Literature DB >> 10352582

Ureterolithiasis: value of the tail sign in differentiating phleboliths from ureteral calculi at nonenhanced helical CT.

I C Boridy1, P Nikolaidis, A Kawashima, S M Goldman, C M Sandler.   

Abstract

PURPOSE: To determine the value of the tail sign in differentiating phleboliths from ureteral calculi at nonenhanced helical computed tomography (CT).
MATERIALS AND METHODS: The nonenhanced helical CT scans in 82 patients with a confirmed diagnosis of pelvic ureterolithiasis were retrospectively reviewed. Each calcification along the ureter was classified as a phlebolith or a ureteral calculus on the basis of clinical and imaging findings and was analyzed for the presence of a tail sign.
RESULTS: Eighty-two patients each had a single ureteral calculus. None of these calculi were associated with a positive tail sign. Sixty-nine phleboliths were present in 35 patients. Forty-five phleboliths (65%) were associated with a positive tail sign. Of the remaining 24 phleboliths, 17 (25%) were associated with a negative tail sign and seven (10%) were indeterminate. The tail sign has a sensitivity of 65% (45 of 69; 95% CI: 53%, 75%) and a specificity of 100% (82 of 82; 95% CI: 96%, 100%) in differentiating phleboliths from ureteral calculi.
CONCLUSION: The tail sign is an important indicator that a suspicious calcification represents a phlebolith. Absence of the tail sign indicates that the calcification remains indeterminate.

Entities:  

Mesh:

Year:  1999        PMID: 10352582     DOI: 10.1148/radiology.211.3.r99ma44619

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  8 in total

1.  Distinguishing pelvic phleboliths from distal ureteral calculi: thin-slice CT findings.

Authors:  Mehmet Arac; Halil Celik; A Yusuf Oner; Serap Gultekin; Terman Gumus; Sule Kosar
Journal:  Eur Radiol       Date:  2004-09-22       Impact factor: 5.315

Review 2.  [Imaging techniques and their impact in treatment management of patients with acute flank pain].

Authors:  A Grosse; C A Grosse; J Mauermann; G Heinz-Peer
Journal:  Radiologe       Date:  2005-10       Impact factor: 0.635

3.  Differentiating kidney stones from phleboliths in unenhanced low-dose computed tomography using radiomics and machine learning.

Authors:  Thomas De Perrot; Jeremy Hofmeister; Simon Burgermeister; Steve P Martin; Gregoire Feutry; Jacques Klein; Xavier Montet
Journal:  Eur Radiol       Date:  2019-02-12       Impact factor: 5.315

Review 4.  Soft-tissue masses and masslike conditions: what does CT add to diagnosis and management?

Authors:  Ty K Subhawong; Elliot K Fishman; Jennifer E Swart; John A Carrino; Samer Attar; Laura M Fayad
Journal:  AJR Am J Roentgenol       Date:  2010-06       Impact factor: 3.959

5.  Differentiation of ureteral stones and phleboliths using Hounsfield units on computerized tomography: a new method without observer bias.

Authors:  Yiloren Tanidir; Ahmet Sahan; Mehmet Kazim Asutay; Tarik Emre Sener; Farhad Talibzade; Asgar Garayev; Ilker Tinay; Cagri Akin Sekerci; Ferruh Simsek
Journal:  Urolithiasis       Date:  2016-09-16       Impact factor: 3.436

6.  Differentiation of distal ureteral stones and pelvic phleboliths using a convolutional neural network.

Authors:  Johan Jendeberg; Per Thunberg; Mats Lidén
Journal:  Urolithiasis       Date:  2020-02-27       Impact factor: 3.436

Review 7.  Multidetector CT urography in imaging of the urinary tract in patients with hematuria.

Authors:  Michael M Maher; Mannudeep K Kalra; Stefania Rizzo; Peter R Mueller; Sanjay Saini
Journal:  Korean J Radiol       Date:  2004 Jan-Mar       Impact factor: 3.500

8.  Low-Dose Unenhanced Computed Tomography with Iterative Reconstruction for Diagnosis of Ureter Stones.

Authors:  Byung Hoon Chi; In Ho Chang; Dong Hoon Lee; Sung Bin Park; Kyung Do Kim; Young Tae Moon; Taekyu Hur
Journal:  Yonsei Med J       Date:  2018-05       Impact factor: 2.759

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.