Discrimination of non-melanoma skin cancer and keratosis from normal skin tissue in vivo and ex vivo by Raman spectroscopy

2019 ◽  
Vol 100 ◽  
pp. 131-141 ◽  
Author(s):  
Ana Mara Ferreira Lima ◽  
Camila Ribeiro Daniel ◽  
Ricardo Scarparo Navarro ◽  
Benito Bodanese ◽  
Carlos Augusto Pasqualucci ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Skin Cancer ◽  
Ex Vivo ◽  
Normal Skin ◽  
Skin Tissue ◽  
Non Melanoma Skin Cancer ◽  
Melanoma Skin

Two-photon microscopy of non-melanoma skin cancer: initial experience and diagnostic criteria ex vivo

2007 ◽  
Author(s):  
Marica B. Ericson ◽  
John Paoli ◽  
Carl Ljungblad ◽  
Adaocha Odu ◽  
Maria Smedh ◽  
...  
Keyword(s):  
Skin Cancer ◽  
Diagnostic Criteria ◽  
Ex Vivo ◽  
Initial Experience ◽  
Two Photon Microscopy ◽  
Two Photon ◽  
Non Melanoma Skin Cancer ◽  
Melanoma Skin

scholarly journals Multiple Roles for VEGF in Non-Melanoma Skin Cancer: Angiogenesis and Beyond

2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Kelly E. Johnson ◽  
Traci A. Wilgus
Keyword(s):  
Skin Cancer ◽  
Critical Role ◽  
Tumor Development ◽  
Skin Carcinogenesis ◽  
Skin Tumors ◽  
Angiogenic Factor ◽  
Non Melanoma Skin Cancer ◽  
New Treatments ◽  
Melanoma Skin

Vascular endothelial growth factor (VEGF) is known to play a critical role in the development of non-melanoma skin cancers. VEGF is a potent pro-angiogenic factor and it is elevated in mouse and human skin tumors. The use of transgenic and knockout mice has shown that VEGF is essential for tumor development in multiple models of skin carcinogenesis and, until recently, the mechanism of action has been primarily attributed to the induction of angiogenesis. However, additional roles for VEGF have now been discovered. Keratinocytes can respond directly to VEGF, which could influence skin carcinogenesis by altering proliferation, survival, and stemness.In vivostudies have shown that loss of epidermal VEGFR-1 or neuropillin-1 inhibits carcinogenesis, indicating that VEGF can directly affect tumor cells. Additionally, VEGF has been shown to promote tumor growth by recruiting macrophages to skin tumors, which likely occurs through VEGFR-1. Overall, these new studies show that VEGF carries out functions beyond its well-established effects on angiogenesis and highlight the need to consider these alternative activities when developing new treatments for non-melanoma skin cancer.

scholarly journals Preoperative AI-Driven Fluorescence Diagnosis of Non-Melanoma Skin Cancer

Diagnostics ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 72
Author(s):  
Victoriya Andreeva ◽  
Evgeniia Aksamentova ◽  
Andrey Muhachev ◽  
Alexey Solovey ◽  
Igor Litvinov ◽  
...  
Keyword(s):  
Skin Cancer ◽  
Normal Skin ◽  
Invasive Procedure ◽  
Biopsy Material ◽  
Fluorescence Diagnosis ◽  
Non Melanoma Skin Cancer ◽  
Skin Cancers ◽  
Abnormal Cells ◽  
Diagnosis Method ◽  
Melanoma Skin

The diagnosis and treatment of non-melanoma skin cancer remain urgent problems. Histological examination of biopsy material—the gold standard of diagnosis—is an invasive procedure that requires a certain amount of time to perform. The ability to detect abnormal cells using fluorescence spectroscopy (FS) has been shown in many studies. This technique is rapidly expanding due to its safety, relative cost-effectiveness, and efficiency. However, skin lesion FS-based diagnosis is challenging due to a number of single overlapping spectra emitted by fluorescent molecules, making it difficult to distinguish changes in the overall spectrum and the molecular basis for it. We applied deep learning (DL) algorithms to quantitatively assess the ability of FS to differentiate between pathologies and normal skin. A total of 137 patients with various forms of primary and recurrent basal cell carcinoma (BCC) were observed by a multispectral laser-based device with a built-in neural network (NN) “DSL-1”. We measured the fluorescence spectra of suspected non-melanoma skin cancers and compared them with “normal” skin spectra. These spectra were input into DL algorithms to determine whether the skin is normal, pigmented normal, benign, or BCC. The preoperative differential AI-driven fluorescence diagnosis method correctly predicted the BCC lesions. We obtained an average sensitivity of 62% and average specificity of 83% in our experiments. Thus, the presented “DSL-1” diagnostic device can be a viable tool for the real-time diagnosis and guidance of non-melanoma skin cancer resection.

scholarly journals Detection of Non-Melanoma Skin Cancer by in vivo Fluorescence Imaging with Fluorocoxib A

Neoplasia ◽  
2015 ◽  
Vol 17 (2) ◽  
pp. 201-207 ◽  
Author(s):  
Hyejun Ra ◽  
Emilio González-González ◽  
Md. Jashim Uddin ◽  
Bonnie L. King ◽  
Alex Lee ◽  
...  
Keyword(s):  
Skin Cancer ◽  
Fluorescence Imaging ◽  
In Vivo Fluorescence ◽  
Non Melanoma Skin Cancer ◽  
In Vivo Fluorescence Imaging ◽  
Melanoma Skin

Does surface preparation alter ALA uptake in superficial non-melanoma skin cancer in vivo?

2008 ◽  
Vol 24 (2) ◽  
pp. 72-75 ◽  
Author(s):  
Harry Moseley ◽  
Lorenzo Brancaleon ◽  
Andrea E. Lesar ◽  
James Ferguson ◽  
Sally H. Ibbotson
Keyword(s):  
Skin Cancer ◽  
Surface Preparation ◽  
Non Melanoma Skin Cancer ◽  
Melanoma Skin

scholarly journals Characterization of Ex Vivo Nonmelanoma Skin Tissue Using Raman Spectroscopy

Photonics ◽  
2021 ◽  
Vol 8 (7) ◽  
pp. 282
Author(s):  
Hieu T. M. Nguyen ◽  
Yao Zhang ◽  
Austin J. Moy ◽  
Xu Feng ◽  
Katherine R. Sebastian ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Skin Cancer ◽  
Cell Carcinoma ◽  
Raman Spectra ◽  
Ex Vivo ◽  
Hair Follicles ◽  
Nonmelanoma Skin Cancer ◽  
Skin Tissue ◽  
Biophysical Model ◽  
Resection Margins

Raman spectroscopy has shown great potential in detecting nonmelanoma skin cancer accurately and quickly; however, little direct evidence exists on the sensitivity of measurements to the underlying anatomy. Here, we aimed to correlate Raman measurements directly to the underlying tissue anatomy. We acquired Raman spectra of ex vivo skin tissue from 25 patients undergoing Mohs surgery with a fiber probe. We utilized a previously developed biophysical model to extract key biomarkers in the skin from the Raman spectra. We then examined the correlations between the biomarkers and the major skin structures (including the dermis, sebaceous glands, hair follicles, fat, and two types of nonmelanoma skin cancer—basal cell carcinoma (BCC) and squamous cell carcinoma (SCC)). SCC had a significantly different concentration of keratin, collagen, and nucleic acid than normal structures, while ceramide differentiated BCC from normal structures. Our findings identified the key proteins, lipids, and nucleic acids that discriminate nonmelanoma tumors and healthy skin using Raman spectroscopy. These markers may be promising surgical guidance tools for detecting tumors in resection margins.

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