{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T19:12:19Z","timestamp":1792869139807,"version":"4.5.0"},"reference-count":48,"publisher":"SAGE Publications","issue":"8","license":[{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Endourology"],"published-print":{"date-parts":[[2024,8]]},"abstract":"<jats:sec>\n                    <jats:title>Objectives:<\/jats:title>\n                    <jats:p>To perform a systematic review on artificial intelligence (AI) performances to detect urinary stones.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>A PROSPERO-registered (CRD473152) systematic search of Scopus, Web of Science, Embase, and PubMed databases was performed to identify original research articles pertaining to AI stone detection or measurement, using search terms (\u201cautomatic\u201d OR \u201cmachine learning\u201d OR \u201cconvolutional neural network\u201d OR \u201cartificial intelligence\u201d OR \u201cdetection\u201d AND \u201cstone volume\u201d). Risk-of-bias (RoB) assessment was performed according to the Cochrane RoB tool, the Joanna Briggs Institute Checklist for nonrandomized studies, and the Checklist for Artificial Intelligence in Medical Imaging (CLAIM).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>\n                      Twelve studies were selected for the final review, including three multicenter and nine single-center retrospective studies. Eleven studies completed at least 50% of the CLAIM checkpoints and only one presented a high RoB. All included studies aimed to detect kidney (5\/12, 42%), ureter (2\/12, 16%), or urinary (5\/12, 42%) stones on noncontrast computed tomography (NCCT), but 42% intended to automate measurement. Stone distinction from vascular calcification interested two studies. All studies used AI machine learning network training and internal validation, but a single one provided an external validation. Trained networks achieved stone detection, with sensitivity, specificity, and accuracy rates ranging from 58.7% to 100%, 68.5% to 100%, and 63% to 99.95%, respectively. Detection Dice score ranged from 83% to 97%. A high correlation between manual and automated stone volume (\n                      <jats:italic toggle=\"yes\">r<\/jats:italic>\n                      \u2009=\u20090.95) was noted. Differentiate distal ureteral stones and phleboliths seemed feasible.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>AI processes can achieve automated urinary stone detection from NCCT. Further studies should provide urinary stone detection coupled with phlebolith distinction and an external validation, and include anatomical abnormalities and urologic foreign bodies (ureteral stent and nephrostomy tubes) cases.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1089\/end.2023.0717","type":"journal-article","created":{"date-parts":[[2024,4,26]],"date-time":"2024-04-26T08:06:39Z","timestamp":1714118799000},"page":"725-740","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":16,"title":["Can Artificial Intelligence Accurately Detect Urinary Stones? A Systematic Review"],"prefix":"10.1177","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3055-2984","authenticated-orcid":false,"given":"Fr\u00e9d\u00e9ric","family":"Panthier","sequence":"first","affiliation":[{"name":"Department of Urology, Westmoreland Street Hospital, UCLH NHS Foundation Trust, London, United Kingdom."},{"name":"Sorbonne University GRC Urolithiasis No. 20 Tenon Hospital, Paris, France."},{"name":"Progressive Endourological Association for Research and Leading Solutions (PEARLS), Paris, France."},{"name":"PIMM, UMR 8006 CNRS-Arts et M\u00e9tiers ParisTech, Paris, France."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alberto","family":"Melchionna","sequence":"additional","affiliation":[{"name":"Department of Urology, Westmoreland Street Hospital, UCLH NHS Foundation Trust, London, United Kingdom."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hugh","family":"Crawford-Smith","sequence":"additional","affiliation":[{"name":"Department of Urology, Westmoreland Street Hospital, UCLH NHS Foundation Trust, London, United Kingdom."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiannis","family":"Phillipou","sequence":"additional","affiliation":[{"name":"Department of Urology, Westmoreland Street Hospital, UCLH NHS Foundation Trust, London, United Kingdom."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simon","family":"Choong","sequence":"additional","affiliation":[{"name":"Department of Urology, Westmoreland Street Hospital, UCLH NHS Foundation Trust, London, United Kingdom."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vimoshan","family":"Arumuham","sequence":"additional","affiliation":[{"name":"Department of Urology, Westmoreland Street Hospital, UCLH NHS Foundation Trust, London, United Kingdom."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sian","family":"Allen","sequence":"additional","affiliation":[{"name":"Department of Urology, Westmoreland Street Hospital, UCLH NHS Foundation Trust, London, United Kingdom."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Clare","family":"Allen","sequence":"additional","affiliation":[{"name":"Department of Radiology, University College London Hospitals, London, United Kingdom."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daron","family":"Smith","sequence":"additional","affiliation":[{"name":"Department of Urology, Westmoreland Street Hospital, UCLH NHS Foundation Trust, London, United Kingdom."},{"name":"Endourology Academy."},{"name":"Social Media Committee, Endourological Society."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2024,8,1]]},"reference":[{"key":"e_1_3_5_2_2","doi-asserted-by":"publisher","DOI":"10.3390\/healthcare11030424"},{"key":"e_1_3_5_3_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0709652105"},{"key":"e_1_3_5_4_2","unstructured":"Recommendations | Renal and Ureteric Stones: Assessment and Management | Guidance | NICE. NICE; 2019. Available from: https:\/\/www.nice.org.uk\/guidance\/ng118\/chapter\/Recommendations#diagnostic-imaging [Last accessed: February7 2023]."},{"key":"e_1_3_5_5_2","doi-asserted-by":"publisher","DOI":"10.1111\/bju.15936"},{"key":"e_1_3_5_6_2","doi-asserted-by":"publisher","DOI":"10.1093\/mind\/LIX.236.433"},{"key":"e_1_3_5_7_2","unstructured":"Chollet F. Deep Learning with Python. Manning Publications Co: Shelter Island NY; 2018."},{"key":"e_1_3_5_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eururo.2015.07.041"},{"key":"e_1_3_5_9_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1000100"},{"key":"e_1_3_5_10_2","unstructured":"JBI Critical Appraisal Tools | JBI. Available from: https:\/\/jbi.global\/critical-appraisal-tools [Last accessed: October 16 2023]."},{"key":"e_1_3_5_11_2","unstructured":"Risk of bias tools\u2014Robvis (visualization tool). Available from: https:\/\/www.riskofbias.info\/welcome\/robvis-visualization-tool [Last accessed: October 31 2023]."},{"key":"e_1_3_5_12_2","doi-asserted-by":"publisher","DOI":"10.1148\/ryai.2020200029"},{"key":"e_1_3_5_13_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-009-9181-0"},{"key":"e_1_3_5_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2018.04.021"},{"key":"e_1_3_5_15_2","doi-asserted-by":"publisher","DOI":"10.1148\/ryai.2019180066"},{"key":"e_1_3_5_16_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11307-020-01554-0"},{"key":"e_1_3_5_17_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00240-020-01180-z"},{"key":"e_1_3_5_18_2","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics12081788"},{"key":"e_1_3_5_19_2","doi-asserted-by":"publisher","DOI":"10.1590\/S1677-5538.IBJU.2022.0132"},{"key":"e_1_3_5_20_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.urology.2022.07.029"},{"key":"e_1_3_5_21_2","doi-asserted-by":"publisher","DOI":"10.1002\/mp.15518"},{"key":"e_1_3_5_22_2","doi-asserted-by":"publisher","DOI":"10.5213\/inj.2346070.035"},{"key":"e_1_3_5_23_2","doi-asserted-by":"publisher","DOI":"10.1089\/end.2022.0722"},{"key":"e_1_3_5_24_2","doi-asserted-by":"publisher","DOI":"10.1089\/end.2023.0066"},{"key":"e_1_3_5_25_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00240-020-01212-8"},{"key":"e_1_3_5_26_2","unstructured":"CDC. ALARA\u2014As Low As Reasonably Achievable. 2022. Available from: https:\/\/www.cdc.gov\/nceh\/radiation\/alara.html [Last accessed: October30 2023]."},{"key":"e_1_3_5_27_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.zemedi.2022.12.002"},{"key":"e_1_3_5_28_2","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.07.3414"},{"key":"e_1_3_5_29_2","doi-asserted-by":"publisher","DOI":"10.1038\/nrurol.2016.154"},{"key":"e_1_3_5_30_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.juro.2009.08.042"},{"key":"e_1_3_5_31_2","doi-asserted-by":"publisher","DOI":"10.23736\/S0393-2249.18.03265-4"},{"key":"e_1_3_5_32_2","doi-asserted-by":"publisher","DOI":"10.1016\/s0221-0363(04)97596-8"},{"key":"e_1_3_5_33_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.euf.2020.06.003"},{"key":"e_1_3_5_34_2","unstructured":"Anonymous. Horos Project\u2014Free DICOM Medical Image Viewer. 2020. Available from: https:\/\/horosproject.org\/ [Last accessed: January28 2020]."},{"key":"e_1_3_5_35_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.mri.2012.05.001"},{"key":"e_1_3_5_36_2","doi-asserted-by":"publisher","DOI":"10.1089\/end.2018.0326"},{"key":"e_1_3_5_37_2","unstructured":"Anonymous. Keras U-Net Starter\u2014LB 0.277. 2019. Available from: https:\/\/kaggle.com\/keegil\/keras-u-net-starter-lb-0-277 [Last accessed: October23 2019]."},{"key":"e_1_3_5_38_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.juro.2008.11.116"},{"key":"e_1_3_5_39_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.aju.2016.06.006"},{"key":"e_1_3_5_40_2","doi-asserted-by":"publisher","DOI":"10.3390\/jcm12196274"},{"key":"e_1_3_5_41_2","unstructured":"Anonymous. Understanding Dice Coefficient. Available from: https:\/\/kaggle.com\/code\/yerramvarun\/understanding-dice-coefficient [Last accessed: October30 2023]."},{"key":"e_1_3_5_42_2","unstructured":"Anonymous. The Basics of Classifier Evaluation: Part 1. 2015. Available from: https:\/\/www.svds.com\/the-basics-of-classifier-evaluation-part-1\/ [Last accessed: October30 2023]"},{"key":"e_1_3_5_43_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.euros.2022.09.024"},{"key":"e_1_3_5_44_2","doi-asserted-by":"publisher","DOI":"10.1097\/RLI.0000000000001034"},{"key":"e_1_3_5_45_2","doi-asserted-by":"publisher","DOI":"10.1136\/bmjoq-2022-002168"},{"key":"e_1_3_5_46_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-023-10213-1"},{"key":"e_1_3_5_47_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41585-023-00796-1"},{"key":"e_1_3_5_48_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.acuroe.2023.08.009"},{"key":"e_1_3_5_49_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00345-021-03671-z"}],"container-title":["Journal of Endourology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1089\/end.2023.0717","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1089\/end.2023.0717","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1089\/end.2023.0717","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T20:16:05Z","timestamp":1777407365000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1089\/end.2023.0717"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8]]},"references-count":48,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2024,8]]}},"alternative-id":["10.1089\/end.2023.0717"],"URL":"https:\/\/doi.org\/10.1089\/end.2023.0717","relation":{},"ISSN":["0892-7790","1557-900X"],"issn-type":[{"value":"0892-7790","type":"print"},{"value":"1557-900X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8]]}}}