Multimodal multiphoton imaging for label-free monitoring of early gastric cancer

Li, Lianhuang; Kang, Deyong; Huang, Zicheng; Zhan, Zhenlin; Feng, Changyin; Zhou, Yongjian; Tu, Haohua; Zhuo, Shuangmu; Chen, Jianxin

doi:10.1186/s12885-019-5497-4

Cited by 25 publications

(20 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Only a few studies investigated the relationship between membrane order and chemotherapy resistance using two‐photon microscopy and a suitable fluidity reporter in real‐time 163–165 . On the other hand, label‐free multiphoton excitation microscopy is emerging as an effective, noninvasive, real‐time, and robust clinical diagnostic tool, although more time‐consuming and cumbersome than the commonly used hematoxylin‐eosin staining 166–168 . The coupling of altered membrane patterns with artificial intelligence technologies can open doors for rapid screening of membrane targeting agents, treatment response monitoring, diagnosis, and prognosis.…”

Section: The Road Ahead: How To Harness Lipid Membrane Properties For...mentioning

confidence: 99%

Lipidomic landscape in cancer: Actionable insights for membrane‐based therapy and diagnoses

Agarwala

Aneja

Kapoor

2021

Medicinal Research Reviews

View full text Add to dashboard Cite

Cancer cells display altered cellular lipid metabolism, including disruption in endogenous lipid synthesis, storage, and exogenous uptake for membrane biogenesis and functions. Altered lipid metabolism and, consequently, lipid composition impacts cellular function by affecting membrane structure and properties, such as fluidity, rigidity, membrane dynamics, and lateral organization. Herein, we provide an overview of lipid membranes and how their properties affect cellular functions. We also detail how the rewiring of lipid metabolism impacts the lipidomic landscape of cancer cell membranes and influences the characteristics of cancer cells. Furthermore, we discuss how the altered cancer lipidome provides cues for developing lipid‐inspired innovative therapeutic and diagnostic strategies while improving our limited understanding of the role of lipids in cancer initiation and progression. We also present the arcade of membrane characterization techniques to cement their relevance in cancer diagnosis and monitoring of treatment response.

show abstract

Section: The Road Ahead: How To Harness Lipid Membrane Properties For...mentioning

confidence: 99%

Lipidomic landscape in cancer: Actionable insights for membrane‐based therapy and diagnoses

Agarwala

Aneja

Kapoor

2021

Medicinal Research Reviews

View full text Add to dashboard Cite

show abstract

“…This imaging equipment has been explained in detail in our previous work [18]. All the multiphoton images were captured via an microscope (LSM 510, Zeiss, Germany) which was inverted and equipped with a femtosecond Ti:sapphire laser (Mira 900-F, Coherent, Inc., USA).…”

Section: B Biomedical Multiphoton Microscopymentioning

confidence: 99%

Label-Free Identification of Early Gastrointestinal Neuroendocrine Tumors via Biomedical Multiphoton Microscopy and Automatic Image Analysis

Huang

Qiu

et al. 2020

IEEE Access

Self Cite

View full text Add to dashboard Cite

At present, early diagnosis and treatment is the most effective way to treat early gastrointestinal neuroendocrine tumors. Therefore, we attempted to carry out multiphoton imaging of early neuroendocrine tumors because of its ability to label-free image tissue microstructure at the cellular level. Imaging results show that this imaging technique can quickly identify the histopathological changes in mucosa and submucosa caused by tumor invasion. Furthermore, we performed automatic image analysis on SHG images and extracted two optical diagnostic features-collagen density and average intensity, and also found obvious differences in the density as well as average intensity of collagen fibers in tumor microenvironment using a series of quantitative analysis. These findings may further facilitate the development of multiphoton microscopic imaging technique for clinical use. INDEX TERMS Multiphoton imaging, image analysis, gastrointestinal neuroendocrine tumors.

show abstract

“…Regarding studies using MPM images, the works presented by Li et al . [ 25 26 ] related to colorectal and gastric tissue respectively, or the study shown by He et al . [ 27 ] about colorectal tissue, obtain sensitivity and specificity values higher than those obtained in our study.…”

Section: Discussionsmentioning

confidence: 99%

Analysis on the Characterization of Multiphoton Microscopy Images for Malignant Neoplastic Colon Lesion Detection under Deep Learning Methods

Terradillos

Saratxaga

Mattana³

et al. 2021

Journal of Pathology Informatics

View full text Add to dashboard Cite

Background: Colorectal cancer has a high incidence rate worldwide, with over 1.8 million new cases and 880,792 deaths in 2018. Fortunately, its early detection significantly increases the survival rate, reaching a cure rate of 90% when diagnosed at a localized stage. Colonoscopy is the gold standard technique for detection and removal of colorectal lesions with potential to evolve into cancer. When polyps are found in a patient, the current procedure is their complete removal. However, in this process, gastroenterologists cannot assure complete resection and clean margins which are given by the histopathology analysis of the removed tissue, which is performed at laboratory. Aims: In this paper, we demonstrate the capabilities of multiphoton microscopy (MPM) technology to provide imaging biomarkers that can be extracted by deep learning techniques to identify malignant neoplastic colon lesions and distinguish them from healthy, hyperplastic, or benign neoplastic tissue, without the need for histopathological staining. Materials and Methods: To this end, we present a novel MPM public dataset containing 14,712 images obtained from 42 patients and grouped into 2 classes. A convolutional neural network is trained on this dataset and a spatially coherent predictions scheme is applied for performance improvement. Results: We obtained a sensitivity of 0.8228 ± 0.1575 and a specificity of 0.9114 ± 0.0814 on detecting malignant neoplastic lesions. We also validated this approach to estimate the self-confidence of the network on its own predictions, obtaining a mean sensitivity of 0.8697 and a mean specificity of 0.9524 with the 18.67% of the images classified as uncertain. Conclusions: This work lays the foundations for performing in vivo optical colon biopsies by combining this novel imaging technology together with deep learning algorithms, hence avoiding unnecessary polyp resection and allowing in situ diagnosis assessment.

show abstract

Multimodal multiphoton imaging for label-free monitoring of early gastric cancer

Cited by 25 publications

References 40 publications

Lipidomic landscape in cancer: Actionable insights for membrane‐based therapy and diagnoses

Lipidomic landscape in cancer: Actionable insights for membrane‐based therapy and diagnoses

Label-Free Identification of Early Gastrointestinal Neuroendocrine Tumors via Biomedical Multiphoton Microscopy and Automatic Image Analysis

Analysis on the Characterization of Multiphoton Microscopy Images for Malignant Neoplastic Colon Lesion Detection under Deep Learning Methods

Contact Info

Product

Resources

About