Computer-Aided Detection of Quantitative Signatures for Breast Fibroepithelial Tumors Using Label-Free Multi-Photon Imaging
Abstract
:1. Introduction
2. Results
2.1. MPM Imaging Characterizes Morphological Distinctions between Epithelial and Stromal Regions for FA and PT Lesions
2.2. Deep-Learning-Based Image Segmentation Approach for Differentiating Epithelial and Stromal Morphologies
2.3. Computer-Assisted Scoring Helps to Diagnose FA and PT Lesions
3. Discussion
4. Materials and Methods
4.1. Patient-Derived Samples
4.2. Preparation of Tissue Sections
4.3. Image Acquisition by Multi-Photon Microscopy
4.4. Image Segmentation by SegNet
4.5. Statistical Analysis
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Sample Availability
List of Abbreviations
FA | Fibroadenoma |
PT | Phyllodes tumor |
CNB | Core needle biopsy |
VAB | Vacuum-assisted biopsy |
HE | Hematoxylin–eosin |
PSR | Picro-sirius red |
MPM | Multi-photon microscopy |
DM | Dichroic mirror |
FoV | Field of view |
AF | Autofluorescence |
SHG | Second harmonic generation |
NADH | Nicotinamide adenine dinucleotide |
FAD | Flavin adenine dinucleotide |
AI | Artificial intelligence |
IoU | Intersection of union |
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Characteristic | Post-Operative Diagnosis | |
---|---|---|
Fibroadenoma | Phyllodes | |
No. of patients | 5 | 5 |
Age (median years) | 38 (IQR; 27–41) | 44 (IQR; 40–47) |
Median size on Imaging (cm) | 3.0 (IQR; 3.0–3.1) | 2.9 (IQR; 1.4–3.5) |
Number of biopsy (n) (min–max) | 3 (2–4) | 3 (3–6) |
Type of biopsy (n) | ||
Core needle biopsy (14 gauge) | 3 | 4 |
Vacuum-assisted breast biopsy (10 gauge) | 2 | 1 |
Pre-operative diagnosis (n) | ||
Fibroadenoma | 3 | 2 |
Phyllodes | 0 | 3 |
Difficult to distinguish | 2 | 0 |
Histological type (n) | ||
Benign | 5 | |
Borderline/malignant | 0 |
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Kobayashi-Taguchi, K.; Saitou, T.; Kamei, Y.; Murakami, A.; Nishiyama, K.; Aoki, R.; Kusakabe, E.; Noda, H.; Yamashita, M.; Kitazawa, R.; et al. Computer-Aided Detection of Quantitative Signatures for Breast Fibroepithelial Tumors Using Label-Free Multi-Photon Imaging. Molecules 2022, 27, 3340. https://doi.org/10.3390/molecules27103340
Kobayashi-Taguchi K, Saitou T, Kamei Y, Murakami A, Nishiyama K, Aoki R, Kusakabe E, Noda H, Yamashita M, Kitazawa R, et al. Computer-Aided Detection of Quantitative Signatures for Breast Fibroepithelial Tumors Using Label-Free Multi-Photon Imaging. Molecules. 2022; 27(10):3340. https://doi.org/10.3390/molecules27103340
Chicago/Turabian StyleKobayashi-Taguchi, Kana, Takashi Saitou, Yoshiaki Kamei, Akari Murakami, Kanako Nishiyama, Reina Aoki, Erina Kusakabe, Haruna Noda, Michiko Yamashita, Riko Kitazawa, and et al. 2022. "Computer-Aided Detection of Quantitative Signatures for Breast Fibroepithelial Tumors Using Label-Free Multi-Photon Imaging" Molecules 27, no. 10: 3340. https://doi.org/10.3390/molecules27103340