Aims: The objectives of the present study are to describe the algorithm for VH(®) IVUS using the 45-MHz rotational IVUS catheter and the associated ex vivo validation in comparison to the gold standard histology.
Methods And Results: The first phase of the present study was to construct the 45 MHz VH IVUS algorithm by using a total of 55 human coronary artery specimens [111 independent coronary lesions and 510 homogenous regions of interest (ROIs)], obtained at autopsy. Regions were selected from histology and matched with their corresponding IVUS data to build the plaque classification system using spectral analysis and statistical random forests. In the second phase, the ex vivo validation of the VH IVUS algorithm assessed a total of 1060 ROIs (120 lesions from 60 coronary arteries) in comparison with histology. In an independent manner, two interventional cardiologists also classified a randomly selected subset of the ROIs for assessment of inter- and intra-observer reproducibility of VH IVUS image interpretation.When including all ROIs, the predictive accuracies were 90.8% for fibrous tissue, 85.8% for fibro fatty tissue, 88.3% for necrotic core, and 88.0% for dense calcium. The exclusion of ROIs in the acoustically attenuated areas improved the predictive accuracies, ranging from 91.9 to 96.8%. The independent analysis of randomly selected 253 ROIs showed substantial agreement for inter-observer (k = 0.66) and intra-observer (k = 0.88) reproducibility.
Conclusion: Tissue classification by 45 MHz VH IVUS technology, when not influenced by calcium-induced acoustic attenuation, provided combined tissue accuracy >88% to identify tissue types compared with the gold standard histologic assessment, with high inter- and intra-observer reproducibility.
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http://dx.doi.org/10.1093/ehjci/jev039 | DOI Listing |
mRNA delivery offers new opportunities for disease treatment by directing cells to produce therapeutic proteins. However, designing highly stable mRNAs with programmable cell type-specificity remains a challenge. To address this, we measured the regulatory activity of 60,000 5' and 3' untranslated regions (UTRs) across six cell types and developed PARADE (Prediction And RAtional DEsign of mRNA UTRs), a generative AI framework to engineer untranslated RNA regions with tailored cell type-specific activity.
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Department of Assisted Reproduction, Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai, China.
Manual semen evaluation methods are subjective and time-consuming. In this study, a deep learning algorithmic framework was designed to enable non-invasive multidimensional morphological analysis of live sperm in motion, improve current clinical sperm morphology testing methods, and significantly contribute to the advancement of assisted reproductive technologies. We improved the FairMOT tracking algorithm by incorporating the distance and angle of the same sperm head movement in adjacent frames, as well as the head target detection frame IOU value, into the cost function of the Hungarian matching algorithm.
View Article and Find Full Text PDFAnal Cell Pathol (Amst)
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Circular RNAs (circRNAs), covalently closed single-stranded RNAs, have been implicated in cancer progression. A previous investigation revealed that circ-ZEB1 is expressed abnormally in liver cancer. However, the roles of circ-ZEB1 in non-small cell lung cancer (NSCLC) are unknown.
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