{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T16:14:05Z","timestamp":1787242445276,"version":"build-2736575974"},"reference-count":58,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T00:00:00Z","timestamp":1724284800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Introduction: Measuring elevated post-void residual volume is important for diagnosing urinary outflow tract obstruction and cauda equina syndrome. Catheter placement is exact but painful, invasive, and may cause infection, whereas an ultrasound is accurate, painless, and safe. Aim: The purpose of this single-center study is to evaluate the accuracy of a module for artificial-intelligence (AI)-based fully automated bladder volume (BV) prospective measurement using two-dimensional ultrasound images, as compared with manual measurement by expert sonographers. Methods: Pairs of transverse and longitudinal bladder images were obtained from patients evaluated in an urgent care clinic. The scans were prospectively analyzed by the automated module using the prolate ellipsoid method. The same examinations were manually measured by a blinded expert sonographer. The two methods were compared using the Pearson correlation, kappa coefficients, and the Bland\u2013Altman method. Results: A total of 111 pairs of transverse and longitudinal views were included. A very strong correlation was found between the manual BV measurements and the AI-based module with r = 0.97 [95% CI: 0.96\u20130.98]. The specificity and sensitivity for the diagnosis of an elevated post-void residual volume using a threshold \u2265200 mL were 1.00 and 0.82, respectively. An almost-perfect agreement between manual and automated methods was obtained (kappa = 0.85). Perfect reproducibility was found for both inter- and intra-observer agreements. Conclusion: This AI-based module provides an accurate automated measurement of the BV based on ultrasound images. This novel method demonstrates a very strong correlation with the gold standard, making it a potentially valuable decision-support tool for non-experts in acute settings.<\/jats:p>","DOI":"10.3390\/diagnostics14161829","type":"journal-article","created":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T03:07:38Z","timestamp":1724296058000},"page":"1829","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Revolutionizing Bladder Health: Artificial-Intelligence-Powered Automatic Measurement of Bladder Volume Using Two-Dimensional Ultrasound"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1708-5058","authenticated-orcid":false,"given":"Evan Avraham","family":"Alpert","sequence":"first","affiliation":[{"name":"Department of Emergency Medicine, Eisenberg R&D Authority, Shaare Zedek Medical Center, Jerusalem 9112001, Israel"},{"name":"Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 9190500, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1830-1031","authenticated-orcid":false,"given":"Daniel David","family":"Gold","sequence":"additional","affiliation":[{"name":"Department of Emergency Medicine, Eisenberg R&D Authority, Shaare Zedek Medical Center, Jerusalem 9112001, Israel"},{"name":"Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 9190500, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deganit","family":"Kobliner-Friedman","sequence":"additional","affiliation":[{"name":"Department of Emergency Medicine, Eisenberg R&D Authority, Shaare Zedek Medical Center, Jerusalem 9112001, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Wagner","sequence":"additional","affiliation":[{"name":"Division of Hospital Medicine, Department of Medicine, Prisma Health Greenville Memorial Hospital, 701 Grove Rd, Greenville, SC 29605, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8497-0423","authenticated-orcid":false,"given":"Ziv","family":"Dadon","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 9190500, Israel"},{"name":"Jesselson Integrated Heart Center, Eisenberg R&D Authority, Shaare Zedek Medical Center, Jerusalem 9112001, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1002\/jcu.23619","article-title":"Diagnostic accuracy of Point of Care UltraSound (POCUS) in clinical practice: A retrospective, emergency department based study","volume":"52","author":"Spampinato","year":"2024","journal-title":"J. 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