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Interventional (IR)Guideline

SIR Foundation Research Consensus Panel Sets Priorities for Acute DVT Intervention Studies

SIR Foundation research consensus panel calls for standardized acute DVT intervention endpoints: biologically informed patient selection, anatomic/physiologic metrics, validated severity tools, longitudinal biomarkers, and economic/QoL measures to advance precision and reduce po…

Journal of vascular and interventional radiology : JVIR

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Musculoskeletal (MSK)AI / InformaticsResearch

ChatGPT-5 outperforms ChatGPT-4o in detecting lumbar spondylolisthesis on standing lateral radiographs but remains limited compared with spine surgeons

ChatGPT-5 outperformed ChatGPT-4o for detecting lumbar spondylolisthesis on standing lateral radiographs, with sensitivity 67.5% vs 49.4% and accuracy 61.5% vs 55.5%, but both remained limited compared with fellowship-trained spine surgeons.

European journal of orthopaedic surgery & traumatology : orthopedie traumatologie
Nuclear / MolecularBody / AbdominalChest / ThoracicAI / InformaticsEducationTrainee

FDG-PET/CT in Lymphoma: Staging, Deauville Scoring, and Prognostic Biomarkers

FDG-PET/CT is central to lymphoma management: Lugano staging, Deauville response assessment, and total metabolic tumor volume as a powerful prognostic biomarker. In Hodgkin lymphoma, interim PET guides treatment de-escalation; in DLBCL, it is prognostic but not yet actionable. P…

PET clinics
Musculoskeletal (MSK)AI / InformaticsResearch

Deep-learning denoising lifts low-field 0.55T knee MRI accuracy to near 3T

Deep-learning denoising raised low-field 0.55T knee MRI sensitivity from 0.83 to 0.97 and diagnostic accuracy from 0.83 to 0.98, approaching conventional 3T (sensitivity 0.95, accuracy 0.97) in a retrospective study of 33 knee MRIs.

European journal of radiology
Neuro / Head & NeckEducationTrainee

Contrast Leak on CT Detector Creates Stroke-Mimicking Artifact

Contrast leaked onto CT detector created peripheral dark artifacts mimicking stroke on cranial exams. Confirmed via phantom; radiologists must recognize this scanner-based artifact for quality control and to avoid misdiagnosis.

AJNR. American journal of neuroradiology
Body / AbdominalNuclear / MolecularAI / InformaticsResearch

DCE-MRI habitat fusion model accurately predicts microvascular invasion in liver cancer

A transformer-based model combining DCE-MRI habitat and conventional radiomics with clinical predictors achieved an AUC of 0.923 (95% CI 0.858-0.988) for predicting microvascular invasion in hepatocellular carcinoma, and stratified recurrence-free survival (p=0.033).

Journal of hepatocellular carcinoma
Body / AbdominalMusculoskeletal (MSK)AI / InformaticsResearch

AI-derived vertebral bone density and paraspinal muscle-fat metrics improve vertebral fracture detection in breast cancer survivors on routine CT

In breast cancer survivors, AI-derived vertebral bone density (vBMD) and paraspinal muscle-fat ratio on routine CT helped identify moderate-severe vertebral fractures. AI-vBMD AUC 0.738, adding muscle-fat ratio improved AUC to 0.786, full model AUC 0.828.

Journal of clinical medicine
Chest / ThoracicGeneralAI / InformaticsNews

Expertise and Model Confidence Key to Safe Radiologist-LLM Interaction

In a chest imaging study, reader expertise (odds ratio 2.06) and high model confidence (OR 3.82) were independently associated with correct radiologist-large language model collaboration. However, expert readers were less influenced by model confidence, and high rationale qualit…

Radiology Business
GeneralEducationBriefTrainee

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