IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-40740-w.html
   My bibliography  Save this article

Infrared spectroscopic laser scanning confocal microscopy for whole-slide chemical imaging

Author

Listed:
  • Kevin Yeh

    (University of Illinois at Urbana-Champaign
    University of Illinois at Urbana-Champaign)

  • Ishaan Sharma

    (University of Illinois at Urbana-Champaign)

  • Kianoush Falahkheirkhah

    (University of Illinois at Urbana-Champaign
    University of Illinois at Urbana-Champaign)

  • Matthew P. Confer

    (University of Illinois at Urbana-Champaign)

  • Andres C. Orr

    (University of Illinois at Urbana-Champaign)

  • Yen-Ting Liu

    (University of Illinois at Urbana-Champaign
    University of Illinois at Urbana-Champaign)

  • Yamuna Phal

    (University of Illinois at Urbana-Champaign
    University of Illinois at Urbana-Champaign)

  • Ruo-Jing Ho

    (University of Illinois at Urbana-Champaign
    University of Illinois at Urbana-Champaign)

  • Manu Mehta

    (University of Illinois at Urbana-Champaign)

  • Ankita Bhargava

    (University of Illinois Laboratory High School)

  • Wenyan Mei

    (University of Illinois at Urbana-Champaign
    University of Illinois at Urbana-Champaign
    University of Illinois at Urbana-Champaign)

  • Georgina Cheng

    (University of Illinois at Urbana-Champaign
    Carle Health)

  • John C. Cheville

    (Mayo Clinic)

  • Rohit Bhargava

    (University of Illinois at Urbana-Champaign
    University of Illinois at Urbana-Champaign
    University of Illinois at Urbana-Champaign
    University of Illinois at Urbana-Champaign)

Abstract

Chemical imaging, especially mid-infrared spectroscopic microscopy, enables label-free biomedical analyses while achieving expansive molecular sensitivity. However, its slow speed and poor image quality impede widespread adoption. We present a microscope that provides high-throughput recording, low noise, and high spatial resolution where the bottom-up design of its optical train facilitates dual-axis galvo laser scanning of a diffraction-limited focal point over large areas using custom, compound, infinity-corrected refractive objectives. We demonstrate whole-slide, speckle-free imaging in ~3 min per discrete wavelength at 10× magnification (2 μm/pixel) and high-resolution capability with its 20× counterpart (1 μm/pixel), both offering spatial quality at theoretical limits while maintaining high signal-to-noise ratios (>100:1). The data quality enables applications of modern machine learning and capabilities not previously feasible – 3D reconstructions using serial sections, comprehensive assessments of whole model organisms, and histological assessments of disease in time comparable to clinical workflows. Distinct from conventional approaches that focus on morphological investigations or immunostaining techniques, this development makes label-free imaging of minimally processed tissue practical.

Suggested Citation

  • Kevin Yeh & Ishaan Sharma & Kianoush Falahkheirkhah & Matthew P. Confer & Andres C. Orr & Yen-Ting Liu & Yamuna Phal & Ruo-Jing Ho & Manu Mehta & Ankita Bhargava & Wenyan Mei & Georgina Cheng & John C, 2023. "Infrared spectroscopic laser scanning confocal microscopy for whole-slide chemical imaging," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-40740-w
    DOI: 10.1038/s41467-023-40740-w
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-40740-w
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-023-40740-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Seth Kenkel & Shachi Mittal & Rohit Bhargava, 2020. "Closed-loop atomic force microscopy-infrared spectroscopic imaging for nanoscale molecular characterization," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    2. Kwanghun Chung & Jenelle Wallace & Sung-Yon Kim & Sandhiya Kalyanasundaram & Aaron S. Andalman & Thomas J. Davidson & Julie J. Mirzabekov & Kelly A. Zalocusky & Joanna Mattis & Aleksandra K. Denisin &, 2013. "Structural and molecular interrogation of intact biological systems," Nature, Nature, vol. 497(7449), pages 332-337, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Le Wang & Haonan Lin & Yifan Zhu & Xiaowei Ge & Mingsheng Li & Jianing Liu & Fukai Chen & Meng Zhang & Ji-Xin Cheng, 2024. "Overtone photothermal microscopy for high-resolution and high-sensitivity vibrational imaging," Nature Communications, Nature, vol. 15(1), pages 1-13, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Daniel Soudry & Suraj Keshri & Patrick Stinson & Min-hwan Oh & Garud Iyengar & Liam Paninski, 2015. "Efficient "Shotgun" Inference of Neural Connectivity from Highly Sub-sampled Activity Data," PLOS Computational Biology, Public Library of Science, vol. 11(10), pages 1-30, October.
    2. Fu-Ting Hsiao & Hung-Jen Chien & Ya-Hsien Chou & Shih-Jung Peng & Mei-Hsin Chung & Tzu-Hui Huang & Li-Wen Lo & Chia-Ning Shen & Hsiu-Pi Chang & Chih-Yuan Lee & Chien-Chia Chen & Yung-Ming Jeng & Yu-We, 2023. "Transparent tissue in solid state for solvent-free and antifade 3D imaging," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    3. Adam L Tyson & Charly V Rousseau & Christian J Niedworok & Sepiedeh Keshavarzi & Chryssanthi Tsitoura & Lee Cossell & Molly Strom & Troy W Margrie, 2021. "A deep learning algorithm for 3D cell detection in whole mouse brain image datasets," PLOS Computational Biology, Public Library of Science, vol. 17(5), pages 1-17, May.
    4. Kohei Otomo & Takaki Omura & Yuki Nozawa & Steven J. Edwards & Yukihiko Sato & Yuri Saito & Shigehiro Yagishita & Hitoshi Uchida & Yuki Watakabe & Kiyotada Naitou & Rin Yanai & Naruhiko Sahara & Satos, 2024. "descSPIM: an affordable and easy-to-build light-sheet microscope optimized for tissue clearing techniques," Nature Communications, Nature, vol. 15(1), pages 1-19, December.
    5. Nikita Vladimirov & Fabian F. Voigt & Thomas Naert & Gabriela R. Araujo & Ruiyao Cai & Anna Maria Reuss & Shan Zhao & Patricia Schmid & Sven Hildebrand & Martina Schaettin & Dominik Groos & José María, 2024. "Benchtop mesoSPIM: a next-generation open-source light-sheet microscope for cleared samples," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    6. Dheeraj S. Roy & Young-Gyun Park & Minyoung E. Kim & Ying Zhang & Sachie K. Ogawa & Nicholas DiNapoli & Xinyi Gu & Jae H. Cho & Heejin Choi & Lee Kamentsky & Jared Martin & Olivia Mosto & Tomomi Aida , 2022. "Brain-wide mapping reveals that engrams for a single memory are distributed across multiple brain regions," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    7. Santiago Mañosas & Aritz Sanz & Cristina Ederra & Ainhoa Urbiola & Elvira Rojas-de-Miguel & Ainhoa Ostiz & Iván Cortés-Domínguez & Natalia Ramírez & Carlos Ortíz-de-Solórzano & Arantxa Villanueva & Ma, 2022. "An Image-Based Framework for the Analysis of the Murine Microvasculature: From Tissue Clarification to Computational Hemodynamics," Mathematics, MDPI, vol. 10(23), pages 1-20, December.
    8. Jiayi Wang & Mengke Zhao & Meina Wang & Dong Fu & Lin Kang & Yu Xu & Liming Shen & Shilin Jin & Liang Wang & Jing Liu, 2024. "Human neural stem cell-derived artificial organelles to improve oxidative phosphorylation," Nature Communications, Nature, vol. 15(1), pages 1-24, December.
    9. Jingtan Zhu & Xiaomei Liu & Zhang Liu & Yating Deng & Jianyi Xu & Kunxing Liu & Ruiying Zhang & Xizhi Meng & Peng Fei & Tingting Yu & Dan Zhu, 2024. "SOLID: minimizing tissue distortion for brain-wide profiling of diverse architectures," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    10. Daniel P Riordan & Sushama Varma & Robert B West & Patrick O Brown, 2015. "Automated Analysis and Classification of Histological Tissue Features by Multi-Dimensional Microscopic Molecular Profiling," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-18, July.
    11. Hyoungjun Park & Myeongsu Na & Bumju Kim & Soohyun Park & Ki Hean Kim & Sunghoe Chang & Jong Chul Ye, 2022. "Deep learning enables reference-free isotropic super-resolution for volumetric fluorescence microscopy," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    12. Junyoung Seo & Yeonbo Sim & Jeewon Kim & Hyunwoo Kim & In Cho & Hoyeon Nam & Young-Gyu Yoon & Jae-Byum Chang, 2022. "PICASSO allows ultra-multiplexed fluorescence imaging of spatially overlapping proteins without reference spectra measurements," Nature Communications, Nature, vol. 13(1), pages 1-17, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-40740-w. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.