| Literature DB >> 26687775 |
Nadine Vogler1, Thomas Bocklitz2, Firas Subhi Salah3,4, Carsten Schmidt5, Rolf Bräuer3, Tiantian Cui3,6, Masoud Mireskandari3, Florian R Greten7, Michael Schmitt8, Andreas Stallmach5, Iver Petersen3, Jürgen Popp1,8.
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.Entities:
Keywords: Raman microspectroscopy; cancer diagnosis; chemometrics
Mesh:
Year: 2015 PMID: 26687775 DOI: 10.1002/jbio.201500237
Source DB: PubMed Journal: J Biophotonics ISSN: 1864-063X Impact factor: 3.207