Literature DB >> 16328253

Delimitation of squamous cell cervical carcinoma using infrared microspectroscopic imaging.

Wolfram Steller1, Jens Einenkel, Lars-Christian Horn, Ulf-Dietrich Braumann, Hans Binder, Reiner Salzer, Christoph Krafft.   

Abstract

Infrared (IR) spectroscopic imaging coupled with microscopy has been used to investigate thin sections of cervix uteri encompassing normal tissue, precancerous structures, and squamous cell carcinoma. Methods for unsupervised distinction of tissue types based on IR spectroscopy were developed. One-hundred and twenty-two images of cervical tissue were recorded by an FTIR spectrometer with a 64x64 focal plane array detector. The 499,712 IR spectra obtained were grouped by an approach which used fuzzy C-means clustering followed by hierarchical cluster analysis. The resulting false color maps were correlated with the morphological characteristics of an adjacent section of hematoxylin and eosin-stained tissue. In the first step, cervical stroma, epithelium, inflammation, blood vessels, and mucus could be distinguished in IR images by analysis of the spectral fingerprint region (950-1480 cm(-1)). In the second step, analysis in the spectral window 1420-1480 cm(-1) enables, for the first time, IR spectroscopic distinction between the basal layer, dysplastic lesions and squamous cell carcinoma within a particular sample. The joint application of IR microspectroscopic imaging and multivariate spectral processing combines diffraction-limited lateral optical resolution on the single cell level with highly specific and sensitive spectral classification on the molecular level. Compared with previous reports our approach constitutes a significant progress in the development of optical molecular spectroscopic techniques toward an additional diagnostic tool for the early histopathological characterization of cervical cancer.

Entities:  

Mesh:

Substances:

Year:  2005        PMID: 16328253     DOI: 10.1007/s00216-005-0124-4

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


  9 in total

1.  Infrared micro-spectroscopic studies of epithelial cells.

Authors:  Melissa Romeo; Brian Mohlenhoff; Michael Jennings; Max Diem
Journal:  Biochim Biophys Acta       Date:  2006-05-19

2.  Detection of cervical cancer based on photoacoustic imaging-the in-vitro results.

Authors:  Kuan Peng; Ling He; Bo Wang; Jiaying Xiao
Journal:  Biomed Opt Express       Date:  2014-12-15       Impact factor: 3.732

Review 3.  Advances in Digital Pathology: From Artificial Intelligence to Label-Free Imaging.

Authors:  Frederik Großerueschkamp; Hendrik Jütte; Klaus Gerwert; Andrea Tannapfel
Journal:  Visc Med       Date:  2021-08-24

4.  Elliptically polarized light for depth resolved optical imaging.

Authors:  Anabela Da Silva; Carole Deumié; Ivo Vanzetta
Journal:  Biomed Opt Express       Date:  2012-10-23       Impact factor: 3.732

5.  Patterns Prediction of Chemotherapy Sensitivity in Cancer Cell lines Using FTIR Spectrum, Neural Network and Principal Components Analysis.

Authors:  Rezvan Zendehdel; Ali Masoudi-Nejad; Farshad H Shirazi
Journal:  Iran J Pharm Res       Date:  2012       Impact factor: 1.696

6.  Similarity maps and hierarchical clustering for annotating FT-IR spectral images.

Authors:  Qiaoyong Zhong; Chen Yang; Frederik Großerüschkamp; Angela Kallenbach-Thieltges; Peter Serocka; Klaus Gerwert; Axel Mosig
Journal:  BMC Bioinformatics       Date:  2013-11-20       Impact factor: 3.169

7.  Resolving Interobserver Discrepancies in Lung Cancer Diagnoses by Spectral Histopathology.

Authors:  Ali Akalin; Ayşegül Ergin; Stanley Remiszewski; Xinying Mu; Dan Raz; Max Diem
Journal:  Arch Pathol Lab Med       Date:  2018-08-24       Impact factor: 5.534

8.  Discrimination of Human Cell Lines by Infrared Spectroscopy and Mathematical Modeling.

Authors:  Rezvan Zendehdel; Farshad H Shirazi
Journal:  Iran J Pharm Res       Date:  2015       Impact factor: 1.696

9.  Breast cancer characterization based on image classification of tissue sections visualized under low magnification.

Authors:  C Loukas; S Kostopoulos; A Tanoglidi; D Glotsos; C Sfikas; D Cavouras
Journal:  Comput Math Methods Med       Date:  2013-08-31       Impact factor: 2.238

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.