All-digital histopathology by infrared-optical hybrid microscopy

Area of Science:

• Biomedical Optics
• Spectroscopic Imaging
• Digital Pathology

Background:

• Traditional optical microscopy for biomedical samples relies on staining for visualization.
• Mid-infrared (mid-IR) spectroscopic imaging offers label-free molecular information but is incompatible with standard optical microscopy.
• Existing limitations hinder the integration of IR spectroscopy into routine clinical and research workflows.

Purpose of the Study:

• To develop an IR-optical hybrid (IR-OH) approach for sensitive, label-free molecular composition measurement using a standard optical microscope.
• To overcome the incompatibility of mid-IR light with conventional optical imaging components.
• To enable high-resolution, stain-free imaging and analysis of biomedical samples.

Main Methods:

• Conceptualized and implemented an IR-optical hybrid (IR-OH) microscopy technique.
• Utilized wide-field interferometric detection of absorption-induced sample expansion to measure molecular composition.
• Integrated mid-IR spectroscopic analysis with a visible light optical microscope platform.
• Applied machine learning for automated histopathologic segmentation and virtual staining.

Main Results:

• IR-OH imaging achieved 10-fold greater coverage and fourfold higher spatial resolution than state-of-the-art IR microscopy.
• Demonstrated mitigation of scattering effects, leading to improved spectral consistency.
• Generated full slide infrared absorption images of unstained breast tissue sections.
• Successfully produced computationally stained (stainless) images with morphological detail comparable to conventional methods.

Conclusions:

• The IR-OH approach enables sensitive, label-free molecular imaging compatible with standard optical microscopy platforms.
• This technology offers significant improvements in imaging coverage, spatial resolution, and spectral consistency over existing IR microscopy techniques.
• IR-OH facilitates automated histopathologic analysis and stain-free digital pathology, presenting a cost-effective alternative to traditional staining protocols.