Reproducibility Analysis of Brain Volumetry Measured from Inter MR Scanner of Multi-Institute.
10.13104/jksmrm.2012.16.3.243
- Author:
Won Beom JUNG
1
;
Min Jae KANG
;
Doo Beom SON
;
Young Joo KIM
;
Young Min LEE
;
Young Hoon KIM
;
Choong Ki EUN
;
Chi Woong MUN
Author Information
1. Department of Biomedical Engineering, and U-Health care Research Center, Inje University, Korea. mcw@inje.ac.kr
- Publication Type:Original Article
- Keywords:
Multi-center study;
Inter MR scanner variation;
Brain volumetry;
Magnetic resonance image;
Automatic segmentation
- MeSH:
Brain;
Calibration
- From:Journal of the Korean Society of Magnetic Resonance in Medicine
2012;16(3):243-252
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
PURPOSE: The aim of this study was to evaluate the variations of brain volumetry between the different MR scanners or the different institutes. MATERIALS AND METHODS: Ten normal subjects were scanned at four different MR scanners, two of them were the same models, to measure inter-MR scanner variations using intraclass correlation coefficient (ICC), coefficient of variation (CV) and percent volume difference (PVD) and to calculate minimal thresholds to detect the significant volumetric changes in gray matter and subcortical regions. RESULTS: Averaged statistical reliability (ICC = 0.837) and volumetric variation (CV = 4.310%) in all segmented regions were observed on overall MR scanners. Comparing the segmented volumes with PVD between two MR scanners, volumetric differences on same models were the lowest (PVD = 3.611%) and volume thresholds were calculated with 7.168%. PVD results and thresholds values on systemically different MR scanners were evaluated with 5.785% and 11.340% respectively. CONCLUSION: Authors conclude that the reliability of brain volumetry is not so high. Calibration studies of MRI system and image processing are essential to reduce the volumetric variability. Additionally, frameworks comprised of database and algorithms with high-speed image processing are also required for the efficient image data management.
