Objective  To develop a prediction model to estimate the chances of a live birth over multiple complete cycles of in vitro fertilisation (IVF) based on a couple’s specific characteristics and treatment information.

Design  Population based cohort study.

Setting  All licensed IVF clinics in the UK. National data from the Human Fertilisation and Embryology Authority register.

Participants  All 253 417 women who started IVF (including intracytoplasmic sperm injection) treatment in the UK from 1999 to 2008 using their own eggs and partner’s sperm.

Main outcome measure  Two clinical prediction models were developed to estimate the individualised cumulative chance of a first live birth over a maximum of six complete cycles of IVF—one model using information available before starting treatment and the other based on additional information collected during the first IVF attempt. A complete cycle is defined as all fresh and frozen-thawed embryo transfers arising from one episode of ovarian stimulation.

Results  After exclusions, 113 873 women with 184 269 complete cycles were included, of whom 33 154 (29.1%) had a live birth after their first complete cycle and 48 925 (43.0%) after six complete cycles. Key pretreatment predictors of live birth were the woman’s age (31 v 37 years; adjusted odds ratio 1.66, 95% confidence interval 1.62 to 1.71) and duration of infertility (3 v 6 years; 1.09, 1.08 to 1.10). Post-treatment predictors included number of eggs collected (13 v 5 eggs; 1.29, 1.27 to 1.32), cryopreservation of embryos (1.91, 1.86 to 1.96), the woman’s age (1.53, 1.49 to 1.58), and stage of embryos transferred (eg, double blastocyst v double cleavage; 1.79, 1.67 to 1.91). Pretreatment, a 30 year old woman with two years of unexplained primary infertility has a 46% chance of having a live birth from the first complete cycle of IVF and a 79% chance over three complete cycles. If she then has five eggs collected in her first complete cycle followed by a single cleavage stage embryo transfer (with no embryos left for freezing) her chances change to 28% and 56%, respectively.

Conclusions  This study provides an individualised estimate of a couple’s cumulative chances of having a baby over a complete package of IVF both before treatment and after the first fresh embryo transfer. This novel resource may help couples plan their treatment and prepare emotionally and financially for their IVF journey.

https://www.bmj.com/content/bmj/355/bmj.i5735.full.pdf

Predicting the chances of a live birth after one or more complete cycles of in vitro fertilisation: population based study of linked cycle data from 113 873 women

© The Author 2016. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Cumulative live birth rates after one or more complete cycles of IVF: a population-based study of linked cycle data from 178,898 women.

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. 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. 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. 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.

/pdf/towards-the-automation-of-early-stage-human-embryo-45h5k7kd1l.pdf

Towards the automation of early-stage human embryo development detection

Expectations of assisted conception for infertility

To study the association between the numbers of oocytes retrieved and the cumulative live birth rates (LBR) in women aged 35–40 years undergoing long GnRH agonist IVF/ICSI cycles. A total of 931 women aged 35–40 years who underwent their first cycle of IVF/ICSI treatment between January 2010 and December 2013 at Nanjing Drum Tower Hospital were identified and reviewed. The main endpoint of this study was the cumulative LBR after one complete oocyte retrieval, which included fresh and all subsequent frozen–thaw embryo transfer cycles. Odds ratios (OR) and 95% confidence interval (CI) for live birth were estimated by multivariate logistic regression analysis. Furthermore, all the women were divided into four groups based on the number of oocytes retrieved: 0–4, 5–9, 10–14 or ≥15 oocytes group. Variables were then compared among groups. We found that 634 out of the 931 patients (68.1%) achieved at least one live birth. The number of oocytes retrieved was an independent predictive factor for live birth, with OR 1.20 (95% CI 1.15–1.26) when adjusted for age (years), duration of infertility and Gn (gonadotrophin) doses. The cumulative LBR in the four different oocyte groups was 35.6, 68.8, 83.4 and 89.2%, respectively. When the 1–4 oocytes group was issued as a reference, the ORs for cumulative LBR gradually increased to 3.66, 6.74 and 11.77 in other three oocytes groups, respectively. The moderate–severe ovarian hyperstimulation syndrome (OHSS) rate was dramatically increased in the ≥15 oocytes group (6.9%) when compared to that in the 10–14 oocytes group (0.8%), while the cumulative LBR only increased 5.8% (from 83.4 to 89.2%). The ideal number of oocytes retrieved in women aged 35–40 years is 10–14 oocytes, which achieves a high cumulative LBR while maintaining an acceptable low OHSS rate.

Association between the number of oocytes retrieved and cumulative live birth rate in women aged 35–40 years undergoing long GnRH agonist IVF/ICSI cycles

Background: Many studies on assisted reproductive technology examine live birth rate per cycle However, after a cycle fails, couples often want to know what their chances are of having a live birth if they continue treatment From a patients’ perspective, the cumulative probability of live birth is more informative

Materials and Methods: This study includes patients who underwent fresh, frozen and non-donor ICSI cycles at our IVF unit between 2006-2012 Patients were divided into two groups; Group 1 represented those who underwent only Day 5 transfers, Group 2 represented only Day 3 transfers Patients who underwent both were excluded ­Cycles were analyzed until the first live birth or the end of the 3rd cycle Using Kaplan-Meier analysis, we estimated the cumulative live birth rates for each group and according to female age

Results: The mean age for Group 1 was significantly lower than for Group 2 After 3 cycles, Group 1’s CLBR was 79% versus 66% in Group 2 When analyzing the live births by age and group, there was a significant difference in the CLBR after 3 cycles with the women less than 35 years having the highest CLBR and the women 40 years or older having the lowest CLBR

Conclusion: In women less than 35 years, excellent CLBR can be achieved irrespective of the transfer day For women 40 years and above, better results of CLBR are observed with Day 5 transfers Our findings may impact the counseling of couples considering IVF treatment

Cumulative live birth rate and assisted reproduction: impact of female age and transfer day.

Session 41: Keys for success for embryo cryopreservation

A prospective, randomized study to compare P1 culture medium with the new early cleavage medium (ECM) for day 3 transfers

Complex and High-Risk Percutaneous Intervention Assisted By Extracorporeal Membrane Oxygenation (ECMO)

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Papers

Cumulative live birth rate and assisted reproduction: impact of female age and transfer day.

Session 41: Keys for success for embryo cryopreservation

A prospective, randomized study to compare P1 culture medium with the new early cleavage medium (ECM) for day 3 transfers

Complex and High-Risk Percutaneous Intervention Assisted By Extracorporeal Membrane Oxygenation (ECMO)