Diabetes Mellitus refers to a group of prevalent metabolic disorders manifested by the persistent rise in blood sugar level. Once sweet and pleasing, when in compulsive excess, sugar in diabetics threatens with hyperglycemic coma and imminent death if left untreated, setting the human life on a new road with major complications including cardiovascular disease, stroke, kidney failure, early onset dementia etc.
Despite its grave nature, one of the key manifestations of diabetes is a fruity, sweet-smelling odor. In fact, over centuries the fruity smell of the sugar-enriched urine of diabetics, which attracts ants and flies, has been used as the main biomarker. Medical records of diabetes in ancient Egypt, India, and Greece describe the sweetened with honey urine, i.e. āmelliteā (Latin mellitusĀ meaning honey-sweet) as the principal indication of the disease, with the first complete clinical description given by the Greek physician Aretaeus of Cappadocia (1st century AD).
Upon the arrival of the technological era and analytical means for blood sugar detection, new approaches have been implemented, which are generally divided into (1) methods for continuous or (2) methods for single point glucose sampling. While accurate, single point glucosometry is invasive as it necessitates a finger-prick (i.e. blood-letting); urine dipsticks, on the other hand, although non-invasive, afford low sensitive readouts which are prone to variations.
Continuous glucose sensing methods range from (1) invasive implantable sensors for microdialysis and subcutaneous sensing to (2) semi-invasive microneedle sensors and (3) non-invasive optical and transdermal measurements. The principal shortfalls of transdermal approaches such as impedance spectrometry, sonography or reverse iontophoresis is the dependence of the readings on the age, skin type and condition as well as an individualsā constitution.
Optical methods of glucose measurement are inherently non-invasive and hold major promise in sensitivity and specificity, with a major drawback, however, being poor penetration depth and readout attenuation. To circumvent the downsides of non-invasive optical glucose sensing, scientists from the Institute of Biological and Medical Imaging at Helmholtz Zentrum Munich, Germany, developed and validated a new method dubbed āExtended Near-infrared Optoacoustic Spectrometryā for quantification of the physiological concentration of glucose.
Unlike an antique glucose sensing reliant on the taste and smell of urine, and more recent methods conditional to a chemical or optical signature of glucose, this new approach uses the hybrid optoacoustic (photoacoustic) readouts of glucose spectrum (i.e. glucose melody) resonating under interrogation by different wavelengths of light. The principal advantage of using this approach is that unlike optical glucose sensing, prone to strong signal attenuation and erroneous readouts in deep tissue, this method utilizes sound as glucose readout. Because of low scattering and superb propagation of acoustic waves in biological tissue, the new methodology is more sensitive and accurate, hence yielding an improved āintensity, tone and timbreā for glucose from deep tissue.
The researchers applied different computational approaches for detecting and decoding the optoacoustic spectrum of glucose and optimized their methodology for the best outcome in terms of sensitivity and accuracy. The study is limited to sensing physiological amounts of glucose in water, with an incredible Ā±10 mg/dl precision, but sets a clear vision for futureĀ applications in human. Due to the importance of glucose sensing for research and diagnosis of carbohydrate and fat metabolism disorders as well as an array of other conditions, including morbid obesity and cancer, this new development holds major potential for clinical translation and healthcare.
These findings are described in the article entitled Extended Near-Infrared Optoacoustic Spectrometry for Sensing Physiological Concentrations of Glucose, recently published in the journal Frontiers in Endocrinology. This work was conducted by Ara Ghazaryan, Saak V. Ovsepian and Vasilis Ntziachristos from the Institute of Biological and Medical Imaging at Helmholtz Zentrum Munich, Germany.