FAIMS analysis of urine gaseous headspace is capable of differentiating ovarian cancer
Research output: Contribution to journal › Article › Scientific › peer-review
|Number of pages||6|
|Early online date||2018|
|Publication status||Published - Dec 2018|
|Publication type||A1 Journal article-refereed|
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.