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Electronic Nose Technology for Detection of Invasive Pulmonary Aspergillosis in Prolonged Chemotherapy-Induced Neutropenia: a Proof-of-Principle Study
Author(s) -
Koen de Heer,
Marc P. van der Schee,
Koos Zwinderman,
Inge A. H. van den Berk,
Caroline E. Visser,
Rien van Oers,
Peter J. Sterk
Publication year - 2013
Publication title -
journal of clinical microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.349
H-Index - 255
eISSN - 1070-633X
pISSN - 0095-1137
DOI - 10.1128/jcm.02838-12
Subject(s) - aspergillosis , neutropenia , electronic nose , medicine , receiver operating characteristic , diagnostic accuracy , exhalation , surgery , chemotherapy , radiology , immunology , biology , neuroscience
Although the high mortality rate of pulmonary invasive aspergillosis (IA) in patients with prolonged chemotherapy-induced neutropenia (PCIN) can be reduced by timely diagnosis, a diagnostic test that reliably detects IA at an early stage is lacking. We hypothesized that an electronic nose (eNose) could fulfill this need. An eNose can discriminate various lung diseases through the analysis of exhaled volatile organic compounds (VOCs). An eNose is cheap and noninvasive and yields results within minutes. In a single-center prospective cohort study, we included patients who were treated with chemotherapy expected to result in PCIN. Based on standardized indications, a full diagnostic workup was performed to confirm invasive aspergillosis or to rule it out. Patients with no aspergillosis were considered controls, and patients with probable or proven aspergillosis were considered index cases. Exhaled breath was examined with a Cyranose 320 (Smith Detections, Pasadena, CA). The resulting data were analyzed using principal component reduction. The primary endpoint was cross-validated diagnostic accuracy, defined as the percentage of patients correctly classified using the leave-one-out method. Accuracy was validated by 100,000 random classifications. We included 46 subjects who underwent 16 diagnostic workups, resulting in 6 cases and 5 controls. The cross-validated accuracy of the eNose in diagnosing IA was 90.9% (P = 0.022; sensitivity, 100%; specificity, 83.3%). Receiver operating characteristic analysis showed an area under the curve of 0.93. These preliminary data indicate that PCIN patients with IA have a distinct exhaled VOC profile that can be detected with eNose technology. The diagnostic accuracy of the eNose for invasive aspergillosis warrants validation.

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