Measurement consistency from magnetic resonance images.
OBJECTIVE
In quantifying medical images, length-based measurements are still obtained manually. Due to possible human error, a measurement protocol is required to guarantee the consistency of measurements. In this work, we review various statistical techniques that can be used in determining measurement consistency. The focus is on detecting a possible measurement bias and determining the robustness of the procedures to outliers.


METHODS
We review correlation analysis, linear regression, Bland-Altman method, paired t-test, and analysis of variance (ANOVA). These techniques were applied to measurements, obtained by two raters, of head and neck structures from magnetic resonance images.


RESULTS
The correlation analysis and the linear regression were shown to be insufficient for detecting measurement inconsistency. They are also very sensitive to outliers. The widely used Bland-Altman method is a visualization technique, so it lacks the numeric quantification. The paired t-test tends to be sensitive to small measurement bias. In contrast, ANOVA performs well even under small measurement bias.


CONCLUSIONS
In almost all cases, using only one method is insufficient and it is recommended that several methods be used simultaneously. In general, ANOVA performs the best.
Chung
Dongjun
D
Department of Statistics, University of Wisconsin-Madison, Madison, WI 53705, USA.
Chung
Moo K
MK
Durtschi
Reid B
RB
Gentry
Lindell R
LR
Vorperian
Houri K
HK
D000465:Algorithms; D006257:Head / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009333:Neck / Q000033:anatomy & histology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
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