Korean Journal of Radiology

The Korean Society of Radiology (대한영상의학회)
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Influence of Signal Intensity Non-Uniformity on Brain Volumetry Using an Atlas-Based Method

  • Goto, Masami (Department of Radiological Technology, University of Tokyo Hospital) ;
  • Abe, Osamu (Department of Radiology, Nihon University School of Medicine) ;
  • Miyati, Tosiaki (Graduate School of Medical Science, Kanazawa University) ;
  • Kabasawa, Hiroyuki (Japan Applied Science Laboratory, GE Healthcare) ;
  • Takao, Hidemasa (Department of Radiology, University of Tokyo Hospital) ;
  • Hayashi, Naoto (Department of Computational Diagnostic Radiology and Preventive Medicine, University of Tokyo Hospital) ;
  • Kurosu, Tomomi (Department of Radiological Technology, University of Tokyo Hospital) ;
  • Iwatsubo, Takeshi (Department of Neuropathology, University of Tokyo) ;
  • Yamashita, Fumio (Department of Radiology, National Center Hospital of Neurology and Psychiatry) ;
  • Matsuda, Hiroshi (Department of Nuclear Medicine, Saitama Medical University International Medical Center) ;
  • Mori, Harushi (Department of Radiology, University of Tokyo Hospital) ;
  • Kunimatsu, Akira (Department of Radiology, University of Tokyo Hospital) ;
  • Aoki, Shigeki (Department of Radiology, Juntendo University) ;
  • Ino, Kenji (Department of Radiological Technology, University of Tokyo Hospital) ;
  • Yano, Keiichi (Department of Radiological Technology, University of Tokyo Hospital) ;
  • Ohtomo, Kuni (Department of Radiology, University of Tokyo Hospital) ;
  • Japanese Alzheimer's Disease Neuroimaging Initiative, Japanese Alzheimer's Disease Neuroimaging Initiative (Japanese Alzheimer's Disease Neuroimaging Initiative)
  • Published : 2012.08.01
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Abstract

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 ${\times}$ [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.

Keywords

References

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