EMBRYO SELECTION IS VITAL FOR SUCCESSFUL IVF WHY TIME-LAPSE - - PowerPoint PPT Presentation

EMBRYO SELECTION IS VITAL FOR SUCCESSFUL IVF – WHY TIME-LAPSE IMAGING IS PROVING IMPORTANT

• Prof. Fishel Simon

THE EMBRYO – WHY THE FOCUS?

• Largest single cause of IVF

failure.

• Single main cause of early

miscarriage.

5 10 15 20 25 30 35 40 45 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44

Live Birth Female age

%

~ 35% of embryos make babies

THE EMBRYO – A NEED TO SELECT THE MOST VIABLE Time Lapse Imaging (non-invasive)

• PGT-A (preimplantation Genetic Screening-Aneuploidy)

SELECTING EMBRYOS – TIME LAPSE IMAGING

• There’s Time-Lapse Imaging…

(using it as a closed microscope)

• Predicting blastulation
• and there’s
• CAREmaps!

CAREMAPS – COMPUTING MORPHOKINETICS

• Time to cell stages.
• Durations.
• Dynamics e.g.
• Pronuclei.
• Reverse cleavage.
• Compaction.
• Blastulation.
• Strings.

morphokinetic

TIME-LAPSE IMAGING – CONSTANT VISUAL OF MORPHODYNAMICS

Intracytoplasmic

• Granulation.
• Refractile bodies.
• Vacuolation.
• Smooth Endoplasmic Reticulum

Clustures.

• Multi Nuclei.
• Pronuclei.

Extracytoplasmic

• Polar body.
• Perivitelline space.
• Zona Pellucida.
• Fragments.

Imaging - Single v 300/day!

CAREMAPS ATLAS

BMA Annual Book Awards 2016

BLASTOCOEL COLLAPSE IS NOT A GOOD THING

‘Embryos that exhibit collapse are as likely to hatch as those that do not, but are less likely to implant and should not be replaced if alternatives are available’.

(Meseguer et al 2015, Human Reprod)

715 transferred blastocysts

Difficult to detect without TLI.

TIME LAPSE ALLOWS NOVEL OBSERVATIONS

• Which may be used to enhance embryo selection.

CARE Fertility example:

• Angle between polar bodies.

AN ACTIVE ACTIVATED EGG & PIV!

SIGNIFICANTLY  CPR WHERE ANGLE OF PB2 EXTRUSION WAS >45° FROM PB1.

• Retrospective Logistic

regression analysis of 2,367 ICSI transferred blastocysts, all ages – known clinical outcome (KID)

(p<0.001, n=2,367)

8 16 24 32 40 < 45 > 45 % Angle between PBs

Clinical Pregnancy

TIME-LAPSE TO PREDICT BLASTULATION

• A high percentage of blastocyts never make

babies.

• A significant percentage of blastocysts result in

miscarriage.

• Some blastocysts make unhealthy babies.
• A case(s) in point…

Of the 9, 7 predicted to be a blastocyst. They did. All 7 were chromosomally abnormal!

‘CAREMAPS’

M.A.P.S Morphokinetic Algorithms to Predict Success

TLI – COMPUTING MORPHOKINETICS

VP= t1 - tPNf CC1=t2 - t2PB CC2= t4 - t2 CC3= t8 - t4 CC4= t16 – t8 S2= t4 - t3 S3= t8 - t5 Compaction= tM - tSC Blastulation= tHN – tSB Collapse= tBCend(n)- tBCi(n)

PRIBENSZKY ET AL 2017: TIME-LAPSE META-ANALYSIS

• Meta-analysis of RCT of morphokinetic algorithms v single

time point morphology for embryo selection.

• Outcome measures:
• Clinical pregnancy, Live birth, EPL, Stillbirth.
• 5 RCTs (n=1637)
• LB: 44.2% v 31.3% (OR= 1.668; P<0.009)
• EPL: 15.3% v 21.3% (OR= 0.662; P<0.019)
• Stillbirth: NS

PRIBENSZKY ET AL 2017: TIME-LAPSE META-ANALYSIS

Favours control Favours time-lapse

“time-lapse is shown to significantly improve overall clinical outcome”

TLI – COMPUTING MORPHOKINETICS: ‘CAREMAPS’

VP= t1 - tPNf CC1=t2 - t2PB CC2= t4 - t2 CC3= t8 - t4 CC4= t16 – t8 S2= t4 - t3 S3= t8 - t5 Compaction= tM - tSC Blastulation= tHN – tSB Collapse= tBCend(n)- tBCi(n)

TLI - QA

QA – ATTAINMENT SCORES

IMPROVED OBJECTIVITY: QUALITY ASSURANCE

Interobserver and intraobserver agreement for assessed parameters

CREATING A TIME LAPSE ALGORITHM

• An algorithm is a detailed step-by-step instruction or formula

for solving a problem or completing a task.

• Objective and based on data.
• Ranks embryos according to their likelihood of:

Asking: “Which embryo should I transfer?”

A CHOICE OF ALGORITHMS:

• Easy to use.
• Derived from large

heterogeneous data.

• Supporting

evidence. suggesting better than morphology alone.

• Many to choose

from.

• Can retro-test on
• wn data.
• Little evidence to

support transferability.

• Barrie et al *2017

Fertil Steril.

• Takes time and

expertise.

• Data and experience

grow quickly.

• Can be as simply or

complex.

• Reassurance that

built and validated in house. Integrated software Published In house derived

* ‘These results highlight the need for the development of in-house ESAs that are specific to the patient, treatment, and environment.’

WHAT MAKES A GOOD ALGORITHM?

• Based on large data and tested independently.
• A high predictability score (e.g. Area Under ROC Curve).
• Incorporates variables which are reliably annotated (high IOC).
• Scores are weighted according to importance.
• Allows relative ranking.
• Simple to decode and sense check.

USING TIME-LAPSE DATA ONLY WHEN OUTCOME KNOWN (USING LIVE BIRTH DATA ONLY)

KID positive KID negative KID negative (KID Positive) No KID**

DET

Pregnancy loss

2 x implantations lost 1 x implantations lost One Live Birth KID positive Two Live Birth KID positive No Live Birth KID negative No LB KID 2 x LB KID negative

SET SET DET

> 2,500 LIVE BIRTHS!

“BREAKTHROUGH SCIENCE”

Nominated for the Rbmonline Robert Edwards 2013 Award

TIME-LAPSE IMAGING – CONSTANT VISUAL OF MORPHODYNAMICS

Intracytoplasmic

• Granulation.
• Refractile bodies.
• Vacuolation.
• Smooth Endoplasmic Reticulum

Clustures.

• Multi Nuclei.
• Pronuclei.

Extracytoplasmic

• Polar body.
• Perivitelline space.
• Zona Pellucida.
• Fragments.

Imaging - Single v 300/day!

CARE FERTILITY GROUP – 1000 LIVE BIRTHS Mean ♀ Age: CAREmaps = 36.9 v SI = 35.3

Live births = 973 deliveries

INCLUSIVE CONFOUNDING VARIABLES

• Embryoscope (y/n)
• Patient age (<38/38+)
• Day of embryo transfer
• No. embryos transferred
• Patient type
• Donor age
• Total previous cycles
• Total no. previous live births
• ICSI (y/n)
• Total no. miscarriages
• Intralipid (y/n)
• Duration of infertility
• Total # ectopic
• BMI
• AMH
• AFC
• Gonadotropin type
• Gonadotropin dosing days
• Gonadotropin total dose
• # Eggs collected
• # M2 eggs
• Ratio M2 eggs to total
• # M2 eggs fertilised

CONFOUNDING VARIABLES INCLUDED IN THE MODEL

• Embryoscope (y/n)
• Patient age (<38/38+)
• Day of embryo transfer
• No. embryos transferred
• Patient type
• Donor age
• Total previous cycles
• Total no. previous live births
• ICSI (y/n)
• Total no. miscarriages
• Intralipid (y/n)
• Duration of infertility
• Total # ectopic
• BMI
• AMH
• AFC
• Gonadotropin type
• Gonadotropin dosing days
• Gonadotropin total dose
• # Eggs collected
• # M2 eggs
• Ratio M2 eggs to total
• # M2 eggs fertilised

CARE FERTILITY DATA (LIVE BIRTH OUTCOME ONLY) 24,000 records of treatment

Statistical Analysis: *multiple variable logistic regression models were fit to assess the effects of embryo rank on each potential confounder * Akaike information criterion (AIC) penalty fit for number of parameters and stepwise selection

• 21,379 Standard

incubation treatments

• 2,527 Embryoscope

treatments

• 14,878 unique patients

LIVE BIRTHS (DELIVERY EVENTS AGE <38) – SIG POINTS

0,0 10,0 20,0 30,0 40,0 50,0 60,0 # pos Beta # with >=1FH Biochem Loss # Implantations # Clin miscarriage # Live Birth Event babies/EmbTrd

TLI SI

* P<0.0001 * P<0.0001 * P<0.0001 * P<0.0001 * P<0.001

LIVE BIRTHS (DELIVERY EVENTS)

5 10 15 20 25 30 35 40 45 Overall Single Blast Uplift

CAREmaps SI

19% 25%

* * * *

* P<0.0001

Significance diluted in >37 age group

CAREMAPS – HIERARCHICAL RANKING OF EMBRYOS Time-Lapse Imaging Algorithms Rank Human Preimplantation Embryos According to their Probability to Result in a Live Birth.

Simon Fishel1a*, Alison Campbella, Sue Montgomeryb, Rachel Smithc, Lynne Niced, Samantha Duffyb, Lucy Jennere, Kathryn Berrisford, Louise Kellame, Rob Smithf, Fiona Foadg, Ashley Becclesa 2nd Study in the ‘Trilogy’ – Rbmonline – 2018

HIERARCHICAL SELECTION OF EMBRYOS:

Single Blast Transfer

A tSB or relSBIVF ≤ 93.1h B tSB or relSBIVF >93.1 h dB ≤ 12.5 h C tSB or relSBIVF >93.1 h dB >12.5 h D Unable to be annotated # ET % LBR Miscarriage (%) A 373 51.7 24.0 B 297 35.0 32.5 C 93 31.2 32.6 D 80 13.8 35.3

0,0 10,0 20,0 30,0 40,0 50,0 60,0

A B C X % LBR Miscarriage (%)

47.7%

P < 0.001

RANKED EMBRYO LB OUTCOME

Strong evidence of an effect of embryo rank

• n the odds of live

births. A has a 233% chance of LB compared to D

• D << A (OR = 0.3046; P<0.010)
• D << B (OR = 0.428; P<0.01)
• B < A (OR = 0.7114; P<0.01)
• C <A (OR = 0.6501; P< 0.01)
• B > C (OR = 1.09; P<0.01)
• C >> D (OR=2.135; p<0.01)

CAREMAPS V MORPHOLOGY:

Grade 2:2 highest LB!

CAREMAPS MORPHOKINETICS V MORPHOLOGY

1373 Blast SET cycles 679 (50%) Live Births 3rd Study in the ‘Trilogy’.

10 20 30 40 50 60 70 A B C D % Grade

Live Births (%) v MK Grade

1:1 1:2 2:1 2:2 2:3 3:2 3:3 Live Births (%) 49,4 50,6 60 53,3 28,9 15 20 10 20 30 40 50 60 70 % Morphology

Live Births (%) v Morphology

CAREMAPS MORPHOKINETICS V MORPHOLOGY

Strong evidence of the superiority of the embryo rank model compared with the transfer grade model. (p<0.0001)

CARE FERTILITY STRATEGY TO MAXIMISING LBR

• CAREmaps for all patients ♀age <38 =(19-)25% ↑ Live

Birth.

• ♀age >35 => PGT-A.
• ♀age >35: PGT-A and CAREmaps NOT mutually exclusive.

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