Evaluation of a gas sensor array and pattern recognition for the identification of bladder cancer from urine headspace

Abstract

(2011). Evaluation of a gas sensor array and pattern recognition for the identification of bladder cancer from urine headspace. Analyst, 136 (2) Previous studies have indicated that volatile compounds specific to bladder cancer may exist in urine headspace, raising the possibility that headspace analysis could be used for diagnosis of this particular cancer. In this paper, we evaluate the use of a commercially available gas sensor array coupled with a specifically designed pattern recognition algorithm for this purpose. The 10 best diagnostic performance that we were able to obtain with independent test data provided by healthy volunteers and bladder cancer patients was 70% overall accuracy (70% sensitivity and 70% specificity). When the data of patients suffering from other non-cancerous urological diseases were added to those of the healthy controls, the classification accuracy fell to 65% with 60% sensitivity and 67% specificity. While this is not sufficient for a diagnostic test, it is significantly better than random chance, leading us to conclude that there is useful information in the urine headspace but that a more informative analytical technique, 15 such as mass spectrometry, is required if this is to be exploited fully.

Performance Evaluation and Online Realization of Data-driven Normalization Methods Used in LC/MS based Untargeted Metabolomics Analysis

“…This method makes all metabolites of equal importance, but analytical errors may be amplified due to dilution effects21. Auto scaling has been used to improve the diagnosis of bladder cancer using gas sensor arrays63 and to identify urinary nucleoside markers from urogenital cancer patients64.…”

“…Range Scaling scales the metabolic signals by the variation of biological responses63. A disadvantage of this method lies in a limited number (usually only 2) of values used to describe the variation unlike other scaling methods taking all measurements into account using the standard deviation, which makes this algorithm relatively sensitive to outliers12.…”

Application and Uses of Electronic Noses for Clinical Diagnosis on Urine Samples: A Review

“…The following sections provide an overview of the state-of-the-art of the application of electronic noses for the analysis of urine samples by classifying those applications depending on the target investigated, thus including the discrimination of bacteria cultures (Section 2.2) [49,50,51,52], or the detection of urinary tract infections (Section 2.3) [53,54,55,56,57,58], cancer diseases (Section 2.4) [59,60,61,62,63,64,65,66], diabetes (Section 2.5) [67,68], kidney diseases (Section 2.6) [69,74], bowel diseases (Section 2.7) [70,71,72] and exposure to toxic agents (Section 2.8) [73] (reference [74] wasn’t included in Table 1 since it refers to breath analysis).…”

“…Weber et al [60], in order to provide a more sensitive, rapid and convenient diagnosis system, studied the interaction between the VOCs connected to transitional cell carcinoma (TCC) of bladder and a gas sensor array composed of 12 metal-oxide sensor (MOS), 10 metal-oxide-semiconductor field-effect transistor (MOSFET), a capacitance-based humidity sensor and an infrared-based CO 2 sensor. Urine samples were collected from patients with urological pathologies (not only with cancer disease) and healthy subjects, and divided into four different groups, each containing every type of sample.…”

Re-Centering Multispecies Practices

“…The work of the dogs has thus informed research into the development of 'electronic noses' for the early diagnose of cancer (e.g. using a gas sensor array coupled with a pattern recognition algorithm [28]). At the moment, the success rate of these devices (65%) is still significantly lower than the success rate of the dogs, but a better understanding of how the dogs work and what they find could significantly contribute to the improvement of such sensors.…”