Detection of Ovarian Cancer through Exhaled Breath by Electronic Nose: A Prospective Study.

ABSTRACT: Diagnostic methods for the early identification of ovarian cancer (OC) represent an unmet clinical need, as no reliable diagnostic tools are available. Here, we tested the feasibility of electronic nose (e-nose), composed of ten metal oxide semiconductor (MOS) sensors, as a diagnostic tool for OC detection. Women with suspected ovarian masses and healthy subjects had volatile organic compounds analysis of the exhaled breath using e-nose. E-nose analysis was performed on breath samples collected from 251 women divided into three groups: 86 OC cases, 51 benign masses, and 114 controls. Data collected were analyzed by Principal Component Analysis (PCA) and K-Nearest Neighbors' algorithm (K-NN). A first 1-K-NN (cases vs. controls) model has been developed to discriminate between OC cases and c

SUBMITTER: Raspagliesi F 

PROVIDER: S-EPMC7565069 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature