Advantages of a Time-Lapse Imaging System in Assisted Reproductive Technology

2015 ◽  
Vol 32 (4) ◽  
pp. 133-142
Author(s):  
Kazuhiro Matsuda ◽  
Masanobu Ito ◽  
Yumiho Yamaguchi ◽  
Fujiyo Matsushita ◽  
Hiromi Kawasaki ◽  
...  
2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
M Sugishima ◽  
K Yumoto ◽  
T Shimura ◽  
Y Mio

Abstract Study question Is it possible to culture ZP-free embryos to eliminate perivitelline threads, which are known to be involved in generating cytoplasmic fragments at the first cleavage? Summary answer ZP-free culturing, an innovative system that decreases the amount of cytoplasmic fragments without disrupting the blastomeres, using incubators with time-lapse imaging. What is known already A study in 2017 observed perivitelline threads in more than 50% of cleavage-stage human embryos using time-lapse imaging, and the rate of cytoplasmic fragmentation (at the first cleavage) was significantly decreased in embryos without perivitelline threads (P < 0.001). While it has been proposed that perivitelline threads play an important role in crosslinking the cumulus cells and oocyte during maturation, the mechanism underlying such a role remains unclear. It is also unknown whether the threads still function in mature MII oocytes. Study design, size, duration A prospective study was conducted using 2,852 normal (2PN/2PB) embryos from c-IVF/ICSI and 113 abnormal (3PN) embryos obtained from c-IVF between 2017 and 2019. The zona pellucida (ZP) of 71 abnormal embryos was removed at the pronuclear stage (“ZP-free”), and the rest (n = 42) were cultured as “ZP-intact”. Normal and abnormal embryos were cultured for five days in bench-top incubators (MINC, COOK) and an incubator equipped with a time-lapse imaging system. Participants/materials, setting, methods Embryos used in this study were donated by 412 couples who underwent c-IVF cycles in our clinic between 2017 and 2019. For ZP removal, 3PN embryos were placed in 0.125M sucrose-containing HEPES media drops to reduce the ooplasm size. Then, ooplasms were completely separated from ZPs by a laser and pipetting. Embryo development and morphology of the three groups (normal, ZP-intact and ZP-free abnormal) were compared based on the degree of cytoplasmic fragmentation. Main results and the role of chance The first cleavage occurred in 97.8% (n = 2,790/2,852) of 2PN/2PB, 83.3% (n = 35/42) of ZP-intact 3PN and 97.2% (n = 69/71) of ZP-free 3PN. Normal (2PN/2PB), ZP-intact and ZP-free 3PN embryos were classified into three groups based on the modified Veeck’s criteria thus: <20% fragmented compared to the total volume of cytoplasm at the first cleavage (Grade 1 and 2, Good); 20–39% fragmented (Grade 3, Fair) and ≧40% fragmented (Grade 4, Poor). Of 69 cleaved ZP-free 3PN embryos, 68.1% (n = 47) showed less than 20% fragments which was significantly higher than 2PN/2PB (43.7%, n = 1,218/2,790) and ZP-intact 3PN (45.7%, n = 16/35; P < 0.05). Furthermore, 24.6% (n = 17/69) of ZP-free 3PN embryos showed 20–39% fragments which was significantly lower than 2PN/2PB (45.9%, n = 1,281/2,790; P < 0.05). In addition, 50.7% of ZP-free 3PN embryos (n = 36) developed to the morula stage after the third cleavage, and 29.6% (n = 21) formed blastocoel and became blastocysts. Thus, removing the ZP before the first cleavage did not adversely affect embryo development and decreased the cytoplasmic fragmentation. Limitations, reasons for caution Due to ethical and clinical limitations, we only examined abnormally fertilized embryos in this study. Moreover, since the relationship between the perivitelline threads and cytoplasmic fragments is unclear, we plan to conduct molecular biological analysis of the perivitelline threads in further studies. Wider implications of the findings: This study revealed that ZP is not always necessary after the pronuclear stage because ZP-free embryos studied herein developed normally and maintained cell adhesion well. This innovative culture method might provide the breakthrough needed for patients to improve embryo quality who obtain embryos with severe fragmentation caused by perivitelline threads. Trial registration number Not applicable


2014 ◽  
Vol 56 (4) ◽  
pp. 305-309 ◽  
Author(s):  
Jun-ichi Funahashi ◽  
Harukazu Nakamura

2019 ◽  
Vol 18 (1) ◽  
Author(s):  
Vidas Raudonis ◽  
Agne Paulauskaite-Taraseviciene ◽  
Kristina Sutiene ◽  
Domas Jonaitis

Abstract Background Infertility and subfertility affect a significant proportion of humanity. Assisted reproductive technology has been proven capable of alleviating infertility issues. In vitro fertilisation is one such option whose success is highly dependent on the selection of a high-quality embryo for transfer. This is typically done manually by analysing embryos under a microscope. However, evidence has shown that the success rate of manual selection remains low. The use of new incubators with integrated time-lapse imaging system is providing new possibilities for embryo assessment. As such, we address this problem by proposing an approach based on deep learning for automated embryo quality evaluation through the analysis of time-lapse images. Automatic embryo detection is complicated by the topological changes of a tracked object. Moreover, the algorithm should process a large number of image files of different qualities in a reasonable amount of time. Methods We propose an automated approach to detect human embryo development stages during incubation and to highlight embryos with abnormal behaviour by focusing on five different stages. This method encompasses two major steps. First, the location of an embryo in the image is detected by employing a Haar feature-based cascade classifier and leveraging the radiating lines. Then, a multi-class prediction model is developed to identify a total cell number in the embryo using the technique of deep learning. Results The experimental results demonstrate that the proposed method achieves an accuracy of at least 90% in the detection of embryo location. The implemented deep learning approach to identify the early stages of embryo development resulted in an overall accuracy of over 92% using the selected architectures of convolutional neural networks. The most problematic stage was the 3-cell stage, presumably due to its short duration during development. Conclusion This research contributes to the field by proposing a model to automate the monitoring of early-stage human embryo development. Unlike in other imaging fields, only a few published attempts have involved leveraging deep learning in this field. Therefore, the approach presented in this study could be used in the creation of novel algorithms integrated into the assisted reproductive technology used by embryologists.


2016 ◽  
Vol 41 ◽  
pp. 72
Author(s):  
Karen Schnauffer ◽  
Niamh Lewis ◽  
Stephen Troup ◽  
Dai Grove-White ◽  
Caroline McG. Argo

2021 ◽  
Vol 116 (3) ◽  
pp. e243
Author(s):  
Daniela Paes de Almeida Ferreira Braga ◽  
Amanda Souza Setti ◽  
Patricia Guilherme ◽  
Livia S. Vingris ◽  
Rodrigo R. Provenza ◽  
...  

2015 ◽  
Vol 104 (3) ◽  
pp. e314-e315
Author(s):  
F. Li ◽  
M. Urich ◽  
J.W. Ayers ◽  
M.I. Abuzeid ◽  
I. Khan

2021 ◽  
Vol 116 (3) ◽  
pp. e235
Author(s):  
Amanda Souza Setti ◽  
Daniela Paes de Almeida Ferreira Braga ◽  
Patricia Guilherme ◽  
Livia S. Vingris ◽  
Rodrigo R. Provenza ◽  
...  

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