Potentiometric multisensor system as a possible simple tool for non-invasive prostate cancer diagnostics through urine analysis

Svetlana Solovieva, Mikhail Karnaukh, Vitaly Panchuk, Evgeny Andreev, Liudmila Kartsova, Elena Bessonova, Andrey Legin, Ping Wang, Hao Wan, Igor Jahatspanian, Dmitry Kirsanov

Research output

7 Citations (Scopus)

Abstract

We report a simple potentiometric multisensor system for distinguishing the urine samples from the patients with diagnosed prostate cancer and from healthy control group. The sensors of the system are sensitive towards variety of cationic and anionic species in urine, as well as to the presence of RedOx pairs. The response of the system represents a complex chemical fingerprint of urine sample that can be related with patient status through multivariate modelling. 89 urine samples were studied (43 from cancer patients confirmed by prostatic puncture biopsy and 46 from healthy control group) and variety of multivariate classification techniques was applied to the potentiometric data. The best results were obtained with logistic regression model yielding 100% sensitivity and 93% specificity in the independent test set of samples.

Original languageEnglish
Pages (from-to)42-47
Number of pages6
JournalSensors and Actuators, B: Chemical
Volume289
DOIs
Publication statusPublished - 15 Jun 2019

Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Instrumentation
  • Condensed Matter Physics
  • Surfaces, Coatings and Films
  • Metals and Alloys
  • Electrical and Electronic Engineering
  • Materials Chemistry

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