Automated Tissue Sectioning and Scanning for 3D Pathology
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Solution Overview
Problem
Current histomorphologic evaluation methods for tissue samples are labor-intensive and require skilled technicians, and image scanning/acquisition in digital pathology is limited to 2-D views, hindering high-throughput processing and data acquisition.
Innovation Solution
A system and method for automated tissue sectioning, staining, and imaging that includes cutting samples into uniform slices, transferring them onto a support, and processing them through modules for deparaffinization, staining, and imaging, enabling 3D image reconstruction and AI analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated tissue sectioning and imaging systems are implemented, then productivity and throughput are improved, but device complexity increases
Solution Approach 1:
The automated tissue processing system is divided into distinct functional modules: a sectioning module for cutting tissue samples, a support for holding sections, and an imaging module for capturing images. Each module operates independently but coordinates through the standardized support structure, enabling high throughput while managing complexity through modular design.
Solution Approach 2:
The support structure serves multiple functions: it holds tissue sections during sectioning, provides a standardized platform for image capture, and enables automated handling between modules. This multi-functional design reduces the need for separate specialized components, improving productivity without proportionally increasing device complexity.
2Measurement precision
If multiple 2-D tissue sections are analyzed, then measurement precision is improved, but loss of information increases due to limited 3D context
Solution Approach 1:
The system transitions from traditional 2-D slide analysis to multi-layer 3D imaging by capturing images of multiple tissue sections mounted in sequential layers on a support. The imaging module acquires images at different depths, and software reconstructs these into 3D representations, preserving spatial architecture information while maintaining measurement precision.
Solution Approach 2:
Multiple 2-D tissue sections are mounted in nested layers on a single support structure, with each section representing a different depth plane. This nested arrangement allows simultaneous analysis of multiple depth levels while maintaining the hierarchical spatial relationships present in the original 3D tissue architecture.
3Manufacturing precision
If manual tissue sectioning and slide preparation are performed, then manufacturing precision is maintained, but loss of time increases due to labor-intensive processes
Solution Approach 1:
The automated system performs self-service tissue sectioning and mounting operations. The sectioning module automatically cuts tissue samples into uniform sections and transfers them to supports without manual intervention. The imaging module then automatically captures images of the mounted sections, eliminating time-consuming manual preparation while maintaining section quality through precision engineering.
Solution Approach 2:
Manual mechanical sectioning and mounting operations are replaced with an automated mechanical system. The sectioning module uses precision-controlled cutting mechanisms to produce uniform tissue sections, and automated transfer mechanisms mount sections onto supports. This mechanical automation replaces skilled manual labor, reducing preparation time while maintaining or improving section quality consistency.
Data Source
AI summary
Disclosed is plate or film for collecting and analyzing a sample. The plate or film includes a surface and a plurality of slices from the sample immobilized on the surface. Further, the plurality of slices are cut from the sample with equal thickness, and the plurality of slices are placed on the surface of the plate or film following their cutting order.