Purpose: To compare image quality and patient radiation dose in a group of patients who underwent 64-detector computed tomography (CT) coronary angiography performed with prospective electrocardiographic (ECG) gating with image quality and radiation dose in a group of patients matched for clinical features who underwent 64-detector CT coronary angiography performed with retrospective ECG gating.
Materials And Methods: Institutional review board approval was obtained for this HIPAA-compliant study, and the informed consent requirement was waived due to the retrospective study design. Two independent reviewers separately scored coronary artery segment image quality and overall image quality for 100 cardiac CT studies (50 in each group). Interobserver variability was calculated. Patient radiation dose for the actual examination z-axis length was recorded, and a normalized dose was calculated for a 12-cm z-axis length of a typical heart.
Results: The two groups matched well for clinical characteristics and CT parameters. There was good agreement for coronary artery segment image quality scores between the independent reviewers (kappa = 0.72). Of the 1253 coronary artery segments scored, the number of coronary artery segments that could not be evaluated in each group was similar (1.1% [seven of 614] in the prospective group vs 1.5% [10 of 647] in the retrospective group, P = .53). Image quality scores were not significantly different when matched for chest cross-sectional area (P > .05). Mean patient radiation dose was 77% lower for prospective gating (4.2 mSv) than for retrospective gating (18.1 mSv) (P < .01).
Conclusion: Use of 64-detector CT coronary angiography performed with prospective ECG gating has similar subjective image quality scores but 77% lower patient radiation dose when compared with use of retrospective ECG gating.
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http://dx.doi.org/10.1148/radiol.2482072192 | DOI Listing |
Integr Environ Assess Manag
January 2025
Federal University of the Agreste of Pernambuco, Garanhuns, Brazil.
The proliferation of cyanobacteria has become a significant water management challenge due to the increasing eutrophication of water supply reservoirs. Cyanobacterial blooms thrive on elevated nutrient concentrations and form extensive green mats, disrupting the local ecosystem. Furthermore, many cyanobacterial species can produce toxins that are lethal to vertebrates called cyanotoxins.
View Article and Find Full Text PDFEnviron Sci Technol
January 2025
Intelligent Transportation Thrust, Systems Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511455, China.
Integrating mobile monitoring data with street view images (SVIs) holds promise for predicting local air pollution. However, algorithms, sampling strategies, and image quality introduce extra errors due to a lack of reliable references that quantify their effects. To bridge this gap, we employed 314 taxis to monitor NO, NO, PM, and PM, and extracted features from ∼382,000 SVIs at multiple angles (0°, 90°, 180°, 270°) and buffer radii (100-500 m).
View Article and Find Full Text PDFJ Neuroophthalmol
January 2025
Department of Ophthalmology (JGJ-C, TE, Y-HC, LRD, RAG), Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts; Frank H. Netter Medical School (JGJ-C), North Haven, Connecticut; and Department of Anesthesiology (DZ), Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts.
Background: Patients with craniosynostosis are at high risk of developing elevated intracranial pressure (ICP) causing papilledema and secondary optic atrophy. Diagnosing and monitoring optic neuropathy is challenging because of multiple causes of vision loss including exposure keratopathy, amblyopia, and cognitive delays that limit examination. Peripapillary hyperreflective ovoid mass-like structures (PHOMS) are an optical coherence tomography (OCT) finding reported in association with papilledema and optic neuropathy.
View Article and Find Full Text PDFEur Radiol
January 2025
Department of Urological Surgical, JiangNan University Medical Center, Wuxi, China.
Objective: To conduct a meta-analysis assessing the diagnostic performance of the node reporting and data system (Node-RADS) for detecting lymph node (LN) invasion.
Method: We performed a systematic literature search of online scientific publication databases from inception up to July 31, 2024. We used the quality assessment of diagnostic accuracy studies-2 (QUADAS-2) to assess the study quality, and heterogeneity was determined by the Q-test and measured with I statistics.
Eur J Nucl Med Mol Imaging
January 2025
Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Spitalgasse 23, Vienna, 1090, Austria.
Purpose: Advancements of deep learning in medical imaging are often constrained by the limited availability of large, annotated datasets, resulting in underperforming models when deployed under real-world conditions. This study investigated a generative artificial intelligence (AI) approach to create synthetic medical images taking the example of bone scintigraphy scans, to increase the data diversity of small-scale datasets for more effective model training and improved generalization.
Methods: We trained a generative model on Tc-bone scintigraphy scans from 9,170 patients in one center to generate high-quality and fully anonymized annotated scans of patients representing two distinct disease patterns: abnormal uptake indicative of (i) bone metastases and (ii) cardiac uptake indicative of cardiac amyloidosis.
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