Influence of Signal Intensity Non-Uniformity on Brain Volumetry Using an Atlas-Based Method

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.

An ex post facto evaluation of the 82nd and 83rd national examination for Physicians' license / 医学教育

The 82 nd and 83 rd National Examination for Physicians' License, which were held in 1988 and 1989 respectively, were evaluated from question to question as well as in all the questions as a whole to set minimum pass scores and analysis “relevance” and “difficulty” in a matrix utilizing a modified Ebel's method.<BR>The evaluators were teachers in different disciplines in nationwide medical schools and teaching hospitals and clinical trainees who had taken and passed the immediate past examinations.<BR>Following data processing, the questionable and difficult questions were on the decrease compared with the preceding year, and it was tentatively concluded that the National Examinations have gradually improved year by year.