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Article: Towards visceral fat estimation at population scale: correlation of visceral adipose tissue assessment using three-dimensional cross-sectional imaging with BIA, DXA, and single-slice CT

TitleTowards visceral fat estimation at population scale: correlation of visceral adipose tissue assessment using three-dimensional cross-sectional imaging with BIA, DXA, and single-slice CT
Authors
Keywordscomputed tomography
correlation
DXA (dual-energy x-ray absorptiometry)
MRI
visceral adipose tissue
Issue Date11-Jul-2023
PublisherFrontiers Media
Citation
Frontiers in Endocrinology, 2023, v. 14 How to Cite?
Abstract

BackgroundIn terms of assessing obesity-associated risk, quantification of visceral adipose tissue (VAT) has become increasingly important in risk assessment for cardiovascular and metabolic diseases. However, differences exist in the accuracy of various modalities, with a lack of up-to-date comparison with three-dimensional whole volume assessment. AimsUsing CT or MRI three-dimensional whole volume VAT as a reference, we evaluated the correlation of various commonly used modalities and techniques namely body impedance analysis (BIA), dual-energy x-ray absorptiometry (DXA) as well as single slice CT to establish how these methods compare. MethodsWe designed the study in two parts. First, we performed an intra-individual comparison of the 4558 participants from the UK Biobank cohorts with matching data of MRI abdominal body composition, DXA with VAT estimation, and BIA. Second, we evaluated 174 CT scans from the publicly available dataset to assess the correlation of the commonly used single-slice technique compared to three-dimensional VAT volume. ResultsAcross the UK Biobank cohort, the DXA-derived VAT measurement correlated better (R-2 0.94, p<0.0001) than BIA (R-2 0.49, p<0.0001) with reference three-dimensional volume on MRI. However, DXA-derived VAT correlation was worse for participants with a BMI of < 20 (R-2 = 0.62, p=0.0013). A commonly used single slice method on CT demonstrated a modest correlation (R-2 between 0.51 - 0.64), with best values at L3- and L4 (R-2 L3 = 0.63, p<0.0001; L4 = 0.64, p<0.0001) compared to reference three-dimensional volume. Combining multiple slices yielded a better correlation, with a strong correlation when L2-L3 levels were combined (R-2 = 0.92, p<0.0001). ConclusionWhen deployed at scale, DXA-derived VAT volume measurement shows excellent correlation with three-dimensional volume on MRI based on the UK Biobank cohort. Whereas a single slice CT technique demonstrated moderate correlation with three-dimensional volume on CT, with a stronger correlation achieved when multiple levels were combined.


Persistent Identifierhttp://hdl.handle.net/10722/340082
ISSN
2022 Impact Factor: 5.2
2020 SCImago Journal Rankings: 1.518
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorChan, B-
dc.contributor.authorYu, Y-
dc.contributor.authorHuang, F-
dc.contributor.authorVardhanabhuti, V-
dc.date.accessioned2024-03-11T10:41:31Z-
dc.date.available2024-03-11T10:41:31Z-
dc.date.issued2023-07-11-
dc.identifier.citationFrontiers in Endocrinology, 2023, v. 14-
dc.identifier.issn1664-2392-
dc.identifier.urihttp://hdl.handle.net/10722/340082-
dc.description.abstract<p>BackgroundIn terms of assessing obesity-associated risk, quantification of visceral adipose tissue (VAT) has become increasingly important in risk assessment for cardiovascular and metabolic diseases. However, differences exist in the accuracy of various modalities, with a lack of up-to-date comparison with three-dimensional whole volume assessment. AimsUsing CT or MRI three-dimensional whole volume VAT as a reference, we evaluated the correlation of various commonly used modalities and techniques namely body impedance analysis (BIA), dual-energy x-ray absorptiometry (DXA) as well as single slice CT to establish how these methods compare. MethodsWe designed the study in two parts. First, we performed an intra-individual comparison of the 4558 participants from the UK Biobank cohorts with matching data of MRI abdominal body composition, DXA with VAT estimation, and BIA. Second, we evaluated 174 CT scans from the publicly available dataset to assess the correlation of the commonly used single-slice technique compared to three-dimensional VAT volume. ResultsAcross the UK Biobank cohort, the DXA-derived VAT measurement correlated better (R-2 0.94, p<0.0001) than BIA (R-2 0.49, p<0.0001) with reference three-dimensional volume on MRI. However, DXA-derived VAT correlation was worse for participants with a BMI of < 20 (R-2 = 0.62, p=0.0013). A commonly used single slice method on CT demonstrated a modest correlation (R-2 between 0.51 - 0.64), with best values at L3- and L4 (R-2 L3 = 0.63, p<0.0001; L4 = 0.64, p<0.0001) compared to reference three-dimensional volume. Combining multiple slices yielded a better correlation, with a strong correlation when L2-L3 levels were combined (R-2 = 0.92, p<0.0001). ConclusionWhen deployed at scale, DXA-derived VAT volume measurement shows excellent correlation with three-dimensional volume on MRI based on the UK Biobank cohort. Whereas a single slice CT technique demonstrated moderate correlation with three-dimensional volume on CT, with a stronger correlation achieved when multiple levels were combined.</p>-
dc.languageeng-
dc.publisherFrontiers Media-
dc.relation.ispartofFrontiers in Endocrinology-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectcomputed tomography-
dc.subjectcorrelation-
dc.subjectDXA (dual-energy x-ray absorptiometry)-
dc.subjectMRI-
dc.subjectvisceral adipose tissue-
dc.titleTowards visceral fat estimation at population scale: correlation of visceral adipose tissue assessment using three-dimensional cross-sectional imaging with BIA, DXA, and single-slice CT-
dc.typeArticle-
dc.identifier.doi10.3389/fendo.2023.1211696-
dc.identifier.pmid37497346-
dc.identifier.scopuseid_2-s2.0-85165917832-
dc.identifier.volume14-
dc.identifier.eissn1664-2392-
dc.identifier.isiWOS:001035316100001-
dc.publisher.placeLAUSANNE-
dc.identifier.issnl1664-2392-

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