Comparison of bioelectrical impedance analysis and computed tomography for the assessment of body composition among gastric cancer patients

Comparison of bioelectrical impedance analysis and computed tomography for the assessment of body composition among gastric cancer patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Comparison of bioelectrical impedance analysis and computed tomography for the assessment of body composition among gastric cancer patients Li Lv, Chunxian Liu, Yudan Wu, Jing Wen, Wenwen Fu, Xiaoxia Chen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4653884/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective To compare the accuracy of Bioelectrical impedance (BIA) and Computer tomography (CT) in evaluating body composition, specifically assessing visceral fat area (VFA) and skeletal muscle index (SMI), in Chinese gastric cancer patients. Method Spearman correlation analysis was employed to evaluate the relationship between the two methods, and the Bland-Altman method was used to assess their agreement. The performance of BIA in diagnosing low muscle mass and visceral obesity was evaluated based on the area under the receiver operating characteristic (ROC) curve. Result There was a significant positive correlation (r = 0.650) between BIA and CT methods for detecting SMI and VFA, p < 0.001;r = 0.772, p < 0.001). Bland Altman analysis revealed an average bias between the BIA and CT measurement systems of 0.920 ± 1.161 kg/m² (95% CI: -1.658-2.898 kg/m²). The average bias for the VFA measurement system was − 12.304 ± 24.973 cm² (95% CI: -61.252–36.644 cm²). The 95% limits of agreement (LOA) range for percentage deviation were − 19.837–33.702%, and for VFA it was − 90.138–57.034%. Significant differences were observed in the mean biases of SMI and VFA measurements between males and females (SMI: 1.008 ± 1.256 kg/m² vs 0.761 ± 0.954 kg/m², P = 0.036; VFA: 16.206 ± 23.807 cm² vs -5.225 ± 25.570 cm², P < 0.001). Using CT as a reference, the cutoff value for identifying low muscle mass using SMI measured by BIA was 9.754 kg/m² for males and 8.498 kg/m² for females. The critical value for identifying visceral obesity using VFA measured by BIA was 70.45 cm² (AUC = 0.895 (0.860–0.930)), AUCmen = 0.771 (0.708–0.833), AUCwomen = 0.770 (0.688–0.853). Conclusion Although a significant correlation was observed, caution should be exercised when using BIA and CT interchangeably for assessing SMI and VFA values. BIA tended to overestimate SMI and underestimate VFA, especially across different genders. This resulted in an underestimation of the prevalence of low muscle mass and an overestimation of visceral obesity. Health sciences/Diseases Health sciences/Health care Health sciences/Health care/Nutrition bioelectrical impedance analysis computed tomography gastric cancer Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4653884","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":328815678,"identity":"7dfd2e13-bb5e-417f-bf99-9009b7c8fc5f","order_by":0,"name":"Li Lv","email":"","orcid":"","institution":"Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Lv","suffix":""},{"id":328815682,"identity":"dc544a71-18bb-4610-bdfc-d11d93a9f0f8","order_by":1,"name":"Chunxian Liu","email":"","orcid":"","institution":"Sun Yat-sen 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patients","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"bioelectrical impedance analysis, computed tomography, gastric cancer ","lastPublishedDoi":"10.21203/rs.3.rs-4653884/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4653884/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eObjective\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo compare the accuracy of Bioelectrical impedance (BIA) and Computer tomography (CT) in evaluating body composition, specifically assessing visceral fat area (VFA) and skeletal muscle index (SMI), in Chinese gastric cancer patients.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethod\u003c/b\u003e\u003c/p\u003e \u003cp\u003eSpearman correlation analysis was employed to evaluate the relationship between the two methods, and the Bland-Altman method was used to assess their agreement. The performance of BIA in diagnosing low muscle mass and visceral obesity was evaluated based on the area under the receiver operating characteristic (ROC) curve.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResult\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThere was a significant positive correlation (r\u0026thinsp;=\u0026thinsp;0.650) between BIA and CT methods for detecting SMI and VFA, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001;r\u0026thinsp;=\u0026thinsp;0.772, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Bland Altman analysis revealed an average bias between the BIA and CT measurement systems of 0.920\u0026thinsp;\u0026plusmn;\u0026thinsp;1.161 kg/m\u0026sup2; (95% CI: -1.658-2.898 kg/m\u0026sup2;). The average bias for the VFA measurement system was \u0026minus;\u0026thinsp;12.304\u0026thinsp;\u0026plusmn;\u0026thinsp;24.973 cm\u0026sup2; (95% CI: -61.252\u0026ndash;36.644 cm\u0026sup2;). The 95% limits of agreement (LOA) range for percentage deviation were \u0026minus;\u0026thinsp;19.837\u0026ndash;33.702%, and for VFA it was \u0026minus;\u0026thinsp;90.138\u0026ndash;57.034%. Significant differences were observed in the mean biases of SMI and VFA measurements between males and females (SMI: 1.008\u0026thinsp;\u0026plusmn;\u0026thinsp;1.256 kg/m\u0026sup2; vs 0.761\u0026thinsp;\u0026plusmn;\u0026thinsp;0.954 kg/m\u0026sup2;, P\u0026thinsp;=\u0026thinsp;0.036; VFA: 16.206\u0026thinsp;\u0026plusmn;\u0026thinsp;23.807 cm\u0026sup2; vs -5.225\u0026thinsp;\u0026plusmn;\u0026thinsp;25.570 cm\u0026sup2;, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Using CT as a reference, the cutoff value for identifying low muscle mass using SMI measured by BIA was 9.754 kg/m\u0026sup2; for males and 8.498 kg/m\u0026sup2; for females. The critical value for identifying visceral obesity using VFA measured by BIA was 70.45 cm\u0026sup2; (AUC\u0026thinsp;=\u0026thinsp;0.895 (0.860\u0026ndash;0.930)), AUCmen\u0026thinsp;=\u0026thinsp;0.771 (0.708\u0026ndash;0.833), AUCwomen\u0026thinsp;=\u0026thinsp;0.770 (0.688\u0026ndash;0.853).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAlthough a significant correlation was observed, caution should be exercised when using BIA and CT interchangeably for assessing SMI and VFA values. BIA tended to overestimate SMI and underestimate VFA, especially across different genders. This resulted in an underestimation of the prevalence of low muscle mass and an overestimation of visceral obesity.\u003c/p\u003e","manuscriptTitle":"Comparison of bioelectrical impedance analysis and computed tomography for the assessment of body composition among gastric cancer patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-25 22:03:19","doi":"10.21203/rs.3.rs-4653884/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d24b46cf-82ba-4a43-b14e-dc0ecbdacf86","owner":[],"postedDate":"July 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":34807338,"name":"Health sciences/Diseases"},{"id":34807340,"name":"Health sciences/Health care"},{"id":34807341,"name":"Health sciences/Health care/Nutrition"}],"tags":[],"updatedAt":"2024-11-25T08:39:34+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-25 22:03:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4653884","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4653884","identity":"rs-4653884","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}