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Blastocyst Grading and Gardner System

Standardized evaluation of blastocoel expansion, inner cell mass (ICM) cohesion, and trophectoderm (TE) cell numbers (AA, AB, BB, CC).

67 sources ↓Last researched 2026-10-20

State of the Field: Blastocyst Grading and Gardner System

Standardized evaluation of blastocoel expansion, inner cell mass (ICM) cohesion, and trophectoderm (TE) cell numbers (AA, AB, BB, CC). Grounded synthesis across 67 primary sources and 15 graded findings within Reproductive Medicine & Human Fertility → Assisted Reproductive Technology & Gamete Donation.

Synopsis · Executive Overview

The Gardner grading system, evaluating blastocoel expansion, inner cell mass (ICM), and trophectoderm (TE), serves as the universal morphology standard for blastocyst assessment. While high-grade embryos (e.g., AA) consistently show higher euploidy, implantation, and live birth rates than low-grade embryos (e.g., CC), the system remains inherently subjective with significant inter-observer variability. Data indicates that Day 5 blastocysts yield superior outcomes to Day 6, and individual components—particularly TE quality and cell count—independently correlate with clinical success. Artificial intelligence and time-lapse monitoring are emerging to reduce human assessment variance, though their clinical superiority over traditional morphology remains under investigation.

Section I · Primary Literature & Evidence Synthesis

What the Peer-Reviewed Record Establishes

The primary research record in Blastocyst Grading and Gardner System is stratified by study design so that meta-analyses and replicated randomised controlled trials (T1–T2) carry greater epistemic weight than observational cohorts (T3–T4) or preclinical laboratory work (T5). Leading graded findings establish the core empirical baseline: [T1] The Gardner-based grading system is the international standard for evaluating blastocysts based on blastocoel expansion and the morphology of the inner cell mass (ICM) and trophectoderm (TE). [12][23] [T1] Integration of time-lapse monitoring (TLM) allows for dynamic assessment of blastocyst development, though its clinical superiority over static morphological grading remains to be fully established by large trials. [18][60]

Further clinical and mechanistic stratification across the literature demonstrates: [T1] There is moderate interobserver variability among embryologists when using traditional grading systems, with AI-based models showing potential for increased consistency. [30][35] [T3] Lower-grade blastocysts (e.g., BC, CB, CC) have lower implantation and live birth rates compared to high-grade blastocysts (e.g., AA, AB), but remain capable of resulting in healthy live births. [25][42]

Section II · Mechanisms, Interventions & Subgroup Calibration

Comparative Evaluation of Levers & Theoretical Models

Within the Tree of Knowledge, this field branches into 4 specialised sub-disciplines: Blastocyst Expansion and Cavitation Dynamics (Assessment of blastocoel volume expansion, zona pellucida thinning, and herniation or hatching stages graded on numerical scales from 1 to 6); Deep Learning and Automated Blastocyst Grading (Application of convolutional neural networks and automated image analysis to replicate or supersede categorical manual Gardner grading); Morphological Concordance with Aneuploidy and Live Birth (Evidence examining the statistical association of Gardner grade categories with preimplantation genetic testing for aneuploidies (PGT-A) and live birth rates); Trophectoderm Epithelial Integrity (Qualitative and quantitative scoring of the trophectoderm monolayer, focusing on cell density, cohesion, and predictive value for placentation and implantation).

Section III · Historical Trajectory & Contested Frontiers

Evolution of the Field, Open Debates & Active Trials

Chronologically, the field evolved through key inflection points: in 1999, Introduction of Gardner Scoring System (Gardner and Schoolcraft introduced the standardized three-parameter system (expansion, ICM, and TE) for grading human blastocysts); in 2011, Istanbul Consensus on Embryo Assessment (Establishment of the first international standardized terminology and grading criteria for human oocytes and blastocysts); in 2025, Updated ESHRE/Alpha Consensus (Revision of morphological assessment standards to include recommendations for time-lapse technology and dynamic developmental events).

Active scientific debates and unresolved methodological tensions centre on: Conflicting evidence regarding whether the ICM or TE is the superior independent predictor of live birth outcomes. (contradiction) Reported high AUC scores (0.90+) for AI models in clinical studies often lack multi-center validation and clinical implementation evidence. (commercial hype)

Section IV · Evidentiary Gaps & Research Frontiers

Open Questions & Priorities for the Next Research Sweep

Methodological priorities and open empirical questions queued for the next research sweep across Blastocyst Grading and Gardner System focus on resolving subgroup effect sizes, causal mechanisms, and long-term outcomes:

  • The precise impact of AI-assisted selection on cumulative live birth rates compared to expert-only manual grading.
  • Standardization of TE cell count metrics to mitigate inter-clinic variability.
  • Clinical validation of whether automated morphological prediction can supersede preimplantation genetic testing for aneuploidy (PGT-A) in low-risk populations.

Evidence Hierarchy (Graded Claims)

  • T1Synthesis of trials
    3 (20%)
  • T2Randomised trial
    0 (0%)
  • T3Observational, large
    11 (73%)
  • T4Observational, small or case-based
    0 (0%)
  • T5Preclinical or mechanistic
    1 (7%)
  • T6Opinion, news or unverified
    0 (0%)
6 settled7 debated2 contested / frontier

Study Designs in Indexed Literature

  • Meta-analyses, Systematic Reviews & Guidelines2 (3%)
  • Randomised Controlled Trials (RCTs)10 (15%)
  • Prospective Cohorts & Clinical Registries42 (63%)
  • Preclinical, Cellular & Computational Models6 (9%)
  • Primary Literature & Archive Records7 (10%)

Publication Timeline Velocity

Fig. 1 — Field Evidence Architecture & Publication Trajectory. Distribution of methodological study designs (67 indexed publications) and 15 extracted claims graded from T1 (meta-analyses and guidelines) to T6.
Primary Citations & Landmark Studies

Key Studies Anchoring This Monograph

Synthesis & Conclusions

State of the Field Conclusions

Taken together, the evidence record in Blastocyst Grading and Gardner System (67 primary sources, 15 graded claims, highest certainty T1 — Synthesis of trials) separates replicated high-tier findings from early-stage hypotheses. The 3 open research priorities detailed above guide the next autonomous literature and clinical trial sweep.

Key Quantitative Takeaways

  • [T1] The Gardner-based grading system is the international standard for evaluating blastocysts based on blastocoel expansion and the morphology of the inner cell mass (ICM) and trophectoderm (TE).
  • [T1] Integration of time-lapse monitoring (TLM) allows for dynamic assessment of blastocyst development, though its clinical superiority over static morphological grading remains to be fully established by large trials.
  • [T1] There is moderate interobserver variability among embryologists when using traditional grading systems, with AI-based models showing potential for increased consistency.
  • [T3] Lower-grade blastocysts (e.g., BC, CB, CC) have lower implantation and live birth rates compared to high-grade blastocysts (e.g., AA, AB), but remain capable of resulting in healthy live births.
  • Open frontier in Blastocyst Grading and Gardner System: The precise impact of AI-assisted selection on cumulative live birth rates compared to expert-only manual grading.
Historical timeline (3 milestones, 1999–2025)
  1. 1999

    Introduction of Gardner Scoring System

    Gardner and Schoolcraft introduced the standardized three-parameter system (expansion, ICM, and TE) for grading human blastocysts.

  2. 2011

    Istanbul Consensus on Embryo Assessment

    Establishment of the first international standardized terminology and grading criteria for human oocytes and blastocysts.

  3. 2025

    Updated ESHRE/Alpha Consensus

    Revision of morphological assessment standards to include recommendations for time-lapse technology and dynamic developmental events.

Evidence by study design (15 findings across T1–T6)

Strongest support first. The bar beside each finding shows its grade.

Synthesis of trials

  1. #1 The Gardner-based grading system is the international standard for evaluating blastocysts based on blastocoel expansion and the morphology of the inner cell mass (ICM) and trophectoderm (TE).

    Blastocyst Grading-Gardner Criteria (2026); P-109 Quantitative Trophectoderm Cell Assessment as a Predictor of I… (2025); The Istanbul consensus update: a revised ESHRE/ALPHA consensus on oo… (2025); Artificial Intelligence in Embryo Selection in Assisted Reproduction… (2024); and 5 more

    Consensus guidelines and clinical studies consistently utilize these three parameters as the foundation for embryo assessment.

  2. #2 Integration of time-lapse monitoring (TLM) allows for dynamic assessment of blastocyst development, though its clinical superiority over static morphological grading remains to be fully established by large trials.

    DebatedThe Istanbul consensus update: a revised ESHRE/ALPHA consensus on oo… (2025); Assessment of human embryo development using morphological criteria … (2016); Time-lapse monitoring as a tool for clinical embryo assessment (2012)

    Experts recommend incorporating dynamic markers into algorithms, but recognize that evidence for improved clinical outcomes is currently limited.

  3. #3 There is moderate interobserver variability among embryologists when using traditional grading systems, with AI-based models showing potential for increased consistency.

    DebatedImage Processing Approach for Grading IVF Blastocyst: A State-of-the… (2023); Embryologist agreement when assessing blastocyst implantation probab… (2022)

    Subjectivity in morphology assessment remains a challenge that data-driven, automated systems aim to address.

Observational, large

  1. #4 Lower-grade blastocysts (e.g., BC, CB, CC) have lower implantation and live birth rates compared to high-grade blastocysts (e.g., AA, AB), but remain capable of resulting in healthy live births.

    Beyond appearance: Can morphologically low‐grade euploid blastocysts… (2024); O-008 Low grade blastocysts result in healthy live births and should… (2022)

    Evidence indicates that while grade correlates with success, low-grade embryos should not necessarily be discarded as they still yield viable pregnancies.

  2. #5 Higher quality blastocysts (by Gardner grade) are associated with higher euploidy rates and improved clinical pregnancy or live birth outcomes compared to lower quality blastocysts.

    Independent inner cell mass and trophectoderm morphology as non-inva… (2026); Embryo Morphology and Euploidy Rate: A Cross-Sectional Analysis of D… (2026); P-246 Independent inner cell mass and trophectoderm morphology as no… (2025); Live birth rate following frozen-thawed blastocyst transfer is highe… (2023); and 4 more

    Morphological grading remains a primary, albeit imperfect, clinical predictor of successful implantation.

  3. #6 Artificial intelligence models trained on digital embryo images can perform automated morphological grading and outcome prediction, often reaching high levels of spatial agreement with human expert annotations.

    A Computational Ensemble Framework for Multiclass Blastocyst Segment… (2026); Blastocyst Grading-Gardner Criteria (2026); Improved prediction of clinical pregnancy using artificial intellige… (2024); Robust Automated Assessment of Human Blastocyst Quality using Deep L… (2018)

    AI is increasingly used to provide objective, reproducible assessments of embryo quality in IVF laboratories.

  4. #7 Blastocysts expanded on Day 5 exhibit significantly higher live birth rates compared to those expanded on Day 6.

    Independent inner cell mass and trophectoderm morphology as non-inva… (2026); P-246 Independent inner cell mass and trophectoderm morphology as no… (2025); Live birth rate following frozen–thawed blastocyst transfer is highe… (2018)

    Day of expansion serves as an important indicator of embryo developmental competence, with delayed expansion generally associated with poorer clinical outcomes.

  5. #8 Among Gardner criteria, inner cell mass (ICM) assessment is significantly associated with clinical pregnancy and live birth rates.

    DebatedBeyond appearance: Can morphologically low‐grade euploid blastocysts… (2024); P-269 Three-dimensional assessment of the inner cell mass is more ef… (2024); O-008 Low grade blastocysts result in healthy live births and should… (2022)

    Some research suggests that 3D quantitative ICM assessment may be more predictive than standard qualitative Gardner grading.

  6. #9 Clinical trophectoderm biopsy is an excellent representative of the inner cell mass karyotype for whole chromosome aneuploidy (96.8% concordance) but is poor for segmental aneuploidies (42.9% concordance).

    DebatedAssessment of aneuploidy concordance between clinical trophectoderm … (2018); Comprehensive analysis of karyotypic mosaicism between trophectoderm… (2010)

    The findings challenge the reliability of using a single TE biopsy to discard embryos based solely on segmental chromosomal abnormalities.

  7. #10 Artificial intelligence models trained on Gardner criteria can reach or exceed expert-level accuracy in blastocyst grading, potentially improving implantation rates compared to manual evaluation.

    DebatedInterpretable artificial intelligence-assisted embryo selection impr… (2023); O-285 Artificial intelligence algorithms reach expert-level accuracy… (2022)

    AI is increasingly used to reduce subjectivity in morphological assessment, though its superiority over experienced embryologists is still under investigation.

  8. #11 Increased TE cell count and larger ICM area are independently associated with improved live birth rates.

    Association between blastocyst morphometrics and live birth, obstetr… (2026)

    Quantitative morphometrics provide additional granular data beyond qualitative Gardner grades.

  9. #12 Quantitative assessment of trophectoderm (TE) cell counts provides a more objective metric that correlates with implantation and live birth rates, though it currently faces challenges due to overlaps between morphological grades.

    DebatedP-109 Quantitative Trophectoderm Cell Assessment as a Predictor of I… (2025)

    Quantitative counting aims to reduce the variability of the Gardner system but requires further validation for standardization.

  10. #13 Blastocyst hatching level prior to vitrification can influence clinical outcomes; specifically, embryos with an ICM hatching level > 50% may show lower implantation potential due to increased rates of apoptosis.

    ContestedImpact of Inner Cell Mass Hatching Levels Before Vitrification on Cl… (2026); Hatching status before embryo transfer is not correlated with implan… (2016)

    While excessive hatching is associated with poor outcomes in some studies, others have found no significant difference in reproductive outcomes for fully hatched blastocysts compared to non-hatched blastocysts post-thaw.

  11. #14 Trophectoderm (TE) morphology is a stronger independent predictor of live birth outcomes than inner cell mass (ICM) grade in fresh single blastocyst transfers.

    DebatedTrophectoderm morphology: an important parameter for predicting live… (2011)

    While one large retrospective study (n=1117) found TE to be the only independent predictor, traditionally both TE and ICM are considered significant.

Preclinical or mechanistic

  1. #15 Artificial intelligence and deep learning models (e.g., STORK, IVY) can automate blastocyst grading and predict pregnancy likelihood with high accuracy (AUC 0.90-0.98), reducing human subjectivity.

    Marketed ahead of evidenceDevelopment of deep learning algorithms for predicting blastocyst fo… (2021); Automatic grading of human blastocysts from time-lapse imaging (2019); Deep learning as a predictive tool for fetal heart pregnancy followi… (2019); Deep learning enables robust assessment and selection of human blast… (2019)

    AI shows high predictive power in retrospective data, but randomized clinical trials are needed to prove it improves birth rates over manual selection.

Where the record disagrees (2 controversies)
  • Conflicting evidence regarding whether the ICM or TE is the superior independent predictor of live birth outcomes.

    Findings #8, #14

  • Reported high AUC scores (0.90+) for AI models in clinical studies often lack multi-center validation and clinical implementation evidence.

    Findings #15

Node lineage & crossover disciplines

Parent lineage, active node, direct child sub-branches, and associated crossover disciplines across the Tree of Knowledge.

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Primary indexed sources (67)

Primary scientific literature, systematic reviews, and clinical trial registrations indexed for this branch.

  1. Independent inner cell mass and trophectoderm morphology as non-invasive predictors of embryo euploidy in IVF — Patryk Piekos, Suset Rodriguez, Joelle Mouhanna et al. Scientific Reports, 2026, cohort, 2 citations · DOI: 10.1038/s41598-025-31167-y
  2. Association between blastocyst morphometrics and live birth, obstetric complications and perinatal outcomes — Hiroki Utsuno, Tomoko Ishimaru, Miho Matsumoto et al. Reproductive BioMedicine Online, 2026, cohort, 1 citations · DOI: 10.1016/j.rbmo.2026.105636
  3. Comparison of Two Types of Calcium (Ca²⁺) Ionophore Treatments for Oocyte Activation in Cases of Suboptimal Fertilization Potential ART Fertility Clinics LLC, 2026, rct
  4. The effect of severe oligozoospermia on embryo dynamics and morphological quality — Men Nguyen Thi, Hoang Le, Anh Vu Thi et al. Journal of Assisted Reproduction and Genetics, 2026, cohort · DOI: 10.1007/s10815-026-03842-0
  5. Gonadotropin Therapy in Idiopathic Hypogonadal Non-Obstructive Indira IVF Hospital Pvt Ltd, 2026, rct
  6. Evaluation of an Undisturbed Embryo Culture System for Embryo Development in IVF/ICSI Cycles Sun Yat-sen University, 2026, rct
  7. Assessment of morphometric and morphological blastocyst parameters in relation to clinical outcomes in frozen single blastocyst transfer cycles: A retrospective study — Matheswari Govindarajan, Durga GedelaRao, Krishna Chaitanya Mantravadi Daehan saengsik uihak hoeji/Clinical and experimental reproductive medicine, 2026, cohort · DOI: 10.5653/cerm.2025.08452
  8. Double Zona Drilling for Trophectoderm Biopsy: A Safe Strategy When Inner Cell Mass Herniates — En‐Hui Cheng, Yi-Pin Lin, Maw-Sheng Lee et al. Diagnostics, 2026, cohort · DOI: 10.3390/diagnostics16060915
  9. BMI Versus Body Fat Percentage - Which is the Better Predictor of Fertility Outcomes in IVF Cycles? IWK Health Centre, 2026, cohort
  10. Impact of Dry vs Humidified Culture Conditions on Blastocyst Development and Aneuploidy: A Time-lapse Sibling Oocyte Study ART Fertility Clinics LLC, 2026, rct
  11. Embryo Morphology and Euploidy Rate: A Cross-Sectional Analysis of Day-3 and Blastocyst-Stage Quality — Giovanna Giovacchini, Paulo Victor Zattar Ribeiro, Cainã Gonçalves Rodrigues et al. JBRA, 2026, cohort · DOI: 10.5935/1518-0557.20260065
  12. Blastocyst Grading-Gardner Criteria — Chollanot Kaset Mendeley Data, 2026, unknown · DOI: 10.17632/52mk85rvzg
  13. Impact of Inner Cell Mass Hatching Levels Before Vitrification on Clinical Pregnancy in Preimplantation Genetic Testing for Euploidy Cycles — Hsiu-Hui Chen, Chien‐Hong Chen, Chun‐Chia Huang et al. Reproductive Medicine and Biology, 2026, cohort · DOI: 10.1002/rmb2.70036
  14. rFSH vs rFSH+rLH in Dydrogesterone-Based Progestin Protocol: A Prospective Study Centrum Clinic IVF Center, 2026, cohort
  15. Alpha-Lipoic Acid Supplementation and IVF Outcomes in Women of Advanced Maternal Age Kaohsiung Veterans General Hospital., 2026, rct
  16. Blastocyst AI Assisted Morphokinetics in ART Viable Biosciences, 2026, cohort
  17. A Computational Ensemble Framework for Multiclass Blastocyst Segmentation: Modelling Morphological Complexity in Human Embryos — R. Barkavi, Yamuna G, Jayaram C International Research Journal of Multidisciplinary Technovation, 2026, unknown · DOI: 10.54392/irjmt2636
  18. The Istanbul consensus update: a revised ESHRE/ALPHA consensus on oocyte and embryo static and dynamic morphological assessment, — The Working Group on the update of the ESHRE/ALPHA Istanbul Consensus, Giovanni Coticchio, Aisling Ahlström et al. Human Reproduction, 2025, unknown, 74 citations · DOI: 10.1093/humrep/deaf021
  19. Blastulation and ploidy prediction using morphology assessment in 33,999 day-3 embryos — Ibrahim Elkhatib, Erkan Kalafat, Aşina Bayram et al. Scientific Reports, 2025, cohort, 4 citations · DOI: 10.1038/s41598-025-19898-4
  20. Timelapse-based 3D reconstruction of blastocysts reveals 3D morphologies of human blastocysts — Bo Huang, Keyi Si, Yaxian Guo et al. npj Digital Medicine, 2025, cohort, 1 citations · DOI: 10.1038/s41746-025-02028-9
  21. P-246 Independent inner cell mass and trophectoderm morphology as non-invasive predictors of embryo euploidy in in vitro fertilization — Patryk Piekos, Suset Rodriguez, Rosa Rubino et al. Human Reproduction, 2025, cohort · DOI: 10.1093/humrep/deaf097.554
  22. Use of the SiDTM v2.0 Algorithm to Assist Embiyologists in Sperm Selection During ICSI Procedures Instituto Valenciano de Infertilidad, IVI VALENCIA, 2025, rct
  23. P-109 Quantitative Trophectoderm Cell Assessment as a Predictor of Implantation and Live Birth Rates — V Montalvo, A Munuera, C Gamez et al. Human Reproduction, 2025, cohort · DOI: 10.1093/humrep/deaf097.418
  24. Improved prediction of clinical pregnancy using artificial intelligence with enhanced inner cell mass and trophectoderm images — Hyung Min Kim, Taehoon Ko, Hyoeun Kang et al. Scientific Reports, 2024, cohort, 12 citations · DOI: 10.1038/s41598-024-52241-x
  25. Beyond appearance: Can morphologically low‐grade euploid blastocysts yield successful pregnancies? — Takahiro Suzuki, Chiharu Ishida, Yoko Yoshioka et al. Reproductive Medicine and Biology, 2024, cohort, 4 citations · DOI: 10.1002/rmb2.12560
  26. Artificial Intelligence in Embryo Selection in Assisted Reproduction for Embryos Cultured to the Fifth Day of Development University Hospital, Clermont-Ferrand, 2024, rct
  27. P-269 Three-dimensional assessment of the inner cell mass is more effective at predicting implantation and live birth than Gardner grading — R Morgan, Chloe He, Céline Jacques et al. Human Reproduction, 2024, cohort · DOI: 10.1093/humrep/deae108.639
  28. International Pilot Study for Dual Non-invasive Assesment of Embryo Development Igenomix, 2024, cohort
  29. An annotated human blastocyst dataset to benchmark deep learning architectures for in vitro fertilization — Florian Kromp, Raphael Wagner, Başak Balaban et al. Scientific Data, 2023, unknown, 27 citations · DOI: 10.1038/s41597-023-02182-3
  30. Image Processing Approach for Grading IVF Blastocyst: A State-of-the-Art Review and Future Perspective of Deep Learning-Based Models — Iza Sazanita Isa, Umi Kalsom Yusof, Murizah Mohd Zain Applied Sciences, 2023, systematic review, 25 citations · DOI: 10.3390/app13021195
  31. Live birth rate following frozen-thawed blastocyst transfer is higher in high-grade day 6 blastocysts than in low-grade day 5 blastocysts — Wenhao Shi, Hanying Zhou, Lijuan Chen et al. Frontiers in Endocrinology, 2023, cohort, 15 citations · DOI: 10.3389/fendo.2022.1066757
  32. Mitochondrial DNA quantification correlates with the developmental potential of human euploid blastocysts but not with that of mosaic blastocysts — Wen Luo, Yimin Zheng, Hao Yan et al. BMC Pregnancy and Childbirth, 2023, cohort, 10 citations · DOI: 10.1186/s12884-023-05760-w
  33. Interpretable artificial intelligence-assisted embryo selection improved single-blastocyst transfer outcomes: a prospective cohort study. — Wang S, Chen L, Sun H Reproductive biomedicine online, 2023, cohort, 6 citations · DOI: 10.1016/j.rbmo.2023.103371
  34. Validating Incubators in the Lab: Optimizing Culture and Investigating blasTulation Yield Reproductive Medicine Associates of New Jersey, 2023, rct
  35. Embryologist agreement when assessing blastocyst implantation probability: is data-driven prediction the solution to embryo assessment subjectivity? — Daniel E. Fordham, Dror Rosentraub, Avital Luba Polsky et al. Human Reproduction, 2022, case control, 52 citations · DOI: 10.1093/humrep/deac171
  36. Chromosomal mosaicism in human blastocysts: a cytogenetic comparison of trophectoderm and inner cell mass after next-generation sequencing — Effrosyni A. Chavli, Myrthe van den Born, Cindy Eleveld et al. Reproductive BioMedicine Online, 2022, cohort, 16 citations · DOI: 10.1016/j.rbmo.2022.06.004
  37. Embryo morphology and live birth in the United States — Michael S. Awadalla, Jacqueline R. Ho, Lynda K. McGinnis et al. F&S Reports, 2022, cohort, 8 citations · DOI: 10.1016/j.xfre.2022.02.006
  38. Developmental Potential of embryos does not Impact Pregnancy Outcomes, but it Affects Live Birth Rates in Frozen Blastocyst Transfer Cycles. — Andrabi SW, Arora PR, Mir J et al. JBRA assisted reproduction, 2022, cohort, 4 citations · DOI: 10.5935/1518-0557.20210109
  39. O-285 Artificial intelligence algorithms reach expert-level accuracy in automated grading of blastocyst morphology assessment based on static embryo images and Gardner criteria — Florian Kromp, Başak Balaban, V Cottin et al. Human Reproduction, 2022, cohort, 4 citations · DOI: 10.1093/humrep/deac106.078
  40. Retrospective Evaluation Blastocyst Development by Artificial Intelligency University Hospital, Clermont-Ferrand, 2022, cohort
  41. Evaluation of SiD's System for Improving Assisted Reproduction Treatments IVF 2.0 Limited, 2022, rct
  42. O-008 Low grade blastocysts result in healthy live births and should not be discarded — Ben W. Mol, Masoud Afnan, James M. Kemper et al. Human Reproduction, 2022, cohort · DOI: 10.1093/humrep/deac104.008
  43. Developmental Potential of embryos does not Impact Pregnancy Outcomes, but it Affects Live Birth Rates in Frozen Blastocyst Transfer Cycles. — Andrabi SW, Arora PR, Mir J et al. JBRA assisted reproduction, 2022, cohort · DOI: 10.5935/1518-0557.20210105
  44. Development of deep learning algorithms for predicting blastocyst formation and quality by time-lapse monitoring — Qiuyue Liao, Qi Zhang, Xue Feng et al. Communications Biology, 2021, computational, 93 citations · DOI: 10.1038/s42003-021-01937-1
  45. Association between morphologic grading and implantation rate of Euploid blastocyst — Hua Lou, Na Li, Yichun Guan et al. Journal of Ovarian Research, 2021, cohort, 50 citations · DOI: 10.1186/s13048-021-00770-8
  46. A Deep Learning Framework Design for Automatic Blastocyst Evaluation With Multifocal Images — Shanshan Wang, Cong Zhou, Dan Zhang et al. IEEE Access, 2021, cohort, 41 citations · DOI: 10.1109/access.2021.3053098
  47. Cellular Fragments in the Perivitelline Space Are Not a Predictor of Expanded Blastocyst Quality — Bo Yu, Helena T. A. van Tol, Tom A. E. Stout et al. Frontiers in Cell and Developmental Biology, 2021, animal, 8 citations · DOI: 10.3389/fcell.2020.616801
  48. PROspective Study of Mothers' and Infants' Social and Epidemiologic Determinants of Health Northwestern University, 2021, cohort
  49. Blastocyst score, a blastocyst quality ranking tool, is a predictor of blastocyst ploidy and implantation potential — Qiansheng Zhan, Etty Sierra, Jonas E. Malmsten et al. F&S Reports, 2020, cohort, 61 citations · DOI: 10.1016/j.xfre.2020.05.004
  50. Analysis of bovine blastocysts indicates ovarian stimulation does not induce chromosome errors, nor discordance between inner-cell mass and trophectoderm lineages — Desmond A. R. Tutt, Giuseppe Silvestri, María Serrano Albal et al. Theriogenology, 2020, animal, 33 citations · DOI: 10.1016/j.theriogenology.2020.11.021
  51. eValuating iDA Selection Ability. The VISA Study. Vitrolife, 2020, rct
  52. Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilization. — Khosravi P, Kazemi E, Zhan Q et al. NPJ digital medicine, 2019, computational, 472 citations · DOI: 10.1038/s41746-019-0096-y
  53. Deep learning as a predictive tool for fetal heart pregnancy following time-lapse incubation and blastocyst transfer — D Tran, S Cooke, Peter J. Illingworth et al. Human Reproduction, 2019, computational, 313 citations · DOI: 10.1093/humrep/dez064
  54. Automatic grading of human blastocysts from time-lapse imaging — Mikkel Fly Kragh, Jens Rimestad, Jørgen Berntsen et al. Computers in Biology and Medicine, 2019, computational, 134 citations · DOI: 10.1016/j.compbiomed.2019.103494
  55. Assessment of aneuploidy concordance between clinical trophectoderm biopsy and blastocyst — Andrea R. Victor, Darren Karl Griffin, Alan J. Brake et al. Human Reproduction, 2018, cohort, 153 citations · DOI: 10.1093/humrep/dey327
  56. Live birth rate following frozen–thawed blastocyst transfer is higher with blastocysts expanded on Day 5 than on Day 6 — Lucile Ferreux, Mathilde Bourdon, Amira Sallem et al. Human Reproduction, 2018, cohort, 123 citations · DOI: 10.1093/humrep/dey004
  57. Robust Automated Assessment of Human Blastocyst Quality using Deep Learning — Pegah Khosravi, Ehsan Mohamad Kazemi, Qiansheng Zhan et al. bioRxiv (Cold Spring Harbor Laboratory), 2018, cohort, 24 citations · DOI: 10.1101/394882
  58. Comparison of clinical outcome of frozen embryo transfer after embryo selection based on morphokinetic versus morphologic criteria for freezing — Le Nhat Quang, Le Thi Bich Tram, Nguyen Huyen Minh Thuy et al. Biomedical Research and Therapy, 2018, cohort, 2 citations · DOI: 10.15419/bmrat.v5i12.510
  59. Blastocyst culture in the Era of PGS and FreezeAlls: Is a ‘C’ a failing grade? — Dean E. Morbeck Human Reproduction Open, 2017, unknown, 46 citations · DOI: 10.1093/hropen/hox017
  60. Assessment of human embryo development using morphological criteria in an era of time-lapse, algorithms and ‘OMICS’: is looking good still important? — David K. Gardner, Başak Balaban Molecular Human Reproduction, 2016, expert opinion, 234 citations · DOI: 10.1093/molehr/gaw057
  61. Hatching status before embryo transfer is not correlated with implantation rate in chromosomally screened blastocysts. — Rodriguez-Purata J, Gingold J, Lee J et al. Human reproduction (Oxford, England), 2016, cohort, 18 citations · DOI: 10.1093/humrep/dew205
  62. Mitochondrial DNA in Day 3 embryo culture medium is a novel, non-invasive biomarker of blastocyst potential and implantation outcome — Sara Stigliani, Luca Persico, Corrado Lagazio et al. Molecular Human Reproduction, 2014, cohort, 102 citations · DOI: 10.1093/molehr/gau086
  63. Prediction of embryo viability by morphology and metabolomic profiling — Aisling Ahlström Gothenburg University Publications Electronic Archive (Gothenburg University), 2013, cohort
  64. Time-lapse monitoring as a tool for clinical embryo assessment — Kirstine Kirkegaard, Inge Agerholm, Hans Jakob Ingerslev Human Reproduction, 2012, expert opinion, 240 citations · DOI: 10.1093/humrep/des079
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