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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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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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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. |
format | Online Article Text |
id | pubmed-9836251 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
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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