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Analytical Chemistry

Breathalyzer-like nanoarray sensor detects disease

Researchers use carbon nanotubes, gold nanoparticles, and artificial intelligence to identify ‘breath prints’ of 17 diseases

by Ryan Cross
December 30, 2016 | A version of this story appeared in Volume 95, Issue 1

A sophisticated breathalyzer-like device developed by a consortium of researchers led by Hossam Haick of Technion—Israel Institute of Technology can detect signatures of 17 different diseases, including ovarian cancer, multiple sclerosis, and ulcerative colitis.

Using breath as an indicator of disease is a “basic idea that goes back to the ancient Greeks,” Haick says. Although previous studies found that patients with a particular disease have different breath compounds compared with healthy controls, Haick says the new study proves the “hypothesis that different diseases have different ‘breath prints’.”

The researchers developed a so-called artificially intelligent nanoarray, a collection of electrically conductive gold nanoparticles and single-walled carbon nanotubes. These are coated with various organic layers that function as sensors whose electrical resistivity changes when in contact with volatile organic compounds from a patient’s breath. Patterns emerging from analysis of the complex mixture of breath compounds interacting with the nanoarray create breath prints used to detect and differentiate between diseases (ACS Nano 2016, DOI: 10.1021/acsnano.6b04930). Algorithms further help by reducing variability from factors such as age, gender, smoking, and country-of-residence.

The researchers used gas chromatography-mass spectrometry to validate the results by comparing levels of 13 organic compounds in breath. Haick says he originally thought that one kind of molecule would be enough to differentiate between diseases, but it wasn’t that simple. “What really mattered was the combinations,” he says.

In blind tests, the device identified diseases with 86% accuracy on average, although it was more accurate for some diseases (such as gastric cancer) than others (such as Parkinson’s). Haick anticipates that future iterations of the technology will accelerate first-line medical evaluations to a matter of minutes.


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