Fourier transform infrared spectroscopic imaging of colon tissues: evaluating the significance of amide I and C\u2013H stretching bands in diagnostic applications with machine learning

Cai Li Song,Martha Z Vardaki,Robert D Goldin,Sergei G Kazarian

doi:10.1007/s00216-019-02069-6

Abstract

Fourier transform infrared (FTIR) spectroscopic imaging of colon biopsy tissues in transmission combined with machine learning for the classification of different stages of colon malignancy was carried out in this study. Two different approaches, an optical and a computational one, were applied for the elimination of the scattering background during the measurements and compared with the results of the machine learning model without correction for the scattering. Several different data processing pathways were implemented in order to obtain a high accuracy of the prediction model. This study demonstrates, for the first time, that C–H stretching and amide I bands are of little to no significance in the classification of the colon malignancy, based on the Gini importance values by random forest (RF). The best prediction outcome is found when supervised RF classification was carried out in the fingerprint region of the spectral data between 1500 and 1000 cm−1 (excluding the contribution of amide I and II bands). An overall prediction accuracy higher than 90% is achieved through the RF. The results also show that dysplastic and hyperplastic tissues are well distinguished. This leads to the insight that the important differences between hyperplastic and dysplastic colon tissues lie within the fingerprint region of FTIR spectra. In this study, computational correction performed better than optical correction, but the findings show that the disease states of colon biopsies can be distinguished effectively without elimination of Mie scattering effect.Graphical abstract

Highlights

Colon cancer is a disease in the large intestine in which abnormal cells divide uncontrollably
Fourier transform infrared (FTIR) spectroscopy has been shown as a promising technique to enhance the clinical diagnosis in a label-free way by investigating the chemical content of the biopsy samples [3,4,5,6]
Computation correction with Resonant Mie scattering (RMieS) algorithm was more efficient at recovering a flat baseline of the spectra (Fig. 3) compared with correction with the added lens but was more time consuming

Summary

Introduction

Colon cancer is a disease in the large intestine in which abnormal cells divide uncontrollably. Most cases of the colon cancer begin as a small adenomatous polyp which lines the inner. Surface of the colon [1]. In the UK, colon cancer is the fourth most common cancer with 16,000 deaths every year, making it the second most common cause of cancer death in 2016 [2]. Detection of colon cancer can help reduce mortality and morbidity. FTIR spectroscopy has been shown as a promising technique to enhance the clinical diagnosis in a label-free way by investigating the chemical content of the biopsy samples [3,4,5,6]

Objectives

Methods

Results

Conclusion