Embryo Viability Scoring With FLIM and AI Data Fusion
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Solution Overview
Problem
Existing methods for determining embryo viability are limited in their ability to comprehensively assess both structural and functional endpoints, as well as integrate patient demographics, leading to suboptimal selection of embryos for IVF procedures.
Innovation Solution
An AI-based imaging system and method that utilizes fluorescence lifetime imaging microscopy (FLIM) to capture morphological and metabolic endpoints, combined with parental health data, to calculate an embryo viability score and rank embryos for implantation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional embryo assessment methods are used, then the process is simple and quick, but the accuracy and comprehensiveness of embryo selection is limited
Solution Approach 1:
The system segments the embryo assessment process into multiple independent analysis dimensions: morphological analysis of structural features, metabolic analysis of functional parameters, and demographic analysis of parental factors. Each dimension is processed separately by specialized algorithms and then integrated to produce a comprehensive viability score, allowing complex assessment without overwhelming system complexity
Solution Approach 2:
The system transitions from traditional two-dimensional morphological assessment to multi-dimensional evaluation by incorporating metabolic parameters (functional dimension), parental demographic data (contextual dimension), and temporal dynamics of embryo development. This dimensional expansion enables more accurate viability prediction while systematically managing complexity through modular processing
2Reliability
If only morphological endpoints are assessed, then the analysis is straightforward, but the functional and metabolic characteristics of embryos are not captured
Solution Approach 1:
The system introduces specialized imaging modalities as intermediaries to bridge the gap between observable morphological features and unobservable metabolic/functional states. FLIM (fluorescence lifetime imaging microscopy) and Raman spectroscopy act as intermediary techniques that translate internal metabolic processes into detectable optical signals, enabling non-invasive functional assessment without direct measurement of metabolic pathways
Solution Approach 2:
The system replaces direct mechanical or chemical measurement of metabolic parameters with optical detection methods. Instead of physically measuring metabolic rates or functional activity, the system uses light-based techniques (FLIM, Raman spectroscopy) to detect optical signatures that correlate with metabolic state, substituting complex mechanical/chemical measurement systems with more manageable optical detection
3Measurement precision
If parental health data is not integrated, then the analysis focuses only on embryo characteristics, but the overall viability prediction is less accurate
Solution Approach 1:
The system merges three distinct data streams: embryo morphological data, embryo functional/metabolic data, and parental demographic/health data. These separate information sources are integrated through a unified analytical framework that weights and combines them to produce a comprehensive viability score, achieving improved accuracy while managing integration complexity through structured data architecture
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the accuracy of embryo selection for IVF by integrating morphological, metabolic, and demographic data, improving the chances of successful implantation and pregnancy.
Implementation Method 1
an excitation device configured to direct excitation energy at an embryo
Implementation Method 2
an imaging device configured to detect photons emitted from the embryo
Data Source
AI summary
A method and system for determining the viability of an embryo using an embryo morpho-metabolic index (EMMI) and Em-Lux device is disclosed herein. The EMMI integrates morphological and metabolic endpoints to evaluate embryos, aiding IVF facilities in selecting embryos with the highest probability of successful implantation.