Label-free multiphoton excitation imaging as a promising diagnostic tool for breast cancer.
Takahiro MatsuiAkio IwasaMasafumi MimuraSeiji TaniguchiTakao SudoYutaka UchidaJunichi KikutaHidetomo MorizonoRie HoriiYuichi MotoyamaEiichi MoriiShinji OhnoYasujiro KiyotaMasaru IshiiPublished in: Cancer science (2022)
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.
Keyphrases
- label free
- deep learning
- artificial intelligence
- machine learning
- endothelial cells
- high resolution
- induced pluripotent stem cells
- gene expression
- end stage renal disease
- convolutional neural network
- newly diagnosed
- living cells
- chronic kidney disease
- mental health
- healthcare
- energy transfer
- prognostic factors
- magnetic resonance
- patient reported outcomes
- magnetic resonance imaging
- young adults
- toll like receptor
- social media
- high speed
- health information