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




Repeated implantation failure (RIF)

Aged patients

Reduced ovarian reserve

Endometriosis

Severe male factor

Recurrent miscarriage




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)


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


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


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


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


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.


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


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


PÁG.24 PÁG.24

P<0.001

N= 872


PÁG.25 PÁG.25

P<0.001

N= 396

Optimal blastocyst


PÁG.26

*

*

229 477 74 134 14


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:


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 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

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