Automated FISH Sample Analysis System for Chromosomal Aberration Detection

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Solution Overview

Problem

Current methods for analyzing fluorescence in situ hybridization (FISH) samples are inefficient in identifying chromosomal aberrations due to manual ROI selection, poor signal-to-noise ratios, and misinterpretation of split or merged fluorescent signals, leading to potential misdiagnosis and lengthy scanning times.

Innovation Solution

A method and system for analyzing labeled biological samples by measuring the relative amount and frequency of nucleic acid probes, using computational scanning and image analysis to identify chromosomal aberrations, and selecting between monochrome and color cameras based on the sample's requirements for optimal image capture.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual ROI selection is used, then diagnostic accuracy can be maintained, but scanning time becomes excessively long and productivity decreases

Engineering Contradiction:

Improvediagnostic accuracyVSAvoidscanning speed

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system performs automatic ROI identification and selection without requiring manual intervention. The computer-controlled scanning system autonomously identifies regions of interest, determines optimal focus positions, and selects areas for analysis, thereby eliminating the time-consuming manual scanning process while maintaining diagnostic accuracy through automated image analysis algorithms

Inventive Principle:

Principle #25Self-service

2Reliability

If conventional scanning strategies are used, then complete coverage of the slide is achieved, but scanning time increases significantly when cells are not evenly distributed

Engineering Contradiction:

Improvescan completenessVSAvoidscanning time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary actions by automatically identifying and selecting ROIs before comprehensive scanning. The computer-controlled system pre-determines which regions contain cells of interest based on preliminary image acquisition and analysis, allowing the main scanning process to focus only on relevant areas rather than systematically scanning the entire slide from center outward

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

Instead of scanning from the center of the slide outward in conventional circular patterns, the system inverts the approach by first identifying relevant regions through preliminary analysis and then scanning only those specific ROIs. This reversal of the scanning logic eliminates wasted time scanning empty areas while ensuring complete coverage of cell-containing regions

Inventive Principle:

Principle #13The other way round (Inversion)

3Productivity

If automated scanning systems are implemented, then scanning efficiency improves, but device complexity and initial setup requirements increase

Engineering Contradiction:

Improvescanning efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The computer-controlled scanning system is designed with multi-functionality to handle various tasks within a single integrated platform. The same system performs ROI identification, focus determination, scanning control, and image analysis, eliminating the need for separate manual operations and reducing overall system complexity despite the automated capabilities

Inventive Principle:

Principle #6Universality (Multi-functionality)

4Measurement precision

If focus ascertainment and exposure time selection are performed manually, then optimal image quality is achieved, but the analysis process becomes more time-consuming

Engineering Contradiction:

Improveimage qualityVSAvoidanalysis time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs self-service by automatically determining optimal focus positions and exposure times without manual intervention. The computer-controlled scanning system autonomously adjusts acquisition parameters based on preliminary image analysis, ensuring optimal image quality is achieved while eliminating the time required for manual focus ascertainment and parameter selection

Inventive Principle:

Principle #25Self-service

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

This approach enables accurate and efficient identification of chromosomal aberrations, reduces scanning time, and improves diagnostic precision by analyzing the relative intensity of fluorescent signals, thereby enhancing the reliability of FISH analysis.

Implementation Method 1

measuring a relative amount and optionally a frequency of at least one label of a nucleic acid probe

Methodology Applied

Scientific EffectHybridization:

Implementation Method 2

fluorescence in situ hybridization (FISH)—stained samples

Methodology Applied

Scientific EffectFluorescence: Fluorescence

Data Source

PatentUS9133506B2Methods and systems for analyzing biological samples

Publication Date: 2015.09.15 APPLIED SPECTRAL IMAGING

AI summary

Methods, computer readable storage media and systems which can be used for analyzing labeled biological samples, identifying chromosomal aberrations, identifying genetically abnormal cells and/or computationally scanning the samples using randomly or randomized scanning methods are provided. Specifically, the present invention can be used to analyze FISH-stained samples and automatically identify chromosomal aberrations associated with abnormal intensity ratio of stained occurrences in the sample.