Alteration of the Exhaled Volatile Organic Compound Pattern in Colorectal Cancer Patients after Intentional Curative Surgery-A Prospective Pilot Study

Abstract

As current follow-up modalities for colorectal carcinoma (CRC) have restricted sensitivity, novel diagnostic tools are needed. The presence of CRC changes the endogenous metabolism, resulting in the release of a specific volatile organic compounds (VOC) pattern that can be detected with an electronic nose or Aeonose^TM. To evaluate the use of an electronic nose in the follow-up of CRC, we studied the effect of curative surgery on the VOC pattern recognition using Aeonose^TM. A prospective cohort study was performed, in which 47 patients diagnosed with CRC were included, all of whom underwent curative surgical resection. Breath testing was performed before and after surgery using the Aeonose^TM. A machine learning model was developed by discerning between the 94 pre-and postoperative breath samples. The training model differentiated between the pre-and postoperative CRC breath samples with a sensitivity and specificity of 0.78 (95%CI 0.61-0.90) and 0.73 (95%CI 0.56-0.86), respectively, with an accuracy of 0.76 (95%CI 0.66-0.85), and an area under the curve of 0.79 (95%CI 0.68-0.89). The internal validation of the test set resulted in an accuracy of 0.75 (95%CI 0.51-0.91) and AUC of 0.82 (95%CI 0.61-1). In conclusion, our results suggest that the VOC pattern of CRC patients is altered by curative surgery in a short period, indicating that the exhaled VOCs might be closely related to the presence of CRC. However, to use Aeonose^TM as a potential diagnostic tool in the clinical follow-up of CRC patients, the performance of the models needs to be improved through further large-scale prospective research.

Keywords: AeonoseTM; VOCs; colorectal cancer; electronic nose; volatile organic compounds.

Figure 1

Electric nose (Aeonose^TM) technology and model development. Abbreviations: VOCs—volatile organic compounds, SVD—singular value decomposition, AUC—area under the curve.

Figure 2

Patient enrollment.

Figure 3

Scatterplot of the individual predictive values of pre-operative (green/dark blue) breath tests and post-operative (red/light blue) breath tests. The threshold was set on 0.20 (dotted line). All breath tests with a predictive value of >0.20 were classified as positive for CRC.

Figure 4

Receiver operating characteristic (ROC)-curve training (A) and test set (B) after interpolation, representing the diagnostic value of the Aeonose^TM in terms of its ability to discriminate between pre-and postoperative breath samples.