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RISS 인기검색어
- 검색키워드
- 저자 : Harushi Mori (검색결과 2 건)
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Fujisawa, Naoaki,Oya, Soichi,Mori, Harushi,Matsui, Toru The Korean Neurosurgical Society 2015 Journal of Korean neurosurgical society Vol.58 No.5
Chronic lymphocytic inflammation with pontine perivascular enhancement responsive to steroids (CLIPPERS) is a relapsing-remitting disorder for which steroid administration is a key to control the progression. CLIPPERS can exhibit radiological features similar to malignant lymphoma, whose diagnosis is confounded by prior steroid administration. We report a case of CLIPPERS accompanied by abnormal elevation of ${\beta}-2$ microglobulin in the cerebrospinal fluid (CSF). A 62-year-old man started to experience numbness in all fingers of his left hand one year ago, which gradually extended to his body trunk and legs on both sides. Magnetic resonance imaging demonstrated numerous small enhancing spots scattered in his brain and spinal cord. CSF levels of ${\beta}-2$ microglobulin were elevated; although this often indicates central nervous system involvement in leukemia and lymphoma, the lesions were diagnosed as CLIPPERS based on the pathological findings from a biopsy specimen. We emphasize the importance of biopsy to differentiate between CLIPPERS and malignant lymphoma because the temporary radiological response to steroid might be the same in both diseases but the treatment strategies regarding the use of steroid are quite different.
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Influence of Signal Intensity Non-Uniformity on Brain Volumetry Using an Atlas-Based Method
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,K 대한영상의학회 2012 Korean Journal of Radiology Vol.13 No.4
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 x [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. 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 x [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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