Evaluation of an Artificial Intelligence Model for the Prediction of Human Blastocyst Ploidy Without Invasive Procedures
NCT ID: NCT06762704
Last Updated: 2025-01-08
Study Results
Results pending
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
Recruitment Status
NOT_YET_RECRUITING
Total Enrollment
1408 participants
Study Classification
OBSERVATIONAL
Study Start Date
2025-02-28
Study Completion Date
2027-12-31
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
The goal of this clinical trial is to evaluate an artificial intelligence model for the prediction of human blastocyst ploidy without invasive procedures in couples that receive preimplantation genetic testing. The main questions it aims to answer are:
* Is an artificial intelligence model able to predict the ploidy status of a human blastocyst based on its 3D morphology?
* Do quantitative 3D morphological parameters of trophectoderm cells and inner cell mass have strong correlations with human blastocyst ploidy status?
Videos that include multi-view images of each blastocyst from participants will be collected on Day 5/6 of culture, and preimplantation genetic testing results of these blastocysts will be collected 4-8 weeks after trophectoderm biopsy.
* Is an artificial intelligence model able to predict the ploidy status of a human blastocyst based on its 3D morphology?
* Do quantitative 3D morphological parameters of trophectoderm cells and inner cell mass have strong correlations with human blastocyst ploidy status?
Videos that include multi-view images of each blastocyst from participants will be collected on Day 5/6 of culture, and preimplantation genetic testing results of these blastocysts will be collected 4-8 weeks after trophectoderm biopsy.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
Embryo Selection by Noninvasive Preimplantation Genetic Test
NCT04339166
Infertility
Chromosome Abnormality
COMPLETED
NA
Blastocyst Euploidy Assessment and Conditioned embryO traNsfer
NCT02353364
Infertility
UNKNOWN
PHASE1
Cumulative Live Birth Rates After Cleavage-stage Versus Blastocyst-stage Embryo Transfer
NCT03152643
Infertility
COMPLETED
NA
Cumulative Live Birth Rate With eSET After Preimplantation Genetic Screening Versus Conventional In-vitro Fertilization
NCT03118141
Infertility
UNKNOWN
NA
Application of Deep Learning to Jointly Assess Embryo Development to Improve Pregnancy Outcome of Embryo Transfer
NCT05671601
Reproductive Medicine
UNKNOWN
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
Background:
A pilot study has been conducted at The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School from August 2023 to September 2024. Videos and preimplantation genetic testing (PGT) results from 144 blastocysts were retrospectively collected. The artificial intelligence (AI) model first reconstructed the 3D surface of the blastocysts from the videos, and then measured their 3D morphological parameters. Based on these parameters, the model predicted the ploidy status of the blastocysts, and the prediction outputs were compared with the PGT results. The prediction sensitivity, specificity, accuracy and AUC were 90.5%, 91.3%, 90.9% and 0.946, respectively.
Study design:
This is a multi-center, prospective, non-randomized, non-blinded, and single-group study. After being informed about the study and potential risks, all participants will write the informed consents. Videos and PGT results of Day 5/6 blastocysts from each participant will be collected. Blastocysts will be classified as euploid, mosaic, and aneuploid corresponding to \<30%, 30-80%, and \>80% aneuploidy, respectively. Embryo culture, biopsy, and transfer will follow the standard operating procedure (SOP) in the laboratory. The study is non-interventional, and results will not be used to make treatment decisions.
Sample size:
We plan to enroll \~1408 Day 5/6 blastocysts in this trial based on one-sample sensitivity and specificity analysis. Meta-analysis shows that the sensitivity and specificity of the existing AI models are 73.4% (3702/5047) and 69.6% (4892/7028), and those of the non-invasive chromosomal screening methods are 80.3% (678/844) and 73.3% (908/1238) for non-invasively predicting blastocyst ploidy status. This study is presumed to achieve a sensitivity of no less than 85% and a specificity of no less than 80% with a significance level of α = 0.05. A total of 1126 blastocysts are required to achieve a statistical power of 0.9. Assuming a \~20% dropout rate, a total of 1408 blastocysts are anticipated to be enrolled. This sample size calculation is based on the analysis of statistical power and will be regularly revisited/adjusted during the trial period to ensure a high statistical power is achieved.
Data management:
The electronic data capture (EDC) system will be used for data collection. A clinical research coordinator will be assigned at each hospital, and they are responsible for recording the videos and clinical data via the EDC system. A senior clinical research associate will inspect the data in the EDC system regularly among 5 hospitals. The Data Safety and Monitoring Committee (DSMC) is responsible for overseeing the entire research process and the EDC system. For incomplete or missing data in the EDC system, the DSMC will contact the investigators for clarification.
Statistical analysis:
Statistical analysis will be conducted using IBM SPSS Statistics 26. Categorical variables will be described by number and percentage, and numerical variables will be described by mean, standard deviation (SD) and range. The Chi-squared test will be performed to analyze trends in categorical variables, and the t-test will be performed to compare numerical variables among different groups. Pearson correlation will be used to analyze the linear relationship among numerical variables. All statistical tests are two-tailed. P-values of \<0.05 will be considered statistically significant, and odd ratios (ORs) with 95% confidence interval (CI) will be calculated. Logistic regression will be used for multivariate analysis to calculate the adjusted odd ratios (aORs). The performance of the AI for blastocyst ploidy prediction will be evaluated by sensitivity, specificity, accuracy and AUC, with 95% confidence interval.
Missing data will be removed if the proportion of samples with missing values is very small relative to the total sample size. Otherwise, the average, maximum, minimum, medium, or regression model will be used to impute the missing values. Outliers will be treated as the missing data and addressed accordingly.
A pilot study has been conducted at The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School from August 2023 to September 2024. Videos and preimplantation genetic testing (PGT) results from 144 blastocysts were retrospectively collected. The artificial intelligence (AI) model first reconstructed the 3D surface of the blastocysts from the videos, and then measured their 3D morphological parameters. Based on these parameters, the model predicted the ploidy status of the blastocysts, and the prediction outputs were compared with the PGT results. The prediction sensitivity, specificity, accuracy and AUC were 90.5%, 91.3%, 90.9% and 0.946, respectively.
Study design:
This is a multi-center, prospective, non-randomized, non-blinded, and single-group study. After being informed about the study and potential risks, all participants will write the informed consents. Videos and PGT results of Day 5/6 blastocysts from each participant will be collected. Blastocysts will be classified as euploid, mosaic, and aneuploid corresponding to \<30%, 30-80%, and \>80% aneuploidy, respectively. Embryo culture, biopsy, and transfer will follow the standard operating procedure (SOP) in the laboratory. The study is non-interventional, and results will not be used to make treatment decisions.
Sample size:
We plan to enroll \~1408 Day 5/6 blastocysts in this trial based on one-sample sensitivity and specificity analysis. Meta-analysis shows that the sensitivity and specificity of the existing AI models are 73.4% (3702/5047) and 69.6% (4892/7028), and those of the non-invasive chromosomal screening methods are 80.3% (678/844) and 73.3% (908/1238) for non-invasively predicting blastocyst ploidy status. This study is presumed to achieve a sensitivity of no less than 85% and a specificity of no less than 80% with a significance level of α = 0.05. A total of 1126 blastocysts are required to achieve a statistical power of 0.9. Assuming a \~20% dropout rate, a total of 1408 blastocysts are anticipated to be enrolled. This sample size calculation is based on the analysis of statistical power and will be regularly revisited/adjusted during the trial period to ensure a high statistical power is achieved.
Data management:
The electronic data capture (EDC) system will be used for data collection. A clinical research coordinator will be assigned at each hospital, and they are responsible for recording the videos and clinical data via the EDC system. A senior clinical research associate will inspect the data in the EDC system regularly among 5 hospitals. The Data Safety and Monitoring Committee (DSMC) is responsible for overseeing the entire research process and the EDC system. For incomplete or missing data in the EDC system, the DSMC will contact the investigators for clarification.
Statistical analysis:
Statistical analysis will be conducted using IBM SPSS Statistics 26. Categorical variables will be described by number and percentage, and numerical variables will be described by mean, standard deviation (SD) and range. The Chi-squared test will be performed to analyze trends in categorical variables, and the t-test will be performed to compare numerical variables among different groups. Pearson correlation will be used to analyze the linear relationship among numerical variables. All statistical tests are two-tailed. P-values of \<0.05 will be considered statistically significant, and odd ratios (ORs) with 95% confidence interval (CI) will be calculated. Logistic regression will be used for multivariate analysis to calculate the adjusted odd ratios (aORs). The performance of the AI for blastocyst ploidy prediction will be evaluated by sensitivity, specificity, accuracy and AUC, with 95% confidence interval.
Missing data will be removed if the proportion of samples with missing values is very small relative to the total sample size. Otherwise, the average, maximum, minimum, medium, or regression model will be used to impute the missing values. Outliers will be treated as the missing data and addressed accordingly.
Conditions
See the medical conditions and disease areas that this research is targeting or investigating.
The Focus is to Validate the Accuracy of a Non-invasive Artificial Intelligence Model for the Prediction of the Human Blastocyst Ploidy
Preimplantation Genetic Testing (PGT)
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
Observational Model Type
COHORT
Study Time Perspective
PROSPECTIVE
Interventions
Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.
Video recording
Videos of rotating the blastocysts will be recorded during the preparation stage of trophectoderm (TE) biopsy. The focal plane starts from the middle plane of the blastocyst. and then moves downwards until individual TE cells and inner cell mass (ICM) are clearly visible. A biopsy micropipette is used to gently push the blastocyst and rotate the blastocyst each time by a small angle, for instance, smaller than 35° such that more than 10 images can be captured for the entire 360° rotation to achieve high-accuracy measurement. After the first 360° rotation, the second one will be conducted around the axis perpendicular to the previous axis to ensure the whole surface of the blastocyst is captured. The entire rotation process will be video recoded.
Intervention Type
OTHER
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
* Maternal age between 20 and 40; paternal age between 20 and 55.
* Preimplantation genetic testing (PGT) cycles, including PGT for aneuploidy, PGT for monogenic disorders (PGT-M) or PGT for structural chromosome defect (PGT-SR).
* Having at least one Day 5/6 blastocyst developed from two-pronuclear (2PN) embryo which is suitable for trophectoderm biopsy (i.e., degree of expansion: IV, and at least a grade better than C for trophectoderm and inner cell mass grading).
* Couples with written informed consent.
* Preimplantation genetic testing (PGT) cycles, including PGT for aneuploidy, PGT for monogenic disorders (PGT-M) or PGT for structural chromosome defect (PGT-SR).
* Having at least one Day 5/6 blastocyst developed from two-pronuclear (2PN) embryo which is suitable for trophectoderm biopsy (i.e., degree of expansion: IV, and at least a grade better than C for trophectoderm and inner cell mass grading).
* Couples with written informed consent.
Exclusion Criteria
* Couples with contraindications for IVF or PGT.
* Women with all oocytes frozen after retrieval.
* Couples who fail to follow the study protocol.
* Couples deemed ineligible for enrollment by the investigator in consideration of study protocol and treatment safety.
* Women with all oocytes frozen after retrieval.
* Couples who fail to follow the study protocol.
* Couples deemed ineligible for enrollment by the investigator in consideration of study protocol and treatment safety.
Minimum Eligible Age
20 Years
Maximum Eligible Age
55 Years
Eligible Sex
ALL
Accepts Healthy Volunteers
No
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
RenJi Hospital
OTHER
Sponsor Role
collaborator
Jiangxi Maternal and Child Health Hospital
OTHER
Sponsor Role
collaborator
Tangdu Hospital of Air Force Military Medical University
UNKNOWN
Sponsor Role
collaborator
The First Affiliated Hospital of USTC (Anhui Provincial Hospital)
UNKNOWN
Sponsor Role
collaborator
The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School
OTHER
Sponsor Role
lead
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
Wang Shanshan
Director of Department of Reproductive Medicine
Responsibility Role
PRINCIPAL_INVESTIGATOR
Principal Investigators
Learn about the lead researchers overseeing the trial and their institutional affiliations.
Haixiang Sun
Role: PRINCIPAL_INVESTIGATOR
The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
The First Affiliated Hospital of USTC (Anhui Provincial Hospital)
Hefei, Anhui, China
Site Status
The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School
Nanjing, Jiangsu, China
Site Status
Jiangxi Maternal and Child Health Hospital
Nanchang, Jiangxi, China
Site Status
Tangdu Hospital of Air Force Military Medical University
Xi'an, Shaanxi, China
Site Status
Renji Hospital Affiliated to Shanghai Jiao Tong University School of Medicine
Shanghai, Shanghai Municipality, China
Site Status
Countries
Review the countries where the study has at least one active or historical site.
China
Central Contacts
Reach out to these primary contacts for questions about participation or study logistics.
Facility Contacts
Find local site contact details for specific facilities participating in the trial.
Limin Wu
Role: backup
Haixiang Sun
Role: backup
Yan Zhao
Role: backup
Xiaohong Wang
Role: backup
Yun Sun
Role: backup
References
Explore related publications, articles, or registry entries linked to this study.
Scott RT Jr, Ferry K, Su J, Tao X, Scott K, Treff NR. Comprehensive chromosome screening is highly predictive of the reproductive potential of human embryos: a prospective, blinded, nonselection study. Fertil Steril. 2012 Apr;97(4):870-5. doi: 10.1016/j.fertnstert.2012.01.104. Epub 2012 Feb 2.
Reference Type
BACKGROUND
Wang L, Wang X, Liu Y, Ou X, Li M, Chen L, Shao X, Quan S, Duan J, He W, Shen H, Sun L, Yu Y, Cram DS, Leigh D, Yao Y. IVF embryo choices and pregnancy outcomes. Prenat Diagn. 2021 Dec;41(13):1709-1717. doi: 10.1002/pd.6042. Epub 2021 Oct 14.
Reference Type
BACKGROUND
Kushnir VA, Frattarelli JL. Aneuploidy in abortuses following IVF and ICSI. J Assist Reprod Genet. 2009 Mar;26(2-3):93-7. doi: 10.1007/s10815-009-9292-z. Epub 2009 Feb 18.
Reference Type
BACKGROUND
Kim JW, Lee WS, Yoon TK, Seok HH, Cho JH, Kim YS, Lyu SW, Shim SH. Chromosomal abnormalities in spontaneous abortion after assisted reproductive treatment. BMC Med Genet. 2010 Nov 3;11:153. doi: 10.1186/1471-2350-11-153.
Reference Type
BACKGROUND
Sciorio R, Dattilo M. PGT-A preimplantation genetic testing for aneuploidies and embryo selection in routine ART cycles: Time to step back? Clin Genet. 2020 Aug;98(2):107-115. doi: 10.1111/cge.13732. Epub 2020 Apr 6.
Reference Type
BACKGROUND
Munne S, Kaplan B, Frattarelli JL, Child T, Nakhuda G, Shamma FN, Silverberg K, Kalista T, Handyside AH, Katz-Jaffe M, Wells D, Gordon T, Stock-Myer S, Willman S; STAR Study Group. Preimplantation genetic testing for aneuploidy versus morphology as selection criteria for single frozen-thawed embryo transfer in good-prognosis patients: a multicenter randomized clinical trial. Fertil Steril. 2019 Dec;112(6):1071-1079.e7. doi: 10.1016/j.fertnstert.2019.07.1346. Epub 2019 Sep 21.
Reference Type
BACKGROUND
Rosenwaks Z, Handyside AH, Fiorentino F, Gleicher N, Paulson RJ, Schattman GL, Scott RT Jr, Summers MC, Treff NR, Xu K. The pros and cons of preimplantation genetic testing for aneuploidy: clinical and laboratory perspectives. Fertil Steril. 2018 Aug;110(3):353-361. doi: 10.1016/j.fertnstert.2018.06.002. No abstract available.
Reference Type
BACKGROUND
Belandres D, Shamonki M, Arrach N. Current status of spent embryo media research for preimplantation genetic testing. J Assist Reprod Genet. 2019 May;36(5):819-826. doi: 10.1007/s10815-019-01437-6. Epub 2019 Mar 21.
Reference Type
BACKGROUND
Cinnioglu C, Glessner H, Jordan A, Bunshaft S. A systematic review of noninvasive preimplantation genetic testing for aneuploidy. Fertil Steril. 2023 Aug;120(2):235-239. doi: 10.1016/j.fertnstert.2023.06.013. Epub 2023 Jun 24.
Reference Type
BACKGROUND
Alpha Scientists in Reproductive Medicine and ESHRE Special Interest Group of Embryology. The Istanbul consensus workshop on embryo assessment: proceedings of an expert meeting. Hum Reprod. 2011 Jun;26(6):1270-83. doi: 10.1093/humrep/der037. Epub 2011 Apr 18.
Reference Type
BACKGROUND
Ozgur K, Berkkanoglu M, Bulut H, Yoruk GDA, Candurmaz NN, Coetzee K. Single best euploid versus single best unknown-ploidy blastocyst frozen embryo transfers: a randomized controlled trial. J Assist Reprod Genet. 2019 Apr;36(4):629-636. doi: 10.1007/s10815-018-01399-1. Epub 2019 Jan 7.
Reference Type
BACKGROUND
Tiegs AW, Tao X, Zhan Y, Whitehead C, Kim J, Hanson B, Osman E, Kim TJ, Patounakis G, Gutmann J, Castelbaum A, Seli E, Jalas C, Scott RT Jr. A multicenter, prospective, blinded, nonselection study evaluating the predictive value of an aneuploid diagnosis using a targeted next-generation sequencing-based preimplantation genetic testing for aneuploidy assay and impact of biopsy. Fertil Steril. 2021 Mar;115(3):627-637. doi: 10.1016/j.fertnstert.2020.07.052. Epub 2020 Aug 28.
Reference Type
BACKGROUND
Chavez-Badiola A, Flores-Saiffe-Farias A, Mendizabal-Ruiz G, Drakeley AJ, Cohen J. Embryo Ranking Intelligent Classification Algorithm (ERICA): artificial intelligence clinical assistant predicting embryo ploidy and implantation. Reprod Biomed Online. 2020 Oct;41(4):585-593. doi: 10.1016/j.rbmo.2020.07.003. Epub 2020 Jul 5.
Reference Type
BACKGROUND
Diakiw SM, Hall JMM, VerMilyea MD, Amin J, Aizpurua J, Giardini L, Briones YG, Lim AYX, Dakka MA, Nguyen TV, Perugini D, Perugini M. Development of an artificial intelligence model for predicting the likelihood of human embryo euploidy based on blastocyst images from multiple imaging systems during IVF. Hum Reprod. 2022 Jul 30;37(8):1746-1759. doi: 10.1093/humrep/deac131.
Reference Type
BACKGROUND
Barnes J, Brendel M, Gao VR, Rajendran S, Kim J, Li Q, Malmsten JE, Sierra JT, Zisimopoulos P, Sigaras A, Khosravi P, Meseguer M, Zhan Q, Rosenwaks Z, Elemento O, Zaninovic N, Hajirasouliha I. A non-invasive artificial intelligence approach for the prediction of human blastocyst ploidy: a retrospective model development and validation study. Lancet Digit Health. 2023 Jan;5(1):e28-e40. doi: 10.1016/S2589-7500(22)00213-8.
Reference Type
BACKGROUND
Danardono GB, Handayani N, Louis CM, Polim AA, Sirait B, Periastiningrum G, Afadlal S, Boediono A, Sini I. Embryo ploidy status classification through computer-assisted morphology assessment. AJOG Glob Rep. 2023 May 18;3(3):100209. doi: 10.1016/j.xagr.2023.100209. eCollection 2023 Aug.
Reference Type
BACKGROUND
Jiang VS, Bormann CL. Noninvasive genetic screening: current advances in artificial intelligence for embryo ploidy prediction. Fertil Steril. 2023 Aug;120(2):228-234. doi: 10.1016/j.fertnstert.2023.06.025. Epub 2023 Jun 30.
Reference Type
BACKGROUND
Lee CI, Su YR, Chen CH, Chang TA, Kuo EE, Zheng WL, Hsieh WT, Huang CC, Lee MS, Liu M. End-to-end deep learning for recognition of ploidy status using time-lapse videos. J Assist Reprod Genet. 2021 Jul;38(7):1655-1663. doi: 10.1007/s10815-021-02228-8. Epub 2021 May 22.
Reference Type
BACKGROUND
Huang B, Tan W, Li Z, Jin L. An artificial intelligence model (euploid prediction algorithm) can predict embryo ploidy status based on time-lapse data. Reprod Biol Endocrinol. 2021 Dec 13;19(1):185. doi: 10.1186/s12958-021-00864-4.
Reference Type
BACKGROUND
Jiang VS, Kandula H, Thirumalaraju P, Kanakasabapathy MK, Cherouveim P, Souter I, Dimitriadis I, Bormann CL, Shafiee H. The use of voting ensembles to improve the accuracy of deep neural networks as a non-invasive method to predict embryo ploidy status. J Assist Reprod Genet. 2023 Feb;40(2):301-308. doi: 10.1007/s10815-022-02707-6. Epub 2023 Jan 14.
Reference Type
BACKGROUND
Paya E, Pulgarin C, Bori L, Colomer A, Naranjo V, Meseguer M. Deep learning system for classification of ploidy status using time-lapse videos. F S Sci. 2023 Aug;4(3):211-218. doi: 10.1016/j.xfss.2023.06.002. Epub 2023 Jun 30.
Reference Type
BACKGROUND
Shan G, Dai C, Liu H, Wang X, Dou W, Zhang Z, Sun Y. 3D Morphology Measurement for Blastocyst Evaluation From "All Angles". IEEE Trans Biomed Eng. 2023 Jun;70(6):1921-1930. doi: 10.1109/TBME.2022.3232068. Epub 2023 May 19.
Reference Type
BACKGROUND
Shan G, Abdalla K, Liu H, Dai C, Tan J, Law J, Steinberg C, Li A, Kuznyetsova I, Zhang Z, Librach C, Sun Y. Non-invasively predicting euploidy in human blastocysts via quantitative 3D morphology measurement: a retrospective cohort study. Reprod Biol Endocrinol. 2024 Oct 28;22(1):132. doi: 10.1186/s12958-024-01302-x.
Reference Type
BACKGROUND
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
2024-739-02
Identifier Type: -
Identifier Source: org_study_id
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.
RCT Study to Validate niPGT-A Clinical Benefit.
NCT04000152
TERMINATED
NA
Predictive Value of Embryonic Testing
NCT03604107
COMPLETED
Investigating the Cryopreserved Blastocyst's ImplantatiOn Potential After Genetic Screening
NCT03173885
TERMINATED
NA
Preimplantation Genetic Testing for Aneuploidy of Polar Bodies
NCT04538560
UNKNOWN
NA
Cleavage-stage Versus Blastocyst-stage Embryo Transfer in IVF Patients With Few Embryos
NCT06746129
RECRUITING
PHASE3
Performance of CHLOE Algorithm on the Prediction of Blastocyst Formation
NCT05455281
COMPLETED
Hyaluronic Acid-enriched Transfer Medium in Single Blastocyst Transfer
NCT06492785
RECRUITING
NA
A Multicenter Prospective Randomized Controlled Clinical Trial Comparing Constant (5%) Versus Sequential (5%-2%) Oxygen Concentration Embryo Culture Protocols in Assisted Reproductive Technology
NCT07050537
RECRUITING
NA
Study of the Best Blastocyst Post Transfer by aCGH
NCT01664546
UNKNOWN
Comparison Between Biopsied and Non-biopsied Intracytoplasmatic Sperm Injection (ICSI) Embryos and Natural Pregnancy Embryos
NCT04280757
UNKNOWN
PGT-A Versus Blastocyst Morphology Selection
NCT03095053
COMPLETED
NA
Efficiency of Comprehensive Chromosomal Testing of Trophectoderm Biopsies of Blastocysts in In Vitro Fertilization
NCT04758819
RECRUITING
NA
Longitudinal Clinical Observation of a Digital Twin Model for Blastocyst Evaluation in IVF Clinics
NCT07305480
ACTIVE_NOT_RECRUITING
Data Collection and Professional Simulated Use Study to Develop an Embryo Quality Artificial Intelligence (AI) Model
NCT07017972
RECRUITING
Preimplantation Genetic Diagnosis Using Blastocyst Biopsy and Array CGH
NCT01546350
SUSPENDED
PHASE2
Idealizing Pregnancy Outcome With Single Blastocyst Transfer in a FET Cycle
NCT01987856
WITHDRAWN
NA
Preimplantation Genetic Screening in IVF Treatment
NCT05009745
UNKNOWN
NA
International Pilot Study for Dual Non-invasive Assesment of Embryo Development
NCT06524648
RECRUITING
Pregnancy and Developmental Outcomes After Transfer of Reportedly Aneuploid or Mosaic Embryos
NCT04109846
RECRUITING
NA
Comparison of Single vs Group Embryo Culture in Micro-well Group Culture Dish
NCT02050516
UNKNOWN
NA
Next Generation Sequencing Screening for Embryonic Ploidy Status
NCT02032264
COMPLETED
NA
Follow-up Study of Frozen-thawed Embryo Transfer (FTET) Cycles After Cryopreservation of Embryos in Clinical Trial P05787 (P05716)
NCT00702273
COMPLETED
A Prospective Study Comparing the Outcomes of Single Versus Group Culture in Preimplantation Genetic Testing Cycles
NCT03464643
UNKNOWN
NA
Evaluating the Influence of 3D Culture Dish Design on Preimplantation Genetic Development in Sibling Oocytes: a Randomized Trial
NCT06850909
NOT_YET_RECRUITING
NA
Single Embryo TrAnsfeR of Euploid Embryo
NCT02268786
COMPLETED
NA