The accelerating integration of artificial intelligence in medical imaging is a present-state imperative. As radiology departments increasingly adopt AI tools to support diagnostics, workflow optimization, and quality assurance, the conversation has shifted from if to how. Yet even as algorithm performance improves, a critical challenge persists: how to equip the radiology workforce with the knowledge required to safely evaluate, implement, and oversee these tools across diverse clinical settings.

Bayer has confirmed it will discontinue both its Calantic Digital Solutions platform and the services of its subsidiary, Blackford Analysis, marking a full retreat from the radiology AI platform business. The announcement effectively closes a five-year push to centralize access to artificial intelligence tools for diagnostic imaging, an initiative that, despite technical promise, struggled to secure meaningful traction in hospital workflows.

The long-awaited arrival of native DICOM output in digital pathology signals more than a technical milestone. It marks a strategic convergence of imaging standards, data architecture, and AI readiness across healthcare enterprises. As vendors begin aligning digital pathology workflows with established medical imaging protocols, health systems face an opportunity, and an obligation, to reassess how pathology data is stored, shared, and analyzed at scale.

Radiology departments continue to face mounting volume, staffing constraints, and budget pressure. A six-way floating table now integrated into the Carestream Horizon X-ray System targets those challenges by improving patient positioning, reducing technologist effort, and limiting motion artefacts that degrade diagnostic clarity.

Digital breast tomosynthesis entered U.S. screening programs with the promise of sharper lesion visualization and fewer unnecessary recalls. Despite those gains, interval breast cancers, tumors discovered symptomatically after a negative exam and before the next scheduled visit, continue to undermine clinical and financial goals.

The Radiological Society of North America (RSNA) has issued a global call to data scientists, launching the 2025 Intracranial Aneurysm Detection AI Challenge in partnership with the American Society of Neuroradiology, the European Society of Neuroradiology, and the Society of Neurointerventional Surgery.

Chest CT is the linchpin for evaluating lingering respiratory complaints after acute SARS-CoV-2 infection, yet practices vary widely by country, vendor platform and radiologist preference. A new international consensus statement published in Radiology by the Radiological Society of North America aligns 14 nations on when to scan, how to scan and what to call the residual shadows that can persist for months.

“AI has the potential to revolutionize radiology by improving diagnostic accuracy and access to care,” said lead author Paul H. Yi, M.D., associate member (associate professor) in the Department of Radiology and director of Intelligent Imaging Informatics at St. Jude Children’s Research Hospital in Memphis, Tennessee. “However, AI algorithms can sometimes exhibit biases, unintentionally disadvantaging certain groups based on age, sex or race.”