Evidence map›Paper›PMID 35831299›Full record

ArticleNature communications2022

Instant diagnosis of gastroscopic biopsy via deep-learned single-shot femtosecond stimulated Raman histology.

Zhijie Liu, Wei Su, Jianpeng Ao, Min Wang, Qiuli Jiang, Jie He, Hua Gao, Shu Lei, Jinshan Nie, Xuefeng Yan and 4 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed, 1 pooled it
29.6field-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

58 citing papers in PubMed, 1 synthesis or guideline pooled it, 116 citations in OpenAlex.

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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

14 authors at 7 institutions in 2 countries.

Zhijie Liu *State Key Laboratory of Surface Physics and Department of Physics, Human Phenome Institute, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), School of Life Sciences, Yiwu Research Institute, Fudan University, 200433, Shanghai, China.
Wei Su *Endoscopy Center and Endoscopy Research Institute, Shanghai Collaborative Innovation Center of Endoscopy, Zhongshan Hospital, Fudan University, 200032, Shanghai, China.ORCID 0000-0001-7913-9010
Jianpeng Ao *State Key Laboratory of Surface Physics and Department of Physics, Human Phenome Institute, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), School of Life Sciences, Yiwu Research Institute, Fudan University, 200433, Shanghai, China.
Min Wang *Department of Gastroenterology, Shanghai Children Hospital, Shanghai Jiaotong University, 200062, Shanghai, China.
Qiuli JiangDepartment of Pathology, Endoscopic Center, Zhongshan Hospital (Xiamen Branch), Fudan University, 361015, Xiamen, China.
Jie HeDepartment of Pathology, Endoscopic Center, Zhongshan Hospital (Xiamen Branch), Fudan University, 361015, Xiamen, China.
Hua GaoDepartment of Pathology, Endoscopic Center, Zhongshan Hospital (Xiamen Branch), Fudan University, 361015, Xiamen, China.
Shu LeiDepartment of Gastroenterology, Wuhan No. 1 Hospital, 430014, Wuhan, China.
Jinshan NieDepartment of Gastroenterology, the 1st People's Hospital of Taicang, Soochow University, 215400, Suzhou, China.
Xuefeng YanDepartment of Gastroenterology, Shangrao Municipal Hospital, Shangrao, 334000, Jiangxi, China.
Xiaojing GuoDepartment of Health Statistics, Faculty of Health Service, Naval Medical University, Shanghai, China.
Pinghong ZhouEndoscopy Center and Endoscopy Research Institute, Shanghai Collaborative Innovation Center of Endoscopy, Zhongshan Hospital, Fudan University, 200032, Shanghai, China. zhou.pinghong@zs-hospital.sh.cn.ORCID 0000-0002-5434-0540
Hao HuEndoscopy Center and Endoscopy Research Institute, Shanghai Collaborative Innovation Center of Endoscopy, Zhongshan Hospital, Fudan University, 200032, Shanghai, China. hu.hao1@zs-hospital.sh.cn.ORCID 0000-0002-0799-8518
Minbiao JiState Key Laboratory of Surface Physics and Department of Physics, Human Phenome Institute, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), School of Life Sciences, Yiwu Research Institute, Fudan University, 200433, Shanghai, China. minbiaoj@fudan.edu.cn.ORCID 0000-0002-9066-4008
Fudan University · CNShanghai Children's Hospital · CNShanghai University of Medicine and Health Sciences · CNShangrao Normal University · CNShiga University of Medical Science Hospital · JPSoochow University · CNWuhan No.1 Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gastroscopic biopsy provides the only effective method for gastric cancer diagnosis, but the gold standard histopathology is time-consuming and incompatible with gastroscopy. Conventional stimulated Raman scattering (SRS) microscopy has shown promise in label-free diagnosis on human tissues, yet it requires the tuning of picosecond lasers to achieve chemical specificity at the cost of time and complexity. Here, we demonstrate that single-shot femtosecond SRS (femto-SRS) reaches the maximum speed and sensitivity with preserved chemical resolution by integrating with U-Net. Fresh gastroscopic biopsy is imaged in <60 s, revealing essential histoarchitectural hallmarks perfectly agreed with standard histopathology. Moreover, a diagnostic neural network (CNN) is constructed based on images from 279 patients that predicts gastric cancer with accuracy >96%. We further demonstrate semantic segmentation of intratumor heterogeneity and evaluation of resection margins of endoscopic submucosal dissection (ESD) tissues to simulate rapid and automated intraoperative diagnosis. Our method holds potential for synchronizing gastroscopy and histopathological diagnosis.

Indexed as

GastroscopyStomach NeoplasmsBiopsyHistological TechniquesHumansSpectrum Analysis, Raman

Identifiers

PMID35831299
PMCPMC9279377
OpenAlexW4285392824

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.