Breath analysis has been considered a suitable tool to evaluate diseases of the respiratory system and those that involve metabolic changes, such as diabetes. Breath acetone has long been known as a biomarker for diabetes. However, the results from published data by far have been inconclusive regarding whether breath acetone is a reliable index of diabetic screening. Large variations exist among the results of different studies because there has been no “best-practice method” for breath-acetone measurements as a result of technical problems of sampling and analysis. In this mini-review, we update the current status of our development of a laser-based breath acetone analyzer toward real-time, one-line diabetic screening and a point-of-care instrument for diabetic management. An integrated standalone breath acetone analyzer based on the cavity ringdown spectroscopy technique has been developed. The instrument was validated by using the certificated gas chromatography-mass spectrometry. The linear fittings suggest that the obtained acetone concentrations via both methods are consistent. Breath samples from each individual subject under various conditions in total, 1257 breath samples were taken from 22 Type 1 diabetic (T1D) patients, 312 Type 2 diabetic (T2D) patients, which is one of the largest numbers of T2D subjects ever used in a single study, and 52 non-diabetic healthy subjects. Simultaneous blood glucose (BG) levels were also tested using a standard diabetic management BG meter. The mean breath acetone concentrations were determined to be 4.9 ± 16 ppm (22 T1D), and 1.5 ± 1.3 ppm (312 T2D), which are about 4.5 and 1.4 times of the one in the 42 non-diabetic healthy subjects, 1.1 ± 0.5 ppm, respectively. A preliminary quantitative correlation (R = 0.56, p < 0.05) between the mean individual breath acetone concentration and the mean individual BG levels does exist in 20 T1D subjects with no ketoacidosis. No direct correlation is observed in T1D subjects, T2D subjects, and healthy subjects. The results from a relatively large number of subjects tested indicate that an elevated mean breath acetone concentration exists in diabetic patients in general. Although many physiological parameters affect breath acetone, under a specifically controlled condition fast (<1 min) and portable breath acetone measurement can be used for screening abnormal metabolic status including diabetes, for point-of-care monitoring status of ketone bodies which have the signature smell of breath acetone, and for breath acetone related clinical studies requiring a large number of tests.
Over 90% of diabetic patients have Type 2 diabetes. Although an elevated mean breath acetone concentration has been found to exist in Type 1 diabetes (T1D), information on breath acetone in Type 2 diabetes (T2D) has yet to be obtained. In this study, we first used gas chromatography-mass spectrometry (GC-MS) to validate a ringdown breath-acetone analyzer based on the cavity-ringdown-spectroscopy technique, through comparing breath acetone concentrations in the range 0.5-2.5 ppm measured using both methods. The linear fitting of R = 0.99 suggests that the acetone concentrations obtained using both methods are consistent with a largest standard deviation of ±0.4 ppm in the lowest concentration of the range. Next, 620 breath samples from 149 T2D patients and 42 healthy subjects were collected and tested using the breath analyzer. Four breath samples were taken from each subject under each of four different conditions: fasting, 2 h post-breakfast, 2 h post-lunch, and 2 h post-dinner. Simultaneous blood glucose levels were also measured using a standard diabetic-management blood-glucose meter. For the 149 T2D subjects, their exhaled breath acetone concentrations ranged from 0.1 to 19.8 ppm; four different ranges of breath acetone concentration, 0.1-19.8, 0.1-7.1, 0.1-6.3, and 0.1-9.5 ppm, were obtained for the subjects under the four different conditions, respectively. For the 42 healthy subjects, their breath acetone concentration ranged from 0.1 to 2.6 ppm; four different ranges of breath acetone concentration, 0.3-2.6, 0.1-2.6, 0.1-1.7, and 0.3-1.6 ppm, were obtained for the four different conditions. The mean breath acetone concentration of the 149 T2D subjects was determined to be 1.5 ± 1.5 ppm, which was 1.5 times that of 1.0 ± 0.6 ppm for the 42 healthy subjects. No correlation was found between the breath acetone concentration and the blood glucose level of the T2D subjects and the healthy volunteers. This study using a relatively large number of subjects provides new data regarding breath acetone in diabetes (T1D and T2D) and suggests that an elevated mean breath acetone concentration also exists in T2D.
We report for the first time a study of breath acetone and its correlations with blood glucose (BG) and blood β-hydroxybutyrate (BHB) using an animal model of rats.
A laser-locked cavity ring-down spectrometer employing an analog detection scheme Review of Scientific Instruments 71, 347 (2000) Breath analysis is a promising new technique for nonintrusive disease diagnosis and metabolic status monitoring. One challenging issue in using a breath biomarker for potential particular disease screening is to find a quantitative relationship between the concentration of the breath biomarker and clinical diagnostic parameters of the specific disease. In order to address this issue, we need a new instrument that is capable of conducting real-time, online breath analysis with high data throughput, so that a large scale of clinical test (more subjects) can be achieved in a short period of time. In this work, we report a fully integrated, standalone, portable analyzer based on the cavity ringdown spectroscopy technique for near-real time, online breath acetone measurements. The performance of the portable analyzer in measurements of breath acetone was interrogated and validated by using the certificated gas chromatography-mass spectrometry. The results show that this new analyzer is useful for reliable online (online introduction of a breath sample without pretreatment) breath acetone analysis with high sensitivity (57 ppb) and high data throughput (one data per second). Subsequently, the validated breath analyzer was employed for acetone measurements in 119 human subjects under various situations. The instrument design, packaging, specifications, and future improvements were also described. From an optical ringdown cavity operated by the lab-set electronics reported previously to this fully integrated standalone new instrument, we have enabled a new scientific tool suited for large scales of breath acetone analysis and created an instrument platform that can even be adopted for study of other breath biomarkers by using different lasers and ringdown mirrors covering corresponding spectral fingerprints. C 2015 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.[http://dx
For the past two decades, high-frequency oscillations (HFOs) have been enthusiastically studied by the epilepsy community. Emerging evidence shows that HFOs harbour great promise to delineate epileptogenic brain areas and possibly predict the likelihood of seizures. Investigations into HFOs in clinical epilepsy have advanced from small retrospective studies relying on visual identification and correlation analysis to larger prospective assessments using automatic detection and prediction strategies. While most studies have yielded promising results, some have revealed significant obstacles to clinical application of HFOs, thus raising debate about the reliability and practicality of HFOs as clinical biomarkers. In this review, we give an overview of the current state of HFO research and pinpoint the conceptual and methodological issues that have hampered HFO translation. We highlight recent insights gained from long-term data, high-density recordings and multicentre collaborations, and discuss the open questions that need to be addressed in future research.
Objective:To determine the utility of high-frequency activity (HFA) and epileptiform spikes as biomarkers for epilepsy, we examined the variability in their rates and locations using long-term ambulatory intracranial EEG (iEEG) recordings.Methods:This study used continuous iEEG recordings obtained over an average of 1.4 years from 15 patients with drug-resistant focal epilepsy. HFA was defined as 80-170 Hz events with amplitudes clearly larger than the background, which was automatically detected using a custom algorithm. The automatically detected HFA was compared with visually annotated high-frequency oscillations (HFOs). The variations of HFA rates were compared with spikes and seizures on patient-specific and electrode-specific bases.Results:HFA included manually annotated HFOs and high-amplitude events occurring in the 80-170 Hz range without observable oscillatory behavior. HFA and spike rates had high amounts of intra- and inter-patient variability. Rates of HFA and spikes had large variability after electrode implantation in most of the patients. Locations of HFA and/or spikes varied up to weeks in more than one-third of the patients. Both HFA and spike rates showed strong circadian rhythms in all patients and some also showed multiday cycles. Furthermore, the circadian patterns of HFA and spike rates had patient-specific correlations with seizures, which tended to vary across electrodes.Conclusions:Analysis of HFA and epileptiform spikes should consider post-implantation variability. HFA and epileptiform spikes, like seizures, show circadian rhythms. However, the circadian profiles can vary spatially within patients and their correlations to seizures are patient-specific.
Text word count: 3685; abstract word count: 245; title character count: 93; number of references: 47; number of tables and figures: 7. There are supplementary tables and figures for the manuscript. AbstractObjective: To assess the variability in the rates and locations of high-frequency activity (HFA) and epileptiform spikes after electrode implantation, and to examine the long-term patterns of HFA using ambulatory intracranial EEG (iEEG) recordings.Methods: Continuous iEEG recordings obtained over an average of 1.4 years from 15 patients with drug-resistant focal epilepsy were used in this study. HFA was defined as high-frequency events with amplitudes clearly larger than the background, which was automatically detected using a custom algorithm. High-frequency oscillations (HFOs) were also visually annotated by three neurologists in randomly sampled segments of the total data. The automatically detected HFA was compared with the visually marked HFOs. The variations of HFA rates were compared with spikes and seizures on patient-specific and electrode-specific bases.Results: HFA was a more general event that encompassed HFOs manually annotated by different reviewers. HFA and spike rates had high amounts of intra-and inter-patient variability.The rates and locations of HFA and spikes took up to weeks to stabilize after electrode implantation in some patients. Both HFA and spike rates showed strong circadian rhythms in all patients and some also showed multiday cycles. Furthermore, the circadian patterns of HFA and spike rates had patient-specific correlations with seizures, which tended to vary across electrodes. Conclusions: Analysis of HFA and epileptiform spikes should account for post-implantation variability. Like seizures, HFA and epileptiform spikes show circadian rhythms. However, the circadian profiles can vary spatially within patients and their correlations to seizures are patient-specific.Glossary 3, Chen EZ = epileptogenic zone; HFA = high-frequency activity; HFO = high-frequency oscillation; iEEG = intracranial EEG; SOZ = seizure onset zone. 4, Chen
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