Evidence map›Paper›PMID 36123403›Full record

ArticleNature biomedical engineering2023

Label-free intraoperative histology of bone tissue via deep-learning-assisted ultraviolet photoacoustic microscopy.

Rui Cao, Scott D Nelson, Samuel Davis, Yu Liang, Yilin Luo, Yide Zhang, Brooke Crawford, Lihong V Wang

Open access · greenAbstract read
In one paragraph

Article in Nature biomedical engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers.

0numbers the graph read from it
0cells of the map it votes in
80citing papers in PubMed
12.5field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

80 citing papers in PubMed, 164 citations in OpenAlex.

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20 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Rui CaoCaltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA, USA.ORCID 0000-0003-4444-7528
Scott D NelsonDepartment of Pathology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Samuel DavisCaltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA, USA.ORCID 0000-0002-0871-8880
Yu LiangDepartment of Pathology, City of Hope, Duarte, CA, USA.
Yilin LuoCaltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA, USA.
Yide ZhangCaltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA, USA.ORCID 0000-0002-9463-3970
Brooke CrawfordDepartment of Orthopedic Surgery, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA. brookecrawford@mednet.ucla.edu.ORCID 0000-0003-2722-7080
Lihong V WangCaltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA, USA. lvw@caltech.edu.ORCID 0000-0001-9783-4383
California Institute of Technology · USUniversity of California, Los Angeles · USCity of Hope · US

Funding

High-speed panoramic 3D photoacoustic computed tomography of the breastR35CA220436 · NCI · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI WANG, LIHONG · 2018 to 2024
$6.4M
IN VIVO IMAGING OF SINGLE CIRCULATING CELLSR01CA186567 · NCI · WASHINGTON UNIVERSITY · PI WANG, LIHONG · 2013 to 2017
$3.6M
Label-free intraoperative photoacoustic microscopy for rapid diagnosis of tissue biopsies with specimen integrityR01EB028277 · NIBIB · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI D'APUZZO, MASSIMO, WANG, LIHONG · 2019 to 2022
$2.6M
NCI NIH HHS R01 CA186567NCI NIH HHS R35 CA220436NIBIB NIH HHS R01 EB028277
6 · The paper itself

Abstract

Obtaining frozen sections of bone tissue for intraoperative examination is challenging. To identify the bony edge of resection, orthopaedic oncologists therefore rely on pre-operative X-ray computed tomography or magnetic resonance imaging. However, these techniques do not allow for accurate diagnosis or for intraoperative confirmation of the tumour margins, and in bony sarcomas, they can lead to bone margins up to 10-fold wider (1,000-fold volumetrically) than necessary. Here, we show that real-time three-dimensional contour-scanning of tissue via ultraviolet photoacoustic microscopy in reflection mode can be used to intraoperatively evaluate undecalcified and decalcified thick bone specimens, without the need for tissue sectioning. We validate the technique with gold-standard haematoxylin-and-eosin histology images acquired via a traditional optical microscope, and also show that an unsupervised generative adversarial network can virtually stain the ultraviolet-photoacoustic-microscopy images, allowing pathologists to readily identify cancerous features. Label-free and slide-free histology via ultraviolet photoacoustic microscopy may allow for rapid diagnoses of bone-tissue pathologies and aid the intraoperative determination of tumour margins.

Indexed as

Deep LearningMicroscopyBone and BonesMicroscopy, UltravioletTomography, X-Ray Computed

Identifiers

PMID36123403
PMCPMC10321243
OpenAlexW4296293035

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.