Persistent homology approach distinguishes potential pattern between "early" and "not Early" hepatic decompensation groups using MRI modalities

Yashbir Singh, William Jons, Gian Marco Conte, Jaidip Jagtap, Kuan Zhang, Joseph D. Sobek, Pouria Rouzrokh, John E. Eaton, Bradley J. Erickson

Research output: Contribution to journalArticlepeer-review

Abstract

Primary sclerosis cholangitis (PSC) predisposes individuals to liver failure, but it is challenging for radiologists examining radiologic images to predict which patients with PSC will ultimately develop liver failure. Motivated by algebraic topology, a topological data analysis - inspired framework was adopted in the study of the imaging pattern between the "Early Decompensation"and "Not Early"groups. The results demonstrate that the proposed methodology discriminates "Early Decompensation"and "Not Early"groups. Our study is the first attempt to provide a topological representation-based method into early hepatic decompensation and not early groups.

Original languageEnglish (US)
Pages (from-to)488-491
Number of pages4
JournalCurrent Directions in Biomedical Engineering
Volume7
Issue number2
DOIs
StatePublished - Oct 1 2021

Keywords

  • Hepatic decompensation
  • Persistent Homology
  • Primary sclerosing cholangitis
  • Topological data analysis

ASJC Scopus subject areas

  • Biomedical Engineering

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