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Article: Computerized method for automatic evaluation of lean body mass from PET/CT: Comparison with predictive equations

TitleComputerized method for automatic evaluation of lean body mass from PET/CT: Comparison with predictive equations
Authors
KeywordsLean body mass
Standardized uptake value
Issue Date2012
PublisherSociety of Nuclear Medicine. The Journal's web site is located at http://jnm.snmjournals.org
Citation
Journal Of Nuclear Medicine, 2012, v. 53 n. 1, p. 130-137 How to Cite?
AbstractCT has become an established method for calculating body composition, but it requires data from the whole body, which are not typically obtained in routine PET/CT examinations. A computerized scheme that evaluates whole-body lean body mass (LBM) based on CT data from limited-whole-body coverage was developed. The LBM so obtained was compared with results from conventional predictive equations. Methods: LBM can be obtained automatically from limited-whole-body CT data by 3 means: quantification of body composition from CT images in the limited-whole-body scan, based on thresholding of CT attenuation; determination of the range of coverage based on a characteristic trend of changing composition across different levels and pattern recognition of specific features at strategic positions; and estimation of the LBM of the whole body on the basis of a predetermined relationship between proportion of fat mass and extent of coverage. This scheme was validated using 18 whole-body PET/CT examinations truncated at different lengths to emulate limited-whole-body data. LBM was also calculated using predictive equations that had been reported for use in SUV normalization. Results: LBM derived from limited-whole-body data using the proposed method correlated strongly with LBM derived from whole-body CT data, with correlation coefficients ranging from 0.991 (shorter coverage) to 0.998 (longer coverage) and SEMs of LBM ranging from 0.14 to 0.33 kg. These were more accurate than results from different predictive equations, which ranged in correlation coefficient from 0.635 to 0.970 and in SEM from 0.64 to 2.40 kg. Conclusion: LBM of the whole body could be automatically estimated from CT data of limited-whole-body coverage typically acquired in PET/CT examinations. This estimation allows more accurate and consistent quantification of metabolic activity of tumors based on LBM-normalized standardized uptake value. Copyright © 2012 by the Society of Nuclear Medicine, Inc.
Persistent Identifierhttp://hdl.handle.net/10722/135639
ISSN
2023 Impact Factor: 9.1
2023 SCImago Journal Rankings: 2.122
ISI Accession Number ID
Funding AgencyGrant Number
University of Hong Kong
Funding Information:

This work was funded by the University of Hong Kong. No other potential conflict of interest relevant to this article was reported.

References

 

DC FieldValueLanguage
dc.contributor.authorChan, Ten_HK
dc.date.accessioned2011-07-27T01:38:15Z-
dc.date.available2011-07-27T01:38:15Z-
dc.date.issued2012en_HK
dc.identifier.citationJournal Of Nuclear Medicine, 2012, v. 53 n. 1, p. 130-137en_HK
dc.identifier.issn0161-5505en_HK
dc.identifier.urihttp://hdl.handle.net/10722/135639-
dc.description.abstractCT has become an established method for calculating body composition, but it requires data from the whole body, which are not typically obtained in routine PET/CT examinations. A computerized scheme that evaluates whole-body lean body mass (LBM) based on CT data from limited-whole-body coverage was developed. The LBM so obtained was compared with results from conventional predictive equations. Methods: LBM can be obtained automatically from limited-whole-body CT data by 3 means: quantification of body composition from CT images in the limited-whole-body scan, based on thresholding of CT attenuation; determination of the range of coverage based on a characteristic trend of changing composition across different levels and pattern recognition of specific features at strategic positions; and estimation of the LBM of the whole body on the basis of a predetermined relationship between proportion of fat mass and extent of coverage. This scheme was validated using 18 whole-body PET/CT examinations truncated at different lengths to emulate limited-whole-body data. LBM was also calculated using predictive equations that had been reported for use in SUV normalization. Results: LBM derived from limited-whole-body data using the proposed method correlated strongly with LBM derived from whole-body CT data, with correlation coefficients ranging from 0.991 (shorter coverage) to 0.998 (longer coverage) and SEMs of LBM ranging from 0.14 to 0.33 kg. These were more accurate than results from different predictive equations, which ranged in correlation coefficient from 0.635 to 0.970 and in SEM from 0.64 to 2.40 kg. Conclusion: LBM of the whole body could be automatically estimated from CT data of limited-whole-body coverage typically acquired in PET/CT examinations. This estimation allows more accurate and consistent quantification of metabolic activity of tumors based on LBM-normalized standardized uptake value. Copyright © 2012 by the Society of Nuclear Medicine, Inc.en_HK
dc.languageengen_US
dc.publisherSociety of Nuclear Medicine. The Journal's web site is located at http://jnm.snmjournals.orgen_HK
dc.relation.ispartofJournal of Nuclear Medicineen_HK
dc.subjectLean body massen_HK
dc.subjectStandardized uptake valueen_HK
dc.subject.meshAdipose Tissue - radionuclide imaging-
dc.subject.meshBody Composition-
dc.subject.meshModels, Biological-
dc.subject.meshPositron-Emission Tomography and Computed Tomography-
dc.subject.meshWhole Body Imaging-
dc.titleComputerized method for automatic evaluation of lean body mass from PET/CT: Comparison with predictive equationsen_HK
dc.typeArticleen_HK
dc.identifier.emailChan, T: taochan@hku.hken_HK
dc.identifier.authorityChan, T=rp00289en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.2967/jnumed.111.089292en_HK
dc.identifier.pmid22128325-
dc.identifier.scopuseid_2-s2.0-84855374271en_HK
dc.identifier.hkuros187024en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-84855374271&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume53en_HK
dc.identifier.issue1en_HK
dc.identifier.spage130en_HK
dc.identifier.epage137en_HK
dc.identifier.isiWOS:000298660900029-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridChan, T=35147479300en_HK
dc.identifier.issnl0161-5505-

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