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J Biophotonics. 2016 May;9(5):533-41. doi: 10.1002/jbio.201500237. Epub 2015 Dec 20.

Systematic evaluation of the biological variance within the Raman based colorectal tissue diagnostics.

Author information

1
Leibniz Institute of Photonic Technology, 07745, Jena, Germany.
2
Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, 07743, Jena, Germany. thomas.bocklitz@uni-jena.de.
3
Institute of Pathology, Jena University Hospital, 07743, Jena, Germany.
4
Iraqi Centre for Cancer and Medical Genetics Research, Al-Mustansiriya University, Baghdad, Iraq.
5
Clinic for Internal Medicine IV, Jena University Hospital, 07747, Jena, Germany.
6
Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
7
Institute for Tumor Biology and Experimental Therapy, Georg-Speyer-Haus, 60596, Frankfurt, Germany.
8
Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, 07743, Jena, Germany.

Abstract

Being among the most common cancers worldwide screening and early diagnosis of colorectal cancer is of high interest for the health system, the patients and for research. Raman microspectroscopy as a label-free, non-invasive and non-destructive technique is a promising tool for an early diagnosis. However, to ensure a reliable diagnosis specially designed statistical analysis workflows are required. Several statistical approaches have been introduced leading to varying results in the overall accuracy, sensitivity and specificity. In this study a systematic evaluation of different statistical analysis approaches has been performed using a colon cancer mouse model with genotypic identical individuals. Based on the inter-individual Raman spectral variances a measure for the biological variance can be estimated. By applying a leave-one-individual-out cross-validation a clinically relevant discrimination of healthy tissue versus adenoma and carcinoma with an accuracy of 95% is shown. Furthermore, the transfer of a model from tissue to biopsy specimen is demonstrated.

KEYWORDS:

Raman microspectroscopy; cancer diagnosis; chemometrics

PMID:
26687775
DOI:
10.1002/jbio.201500237
[Indexed for MEDLINE]

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