Canine scent detection in the diagnosis of lung cancer: Revisiting a puzzling phenomenon
1. R. Ehmann*§, 2. E. Boedeker#§, 3. U. Friedrich¶, 4. J. Sagert¶, 5. J. Dippon+, 6. G.Friedel# 7. T. Walles#?
1. T. Walles, Schillerhoehe Hospital, Dept of Thoracic Surgery, Solitudestrasse 18, D-70839 Gerlingen, Germany, E-mail: Thorsten.Walles@klinik-schillerhoehe.de
Abstract
Patient prognosis in lung cancer (LC) largely depends on early diagnosis. Exhaled breath of patients may represent the ideal specimen for future LC screening. However, the clinical applicability of current diagnostic sensor technologies based on signal pattern analysis remains incalculable due to their inability to identify a clear target. To test the robustness of the presence of a so far unknown volatile organic compound in the breath of patients with LC, sniffer dogs were applied.
Exhalation samples of 220 volunteers (healthy individuals, confirmed LC, or COPD) were presented to sniffer dogs following a rigid scientific protocol. Patient history, drug administration and clinicopathological data were analysed to identify potential bias or confounders.
LC was identified with an overall sensitivity of 71% and a specificity of 93%. LC detection was independent from COPD and the presence of tobacco smoke and food odors. Logistic regression identified two drugs as potential confounders.
It must be assumed, that a robust and specific volatile organic compound (or pattern) is present in the breath of patients with LC. Additional research efforts are required to overcome the current technical limitations of electronic sensor technologies to engineer a clinically applicable screening tool.
+ Author Affiliations
1.*Ambulante Pneumologie, Rotebuehlplatz 19, 70178 Stuttgart, Germany
2.#Dept of General Thoracic Surgery, Schillerhoehe Hospital, Solitudestrasse 18, 70839 Gerlingen, Germany
3.¶TeamCanin, An der Burg 1, 79843 Loeffingen, Germany
4.+Dept of Mathematics, University of Stuttgart, Pfaffenwaldring 57, 70569 Stuttgart. Germany
5.§both authors contributed equally