Automatic quantification of bone marrow edema on MRI of the wrist in patients with early arthritis

A feasibility study

Journal article (2018)

Authors

Evgeni Aizenberg Leiden University Medical Center
Edgar A.H. Roex Leiden University Medical Center
Wouter P. Nieuwenhuis Leiden University Medical Center
Lukas Mangnus Leiden University Medical Center
Annette H.M. van der Helm-van Mil Leiden University Medical Center
Monique Reijnierse Leiden University Medical Center
Johan L. Bloem Leiden University Medical Center
B.P.F. Lelieveldt Pattern Recognition and Bioinformatics - EEMCS , Leiden University Medical Center
Berend G. Stoel Leiden University Medical Center
Research Group
Pattern Recognition and Bioinformatics (EEMCS) (TU Delft)
Copyright: © 2018 Evgeni Aizenberg, Edgar A.H. Roex, Wouter P. Nieuwenhuis, Lukas Mangnus, Annette H.M. van der Helm-Mil, Monique Reijnierse, Johan L. Bloem, B.P.F. Lelieveldt, Berend G. Stoel
DOI: https://doi.org/10.1002/mrm.26712
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Published Date

2018

Language

English

Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Intelligent Systems

Research Group

Pattern Recognition and Bioinformatics

Abstract

Purpose: To investigate the feasibility of automatic quantification of bone marrow edema (BME) on MRI of the wrist in patients with early arthritis.
Methods: For 485 early arthritis patients (clinically confirmed arthritis of one or more joints, symptoms for less than 2 years), MR scans of the wrist were processed in three automatic stages. First, super-resolution reconstruction was applied to fuse coronal and axial scans into a single high-resolution 3D image. Next, the carpal bones were located and delineated using atlas-based segmentation. Finally, the extent of BME within each bone was quantified by identifying image intensity values characteristic of BME by fuzzy clustering and measuring the fraction of voxels with these characteristic intensities within each bone. Correlation with visual BME scores was assessed through Pearson correlation coefficient.
Results: Pearson correlation between quantitative and visual BME scores across 485 patients was r=0.83, P<0.001. Conclusions: Quantitative measurement of BME on MRI of the wrist has the potential to provide a feasible alternative to visual scoring. Complete automation requires automatic detection and compensation of acquisition artifacts.