ArticleCancer science2022
Label-free multiphoton excitation imaging as a promising diagnostic tool for breast cancer.
Article in Cancer science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- Light and metabolism: label-free optical imaging of metabolic activities in biological systems [Invited].Biomedical optics express · 2025Review
- Optical histopathology based on the nonlabeling analysis with multiphoton excitation imaging.Pathology international · 2025Review
- Perspective on the use of fluorescence molecular imaging for peripheral and deepJournal of biomedical optics · 2025Review
- Quantitative Histopathology Analysis Based on Label-free Multiphoton Imaging for Breast Cancer Diagnosis and Neoadjuvant Immunotherapy Response Assessment.International journal of biological sciences · 2025Article
- Machine Learning Enabled Photoacoustic Spectroscopy for Noninvasive Assessment of Breast Tumor ProgressionACS sensors · 2024Article
- Elastin is responsible for the rigidity of the ligament under shear and rotational stress: a mathematical simulation study.Journal of orthopaedic surgery and research · 2023Article
- Label-free multiphoton excitation imaging as a promising diagnostic tool for breast cancer.Cancer science · 2022Article
Corrections and comments
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Authors and funding
14 authors at 6 institutions in 2 countries.
Funding
Abstract
Histopathological diagnosis is the ultimate method of attaining the final diagnosis; however, the observation range is limited to the two-dimensional plane, and it requires thin slicing of the tissue, which limits diagnostic information. To seek solutions for these problems, we proposed a novel imaging-based histopathological examination. We used the multiphoton excitation microscopy (MPM) technique to establish a method for visualizing unfixed/unstained human breast tissues. Under near-infrared ray excitation, fresh human breast tissues emitted fluorescent signals with three major peaks, which enabled visualizing the breast tissue morphology without any fixation or dye staining. Our study using human breast tissue samples from 32 patients indicated that experienced pathologists can estimate normal or cancerous lesions using only these MPM images with a kappa coefficient of 1.0. Moreover, we developed an image classification algorithm with artificial intelligence that enabled us to automatically define cancer cells in small areas with a high sensitivity of ≥0.942. Taken together, label-free MPM imaging is a promising method for the real-time automatic diagnosis of breast cancer.
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Registered trials
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.