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A Multicenter Pilot Study of Biliary Atresia Screening Using Digital Stool Color Imaging.
Waitayagitgumjon, Kannamon; Poocharoen, Wannisa; Trirongjitmoah, Suchin; Treeprapin, Kriengsak; Suttiwongsing, Arada; Wirifai, Thetiya; Trirongchitmoh, Chira; Tangkabuanbutr, Pitiporn.
Afiliação
  • Waitayagitgumjon K; Department of Surgery, Bhumibol Adulyadej Hospital, Royal Thai Air Force, Bangkok, Thailand.
  • Poocharoen W; Department of Surgery, Queen Sirikit National Institute of Child Health, Ratchathewi, Bangkok, Thailand.
  • Trirongjitmoah S; Department of Surgery, College of Medicine, Rangsit University, Bangkok, Thailand.
  • Treeprapin K; Department of Electrical and Electronics Engineering, Faculty of Engineering, Ubon Ratchathani University, Ubon Ratchathani, Thailand.
  • Suttiwongsing A; Department of Mathematics, Statistics and Computer, Faculty of Science, Ubon Ratchathani University, Ubon Ratchathani, Thailand.
  • Wirifai T; Department of Surgery, Chiangrai Prachanukroh Hospital, Chiang Rai, Thailand.
  • Trirongchitmoh C; Department of Surgery, Khon Kaen Hospital, Khon Kaen, Thailand.
  • Tangkabuanbutr P; Department of Surgery, Sunpasitthiprasong Hospital, Ubon Ratchathani, Thailand.
Pediatr Gastroenterol Hepatol Nutr ; 27(3): 168-175, 2024 May.
Article em En | MEDLINE | ID: mdl-38818277
ABSTRACT

Purpose:

The presence of alcoholic stool in biliary atresia (BA) patients is the basis of a stool color card (SCC), a screening tool that has led to more patients receiving Kasai portoenterostomy earlier. This study aimed to evaluate the color image processing of stool images captured using smartphones. We propose that measuring digital color parameters is a more objective method for identifying BA stools and may improve the sensitivity of BA screening.

Methods:

A prospective study was conducted in five hospitals in Thailand between October 1, 2020, and December 31, 2021. Stools from infants presenting with jaundice, acholic stool, or dark-colored urine were photographed. Digital image color analysis was performed, and software was developed based on the color on the original SCC. Sensitivity and specificity for predicting BA stools were compared between the SCC and the software.

Results:

Of 33 infants eligible for data collection, 19 were diagnosed with BA. Saturation and blue were two potential digital color parameters used to differentiate BA stools. The receiver operating characteristic curve was used to determine the optimum cutoff point of both values, and when saturation ≤56 or blue ≥61 was set as a threshold for detecting BA stool, high accuracy was achieved at 81.8% and 78.8%, respectively.

Conclusion:

Digital image processing is a promising technology. With appropriate cutoff values of saturation in hue, saturation, value and blue in red, green, blue color models, BA stools can be identified, and equivocal-colored stools of non-BA patients can be differentiated with acceptable accuracy in infants presenting with jaundice.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article