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.
Colorado Imaging Associates and TRA Medical Imaging form Affiliated Radiology, a physician-led network of nearly 200 radiologists, to share picture archiving and communication systems, AI, and cross-reading capacity across the Pacific Northwest and Rocky Mountain regions.
Allegheny Health Network (AHN) Employer Profile
Increasing tube voltage (kVp) reduces patient dose when detector exposure is held constant. Higher energy photons penetrate better, so mAs can be lowered, reducing total photon output despite each photon carrying more energy.
In a retrospective study, contrast-enhanced cone-beam breast CT (CE-CBBCT) features differentiated DCIS from invasive lesions (AUC 0.785 in validation) and DCIS with microinvasion from invasive ductal carcinoma (AUC 0.817). External validation needed.
In children after CDH repair, those requiring ECMO had higher RV/LV ratio and eccentricity index at 2-year MRI, suggesting persistent pulmonary hypertension. These normalized by 10 years. ECMO independently predicted elevated EI (OR 7.68, 95% CI 1.93–30.47).
BI-RADS v2025 formally incorporates nonmass lesions (NMLs) on breast ultrasound, which have a high malignancy rate. A pictorial review classifies NMLs by distribution—segmental, linear, focal, regional—showing benign/malignant cases, descriptors, and multimodality correlation.
Beyond the Score: Turning PI-QUAL Into Practice.
The Importance of Defining "Optimal" When Determining Thresholds.
Turfing TURPs: Should We Use MRI to Triage Incidental Low-Grade Prostate Cancer?
Specimen [18F]FDG PET/CT for Assessing Intraoperative Margins in Early-Stage Breast Cancer: A Promising Emerging Technology.
How Radiologists Can Use These Tips for Reporting ARIA on MRI in Daily Practice.
Predicting 5-Year Breast Cancer Risk From Longitudinal Digital Breast Tomosynthesis: What to Tell Patients.
Is Your Daily Workflow Inviting a Cyberattack?
Pediatric AI in radiology lags behind adult applications due to scarce data, off-label use, and regulatory gaps. An AJR expert panel recommends a roadmap to establish dedicated pediatric AI infrastructure and standards, emphasizing diagnostic accuracy, workflow efficiency, and p…
Myocardial Perfusion Imaging: Point-PET Should Replace SPECT as the Standard of Care.
A rubric to assess artificial intelligence (AI)-generated patient-friendly radiology reports was developed. Lay & radiologist raters (n=3 each) had near-perfect agreement (α=0.87). Reports scored 1 on any attribute (except verbosity) were deemed unsafe.
Myocardial Perfusion Imaging: Counterpoint-SPECT Still Plays an Essential Role, and PET Should Be Used in Select Cases Only.
A deep learning model combining pretreatment mammograms and clinical data predicted breast cancer recurrence with an AUC of 0.80 (95% CI 0.74-0.85) in a single-center cohort of 3923 patients, outperforming unimodal approaches.
VA survey: 95% of primary care clinicians and radiologists preferred lung screening incidental findings be reported in the radiology report, not direct contact. Most primary care clinicians also wanted them on baseline and follow-up exams, despite ACR guidance to report only new…
In a real-world lung cancer screening cohort (n=129), AI computer-aided detection (CADe) had 72% sensitivity for malignant nodules on CT, vs 92% for vessel-suppressed images. CADe sensitivity was 38% for ground-glass and 13% for cystic nodules (P<0.001). Subpleural/paramediastin…
Interpretable Machine Learning for Gallbladder Cancer Risk Assessment: From Predictive Performance to Clinical Utility.
AI-based CT quantification in SSc-ILD now moves beyond visual scoring to outcome-oriented biomarkers; deep-learning UIP probability stratifies FVC decline and survival, supporting human-in-the-loop decision support.
An integrated model combining carotid Plaque-RADS, degree of stenosis, and ancillary features (plaque burden, remodeling index, enhancement ratio, perivascular fat density) predicted symptomatic plaques with AUC 0.876 (95% CI: 0.828–0.924), and 0.919 in moderate stenosis subgrou…
Systematic review of 101 studies finds LLM-generated medical reports show moderate acceptance but persistent clinically significant errors and mixed workflow effects; evidence too heterogeneous to support autonomous use, requiring clinician supervision.
In a multicenter study of NSCLC, a PET/CT radiomics model predicted lymph node metastasis with AUC 0.845 (95% CI 0.716–0.973) and PD-L1 expression with AUC 0.776 (95% CI 0.641–0.911) from a single preoperative scan.
In an external validation cohort of 69 brain metastasis patients, a T1 postcontrast MRI radiomics model achieved a C-index of 0.574 (95% CI 0.491-0.658) for overall survival prediction, suggesting limited standalone discrimination.
Deep learning denoising of accelerated 3D T1-weighted brain MRI with transfer-learning fine-tuning or self-supervised Self2Self-AM achieved structural similarity index 0.943, cortical thickness discrepancy 0.16 mm, Dice 0.986, beating conventional denoising.
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…
