The Development and Optimisation of a Urinary Volatile Organic Compound Analytical Platform Using Gas Sensor Arrays for the Detection of Colorectal Cancer
Arasaradnam, Ramesh
Arasaradnam, Ramesh
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Affiliation
Ramesh P. Arasaradnam 1,2,3,* , Ashwin Krishnamoorthy 1,2 , Mark A. Hull 4 , Peter Wheatstone 4 , Frank Kvasnik 5 and Krishna C. Persaud
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Publication date
2025
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Abstract
The profile of Volatile Organic Compounds (VOCs) may help prioritise at-risk
groups for early cancer detection. Urine sampling has been shown to provide good disease
accuracy whilst being patient acceptable compared to faecal analysis. Thus, in this study,
urine samples were examined using an electronic nose with metal oxide gas sensors and
a solid-phase microextraction sampling system. A calibration dataset (derived from a
previous study) with CRC-positive patients and healthy controls was used to train a radial
basis function neural network. However, a blinded analysis failed to detect CRC accurately,
necessitating an enhanced data-processing strategy. This new approach categorised samples
by significant bowel diseases, including CRC and high-risk polyps. Retraining the neural
network showed an area under the ROC curve of 0.88 for distinguishing CRC versus nonsignificant
bowel disease (without CRC, polyps or inflammation). These findings suggest
that, with appropriate training sets, urine VOC analysis could be a rapid, low-cost method
for early detection of precancerous colorectal polyps and CRC.
Citation
Citation: Arasaradnam, R.P.; Krishnamoorthy, A.; Hull, M.A.; Wheatstone, P.; Kvasnik, F.; Persaud, K.C. The Development and Optimisation of a Urinary Volatile Organic Compound Analytical Platform Using Gas Sensor Arrays for the Detection of Colorectal Cancer. Sensors 2025, 25, 599. https://doi.org/ 10.3390/s25030599
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Article