Infrared spectral histopathology (SHP): a novel diagnostic tool for the accurate classification of lung cancer

We report results of a study utilizing a recently developed tissue diagnostic method, based on label-free spectral techniques, for the classification of lung cancer histopathological samples from a tissue microarray. The spectral diagnostic method allows reproducible and objective diagnosis of unsta...

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Veröffentlicht in:Laboratory investigation Jg. 92; H. 9; S. 1358 - 1373
Hauptverfasser: Bird, Benjamin, Miljković, Milos̆, Remiszewski, Stan, Akalin, Ali, Kon, Mark, Diem, Max
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Elsevier Inc 01.09.2012
Nature Publishing Group US
Nature Publishing Group
Schlagworte:
631/1647/1407/1555
631/1647/527/2257
692/699/67/1612
692/700/139
artificial neural network analysis
Biological and medical sciences
Biotechnology
Fundamental and applied biological sciences. Psychology
histopathology
Humans
immunohistochemistry
Investigative techniques, diagnostic techniques (general aspects)
Laboratory Medicine
Lung cancer
Lung Neoplasms - classification
Lung Neoplasms - diagnosis
Medical sciences
Medicine
Medicine & Public Health
Pathology
Pneumology
research-article
spectral histopathology
Spectrophotometry, Infrared - methods
Tumors of the respiratory system and mediastinum
lung cancer
histopathology
artificial neural network analysis
immunohistochemistry
spectral histopathology
Immunohistochemistry
Lung disease
Biotechnology
Respiratory disease
Lung cancer
5: artificial neural network analysis
Malignant tumor
Neural network
Anatomic pathology
Histopathology
Network analysis
Clinical biology
Classification
Bronchus disease
Infrared radiation
Diagnosis
Cancer
Tool
ISSN:0023-6837, 1530-0307, 1530-0307
Online-Zugang:Volltext
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Zusammenfassung:We report results of a study utilizing a recently developed tissue diagnostic method, based on label-free spectral techniques, for the classification of lung cancer histopathological samples from a tissue microarray. The spectral diagnostic method allows reproducible and objective diagnosis of unstained tissue sections. This is accomplished by acquiring infrared hyperspectral data sets containing thousands of spectra, each collected from tissue pixels about 6 μm on edge; these pixel spectra contain an encoded snapshot of the entire biochemical composition of the pixel area. The hyperspectral data sets are subsequently decoded by methods of multivariate analysis, which reveal changes in the biochemical composition between tissue types, and between various stages and states of disease. In this study, a detailed comparison between classical and spectral histopathology (SHP) is presented, which suggests SHP can achieve levels of diagnostic accuracy that is comparable to that of multi-panel immunohistochemistry.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:0023-6837
1530-0307
1530-0307
DOI:10.1038/labinvest.2012.101