@misc{oai:repo.qst.go.jp:00066775,
 author = {赤松, 剛 and 井狩, 彌彦 and Iwao, Yuma and Tashima, Hideaki and 三木, 秀哉 and Yamaya, Taiga and 千田, 道雄 and 赤松 剛 and 岩男 悠真 and 田島 英朗 and 山谷 泰賀},
 month = {Apr},
 note = {【Purpose】
Amyloid PET can reveal in-vivo amyloid-β pathological process as a biomarker of Alzheimer’s disease. Although quantification of amyloid accumulation with standardized uptake value ratio (SUVR) has been widely performed in clinical research, a high-resolution MRI is required for spatial normalization of PET images into standard image space. Therefore, we developed a simple PET-only amyloid quantification method. However, our method cannot be widely used because the high-cost image analysis software is needed. The purpose of this study was to develop software-independent flexible programs for quantification of amyloid PET images.
\n【Method】
We developed three elements of the quantification programs. At first, we generated the program to calculate the normalized cross correlation (NCC) between two PET images, which is essential to perform PET-only adaptive spatial normalization method. Then, we created the program to generate the SUVR-scaled PET images. A reference region used to normalize voxel values can be freely selected. Finally, we made the program to measure SUVR values with any regions-of-interest (ROI). These programs can manage DICOM, Analyze, NIfTI, and NEUROSTAT images.
\n【Result】
Using our developed programs, we were able to obtain same NCC and SUVR values in comparison with those obtained by the commercial image analysis software. Our programs normally worked even though we managed various ROI and image formats. These programs can be applicable to all amyloid tracers using their specific ROI.
\n【Conclusion】
We developed simple and adaptive programs for quantification of amyloid PET images. These programs could be useful for clinical research using amyloid PET and be applied for general-purpose software development., JRC2018（第74回日本放射線技術学会総会学術大会）},
 title = {Development of simple and adaptive programs for quantification of amyloid PET images},
 year = {2018}
}