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Published on: August 15, 2014
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Open-top Bessel beam two-photon light sheet microscopy for three-dimensional pathology.
Won Yeong Park1, Jieun Yun1, Jinho Shin2
1Department of Mechanical Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea.
Elife
|March 15, 2024
Summary
Open-top two-photon light sheet microscopy (OT-TP-LSM) enables intraoperative 3D pathology, complementing traditional methods. This technique visualizes cells and extracellular matrix in 3D, enhancing cancer detection and generating virtual H&E images.
Area of Science:
- Biomedical Optics
- Pathology
- Medical Imaging
Background:
- Traditional pathology relies on destructive hematoxylin and eosin (H&E) staining, offering limited 3D cellular information.
- Existing optical microscopy techniques provide only superficial data due to shallow imaging depths, hindering comprehensive analysis.
Purpose of the Study:
- To develop and evaluate an open-top two-photon light sheet microscopy (OT-TP-LSM) system for intraoperative 3D pathology.
- To achieve deeper imaging and visualize both cellular and extracellular matrix (ECM) components for improved cancer detection.
- To explore the potential of deep learning for generating virtual H&E images from 3D microscopy data.
Main Methods:
- Developed an OT-TP-LSM system utilizing a nondiffractive Bessel beam for extended depth of field two-photon excitation light sheet.
- Implemented selective planar imaging at up to 400 frames/s during lateral tissue translation.
- Collected intrinsic second harmonic generation (SHG) signals for ECM visualization.
- Tested the system on human skin, pancreas, and prostate cancer specimens.
- Employed an unsupervised deep learning network for style transfer of OT-TP-LSM images to virtual H&E images.
Main Results:
- Achieved high imaging depths in various human cancer tissues by using long excitation wavelengths and fluorophores.
- Successfully visualized 3D cellular structures and ECM, significantly enhancing cancer detection capabilities.
- Generated virtual H&E images that closely resembled real H&E stained slides in histological characteristics.
- Demonstrated the system's potential for rapid, non-destructive 3D histopathological examination.
Conclusions:
- OT-TP-LSM offers a promising non-destructive approach for intraoperative 3D pathology, overcoming the limitations of conventional methods.
- The integration of cellular and ECM 3D visualization improves diagnostic accuracy in cancer detection.
- Deep learning-based virtual H&E image generation provides a valuable complement to direct 3D imaging, potentially streamlining pathological workflows.
