We scan the top radiology sources so you don’t have to.
From AI breakthroughs to imaging trends, we serve up real-time radiology insights.
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vRad Now Offering AI-enabled Technology and Support Platform for Radiology Practices
tim.hodson
Mon, 11/10/2025 – 06:00
Nov. 4, 2025 — Virtual Radiologic (vRad) recently announced the successful commercialization of The vRad Platform — a fully integrated, AI-enabled technology and support platform for radiology practices. The vRad Platform optimizes radiologist productivity, provides practice-wide analytics in real time, and helps radiology practices deliver consistent, high-quality patient care across dispersed facilities and reading locations.
Developed and refin… -
SCI Tied to Long-Term Neurologic, Psychiatric, and CVD Risks
Traumatic spinal cord injury has been linked to an elevated long-term risk for neurologic, psychiatric, cardiovascular, and endocrine disorders, underscoring the need for lifelong care. Medscape Medical News
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Proton vs Photon RT in Breast Cancer: Which Is Better?
Recent data show proton and photon radiotherapy lead to similar quality-of-life outcomes in patients with breast cancer. Medscape Medical News
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Association of Interventional Radiologist Clinical Evaluation and Management Services and Procedural Complexity
Clinical evaluation and management (E&M) services performed by interventional radiologists may be undervalued by radiology practices compared with higher work relative value unit (wRVU) interventional radiology (IR) procedural services. The aim of this study was to assess whether higher E&M provision is associated with higher IR procedural complexity and the contribution of nonphysician practitioners (NPPs) in delivering IR services.
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Enhanced osteoporosis screening via multi-output deep learning: Segmentation and classification of metacarpal radiographs
Osteoporosis screening from radiographic images has traditionally relied on isolated methods that fail to capture the complex interplay between structural segmentation and diagnostic classification. This paper introduce OMO-Net, a novel multi-output deep learning architecture that simultaneously performs segmentation and classification on metacarpal radiographs to accurately detect osteoporosis. Unlike conventional approaches, OMO-Net integrates a ResNet-50–based feature extractor with dedicated…
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LG-nnU-net for multilabel anal sphincter segmentation on MRI: quantitative evaluation in patients with anal fistula
To develop and evaluate a novel deep learning–based segmentation framework (LG-nnU-net) for multilabel segmentation of anal sphincter substructures on MRI, aimed at providing robust quantitative anatomical information without implying operative validation for clinical classification improvement.
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Assessment of left ventricular thrombi using cardiac CT: A comparative evaluation of non-contrast, CT-angiography, delayed-enhanced images, and extracellular volume maps
CT-derived extracellular volume mapping and delayed-phase imaging significantly outperform non-contrast and early-phase CT in detecting left ventricular thrombi, providing superior diagnostic accuracy and enhancing clinical decision-making.
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Management of Incidentally Discovered Pineal Cyst on CT and MRI: Recommendations from the ACR Incidental Findings Committee
The ACR Incidental Findings Committee presents recommendations for managing incidental pineal cysts on CT of the head or MRI of the brain. The Pineal Cyst Subcommittee is composed of neuroradiologists and a neurosurgeon who developed the algorithms presented. These recommendations represent a combination of current published evidence as well as expert experience and opinion and were finalized by a formal consensus-building process. The recommendations address commonly encountered incidental find…
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Developing Algorithm-Based Recommendations in the ACR: Defining a New Process
We summarize a new process for developing algorithm-based recommendations for the ACR. This process is currently applied to the ACR’s incidental findings recommendations, and other committees providing evidence-based recommendations may elect to adopt these processes in the future. The prior process relied upon informal consensus and was versatile but more limited in scalability and generalizability. Most importantly, the absence of a formal, evidence-driven process prevented incidental findings…