The detection of patients at risk of gastrointestinal toxicity during pelvic radiotherapy by electronic nose and FAIMS: a pilot study

Sensors (Basel). 2012 Sep 26;12(10):13002-18. doi: 10.3390/s121013002.

Abstract

It is well known that the electronic nose can be used to identify differences between human health and disease for a range of disorders. We present a pilot study to investigate if the electronic nose and a newer technology, FAIMS (Field Asymmetric Ion Mobility Spectrometry), can be used to identify and help inform the treatment pathway for patients receiving pelvic radiotherapy, which frequently causes gastrointestinal side-effects, severe in some. From a larger group, 23 radiotherapy patients were selected where half had the highest levels of toxicity and the others the lowest. Stool samples were obtained before and four weeks after radiotherapy and the volatiles and gases emitted analysed by both methods; these chemicals are products of fermentation caused by gut microflora. Principal component analysis of the electronic nose data and wavelet transform followed by Fisher discriminant analysis of FAIMS data indicated that it was possible to separate patients after treatment by their toxicity levels. More interestingly, differences were also identified in their pre-treatment samples. We believe these patterns arise from differences in gut microflora where some combinations of bacteria result to give this olfactory signature. In the future our approach may result in a technique that will help identify patients at "high risk" even before radiation treatment is started.

Publication types

  • Randomized Controlled Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Electronic Nose*
  • Feces / chemistry
  • Female
  • Gases / analysis
  • Gastrointestinal Diseases / diagnosis*
  • Gastrointestinal Diseases / etiology*
  • Humans
  • Male
  • Pelvic Neoplasms / diagnosis
  • Pelvic Neoplasms / radiotherapy*
  • Pilot Projects
  • Radiation Injuries / diagnosis*
  • Radiation Injuries / etiology
  • Risk Factors
  • Severity of Illness Index
  • Spectrum Analysis / instrumentation
  • Spectrum Analysis / methods*

Substances

  • Gases