Single-Cell Mass Spectrometry Imaging Database for Breast Cancer Subtyping
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Solution Overview
Problem
Current digital pathology methods struggle with the complex heterogeneity of cellular subtypes in cancer, particularly in breast cancer, leading to challenges in fast diagnosis and prognosis due to the lack of direct single cell identification and visualization, and existing mass spectrometry techniques fail to provide instrument-independent, high-resolution, and reproducible molecular profiling.
Innovation Solution
A method utilizing mass spectrometry imaging (MSI) combined with dimensionality reduction algorithms to construct a recognition model for identifying single cells based on molecular profiles, enabling 'on-the-fly' diagnosis by correlating single cell mass spectrometry imaging data with a reference database, allowing for high spatial and sensitivity resolution and instrument-independent analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If mass spectrometry imaging is applied to single cell analysis, then molecular profiling resolution is improved, but device complexity and data processing difficulty increase
Solution Approach 1:
The patent introduces an intermediary database containing reference mass spectra from cells with known characteristics. This database acts as a mediator between the complex mass spectrometry imaging system and the diagnostic interpretation, storing pre-acquired spectral data that can be compared against new samples without requiring re-analysis of reference materials.
Solution Approach 2:
The patent performs preliminary action by acquiring and storing mass spectra from cells with known characteristics before actual diagnostic analysis. This pre-acquired reference data is saved in a database, allowing rapid comparison and classification of new samples without repeating the complex measurement process for reference materials.
2Reliability
If traditional immunohistochemistry is used for receptor testing, then diagnostic information is obtained, but time consumption and subjectivity increase
Solution Approach 1:
The patent replaces the mechanical and chemical processes of immunohistochemistry (staining, microscopy, subjective interpretation) with mass spectrometry imaging combined with automated database comparison. The objective spectral data and algorithmic classification eliminate human subjectivity in interpreting receptor status while providing quantitative molecular profiles.
3Extent of automation
If morphometry-based classification is used, then automation is achieved, but molecular detail and diagnostic accuracy are lost
Solution Approach 1:
The patent changes the fundamental parameters used for cell classification from morphological features (shape, size, texture) to molecular spectral parameters (mass-to-charge ratios, ion intensities). This parameter transformation enables automated analysis while preserving rich molecular information about cell type and state, as each cell's mass spectrum provides a detailed molecular fingerprint.
Data Source
AI summary
The invention relates to methods using an automated system for characterizing or analyzing single cells in a sample based on mass spectrometry imaging. The methods find use in among other in pathology and diagnosis. The invention further relates to a method for constructing a reference database for use herein.