Presentación de PowerPoint - EXCEMED
Transcript of Presentación de PowerPoint - EXCEMED
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Disclosure
Marcos MeseguerValencian Infertility Institute (IVI)Valencia, Spain
Declared no potential conflict of interest.
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How we can use recent technology in the IVF cycles to improve IVF
Marcos Meseguer
Spain
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✓ What makes a difference? technologies?
Excellence in IVF?
IVF Lab
Vitrification
GeneticScreening
IMSI
Macs
PolarizedMicroscopy
Time-Lapse
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Meseguer M. Fertil Steril. 2016;105:295-6.
Time-lapse the remaining questions
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Time-lapse set-up; IVI Valencia
Less disturbancebetter development
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Time-lapse set-up; IVI Valencia
Less disturbancebetter development
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Time-lapse set-up; IVI Valencia
More observations better selection
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Time-lapse set-up; IVI Valencia
Less disturbancebetter development
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INDIVIDUAL CHAMBERS & BENCHTOP
Fast Tº & CO2 recovery
Small volume
Undisturbed culture
Continuous monitoring
Time lapse incubator: Exploring Biomimetics Concepts
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D5+D6 D5
Blastocyst Rate
20%
30%
40%
50%
60%
70%
80%69,00%
64,70%
75,00%69,60%
Dry Conditions
Humid Conditions
Albert C and Meseguer M Alpha 2018
Improved Cultured conditions Dry vs Humid conditions
**
10%
20%
30%
40%
50%
60%
70%
80%
90%
Abortion Pregnancy
Blastocyst Rate
26,50%
66,70%
16,00%
83,30%
Dry Conditions
Humid Conditions
n=1366 EmbryosN=84 patients
Time lapse incubator: Exploring Biomimetics Concepts
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Albert C and Meseguer M Alpha 2018
Improved Cultured conditions Dry vs Humid conditions
n=1366 EmbryosN=84 patients
0
20
40
60
80
100
120
Dry Conditions
Humid Conditions
Time lapse incubator: Exploring Biomimetics Concepts
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Albert C and Meseguer M Alpha 2018
Improved Cultured conditions Dry vs Humid conditionsn=1366 Embryos
N=84 patients
40,0
50,0
60,0
70,0
80,0
90,0
100,0
110,0
120,0
130,0
H1sm H2sm H3sm Ratiosm AVEHsm
Co
un
ts P
er
Seco
nd
Embryo Spent Culture Media Oxidation-ThermoChemoluminiscence (TCL)
Humid
Dry
Time lapse incubator : Exploring Biomimetics Concepts
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The evolution of TL incubators
ESD+; Precision Embryology
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HIGHEST RESOLUTION VIDEOS
ESD+; Precision Embryology
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Accurate Annotations
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Accurate Annotations
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Accurate Annotations
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CLINICAL RESULTS JANUARY 2016–JUNE 2017
All blastocysts 90% SET
Standard incubator (no evaluation on cleavage stage) vs time-lapse
More observations Better selection
Less disturbanceBetter development
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41.1%58.9%
Number of cyclestime-lapse vs conventional
incubator
CI TIME-LAPSE
Conventional incubators vs time-lapse incubators(n = 5574)
CONVENTIONALINCUBATOR
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Ongoing pregnancy
*
*p < 0.05
More observations Better selection
Less disturbanceBetter development
PGS, preimplantation genetic screening. Meseguer M, personal data.
Fresh or deferred first-transfer time-lapse - NO PGS
Age
% O
ngo
ing
pre
gnan
cy
*
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Ongoing pregnancy
Meseguer M, personal data.
PGS first-transfer trophoectoderm biopsy time-lapse vs standard incubator
More observations Better selection
Less disturbanceBetter development
Age
% O
ngo
ing
pre
gnan
cy
*
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56,2
0,8 0,7
41,3
1
55
1,5 0,3
42,4
0,8
52,8
0 0
47,2
00
10
20
30
40
50
60
ABNORMAL ABNORMAL/DESEQ AMPLIFICATION FAILURE NORMAL NORMAL/EQUIL
CI
ESD
GERI
*
*p = 0.022
n = 163
n = 1,832
n = 3,307
Meseguer M, personal data.
Less disturbanceBetter development
% ploidy of the results in each incubatorN = 5,311 blastocysts
*
CONVENTIONAL INCUBATOR
ESD
% p
loid
yOUTCOME FROM DIFFERENT TIME-LAPSE SYSTEMS
GERI
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n = 4,573
n = 3,614n = 366
0
5
10
15
20
25
30
35
40
CI EEVA ESD GERI
Less disturbanceBetter development
Meseguer M, personal data.
% of good-quality blastocysts (A/B) on Day 5 in each incubator
**
CONVENTIONAL INCUBATOR
% o
f go
od
-qu
alit
y b
last
ocy
sts
(A/B
)
OUTCOME FROM DIFFERENT TIME-LAPSE SYSTEMS
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Evolution of the data; exponential growth
1653 2120 363011699
44800
78000
124000
189000
243000
288000
0
50000
100000
150000
200000
250000
300000
350000
YEAR 2009 2010 2011 2012 2013 2014 2015 2016 2017
EMBRYOS RECORDED
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Manual annotations
Database registration
Exponential growth of time required for data acquisition/annotation…
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Next evolutionary steps of automated software analysis for CEM
27
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The evolution of the analysis in DANA: V2.0. Machine vs Embryologists
Del Gallego ASRM 201828
Phase 4
Prospective Automatic
DANA vs Embryologist
320 embryos
Event detection
V.2% Total %V.1%
Precision embryology
92%97%
90%86%
91%
9%13%
87%
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The evolution of the analysis: Software vs embryologist
Del Gallego, ASRM 201829
Phase 4
Prospective Automatic
DANA vs Embryologist
320 embryos
Accuracy
Detected events % of Events in Range
Precision embryology
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Meseguer and Hickman, Eshre 2018
The evolution of the a analysis; artificial Intelligence vs embryologist
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Grade of
Expansion
Cat. 1
2
Cat. 2
3
Cat. 3
4
Kappa
Average
Kappa 0.751
(0.620-0.883)
0.652
(0.521-0.783)
0.790
(0.659-0.921)
0.729
(0.632-0.826)
P-value < 0.001 < 0.001 < 0.001 < 0.001
Inner Cell MassCat. 1
1
Cat. 2
2
Cat. 3
3
Kappa
Average
Kappa da
categoria
0.779
(0.363-0.446)
0.688
(0.137-0.220)
0.681
(0.551-0.811)
0.705
(0.606-0.804)
P-value < 0.001 < 0.001 < 0.001 < 0.001
TrophoectodermCat. 1
1
Cat. 2
2
Cat. 3
3
Kappa 0.382
(0.256-0.507)
0.402
(0.273-0.531)
0.501
(0.370-0.631)
0.438
(0.332-0.544)
P-value < 0.001 < 0.001 < 0.001 < 0.001
Meseguer, Hickman Rocha. Eshre 2018
The evolution of the a analysis; artificial Intelligence vs embryologist
Grade of
Expansion
Cat. 1
2
Cat. 2
3
Cat. 3
4
Cat. 4
5
Kappa
Average
Kappa 0.422
(0.464-0.381)
0.222
(0.181-0.264)
0.508
(0.466-0.549)
0.114
(0.072-0.155)
0.371
(0.342-0.400)
P-value < 0.001 < 0.001 < 0.001 < 0.001 < 0.001
Inner Cell MassCat. 1
1
Cat. 2
2
Cat. 3
3-
Kappa
Average
Kappa da
categoria
0.404
(0.363-0.446)
0.178
(0.137-0.220)
0.285
(0.243-0.326)-
0.267
(0.236-0.298)
P-value < 0.001 < 0.001 < 0.001 - < 0.001
TrophoectodermCat. 1
1
Cat. 2
2
Cat. 3
3
Kappa 0.353
(0.312-0.395)
0.209
(0.167-0.250)
0.376
(0.334-0.417)-
0.299
(0.268-0.331)
P-value < 0.001 < 0.001 < 0.001 - < 0.001
Embryologist vs artificial Intelligence
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Meseguer M, personal data.
Machine Learning Embryo selection Software
360 videos and corresponding metadata (morphokinetics and clinical data); LiveBirth Prediction
1. Image Processing
2. Learning Embeddings of Images
3. Training Prediction Model using Image
4. Creating features from embryo meta-data
5. Training Prediction Model using embryo meta-data
6. Combining two prediction models (image + meta-data) to produce final prediction for the embryo
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RCT, randomized controlled trial. Pribenszky C, et al. Reprod Biomed Online. 2017;35:511-20.
The last metanalysis reported More observations Better selection
Less disturbanceBetter development
Outcomes
Assumed risk(conventional
incubation, median-risk population)
Corresponding risk(time-lapse,Median-riskpopulation)
Relativeeffect
(95% CI)
No. of participants
(studies)
Quality ofevidence (GRADE)
Ongoing pregnancy 410/1,000517/1,000(457–577)
OR 1.542 (1.211–1.965)
1,637 (5 RCTs) Moderate 1.5
Early pregnancy loss 196/1,000139/1,000(103–186)
OR 0.662 (0.469–0.935)
904 (5 RCTs) Moderate 2.5
Live birth 321/1,000441/1,000(349–537)
OR 1.668(1.134–2.455)
481 (3 RCTs) Moderate 3.5
Stillbirth 29/1,00069/1,000(23–188)
OR 2.483(0.794–7.759)
481 (3 RCTs) Low 4.5
GRADE Working Group grades of evidence• High quality: further research is very unlikely to change our confidence in the estimate of effect• Moderate quality: further research is likely to have an important impact on our confidence in the estimate of effect and may
change the estimate• Low quality: further research is very likely to have an important impact on our confidence in the estimate of effect and is
likely to change the estimate• Very low quality: we are very uncertain about the estimate
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Vitrification in IVF
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Vitrification as an adjunct tool to PGT programs
1 hour
Vitrification
NGS
Euploid
blastocysts
Embryo transfer
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0,00%
20,00%
40,00%
60,00%
80,00%
100,00%
SV IR CPR OPR
93,60%
56,20% 60,90%53,90%
N=3552 embryos
6% Euploid Embryos do not Survive
and ~40% do not implant
Overall outcomes in PGT cycles: TE biopsy + blastocyst vitrification
What are the reasons for the failure
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Implantation failure of Euploid Embryos
✓Synchrony embryo-endometrium✓Age: Older patients are more likely
to have “slow” embryos✓Immunology and uterine receptivity
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✓ Harmful effect of vitrification?✓ Embryo quality?
Survival Failure of Euploid Embryos
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Implantation rate according to embryo quality
Own oocytes Ovum donation
IVI data 2016-2017 (Unpublished)
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The biopsied blastocysts…o SV and IRo TE scoreo Expansion
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Evaluation of Survival. Post-warming observations
2. Clearly Dead
T0 post-warmingPost-biopsy 6h post-warming 6h post warming
1. Clearly Alive
T0 post-warming
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PGT Day 5-6 blastocyst. Embryo quality according to ASEBIR
22,40%
56,90%
19,90%
0,60%
A
B
C
D
N=3974 embryos
Embryo quality and PGT outcomes.
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*= P<0.05N=3974 embryos
97,8
63,7 63,357,1
92,9
56,7 59,751,8
92
45,4 44,936,7
0
20
40
60
80
100
120
SV rate (%) IR (%) CPR (%) OPR (%)
ASEBIR PGS D5+D6
A B C
*
*
* ** *
*
Survival and Clinical outcomes for PGT embryos according to embryo quality (ASEBIR)
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PGT. SV and IR according to embryo quality and day of biopsy/vitrification
94,8%95,7%
92,6%91,9%
87,3%85,7%
80,0%
82,0%
84,0%
86,0%
88,0%
90,0%
92,0%
94,0%
96,0%
98,0%
A B C
Survival according to ASEBIR
SV D5 SV D6
* *
Nº warmed D5 embryos
A
B
C
Number of warmed D6 embryos A
B
62,9%58,1%
51,1%
58,4%52,8%
41,0%
0,0%
10,0%
20,0%
30,0%
40,0%
50,0%
60,0%
70,0%
A B C
IR according to ASEBIR
IR D5 IR D6
**
* P<0.05
25,8%
61,3%
12,9%
16,8%
51,6%
31,5%
Day5 Day6
Nº warmed embryos 2159 1815
* P<0.05
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PGT. SV and IR according to Blastocyst expansion and day of biopsy/vitrification
NS
98,9% 99,6%
92,9%
98,6% 99,6%
88,5%
80,0%
85,0%
90,0%
95,0%
100,0%
105,0%
BE BHi BH
Survival rate Day 5/6
SV D5 SV D6
73,7%
53,6%
43,7%
75,0%
43,0%37,7%
0,0%
10,0%
20,0%
30,0%
40,0%
50,0%
60,0%
70,0%
80,0%
BE BHi BH
Implantation rate Day 5/6
IR D5 IR D6
*
Nº embryos D5
BHi
83,8%
11%5,2%
Nº embryos D6
BHi
65,7%
30,8%3,5%
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o Both survival and IR are closely related toembryo quality.
o Type A embryos: comparable resultsbetween day-5 and day 6 (IR).
o Type B and C embryos: higher outcomesfor day 5 vs. day 6 (SV and IR).
o Hatched Blastocysts yield the lowestoutcomes.
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The hatched blastocyst.
Can we do better?
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Evaluation of survival of biopsied blastocysts can be sometimes difficult, especially with hatched blastocysts….
t0
4.5h post warming
1.
**
t0
2h post warming
4.
**
2.
*
t0
3.
*
t0
T0 post-warming 2h post-warming
5.
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TimingProgramming of biopsies and vitrification procedures in order to perform the biopsy at the HiB stage. RESCHEDULE.
If not sure of the quality of the blastocyst once biopsied: Do the tubbing and wait at least 2 hours before going on with the vitrification procedure.
Timing after warming: Make sure about survival: re-expansion.
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Re-expansion of the he warmed biopsied blastocyst
ZP-Included: 3.2h ZP-Included: 4.3h Hatched Blastocysts: 5.3h
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Initiation of re-expansion
Coello, A., et al. (2017) Fertil Steril 108(4): 659-666 e654.
Time-lapse evaluation of re-expansion of warmed blastocysts (No PGT)
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Timing for cryotransfer after warming
64,80% 63,60%
50,00%
35,30%
0,00%
10,00%
20,00%
30,00%
40,00%
50,00%
60,00%
70,00%
up to 4 hours 4-5 hours 5-6 hours >6 hours
Included within the ZPCPR
60,90%68,20%
81,80%
50,00%
0,00%
10,00%
20,00%
30,00%
40,00%
50,00%
60,00%
70,00%
80,00%
90,00%
up to 4hours
4-5 hours 5-6 hours >6 hours
Hatching and Hatched Blastocysts
CPR
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The Operator
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Capalbo et al. (2016). Hum Reprod 31(1): 199-208.
Operator experience and outcome
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This technology is the combination of:
- A single dish were the embryos remain meanwhile the media
are exchanged automatically.
- Automatic sealing “reduce cross contamination risk”
- Very thin dish walls to allow quick vitrification and warming
Fungible of individual use; Gavi Dish, Cassette, Gavi Cartridge
with media, Gavi Cartridge with pipette and seal.
4 steps
Automated Vitrification Instrument
Source: Web search
AUTOMATION IN THE IVF LAB
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Acknowledgements:
Lucia Alegre (DANA)Raquel del Gallego (DANA)
Lorena Bori (ESD+)Ernesto Bosch (Data Analysis)
Belen Aparicio-Ruiz (Eeva)Carmela Albert (Geri)
Sonia Perez-Albala (Eeva)
Thank you
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