Abstract:The risk to maternal-foetal health due to multiple pregnancies can be decreased by reducing the number of transferred embryos. Therefore, new tools for selecting embryos with the highest implantation potential should be developed. The aim of this study is to evaluate the predictive implantation ability of morphological and morphometric variables by analyzing images of embryos. This is a retrospective study of 135 embryo photographs from 112 IVF-ICSI cycles performed between January and March 2011. The embryos … Show more
“…Several other morphometric characteristics have been considered as predictor for developmental competence or implantation, such as zygote size, nuclear size, embryo area and perimeter, equivalent circle radius of the embryo, embryonic roundness, and zona pellucida thickness [ 48 – 50 ]. Morphometric measurements may minimize the variability among different embryologists and clinics.…”
BackgroundEmbryo selection has been based on developmental and morphological characteristics. However, the presence of an important intra-and inter-observer variability of standard scoring system (SSS) has been reported. A computer-assisted scoring system (CASS) has the potential to overcome most of these disadvantages associated with the SSS. The aims of this study were to construct a prediction model, with data mining approaches, and compare the predictive performance of models in SSS and CASS and to evaluate whether using the prediction model would impact the selection of the embryo for transfer.MethodsA total of 871 single transferred embryos between 2008 and 2013 were included and evaluated with two scoring systems: SSS and CASS. Prediction models were developed using multivariable logistic regression (LR) and multivariate adaptive regression splines (MARS). The prediction models were externally validated with a test set of 109 single transfers between January and June 2014. Area under the curve (AUC) in training data and validation data was compared to determine the utility of the models.ResultsIn SSS models, the AUC declined significantly from training data to validation data (p < 0.05). No significant difference was detected in CASS derived models. Two final prediction models derived from CASS were obtained using LR and MARS, which showed moderate discriminative capacity (c-statistic 0.64 and 0.69 respectively) on validation data.ConclusionsThe study showed that the introduction of CASS improved the generalizability of the prediction models, and the combination of computer-assisted scoring system with data mining based predictive modeling is a promising approach to improve the selection of embryo with the highest implantation potential.Electronic supplementary materialThe online version of this article (doi:10.1186/s12958-016-0145-1) contains supplementary material, which is available to authorized users.
“…Several other morphometric characteristics have been considered as predictor for developmental competence or implantation, such as zygote size, nuclear size, embryo area and perimeter, equivalent circle radius of the embryo, embryonic roundness, and zona pellucida thickness [ 48 – 50 ]. Morphometric measurements may minimize the variability among different embryologists and clinics.…”
BackgroundEmbryo selection has been based on developmental and morphological characteristics. However, the presence of an important intra-and inter-observer variability of standard scoring system (SSS) has been reported. A computer-assisted scoring system (CASS) has the potential to overcome most of these disadvantages associated with the SSS. The aims of this study were to construct a prediction model, with data mining approaches, and compare the predictive performance of models in SSS and CASS and to evaluate whether using the prediction model would impact the selection of the embryo for transfer.MethodsA total of 871 single transferred embryos between 2008 and 2013 were included and evaluated with two scoring systems: SSS and CASS. Prediction models were developed using multivariable logistic regression (LR) and multivariate adaptive regression splines (MARS). The prediction models were externally validated with a test set of 109 single transfers between January and June 2014. Area under the curve (AUC) in training data and validation data was compared to determine the utility of the models.ResultsIn SSS models, the AUC declined significantly from training data to validation data (p < 0.05). No significant difference was detected in CASS derived models. Two final prediction models derived from CASS were obtained using LR and MARS, which showed moderate discriminative capacity (c-statistic 0.64 and 0.69 respectively) on validation data.ConclusionsThe study showed that the introduction of CASS improved the generalizability of the prediction models, and the combination of computer-assisted scoring system with data mining based predictive modeling is a promising approach to improve the selection of embryo with the highest implantation potential.Electronic supplementary materialThe online version of this article (doi:10.1186/s12958-016-0145-1) contains supplementary material, which is available to authorized users.
“…1). The morphometric parameters that were measured using ‘line and oval selection tools’ are as follows: mean embryo diameter (MED), mean zona pellucida diameter (MZPD), embryo area (EA), zona pellucida area (ZPA), embryo perimeter (EP), and zona pellucida perimeter (ZPP) [19, 20]. Fig.…”
BackgroundSelenium is one of the trace minerals whose deficiency is known to lead to complications of female reproduction. The identified gaps in researches regarding selenium and pregnancy include optimizing the dosage of selenium supplementation, timing of supplementation, finding the best form and type of selenium, and selenium administration combined with other antioxidants. Hence, this study was conceptualized to address one of the identified gaps, that is, to find out the best timing of selenium administration around the time of pregnancy. Specifically, this study aimed to assess the effects of maternal Selenium-supplementation, administered at various stages of periconception period, on murine blastocyst morphology, percent occurrence of good quality blastocysts, and implantation status.MethodsICR female mice were randomly assigned into the unsupplemented group (Group I) receiving basal diet without selenium, and treatment groups given with 3.0 μg selenium-supplement per day during pregestation only (Group II), pregestation-throughout-gestation (Group III) and gestation only (Group IV). Both blastocyst morphology and implantation status were assessed.ResultsThe morphometric measurements of blastocysts appeared to be unaffected by selenium-supplementation at different stages of periconception. Selenium-supplementation at pregestation only (Group II) and gestation only (Group IV) produced higher percent occurrence of good quality blastocysts and lower percent pre-implantation loss than Group III. Among all the treatment groups, Group III (Selenium-supplementation during pregestation-to-gestation) yielded the lowest quality blastocysts and highest percent pre-implantation loss.ConclusionMaternal selenium-supplementation during pregestation and gestation stages of the periconception period yielded a high percent occurrence of good quality blastocysts and pre-implantation success.
“…Over the last 3-4 decades of human laboratory assisted reproduction, little has changed in embryo evaluation and selection for transfer, with the exceptions of recent time-lapse micro-videography of morphometrics and morphokinetics (Wong et al, 2010;Kirkegaard et al, 2012Kirkegaard et al, , 2013Paternot et al, 2013;Ziebe, 2013;Molina et al, 2014;Basile et al, 2015) and preimplantation genetic screening for aneuploidy (Lyet al, 2011;Franasiak et al, 2014). Classically, embryo analysis and selection has been performed manually with microscopic observations of cleavage rates, embryo cell number (in relation to time of development), degree of cellular fragmentation, blastocyst formation, stage of blastocyst development (early, full, expanding, expanded or hatching) and/or cellular contributions of the blastocyst inner cell mass and trophectoderm.…”
Section: Embryo Analysis and Selection With Microfluidicsmentioning
Microfluidics can be considered both a science and a technology. It is defined as the study of fluid behavior at a sub-microliter level and the investigation into its application to cell biology, chemistry, genetics, molecular biology and medicine. There are at least two characteristics of microfluidics, mechanical and biochemical, which can be influential in the field of mammalian gamete and preimplantation embryo biology. These microfluidic characteristics can assist in basic biological studies on sperm, oocyte and preimplantation embryo structure, function and environment. The mechanical and biochemical characteristics of microfluidics may also have practical and/or technical application(s) to assisted reproductive technologies (ART) in rodents, domestic species, endangered species and humans. This review will consider data in mammals, and when available humans, addressing the potential application(s) of microfluidics to assisted reproduction. There are numerous sequential steps in the clinical assisted reproductive laboratory process that work, yet could be improved. Cause and effect relations of procedural inefficiencies can be difficult to identify and/or remedy. Data will be presented that consider microfluidic applications to sperm isolation, oocyte cumulus complex isolation, oocyte denuding, oocyte mechanical manipulation, conventional insemination, intracytoplasmic sperm injection, embryo culture, embryo analysis and oocyte and embryo cryopreservation. While these studies have progressed in animal models, data with human gametes and embryos are significantly lacking. These data from clinical trials are requisite for making future evidence-based decisions regarding the application of microfluidics in human ART.
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