Prof. Antonio Pellicer - Comtecgroup PPT/Pellicer.pdfProf. Antonio Pellicer Instituto Valenciano de...
Transcript of Prof. Antonio Pellicer - Comtecgroup PPT/Pellicer.pdfProf. Antonio Pellicer Instituto Valenciano de...
Prof. Antonio Pellicer Instituto Valenciano de Infertilidad (IVI)
University of Valencia [email protected]
www.ivi.es
Improving outcomes in ART : Time-lapse technology for monitoring COS
and blastocyst culture
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.
EMBRYONIC IMPLANTATION
MOLECULAR
DIALOGUE
-
Health embryo at blastocyst stage
Adequate Endometrial Receptivity
To select the best embryo/s
HUMAN EMBRYONIC IMPLANTATION
Improvement of ART outcomes
Personalized Embryo Transfer (pET)
Endometrial receptivity assay (ERA)
Other non-invasive methods
Identification/Modification of receptive endometrium
Window of Implantation
Identification of the viable embryo
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
PÁG.8
Time-Lapse Development cc2= t3-t2
t5
CC2
Time post insemination, hours
0 5 10 15 20 25 30
coun
t
0
500
1000
1500
2000
2500
Regular divisionsViable 8 cellViable blastocystImplanted
t5
Time post insemination, hours
30 40 50 60 70 80
coun
t
0
200
400
600
800
1000
1200Regular divisionsViable 8 cellViable blastocystImplanted
PÁG.9
Best correlation
with implantation
success
Predictive ability of embryo implantation
PÁG.10
715, 14%
4510, 86%
Incidence rate of direct division 1-3 in all embryos deviding to 3 cells
Direct division 1-3cells
No direct division1-3 cells
0
10
20
30
DC 1-3 Not DC1-3
2,9 %
28,7%
Impl
anta
tion
Rat
e
*P<0.0001 *
Rubio et al. Fertil Steril 2012; 98(6)
PÁG.11
Morphology
included
ok
Grade A Grade B Grade C Grade D Grade E Discarded
non viable
excluded
yes no
yes no no yes
PÁG.A+
PÁG.11A B+ B C+ C D+ D
CC2 5- 12h CC2 5-12h CC2 5-12h CC2 5-12h
yes no yes no yes no yes no
included
Exclusion Criteria
Direct Cleavage Uneven Blastomere
T5
48-56h
T3
35-40h
T3
35-40h
PÁG.12
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
Meseguer et al. Fertil Steril 2012; 98:1481-9
PÁG.13
Randomized Controlled Trial
Rubio I. et al. Fertil Steril 2014; 102: 1287-94
PÁG.14
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
< 1 mill progressive sperm (A+B)
PÁG.15
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.
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.
SI group
Allocated to intervention(n=412) Received allocated to intervention (n=412)
TMS group
Allocated to intervention(n=444) Received allocated to intervention (n=444)
Randomized (n=856)
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.
Assessed for eligilibility (n=930)
Follow-up (n=412) Follow-up (n=444)
Rubio I. et al. Fertil Steril 2014; 102: 1287-94
PÁG.16
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) 1.86 (1.8-1.9) 1.86 (1.8-1.9) NS
Cryopreserved embryos (per treatment) 3.9 (3.6-4.1) 3.6 (3.4-3.9) NS
46.2 43.1 0.010
20.9 16.6 0.001
Rubio I. et al. Fertil Steril 2014; 102: 1287-94
PÁG.17
Pregnancy (%)
Ongoing pregnancy (%)
Positive ßHCG
Intention to treat All treated cycles All transfers
57.9
49.1
20
25
30
35
40
45
50
55
60
TMS (n=466) SI (n=464)
48.2
36.4
20
25
30
35
40
45
50
TMS (n=466) SI (n=464)
61.6 56.3
202530354045505560
TMS (n=440) SI (n=405)
51.4
41.7
20
25
30
35
40
45
50
55
TMS (n=440) SI (n=405)
54.5
45.3
20
25
30
35
40
45
50
55
60
TMS (n=415) SI (n=373)
65.3 61.1
20
30
40
50
60
TMS (n=415) SI (n=373)
Fetal Heart Beat
p = 0.007
p = 0.0003
p = 0.12
p = 0.005
p = 0.22
p = 0.01
Rubio I. et al. Fertil Steril 2014; 102: 1287-94
PÁG.18
16.6
25.8
0
5
10
15
20
25
30
TMS (n=271) SI (n=228)
All pregnancies
Early pregnancy loss: Positive ßhCG but no FHB
All transferred embryos
p = 0.01
44.9
37.1
20
25
30
35
40
45
50
TMS (n= 775) SI (n=699)
Implantation rate: # embryo sacs / # embryos transferred
Ear
ly p
regn
ancy
loss
(%)
Impl
anta
tion
rate
(%)
p = 0.02
Rubio I. et al. Fertil Steril 2014; 102: 1287-94
PÁG.19
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
Donation 0.83 (0.60-1.14) ns
Age years per year 0.99 (0.94-1.05)
ns
TMS versus SI 1.41 (1.06-1.871) 0.017
Rubio I. et al. Fertil Steril 2014; 102: 1287-94
PÁG.20
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.
Rubio I. et al. Fertil Steril 2014; 102: 1287-94
PÁG.21
Time-lapse data to predict blastocyst development
PÁG.22
Embryo temporal distribution to reach blastocyst stage.
PNF (h)
010203040506070
<22.6 22.7-24.3 24.4-26.3 >26.4
1stC (h)
010203040506070
<25.2 25.3-27.1 27.2-29.1 >29.1
2ndC(h)
01020304050607080
<37.6 37.7-40.1 40.2-43.3 >43.4
p<0.05 p<0.05
Time-lapse data to predict blastocyst development
PÁG.23
Embryo temporal distribution to reach expanded blastocyst stage.
p<0.05 p<0.05
PNF (h)
05
101520253035
<22.6 22.7-24.3 24.4-26.3 >26.4
1stC (h)
05
10152025303540
<25.2 25.3-27.1 27.2-29.1 >29.2
2ndC (h)
05
10152025303540
<37.6 37.7-40.1 40.2-43.3 >43.4
Time-lapse data to predict blastocyst development
PÁG.24 PÁG.24
P<0.001
N= 872
Time-lapse data to predict blastocyst development
PÁG.25 PÁG.25
P<0.001
N= 396
Optimal blastocyst
Time-lapse data to predict blastocyst development
PÁG.26
*
*
229 477 74 134 14
Time-lapse data to predict blastocyst development
PÁG.27
Blastocyst prediction
Tracks cell divisions
Calculates timing intervals
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 markers are outside of range
1. Automated Cell Tracking Software:
Time-lapse data to predict blastocyst development
PÁG.28
Eeva. HIGHHIGH
LOWLOW
PÁG.28
MEDIUMMEDIUM
P2: 9 h 20 min ≤ P2 ≤ 11 h 28 min P3: 0 ≤ P3 ≤ 1 h 44 min
PÁG.29
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
HIgh High-Med Med-High Low
yes no
yes no no yes
cc2
9.33-11.47
s2
0-1.73h
s2
EEVA category Blastocyst Rate Optimal
Algorithm Results Blastocyst prediction (n=840)
PÁG.30
Algorithm Results KID (n=245 transferred embryos)
EEVA category Implantation (%)
HIGH (n=88)
45.5
MEDIUM (n=108)
31.7
LOW (n=49)
30.6
Eeva Morpho
HIgh High-Med Med-High Low
yes no
yes no no yes
cc2
9.33-11.47
s2
0-1.73h
s2
PÁG.31
# p<0.0001 **p<0.001 relative to Morphology only
• 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)
Time-lapse data to predict blastocyst development
Time-lapse and COS
a-
GnR
H
an-G
nRH
hCG FS
H
FSH
N= 319 ICSI oocyte donation cycles N= 2132 embryos
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