Detail publikace

Imaging margins of skin tumors using laser-induced breakdown spectroscopy and machine learning

KISS, K. ŠINDELÁŘOVÁ, A. KRBAL, L. STEJSKAL, V. MRÁZOVÁ, K. VRÁBEL, J. KAŠKA, M. MODLITBOVÁ, P. POŘÍZKA, P. KAISER, J.

Originální název

Imaging margins of skin tumors using laser-induced breakdown spectroscopy and machine learning

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

Nowadays, laser-based techniques play a significant role in medicine, mainly in the ophthalmology, dermatology, and surgical fields. So far, they have presented mostly therapeutic applications, although they have considerable potential for diagnostic approaches. In our study, we focused on the application of laser-based spectroscopy in skin cancer assessment. Recently, lengthy and demanding pathological investigation has been improved with modern techniques of machine learning and analytical chemistry where elemental analysis provides further insight into the investigated phenomenon. This article deals with the complementarity of Laser-Induced Breakdown Spectroscopy (LIBS) with standard histopathology. This includes discussion on sample preparation and feasibility to perform 3D imaging of a tumor. Typical skin tumors were selected for LIBS analysis, namely cutaneous malignant melanoma, squamous cell carcinoma and the most common skin tumor basal cell carcinoma, and a benign tumor was represented by hemangioma. The imaging of biotic elements (Mg, Ca, Na, and K) provides the elemental distribution within the tissue. The elemental images were correlated with the tumor progression and its margins, as well as with the difference between healthy and tumorous tissues and the results were compared with other studies covering this topic of interest. Finally, self-organizing maps were trained and used with a k-means algorithm to cluster various matrices within the tumorous tissue and to demonstrate the potential of machine learning for processing of LIBS data.

Klíčová slova

Laser-Induced Breakdown Spectroscopy, human skin cancer, malignant melanomy

Autoři

KISS, K.; ŠINDELÁŘOVÁ, A.; KRBAL, L.; STEJSKAL, V.; MRÁZOVÁ, K.; VRÁBEL, J.; KAŠKA, M.; MODLITBOVÁ, P.; POŘÍZKA, P.; KAISER, J.

Vydáno

1. 5. 2021

Nakladatel

Royal Society of Chemistry

Místo

CAMBRIDGE

ISSN

1364-5544

Periodikum

Journal of Analytical Atomic Spectrometry

Ročník

36

Číslo

5

Stát

Spojené království Velké Británie a Severního Irska

Strany od

909

Strany do

916

Strany počet

8

URL

https://pubs.rsc.org/en/content/articlelanding/2021/JA/D0JA00469C#!divAbstract

Plný text v Digitální knihovně

http://hdl.handle.net/11012/200991

BibTex

@article{BUT171885,
  author="Kateřina {Kiss} and Anna {Šindelářová} and Lukáš {Krbal} and Václav {Stejskal} and Kristýna {Mrázová} and Jakub {Vrábel} and Milan {Kaška} and Pavlína {Modlitbová} and Pavel {Pořízka} and Jozef {Kaiser}",
  title="Imaging margins of skin tumors using laser-induced breakdown spectroscopy and machine learning",
  journal="Journal of Analytical Atomic Spectrometry",
  year="2021",
  volume="36",
  number="5",
  pages="909--916",
  doi="10.1039/d0ja00469c",
  issn="1364-5544",
  url="https://pubs.rsc.org/en/content/articlelanding/2021/JA/D0JA00469C#!divAbstract"
}