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Two- and three-dimensional CT measurements of urinary calculi length and width: a comparative study
Linköping University, Center for Medical Image Science and Visualization (CMIV). University of Örebro, Sweden.
University of Örebro, Sweden.
University of Örebro, Sweden.
University of Örebro, Sweden.
2015 (English)In: Acta Radiologica, ISSN 0284-1851, E-ISSN 1600-0455, Vol. 56, no 4, 487-492 p.Article in journal (Refereed) Published
Abstract [en]

Background: The standard imaging procedure for a patient presenting with renal colic is unenhanced computed tomography (CT). The CT measured size has a close correlation to the estimated prognosis for spontaneous passage of a ureteral calculus. Size estimations of urinary calculi in CT images are still based on two-dimensional (2D) reformats. Purpose: To develop and validate a calculus oriented three-dimensional (3D) method for measuring the length and width of urinary calculi and to compare the calculus oriented measurements of the length and width with corresponding 2D measurements obtained in axial and coronal reformats. Material and Methods: Fifty unenhanced CT examinations demonstrating urinary calculi were included. A 3D symmetric segmentation algorithm was validated against reader size estimations. The calculus oriented size from the segmentation was then compared to the estimated size in axial and coronal 2D reformats. Results: The validation showed 0.1 +/- 0.7mm agreement against reference measure. There was a 0.4mm median bias for 3D estimated calculus length compared to 2D (P less than 0.001), but no significant bias for 3D width compared to 2D. Conclusion: The length of a calculus in axial and coronal reformats becomes underestimated compared to 3D if its orientation is not aligned to the image planes. Future studies aiming to correlate calculus size with patient outcome should use a calculus oriented size estimation.

Place, publisher, year, edition, pages
SAGE Publications (UK and US) , 2015. Vol. 56, no 4, 487-492 p.
Keyword [en]
Urinary; CT; ureter; kidney; segmentation; computer applications-3D
National Category
Medical Image Processing
URN: urn:nbn:se:liu:diva-117365DOI: 10.1177/0284185114528490ISI: 000351594300015PubMedID: 24646626OAI: diva2:807868

Funding Agencies|Forskningskommitten, Orebro County Council, Sweden

Available from: 2015-04-24 Created: 2015-04-24 Last updated: 2016-01-07

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