Preoperative estimate of natural ureteral length based on computed tomography and/or plain radiography

• Published in: Scientific reports Vol. 11; no. 1; p. 12202
• Main Authors: Hsu, Jen-Ting, Tseng, Jen-Shu, Chen, Marcelo, Sun, Fang-Ju, Chen, Chien-Wen, Lin, Wun-Rong, Chiang, Pai-Kai, Chiu, Allen W.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 09.06.2021; Nature Publishing Group; Nature Portfolio
• Subjects: 692/4025/1861; 692/698/1864/1861; Bladder; Computed tomography; Hospitals; Humanities and Social Sciences; Image databases; multidisciplinary; Radiography; Regression analysis; Science; Science (multidisciplinary); Spine; Spine (lumbar); Statistical analysis; Ureter; Urogenital system; Urography
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-021-91658-6

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 (UL CTU ) 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 (UL CT ) were collected. UL CTU correlated most strongly with UL CT . 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. UL CTU could be estimated by the regression model in three different scenarios as follows: UL CT  + C-P UL CTUL  = 0.405 × UL CTL + 0.626 × C-P L – 0.508 cm UL CTUR  = 0.558 × UL CTR + 0.218 × C-P R  + 6.533 cm UL CT UL CTUL  = 0.876 × UL CTL + 6.337 cm UL CTUR  = 0.710 × UL CTR + 9.625 cm C-P UL CTUL  = 0.678 × C-P L + 4.836 cm UL CTUR  = 0.495 × C-P R + 10.353 cm We provide equations to predict UL CTU 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.