Evidence map›Paper›PMID 41374645›Full record

ArticleSensors (Basel, Switzerland)2025

Virtual Staining-Enabled Colorectal Cancer Metastasis Detection in Liquid Cytology Based on Digital Holography.

Yusen Gao, Xi Xiao, Ran Peng, Hao Wang, Feng Pan

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. 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

5 authors.

Yusen GaoKey Laboratory of Precision Opto-Mechatronics Technology, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China.
Xi XiaoDepartment of Radiation Oncology, Peking University Third Hospital, Beijing 100191, China.
Ran PengDepartment of Radiation Oncology, Peking University Third Hospital, Beijing 100191, China.
Hao WangDepartment of Radiation Oncology, Peking University Third Hospital, Beijing 100191, China.
Feng PanKey Laboratory of Precision Opto-Mechatronics Technology, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China.ORCID 0000-0002-3303-4317

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality, and detecting circulating tumor cells (CTCs) is crucial for early diagnosis and metastasis monitoring. Conventional staining-based cytology is costly, time-consuming, and often compromises sample integrity. In this study, we employed a combined digital holography (DH) and fluorescence imaging approach to develop a virtual staining framework for transforming quantitative phase imaging (QPI) data into interpretable pseudo-stained images. To the best of our knowledge, this is the first application of such a framework to colorectal cancer CTC detection. In our experiments, green fluorescent protein (GFP)-labeled HCT116 cells-generated through lentiviral transfection-were mixed with peripheral blood mononuclear cells (PBMCs) to create training datasets. The trained network achieved 99% classification accuracy and demonstrated strong generalization to unseen donors. This DH-fluorescence-based virtual staining method preserves cell integrity while enabling rapid, label-free, and low-cost liquid cytology diagnostics, highlighting its potential for non-invasive cancer detection and monitoring.

Indexed as

Colorectal NeoplasmsHolographyStaining and LabelingGreen Fluorescent ProteinsHCT116 CellsHumansLeukocytes, MononuclearNeoplasm MetastasisNeoplastic Cells, CirculatingOptical ImagingQuantitative Phase ImagingGreen Fluorescent Proteinscolorectal cancer metastasis detectiondigital holographyliquid cytologyvirtual stain

Identifiers

PMID41374645
PMCPMC12694182

What OpenQuestion holds

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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.