{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T11:09:00Z","timestamp":1791976140224,"version":"4.4.0"},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,6,9]],"date-time":"2021-06-09T00:00:00Z","timestamp":1623196800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,6,9]],"date-time":"2021-06-09T00:00:00Z","timestamp":1623196800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"abstract":"Abstract<\/jats:title>To predict natural ureter lengths based on clinical images. We reviewed our image database of patients who underwent multiphasic computed tomography urography from January 2019 to April 2020. Natural ureteral length (ULCTU<\/jats:sub>) was measured using a three-dimensional curved multiplanar reformation technique. Patient parameters including age, height, and height of the lumbar spine, the index of ureteral length using kidney\/ureter\/bladder (KUB) radiographs (C-P and C-PS) and computed tomography (ULCT<\/jats:sub>) were collected. ULCTU<\/jats:sub> correlated most strongly with ULCT<\/jats:sub>. R square and adjusted R square values from multivariate regression were 0.686 and 0.678 (left side) and 0.516 and 0.503 (right side), respectively. ULCTU<\/jats:sub> could be estimated by the regression model in three different scenarios as follows:\n \n ULCT<\/jats:sub>\u2009+\u2009C-P\n \n ULCTUL<\/jats:sub>\u2009=\u20090.405 $$\\times$$<\/jats:tex-math>\n \u00d7<\/mml:mo>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula> ULCTL<\/jats:sub>$$+$$<\/jats:tex-math>\n +<\/mml:mo>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula> 0.626 $$\\times$$<\/jats:tex-math>\n \u00d7<\/mml:mo>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula> C-PL<\/jats:sub> \u2013 0.508\u00a0cm<\/jats:p>\n <\/jats:list-item>\n \n ULCTUR<\/jats:sub>\u2009=\u20090.558 $$\\times$$<\/jats:tex-math>\n \u00d7<\/mml:mo>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula> ULCTR<\/jats:sub>$$+$$<\/jats:tex-math>\n +<\/mml:mo>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula> 0.218 $$\\times$$<\/jats:tex-math>\n \u00d7<\/mml:mo>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula> C-PR<\/jats:sub>\u2009+\u20096.533\u00a0cm<\/jats:p>\n <\/jats:list-item>\n <\/jats:list><\/jats:p>\n <\/jats:list-item>\n \n ULCT<\/jats:sub>\n \n ULCTUL<\/jats:sub>\u2009=\u20090.876 $$\\times$$<\/jats:tex-math>\n \u00d7<\/mml:mo>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula> ULCTL<\/jats:sub>$$+$$<\/jats:tex-math>\n +<\/mml:mo>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula> 6.337\u00a0cm<\/jats:p>\n <\/jats:list-item>\n \n ULCTUR<\/jats:sub>\u2009=\u20090.710 $$\\times$$<\/jats:tex-math>\n \u00d7<\/mml:mo>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula> ULCTR<\/jats:sub>$$+$$<\/jats:tex-math>\n +<\/mml:mo>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula> 9.625\u00a0cm<\/jats:p>\n <\/jats:list-item>\n <\/jats:list><\/jats:p>\n <\/jats:list-item>\n \n C-P\n \n ULCTUL<\/jats:sub>\u2009=\u20090.678 $$\\times$$<\/jats:tex-math>\n \u00d7<\/mml:mo>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula> C-PL<\/jats:sub>$$+$$<\/jats:tex-math>\n +<\/mml:mo>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula> 4.836\u00a0cm<\/jats:p>\n <\/jats:list-item>\n \n ULCTUR<\/jats:sub>\u2009=\u20090.495 $$\\times$$<\/jats:tex-math>\n \u00d7<\/mml:mo>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula> C-PR<\/jats:sub>$$+$$<\/jats:tex-math>\n +<\/mml:mo>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula> 10.353\u00a0cm<\/jats:p>\n <\/jats:list-item>\n <\/jats:list><\/jats:p>\n <\/jats:list-item>\n <\/jats:list>We provide equations to predict ULCTU<\/jats:sub> based on CT, KUB or CT plus KUB for different clinical scenarios. The formula based on CT plus KUB provided the most accurate estimation, while the others had lower validation values but could still meet clinical needs.<\/jats:p>","DOI":"10.1038\/s41598-021-91658-6","type":"journal-article","created":{"date-parts":[[2021,6,9]],"date-time":"2021-06-09T10:16:45Z","timestamp":1623233805000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Preoperative estimate of natural ureteral length based on computed tomography and\/or plain radiography"],"prefix":"10.1038","volume":"11","author":[{"given":"Jen-Ting","family":"Hsu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jen-Shu","family":"Tseng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marcelo","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fang-Ju","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chien-Wen","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wun-Rong","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pai-Kai","family":"Chiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Allen W.","family":"Chiu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,6,9]]},"reference":[{"key":"91658_CR1","doi-asserted-by":"publisher","first-page":"840","DOI":"10.1016\/s0022-5347(17)63130-6","volume":"97","author":"PD Zimskind","year":"1967","unstructured":"Zimskind, P. 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