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Brown fat detection by infrared thermography—An invaluable research methodology with noteworthy uncertainties confirmed by a mathematical proof

Brown adipose tissue (BAT) represents a pivotal scientific renaissance worthy as a strategy for obesity and diabetes since its re‐discovery in adults over a decade ago. Equally compelling is the adoption of infrared thermography (IRT) in recent times as a precise and viable alternative methodology o...

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Autor principal: Leow, Melvin K. S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9836251/
https://www.ncbi.nlm.nih.gov/pubmed/36379014
http://dx.doi.org/10.1002/edm2.378
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author Leow, Melvin K. S.
author_facet Leow, Melvin K. S.
author_sort Leow, Melvin K. S.
collection PubMed
description Brown adipose tissue (BAT) represents a pivotal scientific renaissance worthy as a strategy for obesity and diabetes since its re‐discovery in adults over a decade ago. Equally compelling is the adoption of infrared thermography (IRT) in recent times as a precise and viable alternative methodology over the ‘gold standard’ PET‐CT scan, given constraints of the latter's high ionizing radiation doses and costs. Unravelling BAT metabolic physiology in live humans has been challenging until recent rigorous validation of IRT against PET. Nevertheless, IRT remains a nascent technique with pitfalls unbeknownst to many researchers. Factors impacting its accuracy merit an in‐depth scientific scrutiny. This article discusses the strengths and pitfalls of IRT as an emergent BAT detection technique and provides a mathematical proof of its limitations that BAT researchers should be cognizant of. Understanding these limitations of IRT can prompt extra efforts to control these uncertainties with greater rigour. In conclusion, this warrants further investigations of improving IRT quality via advanced auto‐segmentation, powerful image processing of thermograms and protocol standardization along the lines of BARCIST 1.0 to minimize errors and enhance the confidence of the global BAT research community in IRT as a robust and reliable BAT research tool.
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spelling pubmed-98362512023-01-18 Brown fat detection by infrared thermography—An invaluable research methodology with noteworthy uncertainties confirmed by a mathematical proof Leow, Melvin K. S. Endocrinol Diabetes Metab Editorial Brown adipose tissue (BAT) represents a pivotal scientific renaissance worthy as a strategy for obesity and diabetes since its re‐discovery in adults over a decade ago. Equally compelling is the adoption of infrared thermography (IRT) in recent times as a precise and viable alternative methodology over the ‘gold standard’ PET‐CT scan, given constraints of the latter's high ionizing radiation doses and costs. Unravelling BAT metabolic physiology in live humans has been challenging until recent rigorous validation of IRT against PET. Nevertheless, IRT remains a nascent technique with pitfalls unbeknownst to many researchers. Factors impacting its accuracy merit an in‐depth scientific scrutiny. This article discusses the strengths and pitfalls of IRT as an emergent BAT detection technique and provides a mathematical proof of its limitations that BAT researchers should be cognizant of. Understanding these limitations of IRT can prompt extra efforts to control these uncertainties with greater rigour. In conclusion, this warrants further investigations of improving IRT quality via advanced auto‐segmentation, powerful image processing of thermograms and protocol standardization along the lines of BARCIST 1.0 to minimize errors and enhance the confidence of the global BAT research community in IRT as a robust and reliable BAT research tool. John Wiley and Sons Inc. 2022-10-31 /pmc/articles/PMC9836251/ /pubmed/36379014 http://dx.doi.org/10.1002/edm2.378 Text en © 2022 The Author. Endocrinology, Diabetes & Metabolism published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Editorial
Leow, Melvin K. S.
Brown fat detection by infrared thermography—An invaluable research methodology with noteworthy uncertainties confirmed by a mathematical proof
title Brown fat detection by infrared thermography—An invaluable research methodology with noteworthy uncertainties confirmed by a mathematical proof
title_full Brown fat detection by infrared thermography—An invaluable research methodology with noteworthy uncertainties confirmed by a mathematical proof
title_fullStr Brown fat detection by infrared thermography—An invaluable research methodology with noteworthy uncertainties confirmed by a mathematical proof
title_full_unstemmed Brown fat detection by infrared thermography—An invaluable research methodology with noteworthy uncertainties confirmed by a mathematical proof
title_short Brown fat detection by infrared thermography—An invaluable research methodology with noteworthy uncertainties confirmed by a mathematical proof
title_sort brown fat detection by infrared thermography—an invaluable research methodology with noteworthy uncertainties confirmed by a mathematical proof
topic Editorial
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9836251/
https://www.ncbi.nlm.nih.gov/pubmed/36379014
http://dx.doi.org/10.1002/edm2.378
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