Organ-Specific CT Radiomics Signatures of Hepatic, Pancreatic, and Renal Parenchyma for Stratification of Glycaemic Status

Organ-Specific CT Radiomics Signatures of Hepatic, Pancreatic, and Renal Parenchyma for Stratification of Glycaemic Status | 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 Research Article Organ-Specific CT Radiomics Signatures of Hepatic, Pancreatic, and Renal Parenchyma for Stratification of Glycaemic Status Sherin Percy V, Dr. Sundarapandian subramanian, Dr. Senthilkumar Aiyappan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8867164/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Purpose To evaluate organ-specific computed tomography (CT) radiomics signatures of the liver, pancreas, and kidneys for stratification of glycaemic status and to determine differential radiomic behaviour across abdominal parenchymal organs. Methods In this prospective study, adult patients undergoing non-contrast abdominal CT were categorised into normoglycemia, prediabetes, and diabetes groups based on fasting plasma glucose and HbA1c. Regions of interest were manually segmented in hepatic, pancreatic, and renal parenchyma. First-order attenuation features and texture features derived from GLCM, GLRLM, and GLSZM matrices were extracted using IBSI-compliant software. Organ-wise radiomic signatures were analysed for group differences and correlation with glycaemic markers. Receiver operating characteristic (ROC) analysis evaluated organ-specific stratification performance. Results A total of 120 patients (mean age 52 ± 11 years) were included. Hepatic mean attenuation showed significant inverse correlation with fasting glucose (r = − 0.41, p < 0.001). Pancreatic entropy and renal gray-level non-uniformity demonstrated significant positive correlations with HbA1c (r = 0.36 and 0.32, respectively; p < 0.01). Organ-wise AUCs for discrimination of diabetes were: liver 0.81, pancreas 0.76, and kidney 0.72. Multi-organ fusion improved AUC to 0.87. Conclusion CT radiomics reveals distinct organ-specific signatures associated with glycaemic status. The liver demonstrates the strongest attenuation-based association, while the pancreas and the kidney exhibit texture-driven heterogeneity changes. Multi-organ phenotyping enhances metabolic stratification beyond single-organ assessment. Radiomics Tomography X-Ray Computed Diabetes Mellitus Prediabetic State Blood Glucose Glycated Haemoglobin A Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 10 Mar, 2026 Editor assigned by journal 09 Mar, 2026 Editor invited by journal 19 Feb, 2026 Submission checks completed at journal 18 Feb, 2026 First submitted to journal 18 Feb, 2026 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-8867164","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":603841286,"identity":"d7c69f5c-36fa-4f06-81d5-bb995684ab25","order_by":0,"name":"Sherin Percy V","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/klEQVRIiWNgGAWjYDACCSBOgDAZH3yoAFLMzA1Ea2E2nHEGRDESoQUK2KQ528C24dciP7v52IeHO+7ImbefMZBmnFcbzd8O1PKjYhtOLQZ3jiXPSDzzzFjmTI6BceG247kzDjM2MPacuY1bi0SOMUNi2+HEGRI8Bskztx3LbQBqYWZsw61Ffkb+Z5CWepCWw7xzjuXOJ6SF4UYOM0hLgoQEj2Ezb0NN7gZCWgxupIEc9sxwBk9aMeOMYwdyNwK1HMTnF/kZyY8Zf7bdkZdgP7z9x4eautx55w8ffPCjAo/DIOAAEHMYAInDcC4xWtgfAIk6IhSPglEwCkbBSAMA7JNfJ/rqm/sAAAAASUVORK5CYII=","orcid":"","institution":"SRM Institute of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Sherin","middleName":"Percy","lastName":"V","suffix":""},{"id":603841288,"identity":"f37967bd-297f-48c8-a819-4617eb219253","order_by":1,"name":"Dr. Sundarapandian subramanian","email":"","orcid":"","institution":"SRM Institute of Science and Technology","correspondingAuthor":false,"prefix":"Dr.","firstName":"Sundarapandian","middleName":"","lastName":"subramanian","suffix":""},{"id":603841294,"identity":"33868955-3d15-4aeb-be93-cbccda0292d4","order_by":2,"name":"Dr. Senthilkumar Aiyappan","email":"","orcid":"","institution":"SRM Institute of Science and Technology","correspondingAuthor":false,"prefix":"Dr.","firstName":"Senthilkumar","middleName":"","lastName":"Aiyappan","suffix":""}],"badges":[],"createdAt":"2026-02-13 04:08:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8867164/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8867164/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104782209,"identity":"f5f44aee-7e03-4180-babd-bce5952fb38b","added_by":"auto","created_at":"2026-03-17 07:56:58","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":507988,"visible":true,"origin":"","legend":"","description":"","filename":"a1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8867164/v1_covered_c05673c7-e6be-4840-b6fe-a0f2a1ef8742.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Organ-Specific CT Radiomics Signatures of Hepatic, Pancreatic, and Renal Parenchyma for Stratification of Glycaemic Status","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-medical-imaging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmim","sideBox":"Learn more about [BMC Medical Imaging](http://bmcmedimaging.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmim/default.aspx","title":"BMC Medical Imaging","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Radiomics, Tomography, X-Ray Computed, Diabetes Mellitus, Prediabetic State, Blood Glucose, Glycated Haemoglobin A","lastPublishedDoi":"10.21203/rs.3.rs-8867164/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8867164/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eTo evaluate organ-specific computed tomography (CT) radiomics signatures of the liver, pancreas, and kidneys for stratification of glycaemic status and to determine differential radiomic behaviour across abdominal parenchymal organs.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this prospective study, adult patients undergoing non-contrast abdominal CT were categorised into normoglycemia, prediabetes, and diabetes groups based on fasting plasma glucose and HbA1c. Regions of interest were manually segmented in hepatic, pancreatic, and renal parenchyma. First-order attenuation features and texture features derived from GLCM, GLRLM, and GLSZM matrices were extracted using IBSI-compliant software. Organ-wise radiomic signatures were analysed for group differences and correlation with glycaemic markers. Receiver operating characteristic (ROC) analysis evaluated organ-specific stratification performance.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 120 patients (mean age 52\u0026thinsp;\u0026plusmn;\u0026thinsp;11 years) were included. Hepatic mean attenuation showed significant inverse correlation with fasting glucose (r = \u0026minus;\u0026thinsp;0.41, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Pancreatic entropy and renal gray-level non-uniformity demonstrated significant positive correlations with HbA1c (r\u0026thinsp;=\u0026thinsp;0.36 and 0.32, respectively; p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Organ-wise AUCs for discrimination of diabetes were: liver 0.81, pancreas 0.76, and kidney 0.72. Multi-organ fusion improved AUC to 0.87.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eCT radiomics reveals distinct organ-specific signatures associated with glycaemic status. The liver demonstrates the strongest attenuation-based association, while the pancreas and the kidney exhibit texture-driven heterogeneity changes. Multi-organ phenotyping enhances metabolic stratification beyond single-organ assessment.\u003c/p\u003e","manuscriptTitle":"Organ-Specific CT Radiomics Signatures of Hepatic, Pancreatic, and Renal Parenchyma for Stratification of Glycaemic Status","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-13 16:49:27","doi":"10.21203/rs.3.rs-8867164/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-03-10T13:13:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-09T11:35:59+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-19T08:47:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-19T04:57:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Imaging","date":"2026-02-19T04:00:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-imaging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmim","sideBox":"Learn more about [BMC Medical Imaging](http://bmcmedimaging.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmim/default.aspx","title":"BMC Medical Imaging","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"64464e0c-8878-4b4f-abfb-620610bae080","owner":[],"postedDate":"March 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-13T16:49:28+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-13 16:49:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8867164","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8867164","identity":"rs-8867164","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}