Evaluation of Automated Volumetric Cartilage Quantification for Hip Preservation Surgery

Austin J. Ramme, Michael S. Guss, Shaleen Vira, Jonathan M. Vigdorchik, Axel Newe, Esther Raithel, Gregory Chang

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Automating the process of femoroacetabular cartilage identification from magnetic resonance imaging (MRI) images has important implications to guiding clinical care by providing a temporal metric that allows for optimizing the timing for joint preservation surgery. In this paper, we evaluate a new automated cartilage segmentation method using a time trial, segmented volume comparison, overlap metrics, and Euclidean distance mapping. We report interrater overlap metrics using the true fast imaging with steady-state precession MRI sequence of 0.874, 0.546, and 0.704 for the total overlap, union overlap, and mean overlap, respectively. This method was 3.28 × faster than manual segmentation. This technique provides clinicians with volumetric cartilage information that is useful for optimizing the timing for joint preservation procedures.

Original languageEnglish (US)
Pages (from-to)64-69
Number of pages6
JournalJournal of Arthroplasty
Volume31
Issue number1
DOIs
StatePublished - Jan 1 2016
Externally publishedYes

Keywords

  • Automated segmentation
  • Cartilage evaluation
  • Interrater
  • Magnetic resonance imaging
  • Variability

ASJC Scopus subject areas

  • Orthopedics and Sports Medicine

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