ArticleProceedings of the National Academy of Sciences of the United States of America2020
All-digital histopathology by infrared-optical hybrid microscopy.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.
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Who cites it
62 citing papers in PubMed, 115 citations in OpenAlex.
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- Photon absorption remote sensing (PARS): comprehensive absorption imaging enabling label-free biomolecule characterization and mapping.Scientific reports · 2026Article
- Mid-infrared microscopy for label-free digital staining: initial clinical assessment.Frontiers in bioengineering and biotechnology · 2026Article
- Monitoring Molecular Uptake and Cancer Cells' Response by Development of Quantitative Drug Derivative Probes for Chemical Imaging.Analytical chemistry · 2025Article
- Ultrasensitive in vivo infrared spectroscopic imaging via oblique photothermal microscopy.Nature communications · 2025Article
- Advanced vibrational microscopes for life science.Nature methods · 2025Review
- Optical Photothermal Infrared Imaging Using Metabolic Probes in Biological Systems.Analytical chemistry · 2025Article
- Laser capture microdissection.Nature reviews. Methods primers · 2025Article
- Structural diversity of Alzheimer-related protein aggregations revealed using photothermal ratio-metric micro-spectroscopy.Biomedical optics express · 2024Article
- Machine learning-assisted mid-infrared spectrochemical fibrillar collagen imaging in clinical tissues.Journal of biomedical optics · 2024Article
- Low-Frequency Coherent Raman Imaging Robust to Optical Scattering.Chemical & biomedical imaging · 2024Article
- Inspiring a convergent engineering approach to measure and model the tissue microenvironment.Heliyon · 2024Review
- Modeling the Thermoelastic Sample Response for Subdiffraction Infrared Spectroscopic Imaging.Chemical & biomedical imaging · 2024Article
- Machine learning assisted mid-infrared spectrochemical fibrillar collagen imaging in clinical tissues.bioRxiv : the preprint server for biology · 2024Article
- Rapid and Label-Free Histopathology of Oral Lesions Using Deep Learning Applied to Optical and Infrared Spectroscopic Imaging Data.Journal of personalized medicine · 2024Article
- Monitoring the synthesis of neutral lipids in lipid droplets of living human cancer cells using two-color infrared photothermal microscopy.Chemical science · 2024Article
- Structural characterization of amyloid aggregates with spatially resolved infrared spectroscopy.Methods in enzymology · 2024Article
- Time-Resolved Mid-Infrared Photothermal Microscopy for Imaging Water-Embedded Axon Bundles.Analytical chemistry · 2023Article
- Bond-selective fluorescence imaging with single-molecule sensitivity.Nature photonics · 2023Article
2 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
Optical microscopy for biomedical samples requires expertise in staining to visualize structure and composition. Midinfrared (mid-IR) spectroscopic imaging offers label-free molecular recording and virtual staining by probing fundamental vibrational modes of molecular components. This quantitative signal can be combined with machine learning to enable microscopy in diverse fields from cancer diagnoses to forensics. However, absorption of IR light by common optical imaging components makes mid-IR light incompatible with modern optical microscopy and almost all biomedical research and clinical workflows. Here we conceptualize an IR-optical hybrid (IR-OH) approach that sensitively measures molecular composition based on an optical microscope with wide-field interferometric detection of absorption-induced sample expansion. We demonstrate that IR-OH exceeds state-of-the-art IR microscopy in coverage (10-fold), spatial resolution (fourfold), and spectral consistency (by mitigating the effects of scattering). The combined impact of these advances allows full slide infrared absorption images of unstained breast tissue sections on a visible microscope platform. We further show that automated histopathologic segmentation and generation of computationally stained (stainless) images is possible, resolving morphological features in both color and spatial detail comparable to current pathology protocols but without stains or human interpretation. IR-OH is compatible with clinical and research pathology practice and could make for a cost-effective alternative to conventional stain-based protocols for stainless, all-digital pathology.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.