Label‐free detection of invasive micropapillary carcinoma of the breast using multiphoton microscopy

He, Jiajia; Kang, Deyong; Shen, Tingfeng; Zheng, Liqin; Zhan, Zhenlin; Xi, Gangqin; Ren, Wenjiao; Chen, Zhong; Qiu, Lida; Xu, Shuoyu; Li, Lianhuang; Chen, Jianxin

doi:10.1002/jbio.202200224

Cited by 3 publications

(1 citation statement)

References 46 publications

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“…The imaging system used in this study has been previously described in detail [26, 27]. In brief, we used a commercial laser scanning confocal microscopy (LSM 880, Zeiss, Germany) in combination with a mode‐locked femtosecond Ti: sapphire laser (Chameleon Ultra II, Coherent, USA) with a tuning range from 690 to 1064 nm to perform multiphoton imaging.…”

Section: Methodsmentioning

confidence: 99%

Label‐free assessment of pathological changes in pancreatic intraepithelial neoplasia by biomedical multiphoton microscopy

Miao,

Zhang,

Zhang

et al. 2024

Journal of Biophotonics

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Pancreatic intraepithelial neoplasia (PanIN) is the most common precursor lesion that has the potential to progress to invasive pancreatic cancer, and early and rapid detection may offer patients a chance for treatment before the development of invasive carcinoma. Therefore, the identification of PanIN holds significant clinical importance. In this study, we first used multiphoton microscopy (MPM) combining two‐photon excitation fluorescence and second‐harmonic generation imaging to label‐free detect PanIN and attempted to differentiate between normal pancreatic ducts and different grades of PanIN. Then, we also developed an automatic image processing strategy to extract eight morphological features of collagen fibers from MPM images to quantify the changes in collagen fibers surrounding the ducts. Experimental results demonstrate that the combination of MPM and quantitative information can accurately identify normal pancreatic ducts and different grades of PanIN. This study may contribute to the rapid diagnosis of pancreatic diseases and may lay the foundation for further clinical application of MPM.

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Section: Methodsmentioning

confidence: 99%

Label‐free assessment of pathological changes in pancreatic intraepithelial neoplasia by biomedical multiphoton microscopy

Miao,

Zhang,

Zhang

et al. 2024

Journal of Biophotonics

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Towards next-generation diagnostic pathology: AI-empowered label-free multiphoton microscopy

Wang,

Pan,

Zhang

et al. 2024

Light Sci Appl

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Diagnostic pathology, historically dependent on visual scrutiny by experts, is essential for disease detection. Advances in digital pathology and developments in computer vision technology have led to the application of artificial intelligence (AI) in this field. Despite these advancements, the variability in pathologists’ subjective interpretations of diagnostic criteria can lead to inconsistent outcomes. To meet the need for precision in cancer therapies, there is an increasing demand for accurate pathological diagnoses. Consequently, traditional diagnostic pathology is evolving towards “next-generation diagnostic pathology”, prioritizing on the development of a multi-dimensional, intelligent diagnostic approach. Using nonlinear optical effects arising from the interaction of light with biological tissues, multiphoton microscopy (MPM) enables high-resolution label-free imaging of multiple intrinsic components across various human pathological tissues. AI-empowered MPM further improves the accuracy and efficiency of diagnosis, holding promise for providing auxiliary pathology diagnostic methods based on multiphoton diagnostic criteria. In this review, we systematically outline the applications of MPM in pathological diagnosis across various human diseases, and summarize common multiphoton diagnostic features. Moreover, we examine the significant role of AI in enhancing multiphoton pathological diagnosis, including aspects such as image preprocessing, refined differential diagnosis, and the prognostication of outcomes. We also discuss the challenges and perspectives faced by the integration of MPM and AI, encompassing equipment, datasets, analytical models, and integration into the existing clinical pathways. Finally, the review explores the synergy between AI and label-free MPM to forge novel diagnostic frameworks, aiming to accelerate the adoption and implementation of intelligent multiphoton pathology systems in clinical settings.

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An overview of invasive micropapillary carcinoma of the breast: past, present, and future

Qiu,

Cui,

Huang

et al. 2024

Front. Oncol.

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Invasive micropapillary carcinoma of the breast (IMPC) exhibits a unique micropapillary structure and “inside-out” growth pattern. Despite its extremely low incidence, IMPC has attracted considerable attention owing to its poor prognosis. Since Siriaunkgul and Tavassoli first proposed the term IMPC in 1993 to describe its morphological characteristics, with tumor cell clusters arranged in a pseudopapillary structure within the glandular cavity, its diagnostic rate has substantially increased. Based on the in-depth study of IMPC, a more comprehensive understanding of its epidemiology, clinicopathological features, and diagnostic criteria has been achieved in recent years. The pathogenesis and specific therapeutic targets of IMPC remain unclear. However, numerous studies have delved into its high-risk biological behavior. This review discusses the opportunities and challenges associated with IMPC.

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Label‐free detection of invasive micropapillary carcinoma of the breast using multiphoton microscopy

Cited by 3 publications

References 46 publications

Label‐free assessment of pathological changes in pancreatic intraepithelial neoplasia by biomedical multiphoton microscopy

Label‐free assessment of pathological changes in pancreatic intraepithelial neoplasia by biomedical multiphoton microscopy

Towards next-generation diagnostic pathology: AI-empowered label-free multiphoton microscopy

An overview of invasive micropapillary carcinoma of the breast: past, present, and future

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