{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T17:41:19Z","timestamp":1783705279015,"version":"3.55.0"},"reference-count":36,"publisher":"Georg Thieme Verlag KG","issue":"04","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Rofo"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>PSA density (PSAd), based on prostate volume (PV), is a decision-making parameter for prostate cancer (PCa) diagnosis and risk stratification. We assessed variability in prostate manual segmentation on MRI and its impact on PV and PSAd.<\/jats:p>\n                  <jats:p>We retrospectively analyzed 68 treatment-na\u00efve patients, aged 66.2\u00b16.9 years, with increased PSA and\/or positive digital endorectal examination who underwent MRI, with available biopsy\/follow-up. Three radiologists (R1, R2, R3) manually segmented the gland on T2-weighted images slice-by-slice. Dice similarity coefficient (DSC), Welch\u2019s t-test, and 95% confidence intervals (CIs) were used.<\/jats:p>\n                  <jats:p>Of 68 patients with a PSA of 7.59\u00b14.80 ng\/mL, 38 had biopsy-confirmed PCa, and the remaining 30 were negative on biopsy\/follow-up. The segmentation time per patient ranged from 4 to 7 min. Pairs R1-R2, R1-R3, and R2-R3 showed a different number of segmented slices (p&lt;0.001) and PV (p&lt;0.001). DSC for prostate gland segmentation ranged from 0.871 to 0.890. An outlier (prostatitis with PSA 35 ng\/mL) was excluded from PSA\/PSAd analysis. Based on segmentation by R1, the PSA was 7.37\u00b13.70 ng\/mL and PSAd was 0.124\u00b10.070 ng\/mL\/mL in the 38 patients with PCa, while these values were 6.91\u00b12.79 ng\/mL and 0.111\u00b10.062 ng\/mL\/mL, respectively, in the 29 patients without PCa. Using the threshold of \u22650.15 ng\/mL\/mL, variations in segmented PV impacted PSAd-based classification, resulting in 1 false negative for R1 and another false negative for R2 (false-negative rate for both 1\/38, 2.63%, 95% CI 0.10\u201313.8%).<\/jats:p>\n                  <jats:p>Segmentation of PV is a time-intensive task. Inter-reader variability can impact PSAd-based diagnosis of PCa. Automated prostate segmentation methods are welcome.<\/jats:p>","DOI":"10.1055\/a-2624-7634","type":"journal-article","created":{"date-parts":[[2025,6,23]],"date-time":"2025-06-23T18:58:06Z","timestamp":1750705086000},"page":"508-515","source":"Crossref","is-referenced-by-count":1,"title":["Variability of segmented prostate volume on MRI: impact on PSA density for prostate cancer diagnosis"],"prefix":"10.1055","volume":"198","author":[{"given":"Anna","family":"Colarieti","sequence":"additional","affiliation":[{"name":"Department of Radiology, University of Eastern Piedmont Amedeo Avogadro School of Medicine, Novara, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alessandro","family":"Venturi","sequence":"additional","affiliation":[{"name":"DeepTrace Technologies s.r.l., Milan, Italy, DeepTrace Technologies s.r.l., Milano, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0089-2905","authenticated-orcid":false,"given":"Massimo","family":"Cressoni","sequence":"additional","affiliation":[{"name":"Department of Radiology, Policlinico San Donato, San Donato Milanese, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matteo","family":"Interlenghi","sequence":"additional","affiliation":[{"name":"DeepTrace Technologies s.r.l., Milan, Italy, DeepTrace Technologies s.r.l., Milano, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Moreno","family":"Zanardo","sequence":"additional","affiliation":[{"name":"Department of Radiology, San Donato Hospital Group, Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Isabella","family":"Castiglioni","sequence":"additional","affiliation":[{"name":"Department of Physics \u201cG. Occhialini\u201d, Universit\u00e0 degli Studi di Milano-Bicocca, Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesco","family":"Sardanelli","sequence":"additional","affiliation":[{"name":"Italian League for the Fight against Tumors (LILT) Milan Monza Brianza, Italian League for the Fight against Tumors (LILT) Milan Monza Brianza, Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"194","published-online":{"date-parts":[[2025,6,23]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"209","DOI":"10.3322\/caac.21660.","article-title":"Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries","volume":"71","author":"H Sung","year":"2021","journal-title":"CA Cancer J Clin"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1002\/ijc.33588.","article-title":"Cancer statistics for the year 2020: An overview","author":"J 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A comparison between PSA, palpation and echography in 95 patients undergoing echo-guided endorectal prostatic biopsy","volume":"85","author":"A Di Donna","year":"1993","journal-title":"Radiol Med"},{"key":"ref33","doi-asserted-by":"publisher","first-page":"438","DOI":"10.1016\/j.eururo.2014.11.037.","article-title":"Magnetic resonance imaging-targeted biopsy may enhance the diagnostic accuracy of significant prostate cancer detection compared to standard transrectal ultrasound-guided biopsy: a systematic review and meta-analysis","volume":"68","author":"IG Schoots","year":"2015","journal-title":"Eur Urol"},{"key":"ref34","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1016\/j.euf.2022.10.002.","article-title":"Prostate-specific Antigen Density Cutoff of 0.15 ng\/ml\/cc to Propose Prostate Biopsies to Patients with Negative Magnetic Resonance Imaging: Efficient Threshold or Legacy of the Past?","volume":"9","author":"F Pellegrino","year":"2023","journal-title":"Eur Urol Focus"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics12020289.","article-title":"Machine Learning in Prostate MRI for Prostate Cancer: Current Status and Future Opportunities","volume":"12","author":"H Li","year":"2022","journal-title":"Diagnostics (Basel)"},{"key":"ref36","doi-asserted-by":"publisher","first-page":"3696","DOI":"10.1007\/s00261-024-04423-4.","article-title":"Emerging and anticipated innovations in prostate cancer MRI and their impact on patient care","volume":"49","author":"ETO Correia","year":"2024","journal-title":"Abdom Radiol (NY)"}],"container-title":["R\u00f6Fo - Fortschritte auf dem Gebiet der R\u00f6ntgenstrahlen und der bildgebenden Verfahren"],"original-title":[],"language":"de","link":[{"URL":"http:\/\/www.thieme-connect.de\/products\/ejournals\/pdf\/10.1055\/a-2624-7634.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T23:53:14Z","timestamp":1774569194000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.thieme-connect.de\/DOI\/DOI?10.1055\/a-2624-7634"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,23]]},"references-count":36,"journal-issue":{"issue":"04","published-online":{"date-parts":[[2026,3,26]]},"published-print":{"date-parts":[[2026,4]]}},"URL":"https:\/\/doi.org\/10.1055\/a-2624-7634","archive":["Portico","CLOCKSS"],"relation":{},"ISSN":["1438-9029","1438-9010"],"issn-type":[{"value":"1438-9029","type":"print"},{"value":"1438-9010","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,23]]}}}