Electronic nose to distinguish bladder cancer by urinary odour feature: A pilot study

Matsumoto, Kazumasa; Murakami, Yousuke; Shimizu, Yuriko; Hirayama, Takahiro; Ishikawa, Wataru

doi:10.3233/cbm-190466

Cited by 14 publications

(9 citation statements)

References 29 publications

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“…The other studies of urine-based diagnoses BLC. Heers (cyranose 320), Bassi (cyranose 320), Matsumoto (cyranose 320), Zhu (optical sensor arrays), Issaq (HPLC-MS), Cauchi (GC–MS), Pasikanti (GC-ToF-MS), Zhou (GC–MS), Weber (GC), and Khalid (GC) …”

Section: Resultsmentioning

confidence: 99%

“…In comparison with GC–MS, the electronic nose (e-nose) that mimics the human olfactory organ in the recognition of different smells is cheaper and faster, and also, the potential for portability is much higher than for GC–MS. However, as with most artificial olfaction systems, the e-nose that was used to detect BLC from the urine headspace − only recognized urinary VOCs with a sensitivity of ca. 70% and accuracy of ca.…”

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confidence: 99%

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Artificially Intelligent Olfaction for Fast and Noninvasive Diagnosis of Bladder Cancer from Urine

et al. 2022

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Globally, bladder cancer (BLC) is one of the most common cancers and has a high recurrence and mortality rate. Current clinical diagnostic approaches are either invasive or inaccurate. Here, we report on a cost-efficient, artificially intelligent chemiresistive sensor array made of polyaniline (PANI) derivatives that can noninvasively diagnose BLC at an early stage and maintain postoperative surveillance through ″smelling″ clinical urine samples at room temperature. In clinical trials, 18 healthy controls and 76 BLC patients (60 and 16 at early and advanced stages, respectively) are assessed by the artificial olfactory system. With the assistance of a support vector machine (SVM), very high sensitivity and accuracy from healthy controls are achieved, exceeding those obtained by the current techniques in practice. In addition, the recurrences of both early and advanced stages are diagnosed well, with the effect of confounding factors on the performance of the artificial olfactory system found to have a negligible influence on the diagnostic performance. Overall, this study contributes a novel, noninvasive, easy-to-use, inexpensive, real-time, accurate method for urine disease diagnosis, which can be useful for personalized care/diagnosis and postoperative surveillance, resulting in saving more lives.

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Section: Resultsmentioning

confidence: 99%

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confidence: 99%

Artificially Intelligent Olfaction for Fast and Noninvasive Diagnosis of Bladder Cancer from Urine

et al. 2022

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“…They reported that the angle of the two sensors (θ) depended on the kinds of chemical substances, thus defining θ as the feature of odor. The resulting diagnostic sensitivity for bladder cancer was 61.4%, and specificity was 52.8%: the authors concluded that this non-invasive instrument is useful for distinguishing bladder cancer from other benign conditions [27].…”

Section: Discussionmentioning

confidence: 97%

Improved Non-Invasive Diagnosis of Bladder Cancer with an Electronic Nose: A Large Pilot Study

Bassi

Palermo

Salmaso

et al. 2021

JCM

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Background: Bladder cancer (BCa) emits specific volatile organic compounds (VOCs) in the urine headspace that can be detected by an electronic nose. The diagnostic performance of an electronic nose in detecting BCa was investigated in a pilot study. Methods: A prospective, single-center, controlled, non-randomized, phase 2 study was carried out on 198 consecutive subjects (102 with proven BCa, 96 controls). Urine samples were evaluated with an electronic nose provided with 32 volatile gas analyzer sensors. The tests were repeated at least two times per sample. Accuracy, sensitivity, specificity, and variability were evaluated using mainly the non-parametric combination method, permutation tests, and discriminant analysis classification. Results: Statistically significant differences between BCa patients and controls were reported by 28 (87.5%) of the 32 sensors. The overall discriminatory power, sensitivity, and specificity were 78.8%, 74.1%, and 76%, respectively; 13/96 (13.5%) controls and 29/102 (28.4%) BCa patients were misclassified as false positive and false negative, respectively. Where the most efficient sensors were selected, the sensitivity and specificity increased up to 91.1% (72.5–100) and 89.1% (81–95.8), respectively. None of the tumor characteristics represented independent predictors of device responsiveness. Conclusions: The electronic nose might represent a potentially reliable, quick, accurate, and cost-effective tool for non-invasive BCa diagnosis.

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“…Later, a study with a similar purpose used a commercial eNose model, made of two angled sensors. 32 The angle between sensors changed according to the chemical substances. This study contemplated 36 patients with untreated bladder cancer, 29 with urolithiasis, and 10 with urinary tract infection, and 27 were healthy.…”

Section: Discussionmentioning

confidence: 99%

Diagnosis of pathological conditions through electronic nose analysis of urine samples: a systematic review and meta-analysis

Afonso

Farraia

Vieira

et al. 2022

Porto Biomedical Journal

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Electronic nose to distinguish bladder cancer by urinary odour feature: A pilot study

Cited by 14 publications

References 29 publications

Artificially Intelligent Olfaction for Fast and Noninvasive Diagnosis of Bladder Cancer from Urine

Artificially Intelligent Olfaction for Fast and Noninvasive Diagnosis of Bladder Cancer from Urine

Improved Non-Invasive Diagnosis of Bladder Cancer with an Electronic Nose: A Large Pilot Study

Diagnosis of pathological conditions through electronic nose analysis of urine samples: a systematic review and meta-analysis

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