Automated Strategy for Tissue Analysis in Anatomic Pathology: Fiducial Marker Integration and Multisurface Tissue Comparison

Background Introduction

In anatomic pathology laboratories, many processes still rely on manual operations, especially in the preparation and processing of paraffin-embedded tissue blocks (PETBs). Manual operations not only lead to inconsistencies in sample handling but may also result in sample misidentification or loss, thereby affecting diagnostic accuracy and efficiency. To address this issue, automation technologies have been introduced to improve laboratory efficiency, reduce human error, and ensure consistency in sample processing.

However, existing automated solutions still face numerous challenges, particularly in tissue sample tracking and the identification of specific regions. For example, during processing, specific areas within PETBs may require further laboratory analysis (e.g., molecular phenotyping in cancer treatment), but the lack of reliable reference points complicates this process and increases the likelihood of errors. Therefore, the research team proposed an automated strategy to achieve precise tissue tracking and multisurface comparison by introducing fiducial markers (FMs) into PETBs, thereby enhancing diagnostic accuracy and efficiency.

Source of the Paper

This paper was co-authored by L. Vannozzi, L. Guachi-Guachi, J. Ruspi, and other researchers from the BioRobotics Institute of Scuola Superiore Sant’Anna in Italy and Inpeco SA in Switzerland. The paper was published in the journal IEEE Transactions on Automation Science and Engineering and is expected to be formally published in 2025. The research was supported by Inpeco SA and is part of the joint project “Advanced Laboratory Automation” between Scuola Superiore Sant’Anna and Inpeco SA.

Research Process and Experimental Design

1. Research Objectives

The goal of this study is to develop an automated platform capable of inserting fiducial markers into PETBs and reconstructing these markers in multisurface tissue slices through image analysis, thereby achieving precise tissue tracking and multisurface comparison.

2. Experimental Process

The research is divided into two main platforms: the Indexing Platform (IDX) and the Virtual Marker Reconstruction Platform (VMR).

2.1 Indexing Platform (IDX)

The primary task of the IDX platform is to insert fiducial markers into PETBs. The specific workflow is as follows:
1. Block Fixation: Insert the PETB into the platform and secure it with a gripper.
2. QR Code Reading: Read the PETB’s QR code to track tissue data.
3. Tissue-Free Area Identification: Identify tissue-free areas within the block through image processing and determine the target position for the fiducial marker.
4. Marker Insertion: Send the target position coordinates to the microcontroller, controlling the end-effector to drill into the PETB and insert the fiducial marker.
5. Marker Verification: Verify the depth of the hole using a laser distance sensor.
6. Marker Filling: Inject the fiducial marker material into the hole using a microdispenser.
7. Cleaning and Preparation: Clean the puncher for the next PETB.
8. Marker Solidification and Flattening: Compress the marker with a dedicated cylinder to ensure it is flat.
9. Block Release: Release the PETB to complete the process.

Innovation: The IDX platform employs a U-Net convolutional neural network (CNN) for image analysis, enabling efficient identification of tissue-free areas within the block and ensuring the precise insertion of fiducial markers. Additionally, the platform integrates a laser distance sensor and a microdispenser to guarantee the accuracy and consistency of marker insertion.

2.2 Virtual Marker Reconstruction Platform (VMR)

The primary task of the VMR platform is to reconstruct fiducial markers after deparaffinization through image analysis. The specific workflow is as follows:
10. Slide Placement: Place the pre-stained glass slide in the VMR platform.
11. QR Code Reading: Read the slide’s QR code to track tissue data.
12. Pre-Staining Image Acquisition: Capture the pre-staining image of the slide.
13. Staining Process: Remove the slide from the platform for staining.
14. Post-Staining Image Acquisition: Capture the image of the slide after staining.
15. Image Comparison: Compare the pre-staining and post-staining images to identify tissue shapes.
16. Marker Reconstruction: Reconstruct the fiducial marker through image analysis.
17. Result Output: Map the reconstructed marker position onto the post-staining slide image.

Innovation: The VMR platform employs a multi-step image analysis method, combining U-Net CNN and connected-component labeling (CCL), to accurately reconstruct fiducial markers after deparaffinization and further verify tissue integrity through shape comparison.

3. Experimental Validation

To validate the platforms’ effectiveness, the research team conducted phased testing of the IDX and VMR platforms.
- IDX Platform Testing: Tested punching force, marker filling precision, the accuracy of the image analysis method, and hardware-software integration performance. The results showed that the IDX platform achieved high success rates and consistency when processing PETBs with different tissue types.
- VMR Platform Testing: Tested image acquisition, marker reconstruction accuracy, and tissue shape comparison. The results demonstrated that the VMR platform could accurately reconstruct fiducial markers after deparaffinization and achieved high similarity scores in tissue shape comparison.

Key Results

1. IDX Platform: When processing PETBs with different tissue types, the IDX platform achieved success rates exceeding 95% in QR code identification, tissue-free area detection, punching, and marker filling.
   
2. VMR Platform: In marker reconstruction and tissue shape comparison tasks, the VMR platform achieved success rates of 98% and 95%, respectively, with an average processing time of approximately 2.83 seconds, without burdening the overall laboratory workflow.
   

Conclusion and Significance

The innovation of this study lies in proposing a comprehensive automated strategy for precise tracking and multisurface comparison of paraffin-embedded tissue blocks through the insertion and reconstruction of fiducial markers. This method not only enhances laboratory efficiency but also reduces the risk of human error, providing significant technical support for future automated laboratories. The results demonstrate that the IDX and VMR platforms exhibit high reliability and consistency when processing PETBs with different tissue types, indicating broad application prospects.

Highlights

1. Innovation: The first to propose an automated strategy for tissue tracking and multisurface comparison through fiducial markers.
   
2. High Reliability: The IDX and VMR platforms achieved high success rates when processing different tissue types.
   
3. Efficiency: The automated workflow significantly improves laboratory efficiency and reduces the risk of human error.
   
4. Broad Application Prospects: The method can be applied to biopsy samples and small paraffin-embedded tissue blocks, further expanding its application in anatomic pathology.
   

Future Outlook

Future research directions include optimizing the platform’s parallel processing capabilities, improving the resolution of image analysis algorithms, and applying this method to smaller tissue blocks or biopsy samples. Additionally, the research team plans to develop dedicated middleware to further integrate robotics in tissue slide processing.

Through this study, significant progress has been made in the automation and standardization of anatomic pathology laboratories, providing robust technical support for clinical diagnostic accuracy and efficiency.