Simultaneous cancer and tumor microenvironment subtyping using confocal infrared microscopy for all-digital molecular histopathology
Copyright © 2018 the Author(s). Published by PNAS..
Histopathology based on spatial patterns of epithelial cells is the gold standard for clinical diagnoses and research in carcinomas; although known to be important, the tissue microenvironment is not readily used due to complex and subjective interpretation with existing tools. Here, we demonstrate accurate subtyping from molecular properties of epithelial cells using emerging high-definition Fourier transform infrared (HD FT-IR) spectroscopic imaging combined with machine learning algorithms. In addition to detecting four epithelial subtypes, we simultaneously delineate three stromal subtypes that characterize breast tumors. While FT-IR imaging data enable fully digital pathology with rich information content, the long spectral scanning times required for signal averaging and processing make the technology impractical for routine research or clinical use. Hence, we developed a confocal design in which refractive IR optics are designed to provide high-definition, rapid spatial scanning and discrete spectral tuning using a quantum cascade laser (QCL) source. This instrument provides simultaneously high resolving power (2-μm pixel size) and high signal-to-noise ratio (SNR) (>1,300), providing a speed increase of ∼50-fold for obtaining classified results compared with present imaging spectrometers. We demonstrate spectral fidelity and interinstrument operability of our developed instrument by accurate analysis of a 100-case breast tissue set that was analyzed in a day, considerably speeding research. Clinical breast biopsies typical of a patients' caseload are analyzed in ∼1 hour. This study paves the way for comprehensive tumor-microenvironment analyses in feasible time periods, presenting a critical step in practical label-free molecular histopathology.
| Errataetall: |
CommentIn: Proc Natl Acad Sci U S A. 2019 Mar 12;116(11):4753-4754. - PMID 30782792 |
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2018 |
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| Erschienen: |
2018 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:115 |
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| Enthalten in: |
Proceedings of the National Academy of Sciences of the United States of America - 115(2018), 25 vom: 19. Juni, Seite E5651-E5660 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Mittal, Shachi [VerfasserIn] |
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| Links: |
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| Themen: |
Breast |
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| Anmerkungen: |
Date Completed 27.08.2018 Date Revised 14.11.2018 published: Print-Electronic CommentIn: Proc Natl Acad Sci U S A. 2019 Mar 12;116(11):4753-4754. - PMID 30782792 Citation Status MEDLINE |
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| doi: |
10.1073/pnas.1719551115 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM285118714 |
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| 500 | |a CommentIn: Proc Natl Acad Sci U S A. 2019 Mar 12;116(11):4753-4754. - PMID 30782792 | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2018 the Author(s). Published by PNAS. | ||
| 520 | |a Histopathology based on spatial patterns of epithelial cells is the gold standard for clinical diagnoses and research in carcinomas; although known to be important, the tissue microenvironment is not readily used due to complex and subjective interpretation with existing tools. Here, we demonstrate accurate subtyping from molecular properties of epithelial cells using emerging high-definition Fourier transform infrared (HD FT-IR) spectroscopic imaging combined with machine learning algorithms. In addition to detecting four epithelial subtypes, we simultaneously delineate three stromal subtypes that characterize breast tumors. While FT-IR imaging data enable fully digital pathology with rich information content, the long spectral scanning times required for signal averaging and processing make the technology impractical for routine research or clinical use. Hence, we developed a confocal design in which refractive IR optics are designed to provide high-definition, rapid spatial scanning and discrete spectral tuning using a quantum cascade laser (QCL) source. This instrument provides simultaneously high resolving power (2-μm pixel size) and high signal-to-noise ratio (SNR) (>1,300), providing a speed increase of ∼50-fold for obtaining classified results compared with present imaging spectrometers. We demonstrate spectral fidelity and interinstrument operability of our developed instrument by accurate analysis of a 100-case breast tissue set that was analyzed in a day, considerably speeding research. Clinical breast biopsies typical of a patients' caseload are analyzed in ∼1 hour. This study paves the way for comprehensive tumor-microenvironment analyses in feasible time periods, presenting a critical step in practical label-free molecular histopathology | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, N.I.H., Extramural | |
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| 650 | 4 | |a breast | |
| 650 | 4 | |a cancer | |
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| 700 | 1 | |a Yeh, Kevin |e verfasserin |4 aut | |
| 700 | 1 | |a Leslie, L Suzanne |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 Bhargava, Rohit |e verfasserin |4 aut | |
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