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Paul Davis

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Lung Cancer
CT
Stepped reminders boost CT lung cancer screening
Trial findings directly address the current lack of effective lung cancer screening interventions.
Example cases illustrate the double-edged role of large language model (LLM) rationale quality. (A) A 50-year-old female patient with a palpable anterior chest wall mass (correct diagnosis: solitary fibrous tumor of the pleura). The LLM incorrectly suggested synovial sarcoma but provided a persuasive rationale (quality score: 4 of 5), describing a well-defined nodule at axial contrast-enhanced CT spanning the pleura and intercostal space with heterogeneous strong enhancement. Four of five readers (80%) accepted the incorrect suggestion. FDG = fluorodeoxyglucose. (B) A 61-year-old male patient with diabetes presented with cough, sputum, and dyspnea (correct diagnosis: mucormycosis). The LLM correctly suggested mucormycosis with an excellent rationale (quality score: 5 of 5), integrating the reverse halo sign on serial axial CT images and rapidly progressive cavitary lesions. Three of five readers initially selected incorrect diagnoses; after LLM output, all five selected the correct diagnosis (100% acceptance). Blue and orange reader icons denote high- and low-expertise readers, respectively.
AI
Model confidence, reader expertise affect reader-LLM collaboration
Ga-68 HER2-PET/CT images before neoadjuvant therapy, at end of second cycle, and before surgery. (A) Baseline scan demonstrated soft-tissue lesion measuring approximately 2.3 × 2.2 cm in upper outer quadrant of left breast, with marked radiotracer uptake and SUVmax of 10.1. (B) At end of second cycle, imaging revealed residual lesion of approximately 2.2 × 1.0 cm in same region, without abnormal radiotracer accumulation. (C) Preoperative imaging demonstrated further reduction in lesion size to approximately 2.0 × 0.6 cm, with no abnormal tracer uptake detected.
Molecular Imaging
PET/CT predicts response to neoadjuvant therapy in breast cancer
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MRI
5 factors that led to California workplace MRI accident
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VLMs miss most lung nodules on chest x-rays
By Will Morton
Findings indicate poor performance of six VLMs for lung nodule detection on chest x-rays.
August 6, 2026
Chatgpt2
Patient-friendly radiology reports improve family comprehension
By Will Morton
Terminology in radiology reports can be difficult for patients and families to comprehend.
August 5, 2026
Pediatric Imaging
Early CTA leads to improved stroke outcomes for patients with BCVI
By Amerigo Allegretto
Early CTA is linked to reduced stroke, decreased complications, and reduced intensive care unit length of stay.
August 5, 2026
Ct Scanner 400
Most histotripsy procedures used for metastatic disease treatment
By Amerigo Allegretto
Trends suggest that histotripsy has low rates of procedure-related complications and is mostly performed in outpatient settings.
August 5, 2026
Liver Cancer 400
Imaging turnaround times continued to climb in 2024
By Erik L. Ridley
The largest increases were found in ultrasound and x-ray.
August 4, 2026
Radiologist Computer Screen X Ray
DBT-based foundational model classifies breast density
By Amerigo Allegretto
DBT-DINO showed strong performance in classifying breast density from DBT images.
August 4, 2026
(A) Free-response receiver operating characteristic (FROC) curve for DBT-DINO and DINOv2 (Meta AI) on the detection task. DINOv2 achieved higher sensitivity than DBT-DINO across most false-positive thresholds. (B) Detection rates of DBT-DINO and DINOv2 for lesions that were ultimately found to be benign (n = 70) and lesions that were found to be cancerous (n = 66). Error bars represent 95% CIs estimated via patient-level bootstrapping with 1000 repetitions. Both models showed similar detection rates for cancerous lesions, whereas DINOv2 detected more benign lesions than DBT-DINO. (C) Example bounding box predictions for DBT-DINO and DINOv2 on the detection test set. Each image is a single two-dimensional section from a three-dimensional digital breast tomosynthesis volume; the first column shows a mediolateral oblique view, and the second and third columns show craniocaudal views. Both models struggled to detect very small lesions, such as the 3-mm-diameter lesion shown in the first column. FP = false positive.
Liebel-Flarsheim recalls Optiray CT contrast agent
By AuntMinnie.com staff writers
The CT contrast agent may contain particulate matter comprising polyethylene, other plastic materials, stainless steel, and glass.
August 4, 2026
Ct Contrast
Can LLMs fill the communication gap with referring clinicians?
By Will Morton
LLMs could potentially help address multiple persistent pain points in radiology workflow.
August 4, 2026
Ai Head
CT-selected thrombectomy shows 1-year benefit in large-core stroke
By Will Morton
Notably, the TESLA trial used a noncontrast CT (NCCT)-alone patient selection protocol.
August 3, 2026
Aneurysm
MRI-based AI model maps local brain aging
By Amerigo Allegretto
The model showed differences in brain structures for normal cognition, mild cognitive impairment, and Alzheimer’s disease.
August 3, 2026
Mri Scan Brain
Curium to acquire Lantheus in $8 billion deal
By AuntMinnie.com staff writers
The combined company would serve oncology, neurology, and cardiology patients across more than 70 countries.
August 3, 2026
Cash Bills
Surveillance imaging doesn't improve pancreatic cancer survival
By Amerigo Allegretto
Study authors are calling for better strategies for early detection and intervention for pancreatic cysts that become malignant.
August 3, 2026
A.) Rate of imaging utilization during surveillance by year, 2008 to 2022. B.) Rate of endoscopic ultrasound (EUS) and pancreatic surgery per 100 person years, 2008 to 2022.
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