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Estimating whole body intermuscular adipose tissue from single cross-sectional magnetic resonance images
1 Department of Medicine, Obesity Research Center, St. Luke's-Roosevelt Hospital, and 2 Institute of Human Nutrition, Columbia University, New York, New York; 3 Laboratory of Epidemiology, Demography and Biometry, Geriatric Epidemiology Section, National Institute on Aging, Bethesda, Maryland;...
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Published in: | Journal of applied physiology (1985) 2007-02, Vol.102 (2), p.748-754 |
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creator | Ruan, Xiang Yan Gallagher, Dympna Harris, Tamara Albu, Jeanine Heymsfield, Steven Kuznia, Patrick Heshka, Stanley |
description | 1 Department of Medicine, Obesity Research Center, St. Luke's-Roosevelt Hospital, and 2 Institute of Human Nutrition, Columbia University, New York, New York; 3 Laboratory of Epidemiology, Demography and Biometry, Geriatric Epidemiology Section, National Institute on Aging, Bethesda, Maryland; and 4 Endocrinology Center for Gynecology, Beijing Obstetrics and Gynecology Hospital, Capital University of Medical Sciences, Beijing, China
Submitted 10 March 2006
; accepted in final form 17 October 2006
Intermuscular adipose tissue (IMAT), a novel fat depot linked with metabolic abnormalities, has been measured by whole body MRI. The cross-sectional slice location with the strongest relation to total body IMAT volume has not been established. The aim was to determine the predictive value of each slice location and which slice locations provide the best estimates of whole body IMAT. MRI quantified total adipose tissue of which IMAT, defined as adipose tissue visible within the boundary of the muscle fascia, is a subcomponent. Single-slice IMAT areas were calculated for the calf, thigh, buttock, waist, shoulders, upper arm, and forearm locations in a sample of healthy adult women, African-American [ n = 39; body mass index (BMI) 28.5 ± 5.4 kg/m 2 ; 41.8 ± 14.8 yr], Asian ( n = 21; BMI 21.6 ± 3.2 kg/m 2 ; 40.9 ± 16.3 yr), and Caucasian ( n = 43; BMI 25.6 ± 5.3 kg/m 2 ; 43.2 ± 15.3 yr), and Caucasian men ( n = 39; BMI 27.1 ± 3.8 kg/m 2 ; 45.2 ± 14.6 yr) and used to estimate total IMAT groups using multiple-regression equations. Midthigh was the best, or near best, single predictor in all groups with adjusted R 2 ranging from 0.49 to 0.84. Adding a second and third slice further increased R 2 and reduced the error of the estimate. Menopausal status and degree of obesity did not affect the location of the best single slice. The contributions of other slice locations varied by sex and race, but additional slices improved predictions. For group studies, it may be more cost-effective to estimate IMAT based on one or more slices than to acquire and segment for each subject the numerous images necessary to quantify whole body IMAT.
race; body composition; fat distribution; muscle fat; imaging
Other correspondence: D. Gallagher, Obesity Research Center, 1090 Amsterdam Ave., New York, New York 10025 (e-mail: dg108{at}columbia.edu ) |
doi_str_mv | 10.1152/japplphysiol.00304.2006 |
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Submitted 10 March 2006
; accepted in final form 17 October 2006
Intermuscular adipose tissue (IMAT), a novel fat depot linked with metabolic abnormalities, has been measured by whole body MRI. The cross-sectional slice location with the strongest relation to total body IMAT volume has not been established. The aim was to determine the predictive value of each slice location and which slice locations provide the best estimates of whole body IMAT. MRI quantified total adipose tissue of which IMAT, defined as adipose tissue visible within the boundary of the muscle fascia, is a subcomponent. Single-slice IMAT areas were calculated for the calf, thigh, buttock, waist, shoulders, upper arm, and forearm locations in a sample of healthy adult women, African-American [ n = 39; body mass index (BMI) 28.5 ± 5.4 kg/m 2 ; 41.8 ± 14.8 yr], Asian ( n = 21; BMI 21.6 ± 3.2 kg/m 2 ; 40.9 ± 16.3 yr), and Caucasian ( n = 43; BMI 25.6 ± 5.3 kg/m 2 ; 43.2 ± 15.3 yr), and Caucasian men ( n = 39; BMI 27.1 ± 3.8 kg/m 2 ; 45.2 ± 14.6 yr) and used to estimate total IMAT groups using multiple-regression equations. Midthigh was the best, or near best, single predictor in all groups with adjusted R 2 ranging from 0.49 to 0.84. Adding a second and third slice further increased R 2 and reduced the error of the estimate. Menopausal status and degree of obesity did not affect the location of the best single slice. The contributions of other slice locations varied by sex and race, but additional slices improved predictions. For group studies, it may be more cost-effective to estimate IMAT based on one or more slices than to acquire and segment for each subject the numerous images necessary to quantify whole body IMAT.
race; body composition; fat distribution; muscle fat; imaging
Other correspondence: D. Gallagher, Obesity Research Center, 1090 Amsterdam Ave., New York, New York 10025 (e-mail: dg108{at}columbia.edu )</description><identifier>ISSN: 8750-7587</identifier><identifier>EISSN: 1522-1601</identifier><identifier>DOI: 10.1152/japplphysiol.00304.2006</identifier><identifier>PMID: 17053107</identifier><identifier>CODEN: JAPHEV</identifier><language>eng</language><publisher>Bethesda, MD: Am Physiological Soc</publisher><subject>Adipose Tissue - anatomy & histology ; Adult ; Aged ; Aged, 80 and over ; Anatomy, Cross-Sectional - economics ; Anatomy, Cross-Sectional - methods ; Biological and medical sciences ; Body Composition ; Body fat ; Body Mass Index ; Cost-Benefit Analysis ; Female ; Fundamental and applied biological sciences. Psychology ; Human body ; Humans ; Magnetic Resonance Imaging - economics ; Magnetic Resonance Imaging - methods ; Male ; Middle Aged ; Muscles - anatomy & histology ; NMR ; Nuclear magnetic resonance ; Predictive Value of Tests ; Tissues ; Whole Body Imaging - economics ; Whole Body Imaging - methods</subject><ispartof>Journal of applied physiology (1985), 2007-02, Vol.102 (2), p.748-754</ispartof><rights>2007 INIST-CNRS</rights><rights>Copyright American Physiological Society Feb 2007</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c647t-af5ca2e677764297025709bfd8152cb3ef56912055cfbc38b6278849192d69f53</citedby><cites>FETCH-LOGICAL-c647t-af5ca2e677764297025709bfd8152cb3ef56912055cfbc38b6278849192d69f53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=18534251$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/17053107$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ruan, Xiang Yan</creatorcontrib><creatorcontrib>Gallagher, Dympna</creatorcontrib><creatorcontrib>Harris, Tamara</creatorcontrib><creatorcontrib>Albu, Jeanine</creatorcontrib><creatorcontrib>Heymsfield, Steven</creatorcontrib><creatorcontrib>Kuznia, Patrick</creatorcontrib><creatorcontrib>Heshka, Stanley</creatorcontrib><title>Estimating whole body intermuscular adipose tissue from single cross-sectional magnetic resonance images</title><title>Journal of applied physiology (1985)</title><addtitle>J Appl Physiol (1985)</addtitle><description>1 Department of Medicine, Obesity Research Center, St. Luke's-Roosevelt Hospital, and 2 Institute of Human Nutrition, Columbia University, New York, New York; 3 Laboratory of Epidemiology, Demography and Biometry, Geriatric Epidemiology Section, National Institute on Aging, Bethesda, Maryland; and 4 Endocrinology Center for Gynecology, Beijing Obstetrics and Gynecology Hospital, Capital University of Medical Sciences, Beijing, China
Submitted 10 March 2006
; accepted in final form 17 October 2006
Intermuscular adipose tissue (IMAT), a novel fat depot linked with metabolic abnormalities, has been measured by whole body MRI. The cross-sectional slice location with the strongest relation to total body IMAT volume has not been established. The aim was to determine the predictive value of each slice location and which slice locations provide the best estimates of whole body IMAT. MRI quantified total adipose tissue of which IMAT, defined as adipose tissue visible within the boundary of the muscle fascia, is a subcomponent. Single-slice IMAT areas were calculated for the calf, thigh, buttock, waist, shoulders, upper arm, and forearm locations in a sample of healthy adult women, African-American [ n = 39; body mass index (BMI) 28.5 ± 5.4 kg/m 2 ; 41.8 ± 14.8 yr], Asian ( n = 21; BMI 21.6 ± 3.2 kg/m 2 ; 40.9 ± 16.3 yr), and Caucasian ( n = 43; BMI 25.6 ± 5.3 kg/m 2 ; 43.2 ± 15.3 yr), and Caucasian men ( n = 39; BMI 27.1 ± 3.8 kg/m 2 ; 45.2 ± 14.6 yr) and used to estimate total IMAT groups using multiple-regression equations. Midthigh was the best, or near best, single predictor in all groups with adjusted R 2 ranging from 0.49 to 0.84. Adding a second and third slice further increased R 2 and reduced the error of the estimate. Menopausal status and degree of obesity did not affect the location of the best single slice. The contributions of other slice locations varied by sex and race, but additional slices improved predictions. For group studies, it may be more cost-effective to estimate IMAT based on one or more slices than to acquire and segment for each subject the numerous images necessary to quantify whole body IMAT.
race; body composition; fat distribution; muscle fat; imaging
Other correspondence: D. Gallagher, Obesity Research Center, 1090 Amsterdam Ave., New York, New York 10025 (e-mail: dg108{at}columbia.edu )</description><subject>Adipose Tissue - anatomy & histology</subject><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Anatomy, Cross-Sectional - economics</subject><subject>Anatomy, Cross-Sectional - methods</subject><subject>Biological and medical sciences</subject><subject>Body Composition</subject><subject>Body fat</subject><subject>Body Mass Index</subject><subject>Cost-Benefit Analysis</subject><subject>Female</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Human body</subject><subject>Humans</subject><subject>Magnetic Resonance Imaging - economics</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Muscles - anatomy & histology</subject><subject>NMR</subject><subject>Nuclear magnetic resonance</subject><subject>Predictive Value of Tests</subject><subject>Tissues</subject><subject>Whole Body Imaging - economics</subject><subject>Whole Body Imaging - methods</subject><issn>8750-7587</issn><issn>1522-1601</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><recordid>eNqFkdFr1TAYxYMo7jr9FzQIDl96TdKmSV8EGZsKA1_mc0jTtM0lbWq-dvP-98vdLdsUxKdA8jsn5_sOQu8o2VLK2aedniY_9XtwwW8JyUmxZYSUz9AmvbKMloQ-RxspOMkEl-IEvQLYEUKLgtOX6IQKwnNKxAb1FzC7Qc9u7PBtH7zFdWj22I2zjcMCZvE6Yt24KYDFswNYLG5jGDAkRaJNDAAZWDO7MGqPB92NdnYGRwvpYjQWJ_vOwmv0otUe7Jv1PEU_Ly-uz79lVz--fj__cpWZshBzpltuNLOlEKIsWCUI44JUddvINJipc9vysqKMcG7a2uSyLpmQsqhoxZqyanl-ij4ffaelHmxj7DhH7dUUU4y4V0E79efL6HrVhRvF0qIklcngbDWI4ddiYVaDA2O916MNC6hSVlX6nv8XpBUXjDCawPd_gbuwxLQtUIyxlFyIg5s4QvcbjbZ9iEyJOnSunnau7jtXh86T8u3TiR91a8kJ-LACGoz2bUy1OHjkJM8Lxg85iyPXu66_ddGq9bfQ7dXl4v21_T0fYlDCFFOikGpq2iT7-G9ZotUDnt8BcfLcUg</recordid><startdate>20070201</startdate><enddate>20070201</enddate><creator>Ruan, Xiang Yan</creator><creator>Gallagher, Dympna</creator><creator>Harris, Tamara</creator><creator>Albu, Jeanine</creator><creator>Heymsfield, Steven</creator><creator>Kuznia, Patrick</creator><creator>Heshka, Stanley</creator><general>Am Physiological Soc</general><general>American Physiological Society</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QP</scope><scope>7QR</scope><scope>7TK</scope><scope>7TS</scope><scope>7U7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>P64</scope><scope>7QO</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20070201</creationdate><title>Estimating whole body intermuscular adipose tissue from single cross-sectional magnetic resonance images</title><author>Ruan, Xiang Yan ; Gallagher, Dympna ; Harris, Tamara ; Albu, Jeanine ; Heymsfield, Steven ; Kuznia, Patrick ; Heshka, Stanley</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c647t-af5ca2e677764297025709bfd8152cb3ef56912055cfbc38b6278849192d69f53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Adipose Tissue - anatomy & histology</topic><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Anatomy, Cross-Sectional - economics</topic><topic>Anatomy, Cross-Sectional - methods</topic><topic>Biological and medical sciences</topic><topic>Body Composition</topic><topic>Body fat</topic><topic>Body Mass Index</topic><topic>Cost-Benefit Analysis</topic><topic>Female</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Human body</topic><topic>Humans</topic><topic>Magnetic Resonance Imaging - economics</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Muscles - anatomy & histology</topic><topic>NMR</topic><topic>Nuclear magnetic resonance</topic><topic>Predictive Value of Tests</topic><topic>Tissues</topic><topic>Whole Body Imaging - economics</topic><topic>Whole Body Imaging - methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ruan, Xiang Yan</creatorcontrib><creatorcontrib>Gallagher, Dympna</creatorcontrib><creatorcontrib>Harris, Tamara</creatorcontrib><creatorcontrib>Albu, Jeanine</creatorcontrib><creatorcontrib>Heymsfield, Steven</creatorcontrib><creatorcontrib>Kuznia, Patrick</creatorcontrib><creatorcontrib>Heshka, Stanley</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Physical Education Index</collection><collection>Toxicology Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of applied physiology (1985)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ruan, Xiang Yan</au><au>Gallagher, Dympna</au><au>Harris, Tamara</au><au>Albu, Jeanine</au><au>Heymsfield, Steven</au><au>Kuznia, Patrick</au><au>Heshka, Stanley</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimating whole body intermuscular adipose tissue from single cross-sectional magnetic resonance images</atitle><jtitle>Journal of applied physiology (1985)</jtitle><addtitle>J Appl Physiol (1985)</addtitle><date>2007-02-01</date><risdate>2007</risdate><volume>102</volume><issue>2</issue><spage>748</spage><epage>754</epage><pages>748-754</pages><issn>8750-7587</issn><eissn>1522-1601</eissn><coden>JAPHEV</coden><abstract>1 Department of Medicine, Obesity Research Center, St. Luke's-Roosevelt Hospital, and 2 Institute of Human Nutrition, Columbia University, New York, New York; 3 Laboratory of Epidemiology, Demography and Biometry, Geriatric Epidemiology Section, National Institute on Aging, Bethesda, Maryland; and 4 Endocrinology Center for Gynecology, Beijing Obstetrics and Gynecology Hospital, Capital University of Medical Sciences, Beijing, China
Submitted 10 March 2006
; accepted in final form 17 October 2006
Intermuscular adipose tissue (IMAT), a novel fat depot linked with metabolic abnormalities, has been measured by whole body MRI. The cross-sectional slice location with the strongest relation to total body IMAT volume has not been established. The aim was to determine the predictive value of each slice location and which slice locations provide the best estimates of whole body IMAT. MRI quantified total adipose tissue of which IMAT, defined as adipose tissue visible within the boundary of the muscle fascia, is a subcomponent. Single-slice IMAT areas were calculated for the calf, thigh, buttock, waist, shoulders, upper arm, and forearm locations in a sample of healthy adult women, African-American [ n = 39; body mass index (BMI) 28.5 ± 5.4 kg/m 2 ; 41.8 ± 14.8 yr], Asian ( n = 21; BMI 21.6 ± 3.2 kg/m 2 ; 40.9 ± 16.3 yr), and Caucasian ( n = 43; BMI 25.6 ± 5.3 kg/m 2 ; 43.2 ± 15.3 yr), and Caucasian men ( n = 39; BMI 27.1 ± 3.8 kg/m 2 ; 45.2 ± 14.6 yr) and used to estimate total IMAT groups using multiple-regression equations. Midthigh was the best, or near best, single predictor in all groups with adjusted R 2 ranging from 0.49 to 0.84. Adding a second and third slice further increased R 2 and reduced the error of the estimate. Menopausal status and degree of obesity did not affect the location of the best single slice. The contributions of other slice locations varied by sex and race, but additional slices improved predictions. For group studies, it may be more cost-effective to estimate IMAT based on one or more slices than to acquire and segment for each subject the numerous images necessary to quantify whole body IMAT.
race; body composition; fat distribution; muscle fat; imaging
Other correspondence: D. Gallagher, Obesity Research Center, 1090 Amsterdam Ave., New York, New York 10025 (e-mail: dg108{at}columbia.edu )</abstract><cop>Bethesda, MD</cop><pub>Am Physiological Soc</pub><pmid>17053107</pmid><doi>10.1152/japplphysiol.00304.2006</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adipose Tissue - anatomy & histology Adult Aged Aged, 80 and over Anatomy, Cross-Sectional - economics Anatomy, Cross-Sectional - methods Biological and medical sciences Body Composition Body fat Body Mass Index Cost-Benefit Analysis Female Fundamental and applied biological sciences. Psychology Human body Humans Magnetic Resonance Imaging - economics Magnetic Resonance Imaging - methods Male Middle Aged Muscles - anatomy & histology NMR Nuclear magnetic resonance Predictive Value of Tests Tissues Whole Body Imaging - economics Whole Body Imaging - methods |
title | Estimating whole body intermuscular adipose tissue from single cross-sectional magnetic resonance images |
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