Skeletonization of renal cysts of autosomal dominant polycystic kidney disease using magnetic resonance imaging

Sayaka Teranaka, Takuro Ishii, Yoshihisa Matsunaga, Akihiro Koyama, Koichi Kamura, Shinichi Sakamoto, Tomohiko Ichikawa, Tatsuo Igarashi

Research output: Contribution to journalArticlepeer-review

Abstract

Autosomal dominant polycystic kidney disease (ADPKD) is a condition in which numerous cysts develop in the renal tubules and grows over the lifetime, resulting in compression of renal parenchyma and worsens renal function. Conventionally, total kidney volume (TKV) is bluntly estimated as a time cross sectional parameter of disease status. In assumption that cyst initiation rate and growth speed of cysts would be another prognostic marker for renal function, and regulate the morphological feature of the enlarged kidney, we attempted to extract a morphological feature of the renal cystic region quantitatively from MRI T2-weighted images. Skeletonization algorithm was applied to the binarized cystic region after extracting cystic regions by discriminant analysis. Then, morphological feature of the renal cystic region was converted to distribution pattern in number and size of cysts, and "branch" of adjacent cysts. The number of "branches" corresponded with the number of cysts, and the cumulative probability curves of "branch" length shifted according to cyst size distribution. The proposed method successfully quantified morphological feature of cystic region objectively in semi-automatic manner. The method would contribute to manage ADPKD patients in deciding time to start therapies after affirmation for consistency with cyst initiation rate, growth speed of cysts and renal function.

Original languageEnglish
Pages (from-to)568-573
Number of pages6
JournalJournal of Medical Imaging and Health Informatics
Volume7
Issue number3
DOIs
Publication statusPublished - 2017 Jun
Externally publishedYes

Keywords

  • ADPKD
  • Cyst initiation rate
  • Growth speed of cysts
  • Magnetic resonance imaging
  • Renal cysts
  • Skeletonization algorithm

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Health Informatics

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