3D imaging of optically cleared tissue using a simplified CLARITY method and on-chip microscopy

Yibo Zhang, Yoonjung Shin, Kevin Sung, Sam Yang, Harrison Chen, Hongda Wang, Da Teng, Yair Rivenson, Rajan P. Kulkarni, Aydogan Ozcan

Research output: Contribution to journalArticlepeer-review

31 Scopus citations


High-throughput sectioning and optical imaging of tissue samples using traditional immunohistochemical techniques can be costly and inaccessible in resource-limited areas. We demonstrate three-dimensional (3D) imaging and phenotyping in optically transparent tissue using lens-free holographic on-chip microscopy as a low-cost, simple, and high-throughput alternative to conventional approaches. The tissue sample is passively cleared using a simplified CLARITY method and stained using 3,3′-diaminobenzidine to target cells of interest, enabling bright-field optical imaging and 3D sectioning of thick samples. The lens-free computational microscope uses pixel super-resolution and multi-height phase recovery algorithms to digitally refocus throughout the cleared tissue and obtain a 3D stack of complex-valued images of the sample, containing both phase and amplitude information. We optimized the tissue-clearing and imaging system by finding the optimal illumination wavelength, tissue thickness, sample preparation parameters, and the number of heights of the lens-free image acquisition and implemented a sparsity-based denoising algorithm to maximize the imaging volume and minimize the amount of the acquired data while also preserving the contrast-to-noise ratio of the reconstructed images. As a proof of concept, we achieved 3D imaging of neurons in a 200-μm-thick cleared mouse brain tissue over a wide field of view of 20.5 mm2. The lens-free microscope also achieved more than an order-of-magnitude reduction in raw data compared to a conventional scanning optical microscope imaging the same sample volume. Being low cost, simple, high-throughput, and data-efficient, we believe that this CLARITY-enabled computational tissue imaging technique could find numerous applications in biomedical diagnosis and research in low-resource settings.
Original languageEnglish (US)
Pages (from-to)e1700553
JournalScience advances
Issue number8
StatePublished - Aug 11 2017
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The Ozcan Research Group at UCLA acknowledges the support of the Presidential Early Career Award for Scientists and Engineers, the Army Research Office (ARO) (W911NF-13-1-0419 and W911NF-13-1-0197), the ARO Life Sciences Division, the NSF CBET Division Biophotonics Program, the NSF Emerging Frontiers in Research and Innovation Award, the NSF EAGER Award, the NSF INSPIRE Award, NSF Partnerships for Innovation: Building Innovation Capacity Program, Office of Naval Research, the NIH, the Howard Hughes Medical Institute, Vodafone Americas Foundation, the Mary Kay Foundation, Steven & Alexandra Cohen Foundation, and King Abdullah University of Science and Technology. This work is based on the research performed in a laboratory renovated by the NSF under grant no. 0963183, which is an award funded under the American Recovery and Reinvestment Act of 2009.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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