Next Article in Journal
Synergistic Inhibition of Triple-Negative Breast Cancer by Acetylsalicylic Acid and Recombinant Human APE1/Ref-1 in a Mouse Xenograft Model
Previous Article in Journal
Cumulative Hydrocortisone Exposure and Early Brain Volumetrics in Very Low Birth Weight Infants: Associations with Neurodevelopmental Outcomes
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

The ART of Embryo Selection: A Review of Methods to Rank the Most Competent Embryo(s) for Transfer to Optimize IVF Success

1
Department of Biology, McMaster University, Hamilton, ON L8S 4L8, Canada
2
Ontario Network of Experts in Fertility (ONE Fertility), Burlington, ON L7N 3T1, Canada
3
Department of Obstetrics and Gynecology, Division of Reproductive Endocrinology and Infertility, McMaster University, Hamilton, ON L8S 4L8, Canada
*
Author to whom correspondence should be addressed.
Biomedicines 2025, 13(11), 2766; https://doi.org/10.3390/biomedicines13112766 (registering DOI)
Submission received: 14 September 2025 / Revised: 25 October 2025 / Accepted: 10 November 2025 / Published: 12 November 2025

Abstract

Within the field of assisted reproductive technologies (ARTs), embryologists regularly face the critical task of identifying embryos with the highest likelihood of implantation and survival. To help aid and standardize this practice, many embryo selection strategies have been developed to give the best chance of pregnancy success. Over the years, there has been a large increase in experimental studies conducted within this area of research. This increase has allowed for the formation of significant and plausible theories of embryo development, especially in cases where the most prominent factors seem identical. These advancements have both expanded the typical process of traditional treatments and have even paved the way for new techniques. The exact combination of all these relevant factors has not been fully elucidated into a single all-encompassing scheme for embryo decision. Morphological, genetic, and developmental indicators are well-studied individually, but the exact methods that should be prioritized in each scenario may change with respect to an individual patient. Deciding whether factors like age, egg quality, lifestyle choices, or previous medical history should alter methods of embryo ranking can result in conflict, especially in the case where a choice is being made between two similar embryos. This article reviews the conventional methods along with emerging technologies that provide the tools for embryologists to evaluate and rank embryos with high implantation potential (HIP). By showcasing these methods, including their respective benefits and drawbacks, this article provides information to allow clinicians to make effective decisions by integrating multiple approaches to embryo selection.

1. Introduction

This review emphasizes biological and embryological selection criteria rather than exploring external demographic or environmental influences, though there is some evidence to highlight these factors as a potential cause(s) of declining birthrates [1]. Embryo grading and progressive development timing will be observed in detail, especially regarding the cleavage and blastocyst stages. Different grading systems will be compared against each other to see which results in the best implantation and success rates. The need for a new, all-encompassing system will also be discussed [2]. Preimplantation genetic testing (PGT) to prevent both aneuploidy and other relevant gene defects has become another crucial procedure regarding many IVF cycles. Many techniques and subcategories of PGT have been explored to help further improve both pregnancy and live birth rate statistics [3]. Additionally, a combination of proteomics, metabolomics, and timelapse imaging to measure morphokinetics will be investigated to see their potential for future forms of analysis [4]. The rising importance of AI investigation as an emerging field will also be explored in the context of timelapse imaging. These factors will be evaluated to explore their current limitations and potential improvements. Additionally, any relevant clinical challenges or potential solutions will be discussed.
This overview of embryological consideration provides insight into the many important facets of embryo selection in ART. The evolution of embryo selection strategies is outlined in Figure 1. This review addresses the future need to emphasize factors that are not regularly highlighted in embryo ranking, especially more abnormal clinical considerations. By recognizing the interplay between these factors, the groundwork for continued advancement in reproductive medicine can be expanded. In the near future, changes can be made to prioritize both scientific rigor and compassionate care for those seeking to build families.

2. Under-Recognized Clinical Considerations Impacting Implantation and Embryo Transfer Success

Implantation is a crucial step for pregnancy, whereby an embryo attaches to the uterine wall. Embryo implantation depends on several factors, including high embryo quality, proper timing and uterine receptivity, and hormonal and lifestyle factors (Table 1). One of the most significant limiting factors of all ART procedures is embryo aneuploidy resulting from maternal age. However, whether embryo ploidy status considers all aspects of age-related fertility decline remains controversial. Separate to ploidy status, abnormalities in the oocyte cytoplasm such as organelle dysfunction, lack of macromolecules, and altered gene expression have been shown to largely affect fertility outcomes [5]. These cytoplasmic factors may compromise embryo development even when chromosomal status appears normal. This is further supported by the increased live birth rate success of older patients when using young donor embryos [6]. Furthermore, as research has advanced, the role of the uterine environment in implantation and early development has become more apparent. In the past, the success of births from donor oocytes was directly indicative of a functional endometrium in older patients. However, more recently, it has been shown that declining endometrial gene expression can decrease fertility in patients above the age of 35 [7]. More specifically, the downregulation of ciliogenesis seems to be the leading cause of this deficiency [7]. A previous history of infertility also impacts the uterine microenvironment [5]. Despite the many negative outcomes of multiple gestation births at older ages, most patients opt to transfer multiple blastocysts despite the risks [8]. Medically, it has been shown that elective single embryo transfers are safer for both the mother and offspring [8]. Individualized treatment strategies should be considered in older patients to optimize outcomes while minimizing the unnecessary risks of multiple gestation pregnancies.
Male factors contribute to approximately one-third of infertility cases worldwide [9]. Age, out of many other individual factors, appears to be the most significant contributor and can contribute to poor semen quality, often resulting in oligo or azoospermia [10]. There is also mild evidence to show that paternal age impacts blastocyst development and euploidy rates [11]. After opting for oocyte donations, fathers of advanced age saw a relative decrease in embryo formation [12]. The most likely causes of this decrease are abnormal sperm morphology and genetics. There are many different criteria considered in modern day sperm analysis. The strict system categorizes sperm quality into three groups based on a histologic assessment of defects in the sperm head, neck, body, and tail [13,14]. The percentage of normal forms determines its prognosis. Additionally, the regulation of epigenetics is crucial to embryo development and can be significantly affected by sperm health [15]. Histone modifications and deoxyribonucleic acid (DNA) methylation through paternal ribonucleic acid (RNA) expression can have the potential to impact embryo viability [15]. Many forms of treatment for maladaptive male factors can be provided through ART [16]. Hormonal therapies, testicular sperm extraction, and intracytoplasmic sperm injection (ICSI) through IVF can all greatly improve fertilization, embryo development, and ultimately pregnancy success.
Different genetic conditions can affect gamete and embryo viability. In many cases, pregnancies involving either the monosomy or trisomy of various chromosomes rarely make it to term [17]. Testing sperm cell aneuploidy remains difficult and is only valuable as a diagnostic tool since there is no method available to determine the genetic composition of live sperm to be used for ICSI. As a result, normal embryo development is more heavily prioritized for ART [17]. IVF treatments can greatly aid both male and female patients that are known to be carriers of the gene associated with cystic fibrosis, both allowing for genetic counseling and increasing pregnancy to up to a 40% success rate [18]. Cystic fibrosis often affects the reproductive systems in both sexes, necessitating assisted reproductive technologies to achieve conception. Regarding both nutrient and medicine absorption, weighing the risks between fetal and maternal health is a crucial balance [18,19]. ART can also aid patients with classic galactosemia and its resulting primary ovarian insufficiency (POI) [20]. This inability to digest galactose largely affects important gonadotropin mechanisms and can greatly impair folliculogenesis even with early diagnosis and other treatments [21]. Structural chromosomal abnormalities including translocations or inversions are another possible cause of patient infertility. Most often, Robertsonian translocations present with a normal phenotype and are only detected through karyotyping [22]. These mutations significantly affect spermatogenesis and are heavily correlated with spontaneous miscarriages [23]. Additionally, Y chromosome microdeletions in sperm cells can lower euploidy rates [24]. Of the aneuploid embryos produced in this study, most saw the deletion or duplication of entire chromosomes [24]. However, in cases where euploid embryos had developed and been transferred, no differences were seen in clinical pregnancy rates [24]. These findings reinforce how subtle genetic alterations can have extreme effects on embryo quality and fertility outcomes. Knowledge of underlying chromosomal defects is an important component of comprehensive infertility assessments. This not only helps patients understand their infertility but helps clinicians develop a treatment plan with targeted therapies to maximize success.
Some other well-known clinical conditions, like polycystic ovarian syndrome (PCOS), can also negatively impact fertility outcomes by causing anovulation through hormone imbalance and the formation of multiple small antral follicles [25]. Letrozole therapy for patients with PCOS across multiple IVF cycles may improve their odds [26]. Proper assessments including cycle priming and supplemental vitamins or medicines should also be integrated into treatment plans [26]. Endometriosis is another prevalent infertility-related condition, and in severe cases, it may chronically affect a patient’s quality of life [27]. The disease itself may potentially hinder crucial steps involved in IVF, including ovarian response to gonadotropins and embryo implantation [28]. However, endometriosis has not been shown to negatively impact embryo aneuploidy or quality [28]. Other factors, such as uterine fibroids or blocked fallopian tubes, can act as physical barriers preventing pregnancy. Additionally, unhealthy weight and other lifestyle factors can have large impacts on fertility outcomes. Higher body mass index (BMI) ratios in women can result in a reduced number of oocytes from controlled ovarian stimulation and a need for a longer stimulation cycle [29]. In comparison to healthy individuals, overweight and obese patients were significantly less likely to achieve clinical pregnancy [29]. In males with higher body mass index ratios, testosterone levels were reduced, and semen was of poorer quality, though no effects on regular sperm parameters were observed [30]. Excess amounts of both physical and psychological stresses have been shown to reduce fertility in both genders, with physical stress having a more predominant effect on females than males [31]. Similarly, both illicit and prescription drug use, alcohol consumption, and smoking have all been correlated with patient infertility [31]. Environmental exposure to heavy metals and other chemicals can also negatively impact reproduction after secondary consumption [31]. It is unknown whether some of these components will become prominent screening factors for gamete viability. However, in certain contexts, they should be considered and spoken about to optimize live birth rate success when other evaluative components appear equal (Table 2). As a result, the promotion of a healthy lifestyle is foundational for infertility treatment.

3. Morphological Assessment

Various grading systems to assess normal embryological development have been developed. As advancements in research continue, assessment criteria may need to be altered to achieve the most desirable results. Underlying genetic or epigenetic variations may result in different embryo development rates. These differences have been strongly correlated with outcomes that underline the importance of developmental milestones. In addition to morphological markers, metabolic and epigenetic factors may need to be taken into consideration [32]. Creating a straightforward ranking system of embryo quality can be extremely complicated, with multiple facets to examine. Highlighting the most important features of development may instead provide a more well-rounded approach.
Evaluations of early-stage zygotes are usually conducted using pronuclear morphology, most specifically number, equality, size and distribution of nucleoli, pronuclear size and alignment, the time of pronuclear breakdown, and the presence or absence of a cytoplasmic halo [33]. Tesarik and Greco [34] first classified zygotes based on size and number as well as the distribution of nucleolar precursors to predict cell cycle progression. Their systems were later adapted and simplified. An additional method was proposed by Senn et al. [35] in 2005, where grades were assigned to six portions including proximity, orientation, and centering of the pronuclei, cytoplasmic halo, and number and polarization of nucleolar precursor bodies; these were then accumulated into a single score. More recently, there has been evidence to show that on average, smaller zygotes develop into higher quality blastocysts [36]. However, whether this distinction remains significant until implantation is unclear [37]. This suggests that while zygote size may be an early predictor of developmental potential, it must be interpreted cautiously within the broader embryological context.
High cell numbers, symmetrical blastomeres, and minimal fragmentation can also be great evaluative factors for embryos assessed at day three of development. Day 3 embryo transfers with six to eight blastomeres are most ideal [38]. Nomura et al. [39] showed that embryos with 7–8 blastomeres were more likely to develop to the blastocyst stage than those with <7 blastomeres on day 3. In the cases of these good quality embryos, earlier implantation seems to result in high clinical and ongoing pregnancy rates [38]. Additionally, it has been observed that lower microdrop volumes when culturing can result in higher day three cell numbers [40]. Whether or not a combination of these factors would contribute to higher pregnancy success rates is unclear. Though asymmetric blastomeres are heavily correlated with poorer implantation rates, pregnancy can still be achieved [41]. Often, this asymmetry is a sign of aneuploidy [41]. However, in cases where the embryo is still euploid and otherwise appears normal, it may reach the blastocyst stage of development [42]. In cases where asymmetry is the only real concern, it should not be used alone to justify selecting against the embryo for transfer and electing to discard. Similarly, day three fragmentation can also lead to successful birth in combination with other healthy factors, but there is some evidence showcasing that early fragmentation may hinder fetal development [43]. A lowered birth rate, preterm births, and other birth abnormalities are heavily correlated with fragmentation [43]. Day three embryo morphology is a crucial factor in ranking embryos for transfer and/or cryopreservation. More recently, with the trend toward extended culture, day 3 preimplantation embryo morphology is an important indicator for the potential to form a blastocyst. In cases where older patients are involved, it can even predict euploidy to prevent bad outcomes [44]. Continued evaluation of these factors is extremely helpful, especially when gross embryo morphology is not different.
Blastocyst development before transfer can also have significant insight into whether the embryo is competent enough to create a pregnancy that leads to a live birth. Across various forms of ART, including IVF, ICSI, and testicular sperm extraction ICSI, more profound blastocoel expansion and a larger blastocyst surface area have both been shown to result in ongoing pregnancy more often than smaller embryos and later developing blastocysts [45]. Similarly, a larger number of trophectoderm cells of good quality at this stage tends to promote better pregnancy results. These cells play a critical role in embryo implantation as the precursor cells that contribute to placental formation to facilitate implantation in the endometrium. The two factors, related by an osmotic gradient caused by a higher concentration of intracellular ions, allow the blastocyst to fill and expand appropriately [46]. Pluripotent stem cells in the center of the blastocyst, known as the inner cell mass (ICM), are key variables to consider when evaluating the implantation potential of blastocysts. Normal development of both the ICM and trophectoderm cells are extremely important morphological factors [47]. Morphokinetic progression shows that faster developing blastocysts (day 5) have higher implantation rates than their slower developing (day 6 or 7) counterparts, even with poorer morphological factors [48]. Ultimately, while morphology remains a valuable tool, developmental speed and cellular behavior may begin to offer powerful insight into an embryo’s potential for a successful pregnancy [49]. The Gardner grading system is a standardized method used in IVF to assess blastocyst quality based on three criteria, namely blastocoele expansion, ICM, and trophectoderm. The expansion stage is scored from one to six, indicating the degree of blastocoele expansion. A lower rating indicates an early and formative expansion, whereas a higher grade indicates more advanced growth [50]. The ICM, which forms the fetus, as well as the placenta-forming trophectoderm, are graded either A, B, or C to indicate cell amount, density, and quality [50]. Higher-quality blastocysts generally correlate with better implantation potential. Though this system is extremely reliable and easy to use, it has one weakness: deciding to implement between similarly graded embryos can be difficult. Utilizing other well-researched factors as well as knowledge of previous development rates can help patients make more well-informed decisions regarding their own treatments. It has been observed that blastocyst embryo transfer(s) as opposed to the cleavage stage embryos results in higher implantation success [51,52].
Embryo morphology is an extremely important criteria to consider for embryo selection. Though it cannot directly indicate the genetic normality of a particular species, the knowledge acquired over the years has allowed for a significant increase in pregnancy success. Additional research in this area has mitigated the need for multiple embryo transfers, mitigating some of the related dangers of multiple gestation pregnancy [53]. Continual improvement of morphological research will likely aid fertility practices all over the world.

4. Preimplantation Genetic Testing

Preimplantation genetic testing (PGT) is used during IVF cycles to screen embryos for genetic abnormalities before uterine transfer and to choose embryos with the best chances of having a healthy pregnancy. PGT can reduce the risk of transferring embryos with genetic anomalies, helping improve pregnancy success rates and decrease miscarriage risk. There are several variations in PGT, including (a) PGT for aneuploidy (PGT-A) to identify an unbalanced chromosome complement in the representative biopsied cells; (b) PGT for monosomic (PGT-M) gene disorders; (c) PGT for structural rearrangements (PGT-SR), and (d) more recently, PGT for polygenic (PGT-P) genetic traits.
PGT-A has consistently been used alongside morphological grading when making the decision to implant. Early PGT-A relied on a single cell biopsy from day 3 embryos and often failed to provide significant positive outcomes. The plausibility of preventing miscarriage through aneuploidy has promoted continuous research, and the advent of better culture media to support blastocyst development has led to trophectoderm biopsies instead of single cells. Along with advanced molecular techniques such as next-generation sequencing (NGS), this has prompted the technique to become more commonly employed in IVF labs around the world [54]. More recently, there have been opposing forces to both simplify the testing process and add greater acuity to the results [55]. Creation of a cost-effective, non-invasive, and a more widely available test could potentially allow more patients to receive this diagnostic test as part of their infertility treatment, though it may come with the sacrifice of data quality. Alternatively, the demand for higher genome resolution has also increased. These contrasting goals reflect the challenge of balancing accessibility with precision. The direction in which PGT-A testing will continue to develop is largely unknown, but the co-existence of these two streams with patient choice for utilization will likely result in the most overall satisfaction [55]. PGT-A testing is extremely helpful in preventing aneuploid transfer; however, about half of euploid transfers still may fail to implement [56]. There is some evidence to show that this is most largely correlated to low trophectoderm quality and late blastocyst expansion occurring on day six or seven [56]. Successful implantation requires proper timing and endometrial receptivity in addition to the transfer of an euploid embryo. Embryo selection based solely on chromosomal status may overlook other critical indicators of success. It is still unclear whether euploidy testing completely offsets the issues caused by older maternal age, especially considering the importance of non-chromosomal oocyte quality factors and acquired uterine factors [56]. Mosaicism can significantly affect PGT-A when testing is performed through trophectoderm biopsy [57]. This can result in both the disregard of low-level ICM mosaics as well as a selection of high-level ICM mosaics depending on which cells were biopsied and both the location and cause of aneuploidy. Since these mitotic errors can occur as early as day three of development, PGT-A testing may negatively affect mosaic outcomes [57]. Live births have resulted from embryos transferred after a mosaic diagnosis. This has fueled the debate about the value of PGT. Mosaics could be the result of a misdiagnosis, or perhaps the preimplantation embryo has the capability to correct or eliminate abnormal cells. Additionally, the need to use whole-genome amplification can result in “allele dropout and loss of heterozygosity in up to 25% of cases”, as well as any relevant laboratory errors [57]. Though PGT-A testing can provide much needed information to patients going through IVF cycles, the practice is not perfect, and other factors still occasionally affect pregnancy outcomes.
In cases where the patient or spouse has a known susceptibility to pass on genetic ailments to their children, PGT for monogenic conditions (-M) can be used to optimize both IVF success and quality of life for the future child. Though PGT-M predates PGT-A testing and usage [54], its use had not become extremely popularized until recently. This is plausibly because the two forms of PGT are most effective when used separately. For women under the age of 35, the usage of PGT-M without PGT-A is preferred to maximize successful results in cases where it is deemed necessary [58]. The implementation and routine usage of PGT-M often depend on prior linkage analysis and detailed family genetic histories, making it most applicable in cases where a known familial mutation has already been identified. Additionally, when used in combination with genetic counseling, PGT-M can remain an effective tool in ART for a variety of patients, including partners with a chromosome translocation or inversions and those using donor gametes [59]. After PGT-M, communication of poor test results to the family and understanding the relevant implications is an important part of the counseling process and can influence decisions made during future IVF cycles [59]. Some of the most common ailments targeted by PGT-M include cystic fibrosis, Tay–Sachs disease, thalassemia, and Huntington’s disease. The use of PGT-M, particularly with its detection of cancer predisposition syndromes, still faces some ethical challenges when considering hereditary conditions [60]. More specifically, the incomplete penetrance and variable expressivity of these syndromes raise questions about PGT-M legitimacy and necessity [61]. While PGT-M offers a powerful means of preventing many serious genetic conditions, its use must be carefully balanced with clear clinical guidelines. In cases where both parents are healthy, PGT-M should not be used as a form of genetic disease prevention.
PGT for structural re-arrangements (-SR) has emerged specifically as a targeted method for couples with chromosomal translocations, inversions, or duplications to prevent transmission of these changes to their children. This can be especially useful if the patients themselves carry balanced chromosomal rearrangements and appear externally asymptomatic [62]. Because of their altered genome, these individuals would have low fertility and could only naturally conceive children that would also be carriers [55]. Like most forms of PGT, PGT-SR is completed through next-generation sequencing of embryonic biopsies, rendering misdiagnosis possible dependent on the size and complexity of the re-arrangement [62]. Additionally, most PGT-SR are performed with standard PGT-A platforms if the affected regions are above the platform’s resolution. This is because embryos with unbalanced translocations can be identified by displaying segmental losses or gains in the regions involved in the translocation [55]. Deciding to utilize PGT-A, PGT-M, or PGT-SR, weighing the risks and benefits of miscarriage avoidance or reducing the chance of a healthy baby, will be a decision for each individual couple that should be informed by appropriate genetic counseling for their chromosomal rearrangement and history [63].
Similarly to PGT-M, PGT for polygenic conditions (-P) is another subset of PGT that focuses on screening for the risk of more genetically complex ailments. Recent advances have made genome-wide genotyping of IVF embryos feasible and affordable, potentially helping to screen for risk factors such as breast cancer, hypertension, diabetes, or schizophrenia [64]. Though PGT-P can reduce genetic risk factors for these ailments, environmental, lifestyle factors, or even random molecular events can still induce these diseases [64]. Its future use may begin to raise some ethical concerns, especially if technology starts being misused to screen for other genetic traits such as height or intelligence [65]. This could later lead to unnecessary usage of IVF amongst the population, potentially introducing otherwise inessential risks and harm [64]. Due to their similarities, it is important to consider the current regulations for PGT-M when creating healthcare regulations for PGT-P to be used in the field [65]. PGT-M and -P do not necessarily select HIP embryos but rather select against a genetic disease or trait. Therefore, they represent a different tool for the selection of embryo(s) for transfer and may be a valuable process for certain patients.

5. Non-Invasive Embryo Assessment

Time-lapse imaging (TLI) of embryos is a new non-invasive technique that requires special incubators with cameras incorporated within to take images of embryos every few minutes. With this technology, correlations between timing and stages of development, termed morphokinetics, are employed to create detailed algorithms for embryo selection. Specifically, it can highlight abnormal cleavage patterns, delayed divisions, or irregular morphologies associated with reduced viability [4]. Another bonus of TLI is that it removes the need to disturb or remove the embryos from the incubator for assessment [66]. This can also help the embryo stay within more regulated oxygen-concentrated environments, simulating the natural conditions of reproductive organs [4]. The KIDScore and early embryo viability assessment (Eeva) algorithms are both proposed to aid in embryo choice after undergoing TLI. The KIDscore algorithm helps to differentiate between morphologically normal day 3 and day 5 embryos based on the presentation of abnormal cleavage patterns during their development, including slow and fast development [67]. These are also further compared and adjusted using Gardner’s grading system [67]. Alternatively, the Eeva test automatically measures cell division timings between first and second mitosis and between second and third mitosis to provide a high or low probability of blastocyst formation [68]. The Eeva system is indicated to provide adjunctive information on events occurring during the first two days of embryo development that may predict further development to the blastocyst stage on day five of embryo culture [68]. Despite its growing adoption, accessibility and cost may limit its widespread use among patients, especially as clinical guidelines still vary. As evidence for improved birth rates and reduced miscarriages is of relatively poor quality, some still argue that regular incubation infrastructure is more than sufficient [69] for most forms of ART. Whether or not this technology continues to improve itself in the future remains to be seen.
Non-invasive PGT (ni-PGT) is a new potential format for conducting PGT without needing to directly biopsy a cell sample. Through collecting blastocoele fluid of fully expanded blastocysts or by sampling spent culture media, free-floating DNA released from the ICM and trophectoderm cells can then be extracted and amplified to undergo genetic analysis, including PGT-A/M/SR [70]. The main advantages of ni-PGT include lowered potential for risk(s) associated with embryo biopsy, as well as reducing the cost of PGT treatment [70]. Furthermore, because the method relies on naturally secreted genetic material, it may offer a more accurate representation of the embryo’s overall genetic status compared to a representative cell biopsy. Additionally, the loss of blastocoele fluid should not, in theory, be detrimental to the embryo [70], as blastocoele collapse is routinely employed for vitrification and re-expansion of the cavity is frequently observed after warming.
Spent media can also be used to analyze protein profiles and metabolites, evaluating biochemical activity and molecular function. By identifying specific biomarkers through mass spectrometry, embryo viability, oocyte quality, implantation potential, developmental competence, or underlying reproductive disorders can all be recognized [71]. It is known that cells demonstrating higher pyruvate and glucose consumption through spent media also tend to showcase a higher likelihood of blastocyst formation [72]. On broader scales, metabolomics studies can also assist in evaluating the efficacy of infertility treatment drugs [73]. Determining the average gamete and embryo health of an individual and tracking changes in response to various treatments can give new insight into possible side effects and may further enhance live birth rates. Similarly, the identification of infertility-related proteins in spent media may give reason for implantation failure [73]. The metabolite 3-hydroxybutyric acid (3-HB) as well as the protein platelet endothelial cell adhesion molecule-1 (PECAM-1) both have new evidence to be implicated in female infertility without being related to other visible infertility disorders [73]. Whether or not these two will emerge as key biomarkers for implantation failure will rely on future research outcomes. If validated, their detection in routine spent media analyses could offer a non-invasive means of predicting reproductive success earlier in the IVF process. Using liquid chromatography–mass spectrometry, 3-HB can be separated and precisely quantified by its unique mass-to-charge ratio [74], while immunoaffinity enrichment coupled to targeted mass spectrometry enables the sensitive detection of low-abundance proteins such as PECAM-1 [75]. Recent large scale proteomic mapping of preimplantation embryos has revealed stage-specific proteomes varying between the morula, cleavage, and blastocyst stages [76]. Metabolic, mitochondrial, and junctional protein presence and function shift by large margins during early development, showing evidence for proteomic reprogramming that may heavily influence implantation potential during a short period of time [76]. A common limitation is the reproducibility of most metabolomic studies. As a direct consequence of the method, different samples of spent media need to be used for evaluation [72]. Depending on the cell, samples taken at different times may vary by large margins due to the complexity of cellular living [72]. Other potential biomarkers related to micro ribonucleic acids (miRNAs) include hsa-miR-661, hsa-miR-21–5p, and hsa-miR-372–5p. All three of these have limited evidence to show increased expression in degenerate embryos never reaching the blastocyst stage [77]. Information on current DNA-based biomarkers is limited. These have the potential to be used alongside protein and metabolic data to increase success with single embryo transfers. Integrating varied approaches could provide a more comprehensive and accurate assessment of embryo viability than relying on a single biomarker type alone.
The utilization of TLI alongside artificial intelligence (AI) programs opens new potential gateways involving ranking for single embryo transfer. At the 2019 meeting of the American Society for Reproductive Medicine, there were several abstracts that investigated the use of AI in analyzing raw TLI embryo development videos for non-invasive embryo selection. AI networks outperformed highly trained embryologists in selecting day 5 euploid blastocysts with high implantation potential [78]. This advantage is likely due to the computer’s ability to consistently recognize subtle, quantitative changes in morphokinetics that may be imperceptible to the human eye. By removing the variability introduced by human subjectivity, these systems can apply the same evaluation criteria across large datasets with unparalleled consistency. However, due to the relative infancy of this technology, standardized material for neural network training has not been introduced [79]. This has resulted in a variety of different neural networks coming to light. Additionally, depending on the training data network’s given some models can assess embryo morphology, while others may be more successful in predicting clinical pregnancy [79]. Most of these networks using convolutional neural network technology require a significant amount of computational power. However, they also establish the gateway for the creation of an AI program capable of combining TLI data as well as separating input clinical information [79]. This mixture of data types could eventually lead to the development of a singular evaluation entity, allowing for all necessary factors to be considered when making selection decisions in a systematic way that healthcare professionals may be unable to provide. The ethics behind such a development are still being debated [80]. Also, artificial intelligence analysis of TLI predicted that a selected embryo would spontaneously abort with 77% accuracy [78]. This significant success inspired the development of new neural network-based scoring models. Some examples, including BlastScoringNet [81] and STORK [82], have both seen success in their testing phases. Additionally, other algorithms focusing on different areas are still being created [82]. It is currently controversial whether images at critical development points or overall video evidence will be most helpful in predictive studies. It seems logical that videos would provide more information about embryo development, leading to better selection; however, individual critical images appear to be sufficient to precisely assess an embryo’s developmental competence [82]. Improvements in software analysis may leave this subject to change in the future.

6. Conclusions

The selection of embryos with the highest implantation potential remains one of the most complex steps in ART. While traditional approaches such as morphological grading and PGT have helped to improve pregnancy outcomes, their limitations indicate a progressive need to implement multifactorial strategies. For the best results, embryo selection will need to rely on an approach that accounts for biological factors while being adaptable to the needs of individual cases. Classic morphological grading using Gardner’s algorithm remains the most accessible and cost-effective method of assessing implantation potential. Improvements to incorporate both genetic and cytoplasmic factors as well as measuring cleavage-stage metrics and pronuclear morphology will aid in future rankings by allowing for a more holistic approach. Emerging non-invasive tools, including TLI, proteomic and metabolomic profiling, and artificial intelligence-driven analyses offer promising avenues to enhance precision without compromising embryo integrity. In removing the need for complete biopsy, embryos will be more likely to make it to term. However, the adoption of these techniques must be balanced against accessibility, cost, technical variability, and ethical considerations. The future of embryo selection will depend on combining established clinical knowledge with these innovations to create individualized, evidence-based protocols. In applying these changes, various fertility centers will be able to continue to support patients in achieving healthy, successful pregnancies.

Author Contributions

Conceptualization, N.A. and M.S.N.; methodology, N.A. and M.S.N.; resources, M.S.N.; writing—original draft preparation, N.A. and M.S.N.; writing—review and editing, N.A., K.K., S.D., M.F., M.F.K., S.A. and M.S.N.; supervision, M.S.N.; project administration, M.S.N.; funding acquisition, M.S.N. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study.

Acknowledgments

The authors appreciate the support of the allied health professionals at ONE Fertility.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

The following abbreviations are used in this manuscript:
AIArtificial Intelligence
ARTAssisted Reproductive Technologies
IVFIn Vitro Fertilization
HIPHigh Implantation Potential
PGTPre-implantation Genetic Testing
PGT-APre-implantation Genetic Testing for Aneuploidy
PGT-MPre-implantation Genetic Testing for Monosomic Gene Disorders
PGT-SRPre-implantation Genetic Testing for Structural Rearrangements
PGT-PPre-implantation Genetic Testing for Polygenic Genetic Traits
Ni-PGTNon-invasive Pre-implantation Genetic Testing
DNADeoxyribonucleic Acid
RNARibonucleic Acid
ICSIIntracytoplasmic Sperm Injection
POIPrimary Ovarian Insufficiency
PCOSPolycystic Ovarian Syndrome
ICMInner Cell Mass
TLITimelapse Imaging

References

  1. Skakkebæk, N.E.; Lindahl-Jacobsen, R.; Levine, H.; Andersson, A.-M.; Jørgensen, N.; Main, K.M.; Lidegaard, Ø.; Priskorn, L.; Holmboe, S.A.; Bräuner, E.V.; et al. Environmental factors in declining human fertility. Nat. Rev. Endocrinol. 2022, 18, 139–157. [Google Scholar] [CrossRef] [PubMed]
  2. Richardson, A.; Brearley, S.; Ahitan, S.; Chamberlain, S.; Davey, T.; Zujovic, L.; Hopkisson, J.; Campbell, B.; Raine-Fenning, N. A clinically useful simplified blastocyst grading system. Reprod. Biomed. Online 2015, 31, 523–530. [Google Scholar] [CrossRef] [PubMed]
  3. Greco, E.; Litwicka, K.; Minasi, M.G.; Cursio, E.; Greco, P.F.; Barillari, P. Preimplantation Genetic Testing: Where We Are Today. Int. J. Mol. Sci. 2020, 21, 4381. [Google Scholar] [CrossRef] [PubMed]
  4. Márquez-Hinojosa, S.; Noriega-Hoces, L.; Guzmán, L.; García, D.; Meseguer, M. Time-lapse embryo culture: A better understanding of embryo development and clinical application. JBRA Assist. Reprod. 2021, 25, 432–443. [Google Scholar] [CrossRef]
  5. Bebbere, D.; Coticchio, G.; Borini, A.; Ledda, S. Oocyte aging: Looking beyond chromosome segregation errors. J. Assist. Reprod. Genet. 2022, 39, 793–800. [Google Scholar] [CrossRef]
  6. Check, J.H.; Jamison, T.; Check, D.; Choe, J.K.; Brasile, D.; Cohen, R. Live delivery and implantation rates of donor oocyte recipients in their late forties are similar to younger recipients. J. Reprod. Med. 2011, 56, 149–152. [Google Scholar]
  7. Peiro, A.D.; Leon, P.S.; Leo, A.P.; Pellicer, A.; Gimeno, P.D. Breaking the ageing paradigm in endometrium: Endometrial gene expression related to cilia and ageing hallmarks in women over 35 years. Hum. Reprod. 2022, 37, 762–776. [Google Scholar] [CrossRef]
  8. Friedman, B.E.; Davis, L.B.; Lathi, R.B.; Westphal, L.M.; Baker, V.L.; Milki, A.A. Age-Related Success with Elective Single versus Double Blastocyst Transfer. ISRN Obstet. Gynecol. 2011, 17, 656204. [Google Scholar] [CrossRef]
  9. Mazzilli, R.; Rucci, C.; Vaiarelli, A.; Cimadomo, D.; Ubaldi, F.M.; Foresta, C.; Ferlin, A. Male factor infertility and assisted reproductive technologies: Indications, minimum access criteria and outcomes. J. Endocrinol. Investig. 2023, 46, 1079–1085. [Google Scholar] [CrossRef]
  10. Opstal, J.V.; Fieuws, S.; Spiessens, C.; Soubry, A. Male age interferes with embryo growth in IVF treatment. Hum. Rep. 2020, 36, 107–115. [Google Scholar] [CrossRef]
  11. Elkhatib, I.; Nogueira, D.; Bayram, A.; Abdala, A.; Ata, B.; Melado, L.; Lawrenz, B.; Kalaft, E.; Gianaroli, L.; Fatemi, H.M. The influence of male age and sperm parameters on blastulation and euploidy rates. Fertil. Steril. 2025, 124, 1006–1015. [Google Scholar] [CrossRef] [PubMed]
  12. Luna, M.; Finkler, E.S.; Barritt, J.; Chama, N.B.; Sandler, B.; Copperman, A.B.; Grunfeld, L. Paternal age and assisted reproductive technology outcome in ovum recipients. Fertil. Steril. 2009, 92, 1772–1775. [Google Scholar] [CrossRef] [PubMed]
  13. Shabtaie, S.A.; Gerkowicz, S.A.; Kohn, T.P.; Ramasamy, R. Role of Abnormal Sperm Morphology in Predicting Pregnancy Outcomes. Curr. Urol. Rep. 2016, 17, 67. [Google Scholar] [CrossRef]
  14. Wang, C.; Swerdloff, R.S. Limitations of semen analysis as a test of male fertility and anticipated needs from newer tests. Fertil. Steril. 2014, 102, 1502–1507. [Google Scholar] [CrossRef]
  15. Buisan, M.V.; Mecca, R.; Jones, C.; Coward, K.; Yeste, M. Contribution of semen to early embryo development: Fertilization and beyond. Hum. Reprod. Update 2023, 29, 395–433. [Google Scholar] [CrossRef]
  16. Ferlin, A.; Calogero, A.E.; Krausz, C.; Lombardo, F.; Paoli, D.; Rago, R.; Scarica, C.; Simoni, M.; Foresta, C.; Rochira, V.; et al. Management of male factor infertility: Position statement from the Italian Society of Andrology and Sexual Medicine (SIAMS). J. Endocrinol. Investig. 2022, 45, 1085–1113. [Google Scholar] [CrossRef]
  17. Harton, G.L.; Tempest, H.G. Chromosomal disorders and male infertility. Asian J. Androl. 2011, 14, 32–39. [Google Scholar] [CrossRef]
  18. Jain, R.; Kazmerski, T.M.; Zuckerwise, L.C.; West, N.E.; Montemayor, K.; Aitken, M.; Cheng, E.; Roe, A.H.; Wilson, A.; Mann, C. Pregnancy in cystic fibrosis: Review of the literature and expert recommendations. J. Cyst. Fibros. 2022, 21, 387–395. [Google Scholar] [CrossRef]
  19. Taylor-Cousar, J.L.; Jain, R.; Kazmerski, T.M.; Aitken, M.L.; West, N.E.; Wilson, A.; Middleton, P.G.; Nash, E.F. Concerns regarding the safety of azithromycin in pregnancy—Relevance for women with cystic fibrosis. J. Cyst. Fibros. 2020, 20, 395–396. [Google Scholar] [CrossRef]
  20. van Erven, B.; Berry, G.T.; Cassiman, D.; Connolly, G.; Forga, M.; Gautschi, M.; Gubbels, C.S.; Hollak, C.E.M.; Janssen, M.C.; Knerr, I. Fertility in adult women with classic galactosemia and primary ovarian insufficiency. Fertil. Steril. 2017, 108, 168–174. [Google Scholar] [CrossRef]
  21. Derks, B.; Greysha, R.C.; Synneva, H.L.; Vos, E.N.; Demirbas, D.; Lai, K.; Treacy, E.P.; Levy, H.L.; Haug, L.E.W.; Golzabo, M.E.R.; et al. The hypergonadotropic hypogonadism conundrum of classic galactosemia. Hum. Reprod. Update 2022, 29, 246–258. [Google Scholar] [CrossRef] [PubMed]
  22. Abbaspour, S.; Isazadeh, A.; Heidari, M.; Heidari, M.; Hajaziman, S.; Nejad, M.S.; Taskhiri, M.H.; Bolhassani, M.; Ebrahimi, A.H.; Keshavarz, P. Prevalence of Chromosomal Abnormalities in Iranian Patients with Infertility. Arch. Iran. Med. 2023, 26, 110–116. [Google Scholar] [CrossRef] [PubMed]
  23. Tunç, E.; Ilgaz, S. Robertsonian translocation (13;14) and its clinical manifestations: A literature review. Reprod. Biomed. Online 2022, 45, 563–573. [Google Scholar] [CrossRef] [PubMed]
  24. Jiang, W.; Xie, Q.; Li, X.; Yang, Y.; Luan, T.; Ni, D.; Chen, Y.; Wang, X.; Zhao, C.; Ling, X. Y chromosome AZFc microdeletion may have negative effect on embryo euploidy: A retrospective cohort study. BMC Med. Genom. 2023, 16, 324. [Google Scholar] [CrossRef]
  25. Siddiqui, S.; Mateen, S.; Ahmad, R.; Moin, S. A brief insight into the etiology, genetics, and immunology of polycystic ovarian syndrome (PCOS). J. Assist. Reprod. Genet. 2022, 39, 2439–2473. [Google Scholar] [CrossRef]
  26. Kotlyar, A.; Seifer, D.B. Women with PCOS who undergo IVF: A comprehensive review of therapeutic strategies for successful outcomes. Reprod. Biol. Endocrinol. 2023, 21, 70. [Google Scholar] [CrossRef]
  27. Allaire, C.; Bedaiwy, M.A.; Yong, P.J. Diagnosis and management of endometriosis. Can. Med. Assoc. J. 2023, 195, 363–371. [Google Scholar] [CrossRef]
  28. Somigliana, E.; Piani, L.L.; Paffoni, A.; Salmeri, N.; Orsi, M.; Banaglia, L.; Vercellini, P.; Vigano, P. Endometriosis and IVF treatment outcomes: Unpacking the process. Reprod. Biol. Endocrinol. 2023, 21, 107. [Google Scholar] [CrossRef]
  29. Turner, F.; Powell, S.G.; Al-Lamee, H.; Ghadvi, A.; Palmer, E.; Drakeley, A.; Sprung, V.S.; Hapangama, D.; Tempest, N. Impact of BMI on fertility in an otherwise healthy population: A systematic review and meta-analysis. BMJ Open 2024, 14, e082123. [Google Scholar] [CrossRef]
  30. Ameratunga, D.; Gebeh, A.K.; Amoako, A. Obesity and Male Infertility. Best Pract. Res. Clin. Obstet. Gynaecol. 2023, 90, 102393. [Google Scholar] [CrossRef]
  31. Sharma, R.; Biedenharn, K.R.; Fedor, J.M.; Agarwal, A. Lifestyle factors and reproductive health: Taking control of your fertility. Reprod. Biol. Endocrinol. 2013, 11, 66. [Google Scholar] [CrossRef]
  32. Urman, B.; Yakin, K.; Ata, B.; Balaban, B. How can we improve current blastocyst grading systems? Curr. Opin. Obstet. Gynecol. 2007, 19, 273–278. [Google Scholar] [CrossRef] [PubMed]
  33. Nasiri, N.; Eftekhari-Yazdi, P. An overview of the available methods for morphological scoring of pre-implantation embryos in in vitro fertilization. Cell J. 2015, 16, 392–405. [Google Scholar] [CrossRef] [PubMed]
  34. Tesarik, J.; Greco, E. The probability of abnormal preimplantation development can be predicted by a single static observation on pronuclear stage morphology. Hum. Reprod. 1999, 14, 1318–1323. [Google Scholar] [CrossRef]
  35. Senn, A.; Urner, F.; Chanson, A.; Primi, M.P.; Wirthner, D.; Germond, M. Morphological scoring of human pronuclear zygotes for prediction of pregnancy outcome. Hum. Reprod. 2005, 21, 234–239. [Google Scholar] [CrossRef]
  36. Kljajic, M.; Saymé, N.; Krebs, T.; Wagenpfeil, G.; Baus, S.; Solomayer, E.F.; Kasoha, M. Zygote Diameter and Total Cytoplasmic Volume as Useful Predictive Tools of Blastocyst Quality. Geburtshilfe Frauenheilkd. 2022, 83, 97–105. [Google Scholar] [CrossRef]
  37. Aydin, S.; Cinar, O.; Demir, B.; Korkmaz, C.; Ozdegirmenci, O.; Dilbaz, S.; Goktolga, U. Is pronuclear scoring a really good predictor for ICSI cycles? Gynecol. Endocrinol. 2010, 27, 742–747. [Google Scholar] [CrossRef]
  38. Racowsky, C.; Jackson, K.V.; Cekleniak, N.A.; Fox, J.H.; Hornstein, M.D.; Ginsburg, E.S. The number of eight-cell embryos is a key determinant for selecting day 3 or day 5 transfer. Fertil. Steril. 2000, 73, 558–564. [Google Scholar] [CrossRef]
  39. Nomura, M.; Iwase, A.; Furui, K.; Kitagawa, T.; Matsui, Y.; Yoshikawa, M.; Kikkawa, F. Preferable correlation to blastocyst development and pregnancy rates with a new embryo grading system specific for day 3 embryos. J. Assist. Reprod. Genet. 2006, 24, 23–28. [Google Scholar] [CrossRef]
  40. Shi, C.; Sun, T.C.; Chen, S.W.; Wang, P.; Liang, R.; Duan, S.N.; Han, H.J.; Shen, H.; Chen, X. Effects of embryo density on cell number of day 3 embryos cultured in a 30-μl drop: A retrospective cohort study. Zygote 2022, 30, 487–494. [Google Scholar] [CrossRef]
  41. Racowsky, C.; Combelles, C.M.H.; Nureddin, A.; Pan, Y.; Finn, A.; Miles, L.; Gale, S.; O’Leary, T.; Jackson, K.V. Day 3 and day 5 morphological predictors of embryo viability. Reprod. Biomed. Online 2003, 6, 323–331. [Google Scholar] [CrossRef] [PubMed]
  42. Klement, A.H.; Ovadia, M.; Wiser, A.; Berkovitz, A.; Shavit, T.; Nemerovsky, L.; Ghetler, Y.; Cohen, I.; Shulma, A. What we learned from extended culture of “rejected” day-3 cleavage stage embryos: A prospective cohort study. J. Ovarian Res. 2017, 10, 35. [Google Scholar] [CrossRef] [PubMed]
  43. Cai, J.; Liu, L.; Chen, J.; Liu, Z.; Jiang, X.; Chen, H.; Ren, J. Day-3-embryo fragmentation is associated with singleton birth weight following fresh single blastocyst transfer: A retrospective study. Front. Endocrinol. 2022, 13, 919283. [Google Scholar] [CrossRef] [PubMed]
  44. Moayeri, S.E.; Allen, R.B.; Brewster, W.R.; Kim, M.H.; Porto, M.; Werlin, L.B. Day-3 embryo morphology predicts euploidy among older subjects. Fertil. Steril. 2008, 89, 118–123. [Google Scholar] [CrossRef]
  45. Marion, E.S.; Chavli, E.A.; Laven, E.; Theunissen, R.P.M.; Koster, M.P.H.; Baart, E.B. Longitudinal surface measurements of human blastocysts show that the dynamics of blastocoel expansion are associated with fertilization methods and ongoing pregnancy. Reprod. Biol. Endocrinol. 2022, 20, 53. [Google Scholar] [CrossRef]
  46. Alström, A.; Westin, C.; Reismer, E.; Wikland, M.; Hardarson, T. Trophectoderm morphology: An important parameter for predicting live birth after single blastocyst transfer. Hum. Reprod. 2011, 26, 3289–3296. [Google Scholar] [CrossRef]
  47. Rozema, D.; Maître, J.L. Forces Shaping the Blastocyst. Cold Spring Harb. Perspect. Biol. 2024, 17, 041519. [Google Scholar] [CrossRef]
  48. Ozgur, K.; Berkkanoglu, M.; Bulut, H.; Donmez, L.; Isikli, A.; Coetzee, K. Blastocyst age, expansion, trophectoderm morphology, and number cryopreserved are variables predicting clinical implantation in single blastocyst frozen embryo transfers in freeze-only-IVF. J. Assist. Reprod. Genet. 2021, 38, 1077–1087. [Google Scholar] [CrossRef]
  49. Bayram, A.; Elkhatib, I.; Kalafat, E.; Adbala, A.; Ferracuti, V.; Melado, L.; Lawrenz, B.; Fatemi, H.; Nogueira, D. Steady morphokinetic progression is an independent predictor of live birth: A descriptive reference for euploid embryos. Hum. Reprod. Open 2024, 2024, 59. [Google Scholar] [CrossRef]
  50. Hardarson, T.; Landuyt, L.V.; Jones, G. The blastocyst. Hum. Reprod. 2012, 27, 72–91. [Google Scholar] [CrossRef]
  51. Gardner, D.K.; Vella, P.; Lane, M.; Wagley, L.; Schlenker, T.; Schoolcraft, W.B. Culture and transfer of human blastocysts increases implantation rates and reduces the need for multiple embryo transfers. Fertil. Steril. 1998, 69, 84–88. [Google Scholar] [CrossRef]
  52. Dawson, K.J.; Conaghan, J.; Ostera, G.R.; Winston, R.M.L.; Hardy, K. Delaying transfer to the third day post-insemination, to select non-arrested embryos, increases development to the fetal heart stage. Hum. Reprod. 1995, 10, 177–182. [Google Scholar] [CrossRef] [PubMed]
  53. Cutting, R. Single embryo transfer for all. Best Pract. Res. Clin. Obstet. Gynaecol. 2018, 53, 30–37. [Google Scholar] [CrossRef] [PubMed]
  54. Penzias, A.; Bendikson, K.; Butts, S.; Coutifaris, C.; Falcone, T.; Fossum, G.; Gitlin, S.; Gracia, C.; Hansen, K.; Barbera, A.L.; et al. The use of preimplantation genetic testing for aneuploidy (PGT-A): A committee opinion. Fertil. Steril. 2018, 109, 429–436. [Google Scholar] [CrossRef] [PubMed]
  55. Viotti, M. Preimplantation Genetic Testing for Chromosomal Abnormalities: Aneuploidy, Mosaicism, and Structural Rearrangements. Genes 2020, 11, 602. [Google Scholar] [CrossRef]
  56. Cimadomo, D.; Rienzi, L.; Conforti, A.; Forman, E.; Canosa, S.; Innocenti, F.; Poli, M.; Hynes, J.; Gemmell, L.; Vaiarelli, A.; et al. Opening the black box: Why do euploid blastocysts fail to implant? A systematic review and meta-analysis. Hum. Reprod. Update 2023, 29, 570–633. [Google Scholar] [CrossRef]
  57. Casper, R.F. PGT-A: Houston, we have a problem. J. Assist. Reprod. Genet. 2023, 40, 2325–2332. [Google Scholar] [CrossRef]
  58. Scriven, P.N. Combining PGT-A with PGT-M risks trying to do too much. J. Assist. Reprod. Genet. 2022, 39, 2015–2018. [Google Scholar] [CrossRef]
  59. Parikh, F.; Athalye, A.; Madon, P.; Khandeparkar, M.; Naik, D.; Sanap, R.; Udumudi, A. Genetic counseling for pre-implantation genetic testing of monogenic disorders (PGT-M). Front. Reprod. Health 2023, 5, 1213546. [Google Scholar] [CrossRef]
  60. Somigliana, E.; Costantini, M.P.; Filippi, F.; Terenziani, M.; Riccaboni, A.; Nicotra, V.; Rago, R.; Paffoni, A.; Mencaglia, L.; Magnolfi, S.; et al. Fertility counseling in women with hereditary cancer syndromes. Crit. Rev. Oncol./Hematol. 2022, 171, 103604. [Google Scholar] [CrossRef]
  61. Calosci, D.; Passaglia, L.; Gabbiato, I.; Cartisano, F.; Affuso, R.; Sorrentino, U.; Zuccarello, D. Public Awareness and Acceptability of PGT-M in Cancer Predisposition Syndromes. Genes 2023, 14, 2069. [Google Scholar] [CrossRef]
  62. Giuliano, R.; Maione, A.; Vallefuoco, A.; Sorrentino, U.; Zuccarello, D. Preimplantation Genetic Testing for Genetic Diseases: Limits and Review of Current Literature. Genes 2023, 14, 2095. [Google Scholar] [CrossRef] [PubMed]
  63. Scriven, P.N. PGT-SR: The red-herring and the siren; interchromosomal effect and screening for unrelated aneuploidy. J. Assist. Reprod. Genet. 2021, 35, 1015–1018. [Google Scholar] [CrossRef] [PubMed]
  64. Siermann, M.; Tšuiko, O.; Vermeesch, J.R.; Raivio, T.; Borry, P. A review of normative documents on preimplantation genetic testing: Recommendations for PGT-P. Genet. Med. Off. J. Am. Coll. Med. Genet. 2022, 24, 1165–1175. [Google Scholar] [CrossRef] [PubMed]
  65. Capalbo, A.; Wert, G.; Mertes, H.; Klausner, L.; Coonen, E.; Spinella, F.; Velde, H.V.; Viville, S.; Sermon, K.; Verneulen, N.; et al. Screening embryos for polygenic disease risk: A review of epidemiological, clinical, and ethical considerations. Hum. Reprod. Update 2024, 30, 529–557. [Google Scholar] [CrossRef]
  66. Kahraman, S.; Sahin, Y.; Yelke, H.; Kumtepe, Y.; Tufekci, M.A.; Yapan, C.C.; Yesil, M.; Cetinkaya, M. High rates of aneuploidy, mosaicism and abnormal morphokinetic development in cases with low sperm concentration. J. Assist. Reprod. Genet. 2020, 37, 629–640. [Google Scholar] [CrossRef]
  67. Gazzo, E.; Peña, F.; Valdéz, F.; Chung, A.; Bonomini, C.; Ascenzo, M.; Velit, M.; Escudero, E. The KidscoreTM D5 algorithm as an additional tool to morphological assessment and PGT-A in embryo selection: A time-lapse study. JBRA Assist. Reprod. 2019, 24, 55–60. [Google Scholar] [CrossRef]
  68. Diamond, M.P.; Suraj, V.; Behnke, E.J.; Yang, X.; Angle, M.J.; Steinmiller, J.C.L.; Watterson, R.; Wirka, K.A.; Chen, A.A.; Shen, S. Using the Eeva Test adjunctively to traditional day 3 morphology is informative for consistent embryo assessment within a panel of embryologists with diverse experience. J. Assist. Reprod. Genet. 2014, 32, 61–68. [Google Scholar] [CrossRef]
  69. Armstrong, S.; Bhide, P.; Jordan, V.; Pacey, A.; Farquhar, C. Time-lapse systems for embryo incubation and assessment in assisted reproduction. Cochrane Database Syst. Rev. 2018, 5, 11320. [Google Scholar] [CrossRef]
  70. Leaver, M.; Wells, D. Non-invasive preimplantation genetic testing (niPGT): The next revolution in reproductive genetics? Hum. Reprod. Update 2019, 26, 16–42. [Google Scholar] [CrossRef]
  71. Jaffe, M.G.K.; McReynolds, S. Embryology in the era of proteomics. Fertil. Steril. 2013, 99, 1073–1077. [Google Scholar] [CrossRef]
  72. Munne, S.; Horcajadas, J.A.; Seth-Smith, M.L.; Perugini, M.; Griffin, D.K. Non-invasive selection for euploid embryos: Prospects and pitfalls of the three most promising approaches. Reprod. Biomed. Online 2025, 51, 105077. [Google Scholar] [CrossRef] [PubMed]
  73. Shi, J.; Wu, X.; Qi, H.; Xu, X.; Hong, S. Application and discoveries of metabolomics and proteomics in the study of female infertility. Front. Endocrinol. 2024, 14, 1315099. [Google Scholar] [CrossRef] [PubMed]
  74. Ren, J.L.; Zhang, A.H.; Kong, L.; Wang, X.J. Advances in mass spectrometry-based metabolomics for investigation of metabolites. RSC Adv. 2018, 8, 22335–22350. [Google Scholar] [CrossRef]
  75. Whiteaker, J.R.; Lundeen, R.A.; Zhao, L.; Schoeherr, R.M.; Burian, A.; Huang, D.; Voytovich, U.; Wang, T.; Kennedy, J.J.; Ivey, R.G. Targeted Mass Spectrometry Enables Multiplexed Quantification of Immunomodulatory Proteins in Clinical Biospecimens. Front. Immunol. 2021, 12, 765898. [Google Scholar] [CrossRef] [PubMed]
  76. Rai, A.; Poh, Q.H.; Okae, H.; Arima, T.; Totonchi, M.; Greening, D.W. Dynamic Proteome Landscape During Preimplantation Human Embryo Development and Trophectoderm Stem Cell-Differentiation. Proteomics 2025, 15, 72–89. [Google Scholar] [CrossRef]
  77. Omes, C.; Conti, A.; Benedetti, L.; Tomasoni, V.; Marchi, D.D.; Nappi, R.E.; Angelis, M.G.C.; Ceccarelli, G. Expression of miRNA from spent pre-implantation embryos culture media. Reprod. Biol. 2024, 24, 100847. [Google Scholar] [CrossRef]
  78. Babayev, E.; Feinberg, E.C. Embryo through the lens: From time-lapse cinematography to artificial intelligence. Fertil. Steril. 2020, 113, 342–343. [Google Scholar] [CrossRef]
  79. Salih, M.; Austin, C.; Warty, R.R.; Tiktin, C.; Rolnik, D.L.; Momeni, M.; Rezatofighi, H.; Reddy, S.; Smith, V.; Vollenhoven, B.; et al. Embryo selection through artificial intelligence versus embryologists: A systematic review. Hum. Reprod. Open 2023, 2023, hoad031. [Google Scholar] [CrossRef]
  80. Koplin, J.J.; Johnston, M.; Webb, A.N.S.; Whittaker, A.; Mills, C. Ethics of artificial intelligence in embryo assessment: Mapping the terrain. Hum. Reprod. 2024, 40, 179–185. [Google Scholar] [CrossRef]
  81. Liu, H.; Chen, L.; Shan, G.; Sun, C.; Lu, C.; Liao, H.; Zhang, S.; Dong, S.; Xu, X.; Yan, Q.; et al. An interpretable artificial intelligence approach to differentiate between blastocysts with similar or same morphological grades. Hum. Reprod. 2025, 40, 1077–1086. [Google Scholar] [CrossRef]
  82. Zaninovic, N.; Rosenwaks, Z. Artificial intelligence in human in vitro fertilization and embryology. Fertil. Steril. 2020, 114, 914–920. [Google Scholar] [CrossRef]
Figure 1. A timeline indicating the evolution of embryo selection strategies and development of related technologies.
Figure 1. A timeline indicating the evolution of embryo selection strategies and development of related technologies.
Biomedicines 13 02766 g001
Table 1. Factors affecting embryo implantation for IVF-derived embryos.
Table 1. Factors affecting embryo implantation for IVF-derived embryos.
Implantation FactorContributing FactorsPossible Clinical Treatment Solutions
Embryo QualityGenetics—embryos with chromosome anomalies have a lower likelihood of implantation.
Maternal Age—egg quality and increased chance of aneuploidy increase with female age.

Sperm Quality—contributes genetic anomalies.
PGT-A is employed to identify euploid embryos.

Advanced IVF culture systems and attention to detail in laboratories.
Endometrial ReceptivityChronic endometritis—inflammation of the uterine lining interferes with implantation.
Asherman’s syndrome–presence of scar tissue in the uterine lining.

Insufficient uterine blood flow
Endometrial biopsy to detect inflammation or infections that can then be treated prior to embryo transfer.
Promote endometrial lining thickness with hormone replacement therapy.
Endometrial receptivity assays to determine optimal timing for embryo transfer.
Hormone BalanceAn unbalanced hormonal milieux can interfere with the endometrial lining.Monitoring of hormone levels (estradiol, progesterone) throughout the cycle.
Supplementation with progesterone to promote endometrial lining growth or other hormones (thyroid stimulation hormone) as needed.
Immunological FactorsImmune response to a foreign object (ie: embryo) results in hindered embryo development and implantation.Immunological testing to identify this issue
Treat with immunoglobulins or corticosteroids to regulate an immune response
Lifestyle and General HealthBody Mass Index (BMI)—overweight and underweight conditions may impair implantation.
Smoking, Alcohol, Drugs—affects gamete, embryo and endometrial quality.
Promote a healthy lifestyle for patients trying to conceive naturally or with assisted conception.
Stress management (ie: mindfulness stress reduction).
Table 2. Summary table comparing different methods of embryo ranking and selection, including different advantages and limitations of each technique.
Table 2. Summary table comparing different methods of embryo ranking and selection, including different advantages and limitations of each technique.
Technique (Most to Least Important)When It Should Be UsedAdvantagesLimitationsCriteria
Blastocyst Morphology/MorphokineticsWhenever possible-May be supplemented with AI analysis in the near future
-Currently supported using non-invasive time-lapse imaging
-Widely available/cost effective
-Grading may be subjective
-No genetic assessment
-Garnder grading system (Good)
-Day5/6 Blastulation
PGT-A/SRWhenever possible, it should be more heavily considered for patients with advanced maternal age or recurrent implantation failure-Help identify embryo- specific genetic abnormalities
-Reduces implantation failure/miscarriage risks
-Invasive Biopsy
-Can be expensive
-Less effective for mosaic embryos
-Normal Result(s) on Day 5-6 trophectoderm biopsy
Ni-PGTWhenever possible, especially in cases where biopsy has raised risks-Non-invasive, Reduces risk of embryo damage
-Complements morphological assessment
-Less accurate than traditional PGT, lower DNA quality
-New, limited clinical adoption
-Normal Result(s) of spent media analysis
Pronuclear Morphology/ MorphokineticsWhenever possible-Currently supported using non-invasive time-lapse imaging
-May help determine cleavage potential
-Predictive Value is limited, implantation potential may change through development-Z-score system
-High cell numbers
-6-8 blastomeres
PGT-M/PIn patients who are known to either have or carry genes for genetic disorders-Helps identify embryos impacted by hereditary disease-Time consuming/expensive
-Some ethical concerns regarding PGT-P testing
-Normal Result(s) on Day 5-6 trophectoderm biopsy
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Amin, N.; Kteily, K.; Deniz, S.; Faghih, M.; Karnis, M.F.; Amin, S.; Neal, M.S. The ART of Embryo Selection: A Review of Methods to Rank the Most Competent Embryo(s) for Transfer to Optimize IVF Success. Biomedicines 2025, 13, 2766. https://doi.org/10.3390/biomedicines13112766

AMA Style

Amin N, Kteily K, Deniz S, Faghih M, Karnis MF, Amin S, Neal MS. The ART of Embryo Selection: A Review of Methods to Rank the Most Competent Embryo(s) for Transfer to Optimize IVF Success. Biomedicines. 2025; 13(11):2766. https://doi.org/10.3390/biomedicines13112766

Chicago/Turabian Style

Amin, Naiya, Karen Kteily, Stacy Deniz, Mehrnoosh Faghih, Megan F. Karnis, Shilpa Amin, and Michael S. Neal. 2025. "The ART of Embryo Selection: A Review of Methods to Rank the Most Competent Embryo(s) for Transfer to Optimize IVF Success" Biomedicines 13, no. 11: 2766. https://doi.org/10.3390/biomedicines13112766

APA Style

Amin, N., Kteily, K., Deniz, S., Faghih, M., Karnis, M. F., Amin, S., & Neal, M. S. (2025). The ART of Embryo Selection: A Review of Methods to Rank the Most Competent Embryo(s) for Transfer to Optimize IVF Success. Biomedicines, 13(11), 2766. https://doi.org/10.3390/biomedicines13112766

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop