טכניון מכון טכנולוגי לישראל
הטכניון מכון טכנולוגי לישראל - בית הספר ללימודי מוסמכים  
M.Sc Thesis
M.Sc StudentBassal Rana
SubjectDetection of Chronic Heart Failure by Breath Samples
DepartmentDepartment of Chemical Engineering
Supervisors Professor Hossam Haick
Professor Zaid A. Abassi
Full Thesis textFull thesis text - English Version


Abstract

Cardiovascular diseases account for ~30% of deaths worldwide, including nearly 40% in high-income countries and ~28% in low- and middle-income countries. Nearly any form of heart disease, mainly cardiovascular, may ultimately lead to heart failure (HF). Rapid diagnosis of heart diseases is a part of therapeutic approach and is important to facilitate rapid and efficient treatment. Unfortunately, currently available diagnostic techniques are time consuming and lack of accuracy. A complementary approach that overcomes many constraints of the conventional diagnostic techniques for HF relies on patterns of volatile biomarkers in the exhaled breath.  Some of the volatile substances among the plasma HF biomarkers, or their metabolic products, are transmitted to the alveolar exhaled breath through exchange via the lung. Based on this hypothesis, the presented research is designed to examine whether nanosensors array can detect HF and, also, to differentiate it from healthy controls. Breath samples were collected from normal rats (control) and rats with congestive heart failure (CHF) at different time points of the disease induction. For each rat, BNP blood test and sodium excretion was measured and breath samples were analyzed using an array of cross-reactive nanosensors and Gas-Chromatography/Mass-Spectrometry (GC-MS) in conjugation with pre-concentration techniques to validate the discrimination and to identify the CHF biomarkers. Analysis of the nanosensors array showed that arterio-venous fistula model developed to CHF condition after seven days of the shunt induction. Moreover, an excellent distinction was achieved with the nanosensor array between: (i) CHF and healthy states, and (ii) between compensated and decompensated CHF, with an accuracy of 88% and 71%, respectively. The chemical analysis of the collected exhaled alveolar breath identified several substances most of alkanes that differ in average abundance in breath samples taken from the CHF and healthy controls samples and between compensated and decompensated CHF samples, which could be associated with CHF related biochemical processes. These results suggest that cross-reactive nanosensors analysis may be used in the future for diagnosis, detection, and screening various stages of chronic heart diseases.