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Retrospective analysis of outcomes after IVF using an aneuploidy risk model derived from time-lapse imaging without PGS

Reproductive BioMedicine Online, 2, 27, pages 140 - 146

Abstract

Time-lapse imaging of human preimplantation IVF embryos has enabled objective algorithms based on novel observations of development (morphokinetics) to be used for clinical selection of embryos. Embryo aneuploidy, a major cause of IVF failure, has been correlated with specific morphokinetic variables used previously to develop an aneuploidy risk classification model. The purpose of this study was to evaluate the effectiveness and potential impact of this model for unselected IVF patients without biopsy and preimplantation genetic screening (PGS). Embryo outcomes – no implantation, fetal heart beat (FHB) and live birth (LB) – of 88 transferred blastocysts were compared according to calculated aneuploidy risk classes (low, medium, high). A significant difference was seen for FHB (P < 0.0001) and LB (P < 0.01) rates between embryos classified as low and medium risk. Within the low-risk class, relative increases of 74% and 56%, compared with rates for all blastocysts, were observed for FHB and LB respectively. The area under the receiver operating characteristic curve was 0.75 for FHB and 0.74 for LB. This study demonstrates the clinical relevance of the aneuploidy risk classification model and introduces a novel, non-invasive method of embryo selection to yield higher implantation and live birth rates without PGS.

The largest single cause of failure of the human embryo to implant, and of early miscarriage, is aneuploidy (errors in numbers of chromosomes of the early (preimplantation) human embryo). More than half of human embryos are believed to be affected by aneuploidy and many must be unwittingly transferred following IVF, resulting in failed implantation, miscarriage or the birth of a baby with a related disorder. It is not possible for embryologists in IVF laboratories to identify aneuploid embryos under the microscope; however, our studies with time-lapse incubation in conjunction with preimplantation genetic screening (PGS) of IVF embryos have allowed us to develop and publish a model that rates each embryo based on its developmental patterns (morphokinetics) as being at low, medium or high risk of aneuploidy. PGS, whilst very effective, requires expensive technology and expertise, is not widely available and requires the embryo to undergo biopsy (removal of cell(s)). In this study, we tested the aneuploidy risk classification model on embryos with a known outcome and, importantly, on those embryos resulting in a live birth. This demonstrated how the model has the potential to greatly enhance IVF outcome without biopsy and PGS. By using such unique, non-invasive and specifically designed embryo selection models, we can now make more informed choices in order to select the most viable embryo to transfer, with the lowest risk of aneuploidy. Selection of an embryo classified as low risk has improved the relative chance of a live birth by 56% over conventional embryo selection.

Keywords: aneuploidy, blastocyst, embryology, IVF, live birth, time-lapse imaging.

Introduction

Since the advent of successful human IVF, fertilization and subsequent embryo culture has moved from the test-tube, held in sealed glass desiccators in ‘warming cabinets’, to the Petri dish in conventional culture incubators (Fishel and Edwards, 1982 and Steptoe and Edwards, 1978), the latter being used clinically worldwide for more than three decades. Recently the introduction of time-lapse imaging had permitted the observation of zygotes and embryos as they pass through fertilization and syngamy to cleavage, compaction, blastulation and even eventual hatching. This novel technology permits the recording and retrospective analysis of temporal morphokinetic variables (Meseguer et al., 2011), not only in varying culture conditions but in a range of clinical scenarios. However, only one commercially available system, the EmbryoScope, provides for uninterrupted culture, for up to 6 days if required, therefore standardizing this variable. Cruz et al. (2011), following a safety evaluation of this time-lapse system, concluded that the periodic light exposure required for image acquisition in the EmbryoScope did not impair embryo quality or reproductive outcome. It has since been demonstrated that culturing in this system improves the incidence of clinical pregnancy (Meseguer et al., 2012). Also, very recently it was demonstrated using this system that aneuploid and euploid embryos have differing morphokinetic variables under standardized IVF culture conditions (Campbell et al., 2013).

The vital decision as to which of a patient‘s embryos should be preferentially selected for transfer following IVF treatment has to date been based primarily on a sequence of two to six chronological observations of the developing embryos. Standard IVF practice currently requires the removal of the culture dish containing the embryos from the incubator into suboptimal ambient conditions, in order for the embryologists to assess each embryo using light microscopy and record their observations relating to the number of cells, the stage of development and morphological features. This is typically performed once daily to minimize disturbance of the embryos in culture. For the vast majority of IVF clinical treatments worldwide, it is the scribed record of this series of static observations along with the status of the embryo at the time of the transfer procedure that dictates which embryo is selected. Various grading schemes exist and a consensus document for embryo grading was recently published in the hope of providing evidence-based guidelines and standard terminology for the accurate reporting of embryo development (Alpha and ESHRE, 2011a and Alpha and ESHRE, 2011b).

However, the viability of embryos is compromised by a significant incidence of aneuploidy, both meiotic (gametes) or mitotic (post fertilization) derived, which is a major cause of IVF failure and miscarriage (Fragouli and Wells, 2011 and Kuliev et al, 2011). Furthermore, despite the ability to assess chromosome copy number (CCN), to date there has been no proven significant correlation between aneuploidy versus euploidy based on static morphological assessment of embryo preimplantation development for reliable clinical application (Fishel et al., 2010). To assess embryo ploidy with >95% accuracy, invasive biopsy of the embryo is required followed by expensive preimplantation genetic screening (PGS) using one of a range of molecular genetics-based technologies to acquire detailed knowledge of each individual CCN (Fishel et al, 2011 and Johnson et al, 2010).

Recent work has demonstrated that aneuploidy screening as a mode of embryo selection in IVF can improve treatment outcome even for patients with the lowest risk of aneuploidy. A randomized pilot study reported a significant increase in clinical pregnancy rate in good-prognosis patients whose embryos were screened for aneuploidy compared with the control group whose embryos were selected for transfer based on morphology alone (Yang et al., 2012). The purpose of the current study was to evaluate the effectiveness and potential impact of a previously established, morphokinetic-based aneuploidy risk classification model (Campbell et al., 2013) for unselected non-PGS IVF patients through time-lapse imaging.

Materials and methods

Data for this research were obtained from the treatment of 69 couples attending an independent IVF clinic (CARE Fertility, Manchester, UK) from April 2011 to December 2012. All protocols complied with the UK regulation (Human Fertilisation and Embryology Act, 1990, 2008). The study did not require ethical or institutional review board approval, having been performed according to previously validated procedures. This was, necessarily, a retrospective cohort study utilizing time-lapse technology (EmbryoScope, Unisense FertiliTech, Denmark) for the recording of embryo developmental variables and treatment outcome data.

Patient criteria

All patients with a known outcome – fetal heart beat (FHB), live birth (LB) or failed implantation – following intracytoplasmic sperm injection (ICSI), EmbryoScope culture and blastocyst embryo transfer were included in this study. Those where the fate of the embryo could not be confirmed, such as a double-embryo transfer resulting in a singleton pregnancy, were excluded. Female age ranged from 25 to 47 years (mean ± SD 36·6 ± 5·1 years).

Ovarian stimulation

Pituitary suppression was performed with a gonadotrophin-releasing hormone agonist (Suprecur, 0.5 ml s.c. daily; Sanofi Aventis, UK) or antagonist (Cetrotide, 0.25 mg daily; Merck Serono, UK). Ovarian stimulation was achieved using human menopausal gonadotrophin (Menopur; Ferring, UK) and/or recombinant FSH (Gonal-F; Merck Serono), with doses ranging from 150 to 600 IU per day according to patient type and response.

Oocyte retrieval and embryology

The detailed methodology for oocyte collection, ICSI and embryo culture using the Embryoscope has been described previously (Campbell et al., 2013). Briefly, ultrasound-guided oocyte collection was performed under sedation and oocyte–cumulus complexes were prepared for ICSI between 2–4 h following harvesting. Following ICSI, oocytes were placed individually in microwells of the EmbryoSlide, loaded into the EmbryoScope and cultured until 5 or 6 days after oocyte collection and ICSI. The integrated microscope of the EmbryoScope was programmed to acquire images of each fertilized oocyte every 20 min through seven focal planes. These time-lapse images were used for the assessment of fertilization and embryo development up to the point of embryo transfer. The time of insemination by ICSI was programmed into the EmbryoScope when the slide was loaded as the time point midway through the ICSI procedure. The EmbryoViewer image analysis software was used to log and display the precise timing of developmental events as they were assessed by the embryologists studying the images. All times were recorded in hours post insemination by ICSI and the ‘annotations’ (detailed recordings of embryo development) were completed prior to embryo transfer. All data were, therefore, blind to outcome.

The two morphokinetic variables used in the aneuploidy risk classification model that was retrospectively applied to the blastocysts in this study were defined as: (i) tSB, the time from insemination to the start of blastulation, when the first sign of a blastocoele cavity forming was visible; and (ii) tB, the time from insemination to the formation of a ‘full blastocyst’, when the blastocoele cavity filled the embryo, the inner cell mass and trophectoderm tissues were distinguishable from each other and there was no more than 10% increase in the outer diameter of the zona pellucida. Embryos were selected for transfer according to a combination of standard morphological grading and clinic-defined novel morphokinetic exclusion criteria which are not correlated to tSB or tB. tSB and tB were not used as selection criteria but were studied retrospectively in relation to the outcome of the embryo transfer.

Outcome measures

Clinical pregnancy was defined by the presence of a gestational sac with FHB during weeks 6–8 of gestation. LB was confirmed by patient completion of a clinic delivery outcome form with birth details that, by regulation, are reported to the UK regulative body, the Human Fertilisation and Embryology Authority.

Embryos with known implantation outcome confirmed by LB, FHB or failed implantation (defined as negative pregnancy test) consisted of all single-blastocyst transfers or double-blastocyst transfers with either a negative pregnancy test or at least two fetal hearts. The data acquired relating to the implantation status of these embryos were defined as known implantation data (KID). A KID value of 1 was given when the outcome for an embryo was positive and 0 when the outcome for an embryo was negative, for FHB and for LB, which were analysed separately. Rates were calculated for comparison according to the following formula, KID positive/(KID positive + KID negative) × 100%. The KID rate was calculated for FHB and for LB.

Due to the time lag in receiving obstetric outcome information following FHB detection, the number of LB KID in this dataset is relatively low compared with the number of FHB KID. Reporting of live birth (positive LB KID) occurs, at the earliest, 10 months after embryo transfer (gestational period plus a delay in the clinic receiving outcome feedback). In order to give the most realistic value for live birth, only KID negatives where the time of transfer was 10 months earlier than the statistical analysis were included in the calculation of LB KID rate.

Aneuploidy risk classification model

The aneuploidy risk classification model variables (tSB and tB) were previously established on a data set where the ploidy status of each embryo was assessed by trophectoderm biopsy and molecular analysis of CCN by either array comparative genomic hybridization or single-nucleotide polymorphism array (Table 1; Campbell et al., 2013). This model was retrospectively applied to the KID data set of standard ICSI blastocyst-transfer cycles, without trophectoderm biopsy, in order to perform an independent validation of the potential benefit of the risk classification model. The model was used to retrospectively classify the risk of aneuploidy (low, medium or high) for each transferred embryo with a KID value (positive or negative).

Table 1 The previously established three-class aneuploidy risk model based on trophectoderm biopsy data.

Risk class Definition
  tB (hpi) tSB (hpi)
Low risk <122.9 <96.2
Medium risk <122.9 ges96.2
High risk ges122.9

Source:Campbell et al. (2013).

hpi = hours post insemination; tSB = time from insemination to the start of blastulation; tB = time from insemination to the formation of a ‘full blastocyst’.

Statistical analysis

The statistical software package R version 2.15.0 (The R Foundation for Statistical Computing) was used to calculate the means, variances and area under the receiver operating characteristic (ROC) curve. A Fisher‘s Exact test for count data was used to test if the classes had different incidences of positive and negative outcome.

Results

When the aneuploidy risk classification model was applied to the KID data set, the medium- and low-risk classes for aneuploidy were significantly different from each other with respect to known implantation rates for FHB (P < 0.0001) and LB (P = 0.01) (Table 2). Of the few embryos classified as high risk subsequent to transfer, none implanted. The aneuploidy risk classification model, therefore, indicated the predictive power for successful implantation and LB, demonstrated by the area under the ROC curve being 0.75 for FHB and 0.74 for LB.

Table 2 Known implantation data rates for fetal heart beat and live birth for each aneuploidy risk class.

Risk class FHB KID LB KID
No. of embryos FHB KID rate No. of embryos LB KID rate
All 88 42.0 46 39.1
Low 33 72.7a 18 61.1b
Medium 51 25.5a 26 19.2b
High 4 0 2 0
Area under the ROC curve 0.75 0.74

a P < 0.0001.

b P < 0.01.

LB KID data were calculated only from treatments where the information could have been obtained (over 10 months from time of embryo transfer).

FHB = fetal heart beat; KID = known implantation data; LB = live birth.

The incidence of positive FHB in the low-risk class was 72.7%, which represents a relative increase of 74% compared with the overall rate across all classes of embryos (42.0%). Correspondingly, the incidence of positive LB in the low-risk class was 61.1%, representing a relative increase of 56% when compared with the LB rate overall (39.1%).

To date, there has been one miscarriage reported following detection of a positive (single) FHB. The remaining FHB KID positives in this dataset were at least at 16 weeks of gestation. It is anticipated that the final relative increase in the low-risk class compared with overall LB rate will be higher than is currently reported, due to outstanding obstetric outcome data and based on the clinic’s overall data (blastocyst transfer data 2009–2011: 11.6% miscarriage rate post-positive FHB, 730 LB positive and 826 FHB positive).

Individual known outcomes were plotted on charts depicting the temporal boundaries derived from the aneuploidy risk classification model according to their tSB and tB values (Figure 1 and Figure 2).

gr1

Figure 1 The previously established three-class aneuploidy risk model applied to embryos with known fetal heart beat outcome (gestational weeks 6–8). Blue crosses represent embryos that resulted in a fetal heart beat and red lines represent embryos that did not result in a fetal heart beat. Area under the ROC curve is 0.75. tSB = time from insemination to the start of blastulation; tB = time from insemination to the formation of a ‘full blastocyst’.

gr2

Figure 2 The previously established three-class aneuploidy risk model applied to embryos with known live birth outcome. Data were calculated only from treatments where the information could have been obtained (over 10 months from time of embryo transfer). Blue crosses represent live birth embryos and red lines represent embryos that did not result in a live birth. Area under the ROC curve is 0.74. tSB = time from insemination to the start of blastulation; tB = time from insemination to the formation of a ‘full blastocyst’.

Discussion

FHB and LB outcomes following the transfer of blastocysts, selected without the use of the PGS or the morphokinetic variables tSB and tB, were used to retrospectively evaluate the potential impact of a published aneuploidy risk classification model (Campbell et al., 2013). The current study demonstrates for the first time, as far as is known, that time-lapse imaging using defined morphokinetic data within a closed system for uninterrupted culture can be used to classify human preimplantation embryos according to their risk of aneuploidy, without performing biopsy and PGS, and that this correlates well with clinical outcome. The opportunity to identify and avoid selecting embryos at high risk of implantation failure using non-invasive objective criteria has been the main driver behind a welter of algorithms and static morphometric grading schemes for more than three decades (Fishel and Edwards, 1982, Fishel, 1986, Alpha and ESHRE, 2011a, and Alpha and ESHRE, 2011b). The importance of linking this work to ploidy is that aneuploid embryos represent the largest single cause of failure and miscarriage following IVF.

Without time-lapse imaging and appropriate morphokinetic algorithms of the later stages of in-vitro embryo development, aneuploidy risk classification of blastocysts by any other non-invasive assessment has inadequate statistical power for clinical use. During the early post-fertilization period, there are mixed reports on the morphokinetic developmental criteria of embryos. Davies et al. (2012), using polar body biopsy for assessing CCN, described delayed early cleavage divisions of aneuploid compared with euploid embryos, and Chavez and colleagues (2012) reported a correlation between some early developmental parameters of 4-cell embryos and their CCN from individual blastomeres. The current study group using time-lapse imaging revealed that aneuploid and euploid embryos develop similarly at least until embryonic genome activation at around the 8-cell, day-3 stage, but during the periblastulation phase, aneuploid embryos have a significant delay in development compared with euploid embryos (Campbell et al., 2012).

CCN as defined by PGS technologies gives highly accurate data on embryo ploidy, although there is debate as to when the embryo biopsy should be performed for optimal clinical outcome. False positives and negatives are still apparent in some cases due to factors such as developmental arrest, mosaicism and putative repair mechanisms (Cater et al, 2012 and Nasmyth and Haering, 2009). Determining embryo CCN is increasingly being considered as more reliable using a multicellular trophoblast biopsy at the blastocyst stage than a single blastomere of an 8-cell embryo on day 3, or inference of oocyte or zygote ploidy status from polar body biopsies. Aneuploidy is reported to be as high as 80% in early cleavage embryos of good morphology, deemed suitable for transfer, and even higher in those rarely chosen for transfer based on morphology (Jaroudi et al., 2012). The risk classification of aneuploidy in embryos is also most reliably performed at the periblastulation stage for IVF patients due to insignificant differences in a range of morphokinetic variables between the aneuploid or euploid status of early cleavage embryos (Campbell et al., 2013). Using conventional microscopy with static imaging, Alfarawati et al. (2011) demonstrated a weak association between blastocyst morphology and aneuploidy and reported an insignificant trend toward aneuploid embryos showing slower progression to the most advanced blastocyst stages. Their study also saw more pronounced delays in embryos with complex or multiple, compared with simple or single, aneuploidy.

Precise morphokinetic criteria using time-lapse imaging were required to develop the aneuploidy risk classification model as applied in this study, but additional variables identifiable from time-lapse imaging that correlate with embryo ploidy may yet be discovered. To date, cell evenness, multinucleation and cell-cycle length have all been assessed and compared using time-lapse imaging between aneuploid and euploid embryos screened at different stages of development, but only tSB and tB were used in a predictive algorithm to classify risk of aneuploidy effectively.

This group’s examination of embryo development with time-lapse imaging from fertilisation through to blastocyst where ploidy was confirmed by trophectoderm biopsy, suggests that fragmentation is a dynamic process which continually changes and may be a completely random process. Fragmentation was observed equally in euploid and aneuploid embryos and incidence or patterning was not correlated to ploidy.

Due to intrinsic and extrinsic factors, it is likely that selection algorithms and models developed using time-lapse imaging systems may not be directly transferable between clinics or even between the wide spectrums of patient populations. Optimal morphokinetic variables may alter according to indication for IVF treatment, endocrinological profile or age (Leibenthron et al., 2012), for example, and differ according to gas tension or media used for embryo culture (Ciray et al, 2012 and Kirkegaard et al, 2013). For these reasons, despite the likelihood that delays in aneuploid embryos, compared with euploid, will be seen during the periblastulation period generally, the values for tSB and tB used in the model that Campbell et al. (2013) developed and tested on independent embryo data may not be directly applicable and will need to be assessed in other settings. To ensure reliable data, it is also essential that strict adherence to standard policies (operating procedures) is required. However, as has been demonstrated, locally defined conditions with strict adherence to protocol can provide predictive algorithms which promise an improved incidence of live birth following IVF.

Larger data are required to test whether the aneuploidy risk classification model is more effective for particular patients or embryos than others and whether particular and specific numerical chromosomes have differing effects on embryo development, aneuploidy risk classification and fate. Miscarriage rates were considered within each risk classification and, within this dataset, there was one miscarriage reported following FHB confirmation. This was from the transfer of a blastocyst classified as medium-risk aneuploidy. Larger studies assessing miscarriage incidence within these aneuploidy risk classes would be of clinical interest.

This risk classification of aneuploidy in blastocysts could be used in conjunction with PGS to prioritize embryos for screening or as an alternative or routine selection method for enhancing live birth outcome where PGS is unavailable, either because it is not permitted due to local regulation or where a non-invasive approach is desired. Aneuploidy screening during IVF treatment is most commonly offered to a small group of patients considered to be at highest risk, usually with advanced female age, but with the increasing availability of safe and non-invasive time-lapse technology, a balanced view should be taken by patients and practitioners as to the most appropriate, effective and efficient method of embryo screening for them. Whilst the technology for genetic screening is widely available, patient access to it may also be limited by the lack of technical expertise in IVF laboratories, the low proportion of IVF centres that have established PGS programmes and its high cost. The possibility of being able to classify the risk of aneuploidy in an embryo using non-invasive imaging only provides any clinic and their patients an accessible lower cost alternative which avoids additional handling and biopsy of the embryo during its preimplantation development. Embryo selection based predominantly on specific time-lapse derived algorithms could rapidly become routine in IVF treatment. This study group believes that using this non-invasive technology to screen out embryos with the highest risk of aneuploidy – a major cause of IVF failure – will result in a paradigm shift in the clinical practice of human conception in vitro and improve the incidence of live birth for most patients.

Acknowledgements

The authors wish to thank Mette Lægdsmand MSc, PhD for data mining and statistical analysis support, Rebecca Fisher for administrative assistance and Louise Best for her help with data updates and calculations. Thanks also go to the CARE Fertility Manchester team for their enthusiasm and support and to Jon, Francesca, Honor and Heidi Campbell and Jill Hunter-Blench.

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Footnotes

a CARE Fertility, John Webster House, 6 Lawrence Drive, Nottingham Business Park, Nottingham NG8 6PZ, United Kingdom CARE Fertility, John Webster House, 6 Lawrence Drive, Nottingham Business Park, Nottingham, NG8 6PZ, United Kingdom

b CARE Fertility, 108–112 Daisy Bank Road, Manchester M14 5QH, United Kingdom CARE Fertility, 108–112 Daisy Bank Road, Manchester, M14 5QH, United Kingdom

lowast Corresponding author.

fx1 Alison Campbell studied at Leicester and Nottingham universities, specializing in assisted reproduction technology. Alison has held a senior embryology position with CARE Fertility since its inception in 1997. Since then she has played a key role in establishing new laboratories and has headed up the embryology teams across the organization. Alison’s current role involves driving standards, best practice and leading research and development across the CARE laboratories in the UK and Ireland. Alison is an experienced clinical embryologist, a member of the HFEA-licensed centres panel and a diplomate of the Royal College of Pathologists. Alison was responsible for the first clinical application of time-lapse microscopy in the UK.