Technology

Use of AI provided a pooled 22 percent increase in adenoma detection but no significant impact for advanced adenomas, according to an analysis of 39 randomized controlled trials examining AI’s impact in detecting colorectal cancer.

The launch of the AVI imaging platform reportedly facilitates direct integration into PACS and RS systems, and automated access to adjunctive CT-based AI applications for a variety of conditions including pulmonary embolism, intracranial hemorrhage and large vessel occlusion

Offering a “safety net” in emergency and inpatient settings, the Chest CT software reportedly provides enhanced triage capabilities and adjunctive detection of 167 radiological features.

In a recent interview, Timothy Fairbairn, Ph.D., and Fatima Rodiguez, M.D., discussed new research findings, recently presented at the American Heart Association (AHA) conference, showing the value of AI-powered quantification of plaque burden from CCTA exams for predicting adverse cardiovascular outcomes.

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

In a recent interview, Hari Kishan Gonuguntla, M.D., discussed AI-powered evaluation of chest X-rays with the Lung Nodule Malignancy Score software and key findings from multinational prospective research presented at the recent ESMO Congress 2025 meeting.

The Harrison.ai Open Platform reportedly emphasizes open architecture, customer ROI and elimination of costly AI platform fees.

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

Catch up on the most well-viewed breast imaging content in October 2025.

The AI-powered cvi42 | Plaque software enables adjunctive on-site interpretation of coronary CT angiography (CCTA) scans for plaque quantification.

Catch up on the most-well viewed radiology content in October 2025.

The newly launched PlaqueIQ™ image analysis modality is reportedly the first CT-based software indicated for the quantification and classification of plaque morphology in the carotid arteries.

In a retrospective analysis of triennial screening mammograms for 134,217 women, a deep learning model offered comparable assessment of interval breast cancer risk across differences in age and breast density.

The AI-enabled e-Lung software may lead to significantly improved and earlier detection of progressive pulmonary fibrosis, even in patients deemed clinically stable, according to new research recently presented at the American College of Chest Physicians (CHEST) conference.

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

Facilitating timely triage, the qER-CTA software enables AI assessment of the internal carotid artery and M1 segment of the middle cerebral artery for possible large vessel occlusions (LVOs).

In a recent interview, Deepa Sheth, M.D., discussed the rising incidence of breast cancer, key considerations in supplemental imaging for women with dense breasts and use of the CIVIE RadPod platform to facilitate consistent quality and imaging reads by fellowship-trained breast radiologists.

Deep learning assessment of MRI offered a 24 percent higher sensitivity than radiologist interpretation for detecting lymph node metastasis in patients with colorectal cancer, according to a new meta-analysis.

Through the use of a multimodal system, Viz Assist provides generative AI summaries of patient histories that may ehance care coordination and facilitate more timely interventions.

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

Concordant mammography detection of breast cancer by radiologists and AI had over a threefold higher likelihood of future incidental breast cancer in comparison to positive radiologist assessment and negative AI evaluation, according to new research involving over 82,000 women.

The AI-enabled LungQ® 4 software reportedly offers enhanced segmentation of peripheral airways and estimates of chronic perfusion deficits based on analysis of chest CT scans.

Facilitating timely detection and follow-up management of patients with aortic aneurysms, the PRAEVAorta2 software reportedly enables automated measurement of aortic diameters on computed tomography (CT) scans.

Through enhanced data interoperability and access to patient histories, the cloud-based InteleHeart may facilitate better communication and workflow efficiencies for radiologists and cardiologists.

A deep learning AI platform, which incorporated radiomic features including CT attenuation metrics, demonstrated a 93.6 percent AUC for detecting invasive adenocarcinoma on chest CT.