All-digital histopathology by infrared-optical hybrid microscopy
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.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2020 |
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| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:117 |
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| Enthalten in: |
Proceedings of the National Academy of Sciences of the United States of America - 117(2020), 7 vom: 18. Feb., Seite 3388-3396 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Schnell, Martin [VerfasserIn] |
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| Links: |
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| Themen: |
Breast cancer |
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| Anmerkungen: |
Date Completed 22.06.2020 Date Revised 17.12.2021 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1073/pnas.1912400117 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM306106191 |
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| 520 | |a 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 | ||
| 650 | 4 | |a Evaluation Study | |
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, N.I.H., Extramural | |
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| 650 | 4 | |a quantum cascade laser | |
| 700 | 1 | |a Mittal, Shachi |e verfasserin |4 aut | |
| 700 | 1 | |a Falahkheirkhah, Kianoush |e verfasserin |4 aut | |
| 700 | 1 | |a Mittal, Anirudh |e verfasserin |4 aut | |
| 700 | 1 | |a Yeh, Kevin |e verfasserin |4 aut | |
| 700 | 1 | |a Kenkel, Seth |e verfasserin |4 aut | |
| 700 | 1 | |a Kajdacsy-Balla, Andre |e verfasserin |4 aut | |
| 700 | 1 | |a Carney, P Scott |e verfasserin |4 aut | |
| 700 | 1 | |a Bhargava, Rohit |e verfasserin |4 aut | |
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