Defining Optimal Cut-offs for Absolute ADC and ADC Ratios in Clinically Significant Prostate Cancer: Correlation with PI-RADS v2.1 and Tumor Aggressiveness

Defining Optimal Cut-offs for Absolute ADC and ADC Ratios in Clinically Significant Prostate Cancer: Correlation with PI-RADS v2.1 and Tumor Aggressiveness | 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 Defining Optimal Cut-offs for Absolute ADC and ADC Ratios in Clinically Significant Prostate Cancer: Correlation with PI-RADS v2.1 and Tumor Aggressiveness Enes Özel, İlyas Dündar, Fatma Durmaz, Sercan Özkaçmaz, Mesut Özgökçe, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8502054/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background To investigate the diagnostic value of apparent diffusion coefficient (ADC) values and ADC ratios (ADC Ratio ) derived from multiparametric MRI (mpMRI) in differentiating benign from malignant peripheral zone lesions and identifying clinically significant prostate cancer (csPCa). Additionally, the study aims to evaluate the relationship between these quantitative parameters, PI-RADS v2.1 scores, and Gleason scores (GS). Methods A total of 188 patients who underwent pre-biopsy mpMRI between January 2021 and January 2025 were reviewed retrospectively. Based on histopathology, patients were stratified into Benign (n=126) and Malignant (n=62) groups. The Benign Group included lesion-free (Group 1, n=53) and lesion-positive (Group 2, n=73) cases. The Malignant Group was sub-classified into clinically non-significant (ncsPCa, Group 3, n=28) and significant cancer (csPCa, Group 4, n=34) according to ISUP standards. Age, PSA, prostate volume (PV), PSA density (PSAD), and PI-RADS scores were recorded. Lesion ADC values and ADC Ratio (lesion-to-contralateral normal tissue) were calculated. Results In the study cohort (mean age: 63.36 ± 7.1 years), mean ADC values in the Malignant Group (767 ± 134 ×10 - ⁶ mm²/s) were significantly lower than in benign tissues (1606 ± 283 ×10 - ⁶ mm²/s; p<0.001). For benign-malignant differentiation, an ADC cut-off of 980 ×10 - ⁶ mm²/s yielded 98.4% sensitivity, 96.8% specificity, and an AUC of 0.99; an ADC Ratio cut-off of 0.57 yielded an AUC of 0.98. In the csPCa group, mean ADC values (734 ×10 - ⁶ mm²/s) were significantly lower than in the ncsPCa group (807 ×10 - ⁶ mm²/s; p=0.032), with an optimal cut-off determined at 765 ×10 - ⁶ mm²/s. However, ADC Ratio did not significantly differ between cancer subgroups (p=0.32). Higher PI-RADS scores were significantly correlated with increased PSAD, lower PV, and higher ISUP grades (p<0.05). Conclusions Lesion ADC values and ADC Ratio demonstrate high diagnostic accuracy for prostate cancer detection. Specifically, absolute ADC values below 765 ×10 - ⁶ mm²/s serve as robust, independent predictors for csPCa. While ADC Ratio excels in distinguishing benign from malignant lesions, its failure to stratify tumor aggressiveness supports the "field cancerization" hypothesis, suggesting microstructural changes in normal-appearing tissue in malignant conditions. Prostate cancer Multiparametric MRI Diffusion-weighted imaging Apparent diffusion coefficient PI-RADS v2.1 Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 21 Feb, 2026 Reviewers agreed at journal 18 Feb, 2026 Reviewers invited by journal 08 Feb, 2026 Editor assigned by journal 06 Feb, 2026 Editor invited by journal 16 Jan, 2026 Submission checks completed at journal 12 Jan, 2026 First submitted to journal 12 Jan, 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-8502054","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":589351451,"identity":"bf511811-8caa-4e5a-b85d-910c75a84995","order_by":0,"name":"Enes Özel","email":"","orcid":"","institution":"Van Yüzüncü Yıl University","correspondingAuthor":false,"prefix":"","firstName":"Enes","middleName":"","lastName":"Özel","suffix":""},{"id":589351452,"identity":"0a93628d-4ef2-43df-8fdf-3141f9bfb8ca","order_by":1,"name":"İlyas 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15:53:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8502054/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8502054/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102747498,"identity":"9d06c84e-86ec-4041-ac58-b9296c2cde74","added_by":"auto","created_at":"2026-02-16 09:04:52","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":674550,"visible":true,"origin":"","legend":"","description":"","filename":"RevisedManuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8502054/v1_covered_293c46af-ef39-48b7-8d4d-a8f8206983d9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Defining Optimal Cut-offs for Absolute ADC and ADC Ratios in Clinically Significant Prostate Cancer: Correlation with PI-RADS v2.1 and Tumor Aggressiveness","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":"Prostate cancer, Multiparametric MRI, Diffusion-weighted imaging, Apparent diffusion coefficient, PI-RADS v2.1","lastPublishedDoi":"10.21203/rs.3.rs-8502054/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8502054/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo investigate the diagnostic value of apparent diffusion coefficient (ADC) values and ADC ratios (ADC\u003csub\u003e\u003cem\u003eRatio\u003c/em\u003e\u003c/sub\u003e) derived from multiparametric MRI (mpMRI) in differentiating benign from malignant peripheral zone lesions and identifying clinically significant prostate cancer (csPCa). Additionally, the study aims to evaluate the relationship between these quantitative parameters, PI-RADS v2.1 scores, and Gleason scores (GS).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA total of 188 patients who underwent pre-biopsy mpMRI between January 2021 and January 2025 were reviewed retrospectively. Based on histopathology, patients were stratified into Benign (n=126) and Malignant (n=62) groups. The Benign Group included lesion-free (Group 1, n=53) and lesion-positive (Group 2, n=73) cases. The Malignant Group was sub-classified into clinically non-significant (ncsPCa, Group 3, n=28) and significant cancer (csPCa, Group 4, n=34) according to ISUP standards. Age, PSA, prostate volume (PV), PSA density (PSAD), and PI-RADS scores were recorded. Lesion ADC values and ADC\u003csub\u003e\u003cem\u003eRatio\u003c/em\u003e\u003c/sub\u003e\u0026nbsp;(lesion-to-contralateral normal tissue) were calculated.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the study cohort (mean age: 63.36 ± 7.1 years), mean ADC values in the Malignant Group (767 ± 134 ×10\u003csup\u003e-\u003c/sup\u003e⁶ mm²/s) were significantly lower than in benign tissues (1606 ± 283 ×10\u003csup\u003e-\u003c/sup\u003e⁶ mm²/s; p\u0026lt;0.001). For benign-malignant differentiation, an ADC cut-off of 980 ×10\u003csup\u003e-\u003c/sup\u003e⁶ mm²/s yielded 98.4% sensitivity, 96.8% specificity, and an AUC of 0.99; an ADC\u003csub\u003e\u003cem\u003eRatio\u003c/em\u003e\u003c/sub\u003e\u0026nbsp;cut-off of 0.57 yielded an AUC of 0.98. In the csPCa group, mean ADC values (734 ×10\u003csup\u003e-\u003c/sup\u003e⁶ mm²/s) were significantly lower than in the ncsPCa group (807 ×10\u003csup\u003e-\u003c/sup\u003e⁶ mm²/s; p=0.032), with an optimal cut-off determined at 765 ×10\u003csup\u003e-\u003c/sup\u003e⁶ mm²/s. However, ADC\u003csub\u003e\u003cem\u003eRatio\u003c/em\u003e\u003c/sub\u003e\u0026nbsp;did not significantly differ between cancer subgroups (p=0.32). Higher PI-RADS scores were significantly correlated with increased PSAD, lower PV, and higher ISUP grades (p\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLesion ADC values and ADC\u003csub\u003e\u003cem\u003eRatio\u003c/em\u003e\u003c/sub\u003e\u0026nbsp;demonstrate high diagnostic accuracy for prostate cancer detection. Specifically, absolute ADC values below 765 ×10\u003csup\u003e-\u003c/sup\u003e⁶ mm²/s serve as robust, independent predictors for csPCa. While ADC\u003csub\u003e\u003cem\u003eRatio\u003c/em\u003e\u003c/sub\u003e\u0026nbsp;excels in distinguishing benign from malignant lesions, its failure to stratify tumor aggressiveness supports the \"field cancerization\" hypothesis, suggesting microstructural changes in normal-appearing tissue in malignant conditions.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"Defining Optimal Cut-offs for Absolute ADC and ADC Ratios in Clinically Significant Prostate Cancer: Correlation with PI-RADS v2.1 and Tumor Aggressiveness","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-12 18:33:40","doi":"10.21203/rs.3.rs-8502054/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"94511381946514332571053378203945644435","date":"2026-02-21T06:08:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"23375068769825475122283696991306780996","date":"2026-02-19T04:18:34+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-09T04:25:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-06T07:48:18+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-16T10:07:38+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-12T16:49:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Imaging","date":"2026-01-12T16:41:30+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":"631fd4e7-2e84-4e90-bc69-4f37f66d09a5","owner":[],"postedDate":"February 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-12T18:33:40+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-12 18:33:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8502054","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8502054","identity":"rs-8502054","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}