Analysis of exhaled breath of lung cancer patients using infrared spectroscopy.

Abstract

e21037 Background: Currently low-dose computed tomography is used for lung cancer (LC) screening, but is limited by radiation exposure, cost, and a high false detection rate (1,2). An accurate, accessible and affordable screening technology is needed to improve detection of LC in high risk individuals. Methods: We conducted an unblinded, prospective cohort study on the effectiveness of a novel technology utilizing infrared absorption measurements via cavity ringdown spectroscopy (IR-CRDS) to differentiate the expired breath of treatment-naïve LC patients from controls without known cancer. Breath samples were taken from 100 LC patients and 98 control subjects but, only 62 non-small cell lung cancer (NSCLC) and 96 control samples were analyzed. Patients on treatment were eligible but, the protocol was amended to exclude these due to signal ambiguities. Samples were also excluded due to missing data, unclear histologic subtypes, or if they were classified as small cell LC samples to prevent obscuring the NSCLC signal. A piecewise cubic spline interpolation was used for the spectra with missing values (3). After first- and second-derivative spectra were computed to increase the information density, a one-dimensional local binary pattern extracted features from the spectra (4). Meaningful spectra-based features were selected using a minimum redundancy maximum relevance algorithm (5). Finally, a classification model was built using a support vector machine classifier (3). Results: The table below characterizes each cohort. The discriminant analysis differentiated between NSCLC and control cases with a cross validation accuracy of 86.1% (89.6% sensitivity and 80.7% specificity) using 20 selected spectra-based features. Conclusions: IR absorption measurements can be used to accurately discriminate between NSCLC and control participants. We continue to build our database to support more robust machine learning models. To our knowledge, this is the first time IR-CRDS has been used to differentiate between NSCLC and control cases. [Table: see text]