American Journal of Roentgenology最新文献

BACKGROUND: Radiologists generally treat pediatric ileocolic intussusceptions emergently given potential worse outcomes from delayed reduction attempts. However, relevant literature is conflicting. OBJECTIVE: To identify factors associated with successful image-guided ileocolic intussusception reduction in children, with attention to the time interval since diagnosis. METHODS: This retrospective study included patients <6 years old who underwent attempted image-guided enema reduction of ileocolic intussusception between May 2009 and July 2023. Patients were separated into two groups: those presenting directly to the institution (nontransferred patients, who all underwent attempted reduction <8 hours after ultrasound diagnosis), and those transferred from outside facilities. EHR data were extracted. Each patient's first image-guided reduction attempt was classified as successful or unsuccessful. Univariable and multivariable analyses were performed. RESULTS: The study included 1065 patients (649 male, 416 female; mean age, 18.1 months; age range, 2.2-71.0 months; 793 nontransferred and 272 transferred patients). In nontransferred patients, the mean interval between ultrasound diagnosis and reduction attempt was 150.8 minutes; in transferred patients, the mean interval between outside facility advanced imaging and reduction attempt was 460.1 minutes (p<.001). Successful reduction occurred in 84.6% and 81.6% of nontransferred and transferred patients, respectively (p=.25). In nontransferred patients, success occurred in 85.6% of attempts <2 hours after diagnosis versus 84.0% of attempts 2-<8 hours after diagnosis (p=.54); the mean interval from diagnosis to attempted reduction was 149.7 minutes and 156.8 minutes for successful and unsuccessful attempts, respectively (p=.53). In multivariable analysis, factors showing independent associations with success were proximal intussusception location (OR=3.63, p<.001) and absence of high-risk ultrasound findings (OR=2.57, p<.001); success was not independently associated with age, sex, bloody stools, reduction method, or time since diagnosis <2 hours (p>.05). In transferred patients, the mean interval from outside advanced imaging to attempted reduction was 463.1 minutes and 440.2 minutes for successful and unsuccessful attempts, respectively (p=.74). CONCLUSION: Intussusception reduction may not require completion emergently (within 2 hours after diagnosis), but potentially may be safely performed on an urgent basis (within 8 hours). CLINICAL IMPACT: The findings have implications for determining the standard of care, including criteria for oncall activation of radiologic resources, in pediatric intussusception management.

Background: Although radiology reports are commonly used for lung cancer staging, this task can be challenging given radiologists' variable reporting styles as well as reports' potentially ambiguous and/or incomplete staging-related information. Objective: To compare performance of ChatGPT large-language models (LLMs) and human readers of varying experience in lung cancer staging using chest CT and FDG PET/CT free-text reports. Methods: This retrospective study included 700 patients (mean age, 73.8±29.5 years; 509 male, 191 female) from four institutions in Korea who underwent chest CT or FDG PET/CT for non-small cell lung cancer initial staging from January, 2020 to December, 2023. Examinations' reports used a free-text format, written exclusively in English or in mixed English and Korean. Two thoracic radiologists in consensus determined the overall stage group (IA, IB, IIA, IIB, IIIA, IIIB, IIIC, IVA, IVB) for each report using the AJCC 8th-edition staging system, establishing the reference standard. Three ChatGPT models (GPT-4o, GPT-4, GPT-3.5) determined an overall stage group for each report using a script-based application programming interface, zero-shot learning, and prompt incorporating a staging system summary. Six human readers (two fellowship-trained radiologists with lesser experience than the radiologists who determined the reference standard, two fellows, two residents) also independently determined overall stage groups. GPT-4o's overall accuracy for determining the correct stage among the nine groups was compared with that of the other LLMs and human readers using McNemar tests. Results: GPT-4o had an overall staging accuracy of 74.1%, significantly better than the accuracy of GPT-4 (70.1%, p=.02), GPT-3.5 (57.4%, p<.001), and resident 2 (65.7%, p<.001); significantly worse than the accuracy of fellowship-trained radiologist 1 (82.3%, p<.001) and fellowship-trained radiologist 2 (85.4%, p<.001); and not significantly different from the accuracy of fellow 1 (77.7%, p=.09), fellow 2 (75.6%, p=.53), and resident 1 (72.3%, p=.42). Conclusions: The best-performing model, GPT-4o, showed no significant difference in staging accuracy versus fellows, but significantly worse performance versus fellowship-trained radiologists. The findings do not support use of LLMs for lung cancer staging in place of expert healthcare professionals. Clinical Impact: The findings indicate the importance of domain expertise for performing complex specialized tasks such as cancer staging.

By exploiting different tissues' characteristic T₁ relaxation times, T₁-weighted images help distinguish normal and abnormal tissues, aiding assessment of diffuse and local pathologies. However, such images do not provide quantitative T₁ values. Advances in abdominal MRI techniques have enabled measurement of abdominal organs' T₁ relaxation times, which can be used to create color-coded quantitative maps. T₁ mapping is sensitive to tissue microenvironments including inflammation and fibrosis and has received substantial interest for noninvasive imaging of abdominal organ pathology. In particular, quantitative mapping provides a powerful tool for evaluation of diffuse disease by making apparent changes in T₁ occurring across organs that may otherwise be difficult to identify. Quantitative measurement also facilitates sensitive monitoring of longitudinal T₁ changes. Increased T₁ in liver helps to predict parenchymal fibro-inflammation, in pancreas is associated with reduced exocrine function from chronic or autoimmune pancreatitis, and in kidney is associated with impaired renal function and aids diagnosis of chronic kidney disease. In this review, we describe the acquisition, postprocessing, and analysis of T₁ maps in the abdomen and explore applications in liver, spleen, pancreas, and kidney. We highlight practical aspects of implementation and standardization, technical pitfalls and confounding factors, and areas of likely greatest clinical impact.