Literature DB >> 32176623

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

Kazumasa Matsumoto, Yasukiyo Murakami, Yuriko Shimizu, Takahiro Hirayama, Wataru Ishikawa, Masatsugu Iwamura.   

Abstract

BACKGROUND: No study has yet investigated the use of electronic nose (eNose) technology to reveal pattern recognition of urological diseases, including bladder cancer.
OBJECTIVE: We sought to determine the diagnostic performance of the eNose in recognizing urinary odour in patients with bladder cancer.
METHODS: The eNose is a commercially available model equipped with two sensors. The angle of the two sensors (θ) depends on the kinds of chemical substances, thus defining θ as the feature of odour. Quantity of odour is the number of θ detected during a measurement. Urine samples were from 36 untreated patients with bladder cancer, 29 with urolithiasis, 10 with urinary tract infection (UTI), and 27 healthy volunteers.
RESULTS: Based on ROC analysis of the quantity in patients with bladder cancer, an optimal cut-off value for θ of 49, 48, and 55 was applied to compare with samples from the healthy volunteer, urolithiasis and UTI groups, respectively. There were significantly differences between bladder cancer and the other conditions using these specific points (p< 0.0001, respectively). The resulting diagnostic sensitivity was 61.4%, 45.6%, and 60.8%, and specificity was 52.8%, 68.4%, and 90.2%, respectively. The AUC for bladder cancer was 0.565, 0.548, and 0.909, respectively.
CONCLUSION: The eNose is a small, portable, rapid, low cost, and noninvasive instrument for distinguishing bladder cancer from other benign conditions.

Entities:  

Keywords:  Bladder cancer; electronic nose; odour; urine

Mesh:

Year:  2020        PMID: 32176623     DOI: 10.3233/CBM-190466

Source DB:  PubMed          Journal:  Cancer Biomark        ISSN: 1574-0153            Impact factor:   4.388


  1 in total

1.  Detection of Lethal Bronzing Disease in Cabbage Palms (Sabal palmetto) Using a Low-Cost Electronic Nose.

Authors:  Martin J Oates; Nawaf Abu-Khalaf; Carlos Molina-Cabrera; Antonio Ruiz-Canales; Jose Ramos; Brian W Bahder
Journal:  Biosensors (Basel)       Date:  2020-11-23
  1 in total

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