Volume 9, Issue 5 pp. 533-541
Full Article

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

Nadine Vogler

Nadine Vogler

Leibniz Institute of Photonic Technology, 07745 Jena, Germany

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Thomas Bocklitz

Corresponding Author

Thomas Bocklitz

Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, 07743 Jena, Germany

Corresponding author: e-mail: [email protected]

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Firas Subhi Salah

Firas Subhi Salah

Institute of Pathology, Jena University Hospital, 07743 Jena, Germany

Iraqi Centre for Cancer and Medical Genetics Research, Al-Mustansiriya University, Baghdad, Iraq

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Carsten Schmidt

Carsten Schmidt

Clinic for Internal Medicine IV, Jena University Hospital, 07747 Jena, Germany

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Rolf Bräuer

Rolf Bräuer

Institute of Pathology, Jena University Hospital, 07743 Jena, Germany

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Tiantian Cui

Tiantian Cui

Institute of Pathology, Jena University Hospital, 07743 Jena, Germany

Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, OH, USA

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Masoud Mireskandari

Masoud Mireskandari

Institute of Pathology, Jena University Hospital, 07743 Jena, Germany

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Florian R. Greten

Florian R. Greten

Institute for Tumor Biology and Experimental Therapy, Georg-Speyer-Haus, 60596 Frankfurt, Germany

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Michael Schmitt

Michael Schmitt

Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, 07743 Jena, Germany

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Andreas Stallmach

Andreas Stallmach

Clinic for Internal Medicine IV, Jena University Hospital, 07747 Jena, Germany

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Iver Petersen

Iver Petersen

Institute of Pathology, Jena University Hospital, 07743 Jena, Germany

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Jürgen Popp

Jürgen Popp

Leibniz Institute of Photonic Technology, 07745 Jena, Germany

Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, 07743 Jena, Germany

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First published: 20 December 2015
Citations: 22

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.

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