Title: | On-Field Test of Tuberculosis Diagnosis through Exhaled Breath Analysis with a Gas Sensor Array |
Author(s): | Ketchanji Mougang YC; Endale Mangamba LM; Capuano R; Ciccacci F; Catini A; Paolesse R; Mbatchou Ngahane HB; Palombi L; Di Natale C; |
Address: | "Department of Electronic Engineering, University of Rome Tor Vergata, via del Politecnico 1, 00133 Roma, Italy. Faculty of Medicine and Pharmaceutical Sciences, University of Douala, Carrefour Ange Raphael, Douala P.O. Box 4035, Cameroon. Center for Respiratory Diseases, Douala Laquintinie Hospital, Avenue du Jamot, Douala P.O. Box 4035, Cameroon. Interdepartmental Centre for Volatilomics 'A D'Amico', University of Rome Tor Vergata, via del Politecnico 1, 00133 Roma, Italy. UniCamillus, Saint Camillus International University of Health and Medical Sciences, 00131 Rome, Italy. Department of Chemical Science and Technology, University of Rome Tor Vergata, via della Ricerca Scientifica, 00133 Rome, Italy. Internal Medicine Service, Douala General Hospital, Douala P.O. Box 4856, Cameroon. Department of Biomedicine and Prevention, University of Rome 'Tor Vergata', Viale Montpellier 1, 00133 Roma, Italy" |
ISSN/ISBN: | 2079-6374 (Electronic) 2079-6374 (Linking) |
Abstract: | "Tuberculosis (TB) is among the more frequent causes of death in many countries. For pulmonary TB, early diagnosis greatly increases the efficiency of therapies. Although highly sensitive tests based on nucleic acid amplification tests (NAATs) and loop-mediated isothermal amplification (TB-LAMP) are available, smear microscopy is still the most widespread diagnostics method in most low-middle-income countries, and the true positive rate of smear microscopy is lower than 65%. Thus, there is a need to increase the performance of low-cost diagnosis. For many years, the use of sensors to analyze the exhaled volatile organic compounds (VOCs) has been proposed as a promising alternative for the diagnosis of several diseases, including tuberculosis. In this paper, the diagnostic properties of an electronic nose (EN) based on sensor technology previously used to identify tuberculosis have been tested on-field in a Cameroon hospital. The EN analyzed the breath of a cohort of subjects including pulmonary TB patients (46), healthy controls (38), and TB suspects (16). Machine learning analysis of the sensor array data allows for the identification of the pulmonary TB group with respect to healthy controls with 88% accuracy, 90.8% sensitivity, 85.7% specificity, and 0.88 AUC. The model trained with TB and healthy controls maintains its performance when it is applied to symptomatic TB suspects with a negative TB-LAMP. These results encourage the investigation of electronic noses as an effective diagnostic method for future inclusion in clinical practice" |
Keywords: | "Humans *Tuberculosis/diagnosis *Tuberculosis, Pulmonary/diagnosis Breath Tests/methods Microscopy Nucleic Acid Amplification Techniques/methods Exhalation Sensitivity and Specificity breath analysis electronic nose tuberculosis (TB) volatile organic compo;" |
Notes: | "MedlineKetchanji Mougang, Yolande Christelle Endale Mangamba, Laurent-Mireille Capuano, Rosamaria Ciccacci, Fausto Catini, Alexandro Paolesse, Roberto Mbatchou Ngahane, Hugo Bertrand Palombi, Leonardo Di Natale, Corrado eng Switzerland 2023/05/26 Biosensors (Basel). 2023 May 22; 13(5):570. doi: 10.3390/bios13050570" |