Hand-Held Breathalyzer Aids Diabetes Diagnosis
By Daniel Beris Posted on 22 Nov 2016 |
Image: An early prototype model of the diabetes breathalyzer (Photo courtesy of OMD).
A novel hand-held device measures acetone levels in exhaled breath, helping doctors diagnose diabetes in a noninvasive manner.
Under development at the University of Oxford (United Kingdom) and Oxford Medical Diagnostics (OMD; Begbroke, United Kingdom), the device features a 7 centimeter long high finesse hollow core, which serves as an optical cavity-enhanced spectroscopy sensor that is coupled to a miniature preconcentrator containing 0.5 grams of adsorbent polymer material. Exhaled acetone from breath is released into the optical cavity, where it is probed by a near-infrared (NIR) diode laser operating at ∼1670 nm.
As the optical cavity mirror has a reflectivity of 99.994%, breath-sampling rates have a precision of 100 parts per billion by volume (PPBV). The researchers validated the device with measurement of exhaled breath in healthy subjects under different conditions, such as after overnight fasting or exercising, and compared the results with mass spectrometry readings. The measurements were a close match and covered a wide range of concentrations, including those that would suggest a patient has undiagnosed type-1 diabetes. The study was published on October 18, 2016, in Analytical Chemistry.
“It was not an easy task, because breath contains molecules of millions of compounds while this test requires detecting only one of them,” said Ian Campbell, CEO of Oxford Medical Diagnostics. “So, what we do is allow the subject to blow into the device, we extract out the volatile organic compound we wish to measure, in this case acetone. The remainder of the breath passes through the device. We then release the molecules that we're interested in into the cavity to make the measurement.”
The new method is based on cavity ringdown spectroscopy, a method that is used to detect volatile organic compounds (VOCs) released from human breath or skin. It is grounded on the premise that those with diabetes exhale elevated levels of acetone, resulting from ketoacidosis. When classified as diabetic ketoacidosis, the high concentration of ketone bodies is usually accompanied by insulin deficiency, hyperglycemia, and dehydration. The problem is that detecting the acetone is difficult because different compounds, including water, CO2, and methane, compromise the results.
Related Links:
University of Oxford
Oxford Medical Diagnostics
Under development at the University of Oxford (United Kingdom) and Oxford Medical Diagnostics (OMD; Begbroke, United Kingdom), the device features a 7 centimeter long high finesse hollow core, which serves as an optical cavity-enhanced spectroscopy sensor that is coupled to a miniature preconcentrator containing 0.5 grams of adsorbent polymer material. Exhaled acetone from breath is released into the optical cavity, where it is probed by a near-infrared (NIR) diode laser operating at ∼1670 nm.
As the optical cavity mirror has a reflectivity of 99.994%, breath-sampling rates have a precision of 100 parts per billion by volume (PPBV). The researchers validated the device with measurement of exhaled breath in healthy subjects under different conditions, such as after overnight fasting or exercising, and compared the results with mass spectrometry readings. The measurements were a close match and covered a wide range of concentrations, including those that would suggest a patient has undiagnosed type-1 diabetes. The study was published on October 18, 2016, in Analytical Chemistry.
“It was not an easy task, because breath contains molecules of millions of compounds while this test requires detecting only one of them,” said Ian Campbell, CEO of Oxford Medical Diagnostics. “So, what we do is allow the subject to blow into the device, we extract out the volatile organic compound we wish to measure, in this case acetone. The remainder of the breath passes through the device. We then release the molecules that we're interested in into the cavity to make the measurement.”
The new method is based on cavity ringdown spectroscopy, a method that is used to detect volatile organic compounds (VOCs) released from human breath or skin. It is grounded on the premise that those with diabetes exhale elevated levels of acetone, resulting from ketoacidosis. When classified as diabetic ketoacidosis, the high concentration of ketone bodies is usually accompanied by insulin deficiency, hyperglycemia, and dehydration. The problem is that detecting the acetone is difficult because different compounds, including water, CO2, and methane, compromise the results.
Related Links:
University of Oxford
Oxford Medical Diagnostics
Latest Critical Care News
- Powerful AI Risk Assessment Tool Predicts Outcomes in Heart Failure Patients
- Peptide-Based Hydrogels Repair Damaged Organs and Tissues On-The-Spot
- One-Hour Endoscopic Procedure Could Eliminate Need for Insulin for Type 2 Diabetes
- AI Can Prioritize Emergency Department Patients Requiring Urgent Treatment
- AI to Improve Diagnosis of Atrial Fibrillation
- Stretchable Microneedles to Help In Accurate Tracking of Abnormalities and Identifying Rapid Treatment
- Machine Learning Tool Identifies Rare, Undiagnosed Immune Disorders from Patient EHRs
- On-Skin Wearable Bioelectronic Device Paves Way for Intelligent Implants
- First-Of-Its-Kind Dissolvable Stent to Improve Outcomes for Patients with Severe PAD
- AI Brain-Age Estimation Technology Uses EEG Scans to Screen for Degenerative Diseases
- Wheeze-Counting Wearable Device Monitors Patient's Breathing In Real Time
- Wearable Multiplex Biosensors Could Revolutionize COPD Management
- New Low-Energy Defibrillation Method Controls Cardiac Arrhythmias
- New Machine Learning Models Help Predict Heart Disease Risk in Women
- Deep-Learning Model Predicts Arrhythmia 30 Minutes before Onset
- Breakthrough Technology Combines Detection and Treatment of Nerve-Related Disorders in Single Procedure