Improving outcomes in ART : Time-lapse technology for monitoring COS and blastocyst culture Prof. Antonio Pellicer Instituto Valenciano de Infertilidad (IVI) University of Valencia apellicer@ivi.es www.ivi.es
DISCLOSURE - Invitation by an unrestricted Educational Grant from COMTECMED to ASRM - IVI is a minor shareholder in Unisense Fertilitech A/S. - IVI is a minor shareholder in Auxogyn Co. - This work has not received any financial support from any commercial entity and the instrumentation, disposables and utensils belong to IVI.
HUMAN EMBRYONIC IMPLANTATION Health embryo at blastocyst stage - To select the best embryo/s MOLECULAR DIALOGUE Adequate Endometrial Receptivity
Improvement of ART outcomes Personalized Embryo Transfer (pet) Identification/Modification of receptive endometrium Identification of the viable embryo Window of Implantation Endometrial receptivity assay (ERA) Other non-invasive methods Invasive methods: CCS (D3 or D5) Non-invasive methods: Morphology Time-lapse Proteomics Metabolomics
Improvement of ART outcomes Personalized Embryo Transfer (pet) Identification of the viable embryo Repeated implantation failure (RIF) Aged patients Reduced ovarian reserve Endometriosis Severe male factor Recurrent miscarriage
Improvement of ART outcomes Personalized Embryo Transfer (pet) Identification of the viable embryo Time-lapse Invasive methods: CCS (D3 or D5).in ALL ART CYCLES?
Time-Lapse Technology Time-Lapse Imaging - Blastomere Activity
Time-Lapse Development cc2= t3-t2 count 2500 2000 1500 1000 Regular divisions Viable 8 cell Viable blastocyst Implanted CC2 500 0 0 5 10 15 20 25 30 Time post insemination, hours t5 1200 1000 800 Regular divisions Viable 8 cell Viable blastocyst Implanted t5 count 600 400 200 PÁG.8 0 30 40 50 60 70 80 Time post insemination, hours
Predictive ability of embryo implantation Best correlation with implantation success PÁG.9
Incidence rate of direct division 1-3 in all embryos deviding to 3 cells 4510, 86% 715, 14% Direct division 1-3 cells No direct division 1-3 cells 30 *P<0.0001 * 28,7% Implantation Rate 20 10 2,9 % 0 DC 1-3 Not DC1-3 PÁG.10 Rubio et al. Fertil Steril 2012; 98(6)
Morphology ok Exclusion Criteria Direct Cleavage Uneven Blastomere non viable included 48-56h excluded T5 yes 35-40h no 35-40h T3 T3 yes no yes no Grade A Grade B Grade C Grade D Grade E Discarded CC2 5-12h CC2 5-12h CC2 5-12h CC2 5-12h yes no yes no yes no yes no A + G.11A B + B C + C D + D PÁG.11
Time-Lapse: Initial findings Embryo morphology correlates with embryo classification by time-lapse Embryo quality and implantation correlate with embryo classification by time-lapse In a retrospective study, time-lapse (n=1372 cycles) as compared to conventional incubators (n=5872 cycles): reduced significantly (2.8% vs 5.2%) cycle cancellation rates Increased significantly (59.1 vs 50%) ongoing pregnancy rates PÁG.12 Meseguer et al. Fertil Steril 2012; 98:1481-9
Randomized Controlled Trial PÁG.13 Rubio I. et al. Fertil Steril 2014; 102: 1287-94
Inclusion Criteria ICSI MII 6 Age 20-38 Previous Cycles 2 BMI 18-25 Basal FSH <12 AMH >7 pmol/l Exclusion Uterine Pathologies Hydrosalpinx Recurrent Miscarriage Endometriosis PÁG.14 < 1 mill progressive sperm (A+B)
Not meeting inclusion criteria (n=22) No embryoslides available, n=8 IVF as fertilization procedure, n=5. Testicular Sperm or Cripto, n=5. Already randomized, n=1. Low respond, n=3. Assessed for eligilibility (n=930) Randomized (n=856) Not meeting inclusion criteria (n=52) Patient request TMS, n=30 IVF as fertilization procedure, n=14. Testicular sperm or cripto, n=5. Already randomized, n=1. Advanced maternal age, n=1. Low respond, n=1. TMS group Allocated to intervention(n=444) Received allocated to intervention (n=444) SI group Allocated to intervention(n=412) Received allocated to intervention (n=412) Follow-up (n=444) Follow-up (n=412) Analyzed (n=438) Excluded (n=6) Cancelled donation, n=2. Embryo vitrified, n= 4. Analyzed (n=405) Excluded (n=7) Endometrial bleeding, n=1. Cancelled donation, n=2. Embryos vitrified, n=4. PÁG.15 Rubio I. et al. Fertil Steril 2014; 102: 1287-94
TMS GROUP(n=438) CONTROL GROUP(n=404) p Blastocyst rate (%) 27.5 24.5 NS Embryo Fragmentation (%) 7.5 (7.2-7.9) 6.9 (6.5-7.1) 0.06 Number of Blastomeres 6.9 (6.8-6.9) 6.9 (6.8-7.0) NS Optimal Embryos (D3) (%) 46.2 43.1 0.010 Blastocyst rate (%) 52.3 50.5 NS Optimal Blastocyst (D5) (%) 20.9 16.6 0.001 Transferred embryos (per treatment) Cryopreserved embryos (per treatment) 1.86 (1.8-1.9) 1.86 (1.8-1.9) NS 3.9 (3.6-4.1) 3.6 (3.4-3.9) NS PÁG.16 Rubio I. et al. Fertil Steril 2014; 102: 1287-94
Intention to treat All treated cycles All transfers Pregnancy (%) Positive ßHCG 60 55 50 45 40 35 30 25 57.9 49.1 p = 0.007 60 55 50 45 40 35 30 25 61.6 56.3 p = 0.12 60 50 40 30 65.3 61.1 p = 0.22 20 TMS (n=466) SI (n=464) 20 TMS (n=440) SI (n=405) 20 TMS (n=415) SI (n=373) Ongoing pregnancy (%) Fetal Heart Beat 50 45 40 35 30 25 48.2 36.4 p = 0.0003 55 50 45 40 35 30 25 51.4 41.7 p = 0.005 60 55 50 45 40 35 30 25 54.5 p = 0.01 45.3 20 TMS (n=466) SI (n=464) 20 TMS (n=440) SI (n=405) 20 TMS (n=415) SI (n=373) PÁG.17 Rubio I. et al. Fertil Steril 2014; 102: 1287-94
All pregnancies All transferred embryos Early pregnancy loss (%) 30 25 20 15 10 5 0 16.6 TMS (n=271) p = 0.01 25.8 SI (n=228) Implantation rate (%) 50 45 40 35 30 25 20 44.9 37.1 p = 0.02 TMS (n= 775) SI (n=699) Early pregnancy loss: Positive ßhCG but no FHB Implantation rate: # embryo sacs / # embryos transferred PÁG.18 Rubio I. et al. Fertil Steril 2014; 102: 1287-94
Model effect values OR p value Incubation TMS versus SI 1.41 (1.06-1.871) 0.017 Day of Transfer Day 5 versus Day 3 1.76 (1.22-2.52) 0.002 Oocyte source Autologous versus 0.83 (0.60-1.14) ns Donation Age years per year 0.99 (0.94-1.05) ns PÁG.19 Rubio I. et al. Fertil Steril 2014; 102: 1287-94
If all of the 6000 treatments in the conventional incubator had been carried out using Time-Lapse Incubator, we could have expected about 545 additional pregnancies. PÁG.20 Rubio I. et al. Fertil Steril 2014; 102: 1287-94
PÁG.21 Time-lapse data to predict blastocyst development
Time-lapse data to predict blastocyst development Embryo temporal distribution to reach blastocyst stage. PNF (h) 1stC (h) 70 60 70 60 50 40 50 40 30 20 10 0 <22.6 22.7-24.3 24.4-26.3 >26.4 30 20 10 0 <25.2 25.3-27.1 27.2-29.1 >29.1 p<0.05 p<0.05 2ndC(h) PÁG.22 80 70 60 50 40 30 20 10 0 <37.6 37.7-40.1 40.2-43.3 >43.4
Time-lapse data to predict blastocyst development Embryo temporal distribution to reach expanded blastocyst stage. PNF (h) 1stC (h) 35 30 25 20 15 10 5 0 <22.6 22.7-24.3 24.4-26.3 >26.4 40 35 30 25 20 15 10 5 0 <25.2 25.3-27.1 27.2-29.1 >29.2 p<0.05 p<0.05 2ndC (h) PÁG.23 40 35 30 25 20 15 10 5 0 <37.6 37.7-40.1 40.2-43.3 >43.4
Time-lapse data to predict blastocyst development N= 872 P<0.001 PÁG.24
Time-lapse data to predict blastocyst development N= 396 Optimal blastocyst P<0.001 PÁG.25
Time-lapse data to predict blastocyst development * * 477 74 134 14 229 PÁG.26
Time-lapse data to predict blastocyst development Tracks cell divisions Calculates timing intervals Blastocyst prediction 1. Automated Cell Tracking Software: Feeds timings to the classification tree Generates an automated prediction 2. Classification Tree HIGH probability to form a blastocyst if cell cycle markers are within range LOW probability to form a blastocyst if cell cycle PÁG.27 markers are outside of range
Eeva. HIGH LOW MEDIUM PÁG.28 P2: 9 h 20 min P2 11 h 28 min P3: 0 P3 1 h 44 min
Algorithm Results Blastocyst prediction (n=840) EEVA category Blastocyst Rate (%) Optimal Blastocyst Rate (%) HIGH (n=103) 77.7 27.2 MEDIUM (n=467) 56.3 19.3 LOW (n=270) 49.6 17.4 9.33-11.47 cc2 yes 0-1.73h no s2 s2 yes no yes no PÁG.29 HIgh High-Med Med-High Low
Algorithm Results KID (n=245 transferred embryos) Eeva Morpho EEVA category Implantation (%) 9.33-11.47 HIGH (n=88) MEDIUM (n=108) LOW (n=49) 45.5 31.7 30.6 cc2 yes 0-1.73h no s2 s2 yes no yes no HIgh High-Med Med-High Low PÁG.30
Time-lapse data to predict blastocyst development Specificity measures false positives Significantly improved in 3 out of 3 embryologists More consistent embryo assessment using D3 morphology + Eeva information Conaghan et al. Fertility & Sterility (2013) # p<0.0001 **p<0.001 relative to Morphology only PÁG.31
Time-lapse and COS N= 319 ICSI oocyte donation cycles N= 2132 embryos a-gnrh hcg an-gnrh FSH FSH
CONCLUSIONS Personalized Medicine is the next step in ART Time-lapse is a good method of embryo selection: correlation with embryo quality, implantation, ongoing pregnancy rates and miscarriage. Time-lapse increases ongoing pregnancy rates by 10% in RCTs Time-lapse is helpful in the prediction of blastocyst development
Aknowledgements Marcos Meseguer Irene Rubio Carmen Rubio Daniela Galliano Manuel Munoz Carlos Simón