The 2026 Chinese lung cancer guideline adds AI and opportunistic screening in low-dose CT, expands molecular testing, and updates treatment regimens for NSCLC, including perioperative, consolidation immunotherapy, and targeted therapy for EGFR, ALK, KRAS, HER2, and MET alteratio…
On 76 test cases, the AI framework achieved Cobb angle MAE 2.4°, Lenke curve type accuracy 0.895, and reduced review time from 8.2 to 1.5 min/case.
An AI model (EAGLE) analyzing noncontrast chest CT achieved 90.0% sensitivity for esophageal cancer and 98.5% specificity in external multicenter testing (11,466 patients), and 99.94% specificity in low-dose screening. Could enable opportunistic esophageal cancer screening.
PSAD remained below 0.11 ng/mL² across all ages in 1037 healthy German men, contrasting with continuously rising PSA. 95th percentile reference: PV 51.39 mL, PSA 2.79 ng/mL, PSAD 0.071 ng/mL².
In a phantom, metal artefact reduction (MAR) restored analysability of coronary artery calcium near pacemaker leads, and deep learning reconstruction (DLR) yielded lowest artefact and CT offset. MAR had minimal effect without metal present.
MRI in three children with juvenile Huntington disease revealed severe bilateral caudate and lentiform atrophy with T2/FLAIR hyperintensity; SWI showed globus pallidus mineral deposition in two, and one had mild thoracic spinal cord thinning. Findings highlight consistent basal…
In 26 patients with periventricular hemorrhagic moyamoya disease, three microangioarchitectural features of target collateral vessels were present in 92.3% of hemorrhagic hemispheres vs 25.0% of contralateral non-hemorrhagic hemispheres (P=0.80). These patterns require longitudi…
In MS patients, intra-soma signal fraction (fis) on high-gradient diffusion MRI was decreased in atrophy-prone gray matter, and correlated with disability (EDSS, ρ=-0.44, p<0.05), suggesting network-based neurodegeneration.
A scoping review of 36 studies found no interventional radiology (IR) curriculum for medical students addressed all six steps of Kern's framework; they focused on problem identification and teaching strategies but lacked needs assessment and evaluation.
A machine reasoning framework with rejection option reduced false positives and anatomically implausible errors in CT kidney segmentation, while preserving acceptance of valid outputs. Robustness persisted under noise.
A deep learning model combining YOLOv10 region-of-interest detection and transformer fusion classified osteoporosis, osteopenia, and normal on knee radiographs with 98.87% accuracy and 98.23% AUC.
A self-supervised physics-guided deep learning framework transformed clinical T1w, T2w, FLAIR MRI into quantitative T1, T2, PD maps in >600 test sessions, showing scanner invariance (inter-group CV ≤1.1%) and high voxel-wise reproducibility (T1/T2 correlation >0.82).
A multistage deep learning model detected pelvic active bleeding on CT with an AUC of 0.901 and accuracy of 77.5%, matching specialists and outperforming residents (inference time 1.93 s).
Deep-learning system using pre/post neoadjuvant chemotherapy DCE-MRI and clinical data predicted residual tumor burden with AUCs 0.8885 internal, 0.8628 external, 0.8695 I-SPY2; NAC response AUCs 0.8400/0.8299; subtype AUCs 0.8066/0.7748/0.7661 in 1,515 patients.
FDA grants 510(k) clearance to Gleamer's ChestView US 1.1, a lung ultrasound device (product code MYN, Radiology committee).
The U.S. FDA has posted a 510(k) clearance for ReVISION 2 from Argus Cognitive, Inc., listing it as a radiology device under product code QIH.
An interpretable ensemble learning model using intratumoral & peritumoral MR-radiomics predicted high-grade cervical cancer with LVSI (HGVI), AUC 0.858 (95% CI 0.762-0.932) in the test set. SHAP analysis showed ADC_peritumoral_3mm as a top contributor.
CT attenuation-defined regional radiomics differentiated well-differentiated from dedifferentiated retroperitoneal liposarcoma with out-of-fold AUC 0.864 (95% CI 0.778-0.940) but did not significantly outperform quantitative CT (AUC 0.849; adjusted P=0.389).
In LVO stroke, a clinical-CT model predicted 90-day outcome (AUC 0.939 in CV), but adding CT imaging score to clinical variables (age, NIHSS, onset-to-CT time) did not significantly improve discrimination in testing (ΔAUC 0.0078, 95% CI -0.0071–0.0227, p=0.305).
A LASSO model identified interstitial lung disease (ILD) in Japanese cancer patients: sensitivity 33.5% (external 19.8%), specificity 99.3% (99.4%), positive predictive value (PPV) 76.7% (65.5%). High PPV aids case confirmation despite low sensitivity.
On MIMIC-CXR, a Siamese network using paired chest radiographs outperformed a single-image model for detecting resolved vs absent findings (AUROC up to 0.87 vs chance 0.45-0.60), demonstrating the value of prior images for longitudinal change detection.
New prospective research reveals about (177Lu)Lu-PSMA-I&T for patients with mCRPC.
Ketamine offers better sedation option than fentanyl in IR
AI model OccuNet detected 94.7% of femoral neck fractures initially missed or deemed indeterminate on radiographs, compared with 86.2% for musculoskeletal radiologists and 68.8% for emergency physicians. Overall sensitivity 97.5%, specificity 98.8%.
Paget's Disease Mimicking Metastasis: A Diagnostic Pitfall
<![CDATA[The Reading Room Podcast: Assessing the Current Landscape of AI and Reimbursement in Radiology, Part 1]]>
RSNA Explores Role of APPs to Address Workforce Challenges
GEHC submits StarGuide GX digital SPECT/CT for FDA clearance
Podcast: MRI safety experts shed light on wishy-washy leadership
Siemens integrates Vuze spinal guidance software into Cios Spin
Mount Nittany Health Employer Profile
What’s the differential diagnosis for this abdominal mass? #foamrad #radiology #ultrasound #ctscan
Harrison.ai lays off staff at home as it pivots to US teleradiology with AI-powered Frontier Radiology, offering 30% productivity gains and 25% bonuses for AI-assisted reads.
Deep learning architectures (CNNs, vision transformers, GANs) now enable advanced medical image interpretation and synthesis, and multimodal foundation models integrating imaging, text, and genomics are emerging, per a narrative review.
