Detection of Airway Colonization by Aspergillus fumigatus by Use of Electronic Nose Technology in Patients with Cystic Fibrosis

Abstract

Currently, there is no noninvasive test that can reliably diagnose early invasive pulmonary aspergillosis (IA). An electronic nose (eNose) can discriminate various lung diseases through an analysis of exhaled volatile organic compounds. We recently published a proof-of-principle study showing that patients with prolonged chemotherapy-induced neutropenia and IA have a distinct exhaled breath profile (or breathprint) that can be discriminated with an eNose. An eNose is cheap and noninvasive, and it yields results within minutes. We determined whether Aspergillus fumigatus colonization may also be detected with an eNose in cystic fibrosis (CF) patients. Exhaled breath samples of 27 CF patients were analyzed with a Cyranose 320. Culture of sputum samples defined the A. fumigatus colonization status. eNose data were classified using canonical discriminant analysis after principal component reduction. Our primary outcome was cross-validated accuracy, defined as the percentage of correctly classified subjects using the leave-one-out method. The P value was calculated by the generation of 100,000 random alternative classifications. Nine of the 27 subjects were colonized by A. fumigatus. In total, 3 subjects were misclassified, resulting in a cross-validated accuracy of the Cyranose detecting IA of 89% (P = 0.004; sensitivity, 78%; specificity, 94%). Receiver operating characteristic (ROC) curve analysis showed an area under the curve (AUC) of 0.89. The results indicate that A. fumigatus colonization leads to a distinctive breathprint in CF patients. The present proof-of-concept data merit external validation and monitoring studies.

FIG 1

Breathprints of CF patients with and without A. fumigatus colonization, in a one-dimensional “jittered” canonical discriminant analysis plot. Squares with a cross represent subjects that were misclassified in the cross-validation. Box-and-whisker plots (with the median shown as a line through the box, the first and third quartiles shown as the lower and upper edges of the box, respectively, and the 95% confidence interval of the median shown as whiskers) are superimposed.

FIG 2

Receiver operating characteristic (ROC) curves showing the true-positive and false-positive rates in detecting A. fumigatus colonization with an eNose as a function of the cutoff value. Dashed line, ROC curve of the non-cross-validated measurements; solid line, the ROC curve of the cross-validated measurements.

FIG 3

Histogram of the cross-validated accuracies produced by the random simulation.

FIG 4

Spider graph of the raw eNose data showing a circular representation of the 32 sensor signals from all 27 samples, zoomed in to demonstrate between-sample differences. As the sensors are exposed to the breath sample, the electrical resistance over the sensors changes. On the axes of the spider graph, the quotient (calculated as [R_max − R_min]/[R_min]) is displayed (R_max, greatest amount of resistance; R_min, smallest amount of resistance). The data have not been normalized.