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KMID : 0880420120130040391
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Korean Journal of Radiology
2012 Volume.13 No. 4 p.391 ~ p.402
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Influence of Signal Intensity Non-Uniformity on Brain Volumetry Using an Atlas-Based Method
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Masami Goto
Osamu Abe
Tosiaki Miyati
Hiroyuki Kabasawa
Hidemasa Takao
Naoto Hayashi
Tomomi Kurosu
Takeshi Iwatsubo
Fumio Yamashita
Hiroshi Matsuda
Harushi Mori
Akira Kunimatsu
Shigeki Aoki
Kenji Ino
Keiichi Yano
Kuni Ohtomo
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Abstract
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Objective: Many studies have reported pre-processing effects for brain volumetry; however, no study has investigated whether non-parametric non-uniform intensity normalization (N3) correction processing results in reduced system dependency when using an atlas-based method. To address this shortcoming, the present study assessed whether N3 correction processing provides reduced system dependency in atlas-based volumetry.
Materials and Methods: Contiguous sagittal T1-weighted images of the brain were obtained from 21 healthy participants, by using five magnetic resonance protocols. After image preprocessing using the Statistical Parametric Mapping 5 software, we measured the structural volume of the segmented images with the WFU-PickAtlas software. We applied six different bias-correction levels (Regularization 10, Regularization 0.0001, Regularization 0, Regularization 10 with N3, Regularization 0.0001 with N3, and Regularization 0 with N3) to each set of images. The structural volume change ratio (%) was defined as the change ratio (%) = (100 × [measured volume - mean volume of five magnetic resonance protocols] / mean volume of five magnetic resonance protocols) for each bias-correction level.
Results: A low change ratio was synonymous with lower system dependency. The results showed that the images with the N3 correction had a lower change ratio compared with those without the N3 correction.
Conclusion: The present study is the first atlas-based volumetry study to show that the precision of atlas-based volumetry improves when using N3-corrected images. Therefore, correction for signal intensity non-uniformity is strongly advised for multi-scanner or multi-site imaging trials.
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KEYWORD
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Atlas-based, Bias correction, Brain volumetry, Intensity non-uniformity, Non-parametric non-uniform intensity normalization
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