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Identification and Quantification of Jaundice by Trans-Conjunctiva Optical Imaging Using a Human Brain-like Algorithm: A Cross-Sectional Study

Jaundice is caused by excess circulating bilirubin, known as hyperbilirubinemia. This symptom is sometimes caused by a critical hepatobiliary disorder, and is generally identified as yellowish sclera when bilirubin levels increase more than 3 mg/dL. It is difficult to identify jaundice accurately, e...

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Autores principales: Kihara, Takuya, Sugihara, Takaaki, Ikeda, Suguru, Matsuki, Yukako, Koda, Hiroki, Onoyama, Takumi, Takata, Tomoaki, Nagahara, Takakazu, Isomoto, Hajime
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10217534/
https://www.ncbi.nlm.nih.gov/pubmed/37238251
http://dx.doi.org/10.3390/diagnostics13101767
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author Kihara, Takuya
Sugihara, Takaaki
Ikeda, Suguru
Matsuki, Yukako
Koda, Hiroki
Onoyama, Takumi
Takata, Tomoaki
Nagahara, Takakazu
Isomoto, Hajime
author_facet Kihara, Takuya
Sugihara, Takaaki
Ikeda, Suguru
Matsuki, Yukako
Koda, Hiroki
Onoyama, Takumi
Takata, Tomoaki
Nagahara, Takakazu
Isomoto, Hajime
author_sort Kihara, Takuya
collection PubMed
description Jaundice is caused by excess circulating bilirubin, known as hyperbilirubinemia. This symptom is sometimes caused by a critical hepatobiliary disorder, and is generally identified as yellowish sclera when bilirubin levels increase more than 3 mg/dL. It is difficult to identify jaundice accurately, especially via telemedicine. This study aimed to identify and quantify jaundice by trans-conjunctiva optical imaging. Patients with jaundice (total bilirubin ≥3 mg/dL) and normal control subjects (total bilirubin <3 mg/dL) were prospectively enrolled from June 2021 to July 2022. We took bilateral conjunctiva imaging with a built-in camera on a smartphone (1st generation iPhone SE) under normal white light conditions without any restrictions. We processed the images using an Algorithm Based on Human Brain (ABHB) (Zeta Bridge Corporation, Tokyo, Japan) and converted them into a hue degree of Hue Saturation Lightness (HSL) color space. A total of 26 patients with jaundice (9.57 ± 7.11 mg/dL) and 25 control subjects (0.77 ± 0.35 mg/dL) were enrolled in this study. The causes of jaundice among the 18 male and 8 female subjects (median age 61 yrs.) included hepatobiliary cancer (n = 10), chronic hepatitis or cirrhosis (n = 6), pancreatic cancer (n = 4), acute liver failure (n = 2), cholelithiasis or cholangitis (n = 2), acute pancreatitis (n = 1), and Gilbert’s syndrome (n = 1). The maximum hue degree (MHD) optimal cutoff to identify jaundice was 40.8 (sensitivity 81% and specificity 80%), and the AUROC was 0.842. The MHD was moderately correlated to total serum bilirubin (TSB) levels (rS = 0.528, p < 0.001). TSB level (≥5 mg/dL) can be estimated by the formula 21.1603 − 0.7371 × [Formula: see text]. In conclusion, the ABHB-based MHD of conjunctiva imaging identified jaundice using an ordinary smartphone without any specific attachments and deep learning. This novel technology could be a helpful diagnostic tool in telemedicine or self-medication.
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spelling pubmed-102175342023-05-27 Identification and Quantification of Jaundice by Trans-Conjunctiva Optical Imaging Using a Human Brain-like Algorithm: A Cross-Sectional Study Kihara, Takuya Sugihara, Takaaki Ikeda, Suguru Matsuki, Yukako Koda, Hiroki Onoyama, Takumi Takata, Tomoaki Nagahara, Takakazu Isomoto, Hajime Diagnostics (Basel) Communication Jaundice is caused by excess circulating bilirubin, known as hyperbilirubinemia. This symptom is sometimes caused by a critical hepatobiliary disorder, and is generally identified as yellowish sclera when bilirubin levels increase more than 3 mg/dL. It is difficult to identify jaundice accurately, especially via telemedicine. This study aimed to identify and quantify jaundice by trans-conjunctiva optical imaging. Patients with jaundice (total bilirubin ≥3 mg/dL) and normal control subjects (total bilirubin <3 mg/dL) were prospectively enrolled from June 2021 to July 2022. We took bilateral conjunctiva imaging with a built-in camera on a smartphone (1st generation iPhone SE) under normal white light conditions without any restrictions. We processed the images using an Algorithm Based on Human Brain (ABHB) (Zeta Bridge Corporation, Tokyo, Japan) and converted them into a hue degree of Hue Saturation Lightness (HSL) color space. A total of 26 patients with jaundice (9.57 ± 7.11 mg/dL) and 25 control subjects (0.77 ± 0.35 mg/dL) were enrolled in this study. The causes of jaundice among the 18 male and 8 female subjects (median age 61 yrs.) included hepatobiliary cancer (n = 10), chronic hepatitis or cirrhosis (n = 6), pancreatic cancer (n = 4), acute liver failure (n = 2), cholelithiasis or cholangitis (n = 2), acute pancreatitis (n = 1), and Gilbert’s syndrome (n = 1). The maximum hue degree (MHD) optimal cutoff to identify jaundice was 40.8 (sensitivity 81% and specificity 80%), and the AUROC was 0.842. The MHD was moderately correlated to total serum bilirubin (TSB) levels (rS = 0.528, p < 0.001). TSB level (≥5 mg/dL) can be estimated by the formula 21.1603 − 0.7371 × [Formula: see text]. In conclusion, the ABHB-based MHD of conjunctiva imaging identified jaundice using an ordinary smartphone without any specific attachments and deep learning. This novel technology could be a helpful diagnostic tool in telemedicine or self-medication. MDPI 2023-05-17 /pmc/articles/PMC10217534/ /pubmed/37238251 http://dx.doi.org/10.3390/diagnostics13101767 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Communication
Kihara, Takuya
Sugihara, Takaaki
Ikeda, Suguru
Matsuki, Yukako
Koda, Hiroki
Onoyama, Takumi
Takata, Tomoaki
Nagahara, Takakazu
Isomoto, Hajime
Identification and Quantification of Jaundice by Trans-Conjunctiva Optical Imaging Using a Human Brain-like Algorithm: A Cross-Sectional Study
title Identification and Quantification of Jaundice by Trans-Conjunctiva Optical Imaging Using a Human Brain-like Algorithm: A Cross-Sectional Study
title_full Identification and Quantification of Jaundice by Trans-Conjunctiva Optical Imaging Using a Human Brain-like Algorithm: A Cross-Sectional Study
title_fullStr Identification and Quantification of Jaundice by Trans-Conjunctiva Optical Imaging Using a Human Brain-like Algorithm: A Cross-Sectional Study
title_full_unstemmed Identification and Quantification of Jaundice by Trans-Conjunctiva Optical Imaging Using a Human Brain-like Algorithm: A Cross-Sectional Study
title_short Identification and Quantification of Jaundice by Trans-Conjunctiva Optical Imaging Using a Human Brain-like Algorithm: A Cross-Sectional Study
title_sort identification and quantification of jaundice by trans-conjunctiva optical imaging using a human brain-like algorithm: a cross-sectional study
topic Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10217534/
https://www.ncbi.nlm.nih.gov/pubmed/37238251
http://dx.doi.org/10.3390/diagnostics13101767
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