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FAIMS analysis of urine gaseous headspace is capable of differentiating ovarian cancer

Research output: Contribution to journalArticleScientificpeer-review

Details

Original languageEnglish
Pages (from-to)519-524
Number of pages6
JournalGynecologic Oncology
Volume151
Issue number3
Early online date2018
DOIs
Publication statusPublished - Dec 2018
Publication typeA1 Journal article-refereed

Abstract

Aim: We hypothesized that field asymmetric waveform ion mobility spectrometry (FAIMS) as a novel artificial olfactory technology could differentiate urine of women with malignant ovarian tumors from controls and women with benign tumors, based on previous findings on the ability of canine olfactory system to “smell” cancer. Patients and methods: Preoperative urine samples from 51 women with ovarian tumors, both benign and malignant, and from 18 women with genital prolapse, as controls, were collected. The samples were analyzed by FAIMS device. Data analysis was processed by quadratic data analysis (QDA) and linear discriminant analysis (LDA), and cross-validated using 10-fold cross-validation. Results: Thirty-three women had malignant ovarian tumors, of which 18 were high-grade cancers. FAIMS distinguished controls from malignancies with the accuracy of 81.3% (sensitivity 91.2% and specificity 63.1%), and benign tumors from malignancies with the accuracy of 77.3% (sensitivity 91.5% and specificity 51.4%). Moreover, low grade tumors were also separated from high grade cancers and benign ovarian tumors with accuracies of 88.7% (sensitivity 87.8% and specificity 89.6%) and 83.9% (sensitivity 73.1% and specificity 92.9%), respectively. Conclusions: This proof of concept-study indicates that the FAIMS from urine has potential to discriminate malignant ovarian tumors from no tumor-bearing controls and benign tumors.

ASJC Scopus subject areas

Keywords

  • FAIMS, Ovarian cancer, Ovarian neoplasm, Owlstone Lonestar, Urine, VOC

Publication forum classification

Field of science, Statistics Finland