Automatic delineation algorithm of reference region for amyloid imaging based on kinetics

  • Takahiro Yamada
  • Shogo Watanabe
  • Takashi Nagaoka
  • Mitsutaka Nemoto
  • Kohei Hanaoka
  • Hayato Kaida
  • Kazunari Ishii
  • Yuichi KimuraEmail author
Original Article



This study aims to develop an algorithm named AutoRef to delineate a reference region for quantitative PET amyloid imaging.


AutoRef sets the reference region automatically using a distinguishing feature in the kinetics of reference region. This is reflected in the shapes of the tissue time activity curve. A statistical shape recognition algorithm of the gaussian mixture model is applied with considering spatial and temporal information on a reference region. We evaluate the BPND with manually set reference region and AutoRef using 86 cases (43 positive cases, 10 equivocal cases, and 33 negative cases) of dynamically scanned 11C-Pittsburgh Compound-B.


From the Bland–Altman plot, the difference between two BPND is 0.099 ± 0.21 as standard deviation, and no significant systematic error is observed between the BPND with AutoRef and with manual definition of a reference region. Although a proportional error is detected, it is smaller than the 95% limits of agreement. Therefore, the proportional error is negligibly small.


AutoRef presents the same performance as the manual definition of the reference region. Further, since AutoRef is more algorithmic than the ordinary manual definition of the reference region, there are few operator-oriented uncertainties in AutoRef. We thus conclude that AutoRef can be applied as an automatic delineating algorithm for the reference region in amyloid imaging.


Amyloid imaging Reference region Kinetic analysis 



I express my gratitude to Dr. Chisa Hosokawa for her enthusiastic guidance from the beginning. This work is supported by MEXT KAKENHI Grant No. 15H01131 and Kindai University Research Grants: KD201805 from 2015 to 2017 and KD1804 from 2018.

Compliance with ethical standards

Conflict of interest

No potential conflict of interests was disclosed.


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Copyright information

© The Japanese Society of Nuclear Medicine 2019

Authors and Affiliations

  1. 1.Department of Biological System Engineering, Graduate School of Biology-Oriented Science and TechnologyKindai UniversityKinokawa-shiJapan
  2. 2.Department of Human Health SciencesGraduate School of Medicine Kyoto UniversityKyotoJapan
  3. 3.Department of Biomedical Engineering, Faculty of Biology-Oriented Science and TechnologyKindai UniversityKinokawa-shiJapan
  4. 4.Division of Positron Emission Tomography, Institute of Advanced Clinical MedicineKindai UniversityOsakasayama-shiJapan
  5. 5.Department of Radiology, Faculty of MedicineKindai UniversityOsakasayama-shiJapan

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