Quantitative assessment of renal obstruction in multi-phase CTU using automatic 3D segmentation of the renal parenchyma and renal pelvis: A proof of concept

Chanoch Kahn, Isaac Leichter, Richard Lederman, Jacob Sosna, Mordechai Duvdevani, Talia Yeshua*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Purpose: Quantitative evaluation of renal obstruction is crucial for preventing renal atrophy. This study presents a novel method for diagnosing renal obstruction by automatically extracting objective indicators from routine multi-phase CT Urography (CTU). Material and methods: The study included multi-phase CTU examinations of 6 hydronephrotic kidneys and 24 non-hydronephrotic kidneys (23,164 slices). The developed algorithm segmented the renal parenchyma and the renal pelvis of each kidney in each CTU slice. Following a 3D reconstruction of the parenchyma and renal pelvis, the algorithm evaluated the amount of the contrast media in both components in each phase. Finally, the algorithm evaluated two indicators for assessing renal obstruction: the change in the total amount of contrast media in both components during the CTU phases, and the drainage time, "T1/2", from the renal parenchyma. Results: The algorithm segmented the parenchyma and renal pelvis with an average dice coefficient of 0.97 and 0.92 respectively. In all the hydronephrotic kidneys the total amount of contrast media did not decrease during the CTU examination and the T1/2 value was longer than 20 min. Both indicators yielded a statistically significant difference (p < 0.001) between hydronephrotic and normal kidneys, and combining both indicators yielded 100% accuracy. Conclusions: The novel algorithm enables accurate 3D segmentation of the renal parenchyma and pelvis and estimates the amount of contrast media in multi-phase CTU examinations. This serves as a proof-of-concept for the ability to extract from routine CTU indicators that alert to the presence of renal obstruction and estimate its severity.

Original languageAmerican English
Article number100458
JournalEuropean Journal of Radiology Open
Volume9
DOIs
StatePublished - Jan 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2022

Keywords

  • 3D kidney segmentation
  • CT urography
  • Renal obstruction
  • Urine drainage rate

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