Biological Sample Image Registration via Spatial Fiducials
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Solution Overview
Problem
Current methods for spatial analysis of biological samples face challenges in accurately aligning high-resolution tissue images with spatial analyte data, particularly due to differences in resolution, orientation, and the absence of fiducials, which hampers the overlay of morphological features with analyte data.
Innovation Solution
The method involves obtaining a first image of a biological sample on a substrate and a second image with spatial fiducials, using common morphological features and user-identified landmarks to register the images, allowing the overlay of image data onto spatial analyte data, even when images are taken at different times or resolutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution tissue images are obtained without fiducials, then image quality and morphological detail are improved, but alignment with spatial analyte data becomes difficult
Solution Approach 1:
The patent introduces spatial fiducials as intermediary markers that are visible in both the high-resolution tissue images and the spatial analyte data. These fiducials serve as a common reference framework, enabling accurate registration and alignment between the two different data types without requiring the images themselves to contain fiducials. The fiducials act as a mediator that bridges the gap between imaging and spatial sequencing data.
Solution Approach 2:
The patent segments the alignment process into distinct components: identifying fiducials in the spatial data, mapping fiducials to image coordinates, and using this transformation to register the entire image with the spatial analyte data. This segmentation allows the high-resolution image to be processed separately from the alignment operation, preserving image quality while achieving accurate registration.
2Adaptability or versatility
If images are taken at different time points and resolutions, then comprehensive spatial and morphological data is captured, but frame of reference alignment becomes complex
Solution Approach 1:
Spatial fiducials serve as a stable intermediary reference that exists across different time points and imaging conditions. By anchoring both the high-resolution images and spatial analyte data to the same fiducial framework, the patent simplifies the registration process despite differences in timing and resolution. The fiducials provide a consistent reference that mediates between varying imaging conditions.
Solution Approach 2:
The patent handles variations in image characteristics (resolution, timing) by transforming coordinates between different frame references using fiducial-based registration. The system accepts images with different parameters and registers them to a common fiducial coordinate system, allowing comprehensive data collection while maintaining alignment through parameter transformation rather than requiring uniform imaging parameters.
3Loss of information
If spatial analyte data is integrated with tissue images, then biological insights are improved, but data processing complexity increases
Solution Approach 1:
Spatial fiducials act as an intermediary that enables integration of spatial analyte data with tissue images without requiring complex direct registration between the two data types. The fiducials provide a common reference framework that simplifies the data fusion process, allowing comprehensive spatial context to be maintained while reducing processing complexity through a standardized registration approach.
Data Source
AI summary
Systems and methods for overlaying image data for a biological sample on spatial analyte data are provided. A first image of the sample on a first substrate and a second image of the sample on the first substrate overlayed on a second substrate are obtained. The second substrate includes spatial fiducials and capture spots. At least one of the first substrate and the second substrate is transparent. A registration for the first image and the second image is determined, using a first pattern of the sample in the first image and a second pattern of the sample in the second image. The registration is used to overlay the first image onto a spatial dataset including spatial analyte data for the capture spots from the sample. A frame of reference of the spatial dataset is known with respect to the second image, based on the spatial fiducials of the second image.