Brown fat detection by infrared thermography—An invaluable research methodology with noteworthy uncertainties confirmed by a mathematical proof
Abstract 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 meth...
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-01-01
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| Series: | Endocrinology, Diabetes & Metabolism |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/edm2.378 |
| _version_ | 1797954352516694016 |
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| author | Melvin K. S. Leow |
| author_facet | Melvin K. S. Leow |
| author_sort | Melvin K. S. Leow |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-04-10T23:16:13Z |
| format | Article |
| id | doaj.art-10169d0c536745cfac06f3454ba2434a |
| institution | Directory Open Access Journal |
| issn | 2398-9238 |
| language | English |
| last_indexed | 2024-04-10T23:16:13Z |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Endocrinology, Diabetes & Metabolism |
| spelling | doaj.art-10169d0c536745cfac06f3454ba2434a2023-01-12T18:13:04ZengWileyEndocrinology, Diabetes & Metabolism2398-92382023-01-0161n/an/a10.1002/edm2.378Brown fat detection by infrared thermography—An invaluable research methodology with noteworthy uncertainties confirmed by a mathematical proofMelvin K. S. Leow0Department of Human Development Singapore Institute for Clinical Sciences, A*STAR Singapore City SingaporeAbstract 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.https://doi.org/10.1002/edm2.378brown adipose tissuedetection accuracyfat segmentationimaginginfrared thermographyprecision |
| spellingShingle | Melvin K. S. Leow Brown fat detection by infrared thermography—An invaluable research methodology with noteworthy uncertainties confirmed by a mathematical proof Endocrinology, Diabetes & Metabolism brown adipose tissue detection accuracy fat segmentation imaging infrared thermography precision |
| 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 | brown adipose tissue detection accuracy fat segmentation imaging infrared thermography precision |
| url | https://doi.org/10.1002/edm2.378 |
| work_keys_str_mv | AT melvinksleow brownfatdetectionbyinfraredthermographyaninvaluableresearchmethodologywithnoteworthyuncertaintiesconfirmedbyamathematicalproof |