepatocellular carcinoma.

A fully convolutional data description (FCDD) model for identifying anomalies on breast MRI demonstrated an 84 percent AUC for detection tasks in a balanced cohort with a 20 percent malignancy prevalence and a 72 percent AUC for detection tasks in an imbalanced group with a 1.85 percent cancer prevalence.

A cloud-based and AI-native radiology operating system, MosaicOS reportedly enables the combination of diagnostic AI tools and workflow enhancements into one scalable platform.

The updated capabilities of SwiftMR include personalized scan settings within the software, artifact reduction and cloud integration.

Emerging research revealed significantly enhanced sensitivity for prostate cancer detection with adjunctive and stand-alone use of AI.

Stay updated with the latest in radiology, including PET, MRI, and AI research, plus essential insights on mammography and cardiac imaging.

EchoGo Amyloidosis, an echocardiography-based AI screening software, demonstrated a 93 percent AUROC for cardiac amyloidosis detection in a new multicenter study.