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Background: Coronary computed tomography angiography (CTA) and optical coherence tomography (OCT) provide additional functional information beyond the anatomy by applying computational fluid dynamics (CFD). This study sought to evaluate a novel approach for estimating computational fractional flow reserve (FFR) from coronary CTA-OCT fusion images.
Methods: Among patients who underwent coronary CTA, 148 patients who underwent both pressure wire-based FFR measurement and OCT during angiography to evaluate intermediate stenosis in the left anterior descending artery were included from the prospective registry. Coronary CTA-OCT fusion images were created, and CFD was applied to estimate computational FFR. Based on pressure wire-based FFR as a reference, the diagnostic performance of Fusion-FFR was compared with that of CT-FFR and OCT-FFR.
Results: Fusion-FFR was strongly correlated with FFR ( = 0.836, < 0.001). Correlation between FFR and Fusion-FFR was stronger than that between FFR and CT-FFR ( = 0.682, < 0.001; z statistic, 5.42, < 0.001) and between FFR and OCT-FFR ( = 0.705, < 0.001; z statistic, 4.38, < 0.001). Area under the receiver operating characteristics curve to assess functionally significant stenosis was higher for Fusion-FFR than for CT-FFR (0.90 vs. 0.83, = 0.024) and OCT-FFR (0.90 vs. 0.83, = 0.043). Fusion-FFR exhibited 84.5% accuracy, 84.6% sensitivity, 84.3% specificity, 80.9% positive predictive value, and 87.5% negative predictive value. Especially accuracy, specificity, and positive predictive value were superior for Fusion-FFR than for CT-FFR (73.0%, = 0.007; 61.4%, < 0.001; 64.0%, < 0.001) and OCT-FFR (75.7%, = 0.021; 73.5%, = 0.020; 69.9%, = 0.012).
Conclusion: CFD-based computational FFR from coronary CTA-OCT fusion images provided more accurate functional information than coronary CTA or OCT alone.
Clinical Trial Registration: [www.ClinicalTrials.gov], identifier [NCT03298282].
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http://dx.doi.org/10.3389/fcvm.2022.925414 | DOI Listing |
Pathol Res Pract
September 2025
Department of Pathology, Xijing Hospital and School of Basic Medicine, Fourth Military Medical University, Xi'an, China. Electronic address:
Background: Dermal clear cell sarcoma (DCCS) is a rare malignant mesenchymal neoplasm. Owing to the overlaps in its morphological and immunophenotypic profiles with a broad spectrum of tumors exhibiting melanocytic differentiation, it is frequently misdiagnosed as other tumor entities in clinical practice. By systematically analyzing the clinicopathological characteristics, immunophenotypic features, and molecular biological properties of DCCS, this study intends to further enhance pathologists' understanding of this disease and provide a valuable reference for its accurate diagnosis.
View Article and Find Full Text PDFPLoS One
September 2025
Department of Smart Manufacturing, Industrial Perception and Intelligent Manufacturing Equipment Engineering Research Center of Jiangsu Province, Nanjing Vocational University of Industry Technology, Nanjing, Jiangsu, China.
In the field of quality control, metal surface defect detection is an important yet challenging task. Although YOLO models perform well in most object detection scenarios, metal surface images under operational conditions often exhibit coexisting high-frequency noise components and spectral aliasing background textures, and defect targets typically exhibit characteristics such as small scale, weak contrast, and multi-class coexistence, posing challenges for automatic defect detection systems. To address this, we introduce concepts including wavelet decomposition, cross-attention, and U-shaped dilated convolution into the YOLO framework, proposing the YOLOv11-WBD model to enhance feature representation capability and semantic mining effectiveness.
View Article and Find Full Text PDFACS Nano
September 2025
State Key Laboratory of Chemo and Biosensing, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, China.
Optical imaging offers high sensitivity and specificity for noninvasive cancer detection, but conventional techniques suffer from limited probe accumulation, tissue autofluorescence, and poor depth resolution. Afterglow luminescence overcomes autofluorescence by emitting persistent light after excitation, yet its utility in vivo remains hindered by weak tumor enrichment and two-dimensional readouts lacking spatial context. Here, we report luminescent-magnetic nanoparticles (LM-NPs) coencapsulating luminescent trianthracene (TA) molecules and iron oxide cores within the amphiphilic polymer pluronic-F127.
View Article and Find Full Text PDFHum Brain Mapp
September 2025
Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, Georgia, USA.
Investigating neuroimaging data to identify brain-based markers of mental illnesses has gained significant attention. Nevertheless, these endeavors encounter challenges arising from a reliance on symptoms and self-report assessments in making an initial diagnosis. The absence of biological data to delineate nosological categories hinders the provision of additional neurobiological insights into these disorders.
View Article and Find Full Text PDFJ Biomed Opt
September 2025
Leibniz University Hannover, Hannover Centre for Optical Technologies, Hannover, Germany.
Significance: Melanoma's rising incidence demands automatable high-throughput approaches for early detection such as total body scanners, integrated with computer-aided diagnosis. High-quality input data is necessary to improve diagnostic accuracy and reliability.
Aim: This work aims to develop a high-resolution optical skin imaging module and the software for acquiring and processing raw image data into high-resolution dermoscopic images using a focus stacking approach.