Evidence map›Paper›PMID 39451680›Full record

ArticleBiosensors2024

Distinguishing of Histopathological Staging Features of H-E Stained Human cSCC by Microscopical Multispectral Imaging.

Rujuan Wu, Jiayi Yang, Qi Chen, Changxing Yang, Qianqian Ge, Danni Rui, Huazhong Xiang, Dawei Zhang, Cheng Wang, Xiaoqing Zhao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biosensors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

10 authors.

Rujuan WuInstitute of Biomedical Optics and Optometry, Key Lab of Optical Instruments and Equipment for Medical Engineering, Ministry of Education, University of Shanghai for Science and Technology, Shanghai 200093, China.ORCID 0009-0003-6607-9217
Jiayi YangDepartment of Dermatology, School of Medicine, Ruijin Hospital, Shanghai Jiao Tong University, Shanghai 200093, China.ORCID 0000-0002-1604-7503
Qi ChenDepartment of Phototherapy, Shanghai Skin Disease Hospital, School of Medicine, Tongji University, Shanghai 200093, China.ORCID 0009-0007-4344-732X
Changxing YangInstitute of Biomedical Optics and Optometry, Key Lab of Optical Instruments and Equipment for Medical Engineering, Ministry of Education, University of Shanghai for Science and Technology, Shanghai 200093, China.ORCID 0009-0006-9664-862X
Qianqian GeInstitute of Biomedical Optics and Optometry, Key Lab of Optical Instruments and Equipment for Medical Engineering, Ministry of Education, University of Shanghai for Science and Technology, Shanghai 200093, China.ORCID 0009-0001-9584-1595
Danni RuiInstitute of Biomedical Optics and Optometry, Key Lab of Optical Instruments and Equipment for Medical Engineering, Ministry of Education, University of Shanghai for Science and Technology, Shanghai 200093, China.
Huazhong XiangInstitute of Biomedical Optics and Optometry, Key Lab of Optical Instruments and Equipment for Medical Engineering, Ministry of Education, University of Shanghai for Science and Technology, Shanghai 200093, China.ORCID 0000-0001-8542-8417
Dawei ZhangEngineering Research Center of Optical Instruments and Systems, Ministry of Education, Key Laboratory of Modern Optical Systems, Shanghai University of Technology, Shanghai 200093, China.
Cheng WangInstitute of Biomedical Optics and Optometry, Key Lab of Optical Instruments and Equipment for Medical Engineering, Ministry of Education, University of Shanghai for Science and Technology, Shanghai 200093, China.ORCID 0000-0002-9354-6752
Xiaoqing ZhaoDepartment of Dermatology, School of Medicine, Ruijin Hospital, Shanghai Jiao Tong University, Shanghai 200093, China.ORCID 0000-0002-9232-1412

Funding

Natural Science Foundation of Shanghai Municipality (No.21ZR1440500) and Shang-hai Science and Technology Commission (21S31902700) No.21ZR1440500;21S31902700
6 · The paper itself

Abstract

Cutaneous squamous cell carcinoma (cSCC) is the second most common malignant skin tumor. Early and precise diagnosis of tumor staging is crucial for long-term outcomes. While pathological diagnosis has traditionally served as the gold standard, the assessment of differentiation levels heavily depends on subjective judgments. Therefore, how to improve the diagnosis accuracy and objectivity of pathologists has become an urgent problem to be solved. We used multispectral imaging (MSI) to enhance tumor classification. The hematoxylin and eosin (H&E) stained cSCC slides were from Shanghai Ruijin Hospital. Scale-invariant feature transform was applied to multispectral images for image stitching, while the adaptive threshold segmentation method and random forest segmentation method were used for image segmentation, respectively. Synthetic pseudo-color images effectively highlight tissue differences. Quantitative analysis confirms significant variation in the nuclear area between normal and cSCC tissues (

Indexed as

Carcinoma, Squamous CellSkin NeoplasmsEosine Yellowish-(YS)HematoxylinHumansImage Processing, Computer-AssistedNeoplasm StagingStaining and LabelingEosine Yellowish-(YS)HematoxylincSCCmicroscopical multispectral imagingtumor staging

Identifiers

PMID39451680
PMCPMC11506349

What OpenQuestion holds

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Registered trials

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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.