ABSTRACT
Purpose: Determination and development of an effective set of models leveraging Artificial Intelligence techniques to generate a system able to support clinical practitioners working with COVID-19 patients. It involves a pipeline including classification, lung and lesion segmentation, as well as lesion quantification of axial lung CT studies. Approach: A deep neural network architecture based on DenseNet is introduced for the classification of weakly-labeled, variable-sized (and possibly sparse) axial lung CT scans. The models are trained and tested on aggregated, publicly available data sets with over 10 categories. To further assess the models, a data set was collected from multiple medical institutions in Colombia, which includes healthy, COVID-19 and patients with other diseases. It is composed of 1,322 CT studies from a diverse set of CT machines and institutions that make over 550,000 slices. Each CT study was labeled based on a clinical test, and no per-slice annotation took place. This enabled a classification into Normal vs. Abnormal patients, and for those that were considered abnormal, an extra classification step into Abnormal (other diseases) vs. COVID-19. Additionally, the pipeline features a methodology to segment and quantify lesions of COVID-19 patients on the complete CT study, enabling easier localization and progress tracking. Moreover, multiple ablation studies were performed to appropriately assess the elements composing the classification pipeline. Results: The best performing lung CT study classification models achieved 0.83 accuracy, 0.79 sensitivity, 0.87 specificity, 0.82 F1 score and 0.85 precision for the Normal vs. Abnormal task. For the Abnormal vs COVID-19 task, the model obtained 0.86 accuracy, 0.81 sensitivity, 0.91 specificity, 0.84 F1 score and 0.88 precision. The ablation studies showed that using the complete CT study in the pipeline resulted in greater classification performance, restating that relevant COVID-19 patterns cannot be ignored towards the top and bottom of the lung volume. Discussion: The lung CT classification architecture introduced has shown that it can handle weakly-labeled, variable-sized and possibly sparse axial lung studies, reducing the need for expert annotations at a per-slice level. Conclusions: This work presents a working methodology that can guide the development of decision support systems for clinical reasoning in future interventionist or prospective studies.
ABSTRACT
Ascorbic acid (AC) used as antioxidant in embryo culture is very sensitive and degrades unavoidably in aqueous solution. Methyl-ß-cyclodextrin (CD) improved the stability of AC in solution to elevated temperature, light, humidity and oxidation. The aim of this study was to evaluate the effect of the complex AC-CD during in vitro maturation (IVM) or in vitro culture (IVC) on oocyte developmental competence and subsequent embryo development and quality. AC-CD (100 µM) was added to IVM media, and maturation level and embryo development were examined. Matured oocytes, their cumulus cells and produced blastocysts were snap-frozen for gene expression analysis by RT-qPCR. Besides, in vitro-produced zygotes were cultured with 100 µM of AC-CD and blastocysts were as well snap-frozen for gene expression analysis. A group without AC-CD (control- ) and other with CD (control+ ) were included. No differences were found on maturation, cleavage or blastocyst rates. However, in matured oocytes, AC-CD downregulated BAX, GPX1 and BMP15. In cumulus cells, AC-CD downregulated BAX/BCL2 and GSTA4 while upregulated BCL2 and CYP51A1. The expression of SL2A1, FADS1, PNPLA and MTORC1 was downregulated in blastocysts derived from oocytes matured with AC-CD, while in blastocysts derived from zygote cultured with AC-CD, CYP51A1 and IGF2R were downregulated and PNPLA2 was upregulated. In conclusion, AC-CD in both IVM and IVC media may reduce accumulated fat by increasing lipolysis and suppressing lipogenesis in blastocysts derived from both oocytes and zygotes cultured with AC-CD, suggesting that CD improves the quality of embryos and bioavailability of AC during IVM and IVC.
