Time-Lapse Systems: A Comprehensive Analysis on Effectiveness

2022 ◽  
Author(s):  
Patricia Fadon ◽  
Eleanor Gallegos ◽  
Salonika Jalota ◽  
Lourdes Muriel ◽  
Cesar Diaz-Garcia
Keyword(s):  
Time Lapse ◽  
Culture Conditions ◽  
Comprehensive Analysis ◽  
Computer Assisted ◽  
Treatment Interventions ◽  
Vitro Fertilization ◽  
Recent Computer ◽  
Conventional Technology ◽  
Selection Of

AbstractTime-lapse systems have quickly become a common feature of in vitro fertilization laboratories all over the world. Since being introduced over a decade ago, the alleged benefits of time-lapse technology have continued to grow, from undisturbed culture conditions and round the clock, noninvasive observations to more recent computer-assisted selection of embryos through the development of algorithms. Despite the global uptake of time-lapse technology, its real impact on clinical outcomes is still controversial. This review aims to explore the different features offered by time-lapse technology, discussing incubation, algorithms, artificial intelligence and the regulation of nonessential treatment interventions, while assessing evidence on whether any benefit is offered over conventional technology.

scholarly journals Using Time Lapse Monitoring for Determination of Morphological Defect Frequency in Feline Embryos after in Vitro Fertilization (IVF)

Animals ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 3 ◽  
Author(s):  
Barbara Kij ◽  
Joanna Kochan ◽  
Agnieszka Nowak ◽  
Wojciech Niżański ◽  
Sylwia Prochowska ◽  
...  
Keyword(s):  
Time Lapse ◽  
Blastocyst Stage ◽  
Hatching Rate ◽  
Vitro Fertilization ◽  
First Results ◽  
Morphological Defects ◽  
Defect Frequency ◽  
Selection Of

Some human, bovine, and mouse in vitro fertilized (IVF) embryos with morphokinetic abnormalities such as fragmentation, direct cleavage, and cytoplasmic vacuoles have the potential to reach the blastocyst stage, which is related to a high potential for implantation. The latest techniques of embryo development observation to enable the evaluation and selection of embryos are based on time lapse monitoring (TLM). The aim of this study was to determine the frequency of morphological defects in feline embryos, their competence to reach the blastocyst stage, and their ability to hatch. Oocyte-cumulus complexes were isolated after the scarification of ovaries and matured in vitro. Matured oocytes were fertilized in vitro by capacitated spermatozoa. Randomly selected oocytes were observed by TLM for seven-to-eight days. Out of 76 developed embryos, 41 were morphologically normal, of which 15 reached the blastocyst stage. Of 35 abnormally developed embryos, 17 reached the blastocyst stage, of which six had single aberrations and 11 had multiple aberrations. The hatching rate (%) was 15.6% in normally cleaving embryos, 6.25% in embryos with single aberrations, and 3.33% in those with multiple aberrations. The present study reports the first results, found by using TLM, about the frequency of the morphological defects of feline embryos, their competence to reach the blastocyst stage, and their ability to hatch.

scholarly journals Performance of a deep learning based neural network in the selection of human blastocysts for implantation

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Charles L Bormann ◽  
Manoj Kumar Kanakasabapathy ◽  
Prudhvi Thirumalaraju ◽  
Raghav Gupta ◽  
Rohan Pooniwala ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Time Lapse ◽  
Vitro Fertilization ◽  
Clinical Patient ◽  
Static Images ◽  
Transfer Order ◽  
Selection Of

Deep learning in in vitro fertilization is currently being evaluated in the development of assistive tools for the determination of transfer order and implantation potential using time-lapse data collected through expensive imaging hardware. Assistive tools and algorithms that can work with static images, however, can help in improving the access to care by enabling their use with images acquired from traditional microscopes that are available to virtually all fertility centers. Here, we evaluated the use of a deep convolutional neural network (CNN), trained using single timepoint images of embryos collected at 113 hr post-insemination, in embryo selection amongst 97 clinical patient cohorts (742 embryos) and observed an accuracy of 90% in choosing the highest quality embryo available. Furthermore, a CNN trained to assess an embryo’s implantation potential directly using a set of 97 euploid embryos capable of implantation outperformed 15 trained embryologists (75.26% vs. 67.35%, p<0.0001) from five different fertility centers.

scholarly journals Solving the "right" problems for effective machine learning driven in vitro fertilization

2021 ◽  
Author(s):  
Itay Erlich ◽  
Assaf Ben-Meir ◽  
Iris Har-Vardi ◽  
James A Grifo ◽  
Assaf Zaritsky
Keyword(s):  
Machine Learning ◽  
In Vitro Fertilization ◽  
Clinical Factors ◽  
Vitro Fertilization ◽  
Data Intensive ◽  
Live Embryo ◽  
The Right ◽  
Visual Properties ◽  
Selection Of

Automated live embryo imaging has transformed in-vitro fertilization (IVF) into a data-intensive field. Unlike clinicians who rank embryos from the same IVF cycle cohort based on the embryos visual quality and determine how many embryos to transfer based on clinical factors, machine learning solutions usually combine these steps by optimizing for implantation prediction and using the same model for ranking the embryos within a cohort. Here we establish that this strategy can lead to sub-optimal selection of embryos. We reveal that despite enhancing implantation prediction, inclusion of clinical properties hampers ranking. Moreover, we find that ambiguous labels of failed implantations, due to either low quality embryos or poor clinical factors, confound both the optimal ranking and even implantation prediction. To overcome these limitations, we propose conceptual and practical steps to enhance machine-learning driven IVF solutions. These consist of separating the optimizing of implantation from ranking by focusing on visual properties for ranking, and reducing label ambiguity.

Venular endothelial cells from bovine heart

1988 ◽  
Vol 254 (6) ◽  
pp. H1211-H1217 ◽  
Author(s):  
M. E. Schelling ◽  
C. J. Meininger ◽  
J. R. Hawker ◽  
H. J. Granger
Keyword(s):  
Endothelial Cells ◽  
In Vitro Model ◽  
Protein Transport ◽  
Culture Conditions ◽  
Support Cell ◽  
Vitro Model ◽  
Microvascular Cells ◽  
Selection Of ◽  
Coronary Angiogenesis

Coronary venular endothelial cells were isolated by a bead-perfusion technique that allowed the selection of endothelial cells from venules of a specific size. Culture conditions for the microvascular cells were established. Cells grew well in supplemented Dulbecco's modified Eagle's medium. The effect of various substrata on the proliferation of the venular endothelial cells was determined. Matrigel, gelatin, and fibronectin supported high levels of proliferation. Cell shape was correlated with ability of the substratum to support cell proliferation. Cells exhibiting a broad, flattened morphology achieved high levels of proliferation. The formation of vessel meshworks by the coronary venular endothelial cells provides an in vitro model for the study of coronary angiogenesis. Confluent monolayers of these cells can be utilized to examine mechanisms of water and protein transport across coronary venules.

309 PROTEOMIC ANALYSIS OF THE BLASTOCOEL FLUID AND REMAINING CELLS OF BOVINE BLASTOCYSTS

2013 ◽  
Vol 25 (1) ◽  
pp. 301
Author(s):  
P. L. Jensen ◽  
M. L. Groendahl ◽  
H. C. Beck ◽  
J. Petersen ◽  
L. Stroebech ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Regenerative Medicine ◽  
Embryonic Stem ◽  
Culture Conditions ◽  
Mass Spectrometry Data ◽  
Venn Diagram ◽  
Vitro Fertilization ◽  
Cord Injury ◽  
Shock Proteins

Human embryonic stem cells (hESC) are derived from the human blastocyst and possess the potential to differentiate into any cell type present in the adult human body. Human ESC are considered to have great potential in regenerative medicine for the future treatment of severe diseases and conditions such as Parkinson’s disease, diabetes, and spinal cord injury. One of today’s challenges in regenerative medicine is to define proper culture conditions for hESC. The natural milieu in the blastocyst may provide clues on how to improve culture conditions, and the aim of the present study was to determine the proteome of the blastocoel fluid and the remaining cells of bovine blastocysts. Bovine blastocysts were produced by in vitro fertilization of oocytes retrieved from slaughterhouse ovaries. The blastocoel from 195 blastocysts (1–8 nL per blastocyst) were isolated by micromanipulation and analysed by nano-HPLC tandem mass spectrometry along with the remaining cells of the blastocyst. Searching the mass spectrometry data against a combined bovine database (SwissProt/TrEMBL), we identified 263 proteins in the blastocoel fluid and 1606 proteins in the cellular compartment of the blastocyst. A Venn diagram showed 124 proteins in overlap between the two compartments of the blastocyst. Several heat shock proteins and specific antioxidants were identified in both the blastocoel and cell material. A selection of proteins identified in the blastocoel fluid is to be tested on hESC in cell culture experiments, with proliferation of undifferentiated cells as the primary endpoint. The results from this study provide new knowledge about early mammalian preimplantation development, and the data can be used in the continued pursue of improving culture conditions for hESC, which further facilitates the clinical application of these cells.

Selection of Reference miRNAs for Relative Quantification in Buffalo (Bubalus bubalis) Blastocysts Produced by Hand-Made Cloning and In Vitro Fertilization

2019 ◽  
Vol 21 (4) ◽  
pp. 200-209 ◽  
Author(s):  
Swati Viviyan Lagah ◽  
Tanushri Jerath Sood ◽  
Prabhat Palta ◽  
Manishi Mukesh ◽  
Manmohan Singh Chauhan ◽  
...  
Keyword(s):  
In Vitro Fertilization ◽  
Bubalus Bubalis ◽  
Relative Quantification ◽  
Vitro Fertilization ◽  
Selection Of ◽  
Reference Mirnas
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