Advertisement

Clinical utility of the normal database of 123I-iodoamphetamine brain perfusion single photon emission computed tomography for statistical analysis using computed tomography-based attenuation correction: a multicenter study

  • Takahiro YamazakiEmail author
  • Yoshitaka Inui
  • Takashi Ichihara
  • Masaki Uno
  • Seiichiro Ota
  • Akihiro Toyoda
  • Masanobu Ishiguro
  • Takashi Kato
  • Kengo Ito
  • Hiroshi Toyama
Original Article
  • 32 Downloads

Abstract

Objectives

We have established a common normal database (NDB) with applicability in multicenter settings for the statistical analysis of brain perfusion single photon emission computed tomography (SPECT) with triple energy window scatter correction, computed tomography-based attenuation correction (CTAC), and spatial resolution compensation. This study aimed to compare the CTAC normal database (CTAC-NDB) with conventional normal databases for the statistical analysis of 123I-iodoamphetamine (123I-IMP) brain perfusion SPECT at three institutions and to assess the clinical efficiency of CTAC-NDB.

Methods

We recruited 45 patients (26 men and 19 women; mean age, 74.2 ± 3.9 years; Mini-Mental State Examination score, 19.8 ± 6.1) with Alzheimer’s disease (AD, n = 26), dementia with Lewy bodies (DLB, n = 9), and mild cognitive impairment (n = 10) from three institutions. Three-dimensional stereotactic surface projection (3D-SSP) technique was used to analyze data obtained from the 123I-IMP brain perfusion SPECT images compared with both CTAC-NDB and conventional NDB. We visually assessed each 3D-SSP z score map to determine the changes in specific findings, such as AD/DLB pattern. Furthermore, the stereotactic extraction estimation analysis software was used to measure the regional z score severity and extent as a semiquantitative assessment.

Results

In the visual assessment, all cases exhibited clearer findings with CTAC-NDB than with conventional NDB in the parietotemporal association cortex as well as in the inferior temporal, frontal, and lateral occipital cortices. Contrarily, the findings from the medial cerebral regions, including the precuneus and the posterior cingulate, became indistinct in 71% of the cases and remained unchanged in 25% of the cases. In the semiquantitative analysis, a similar tendency was observed in the mean z score in the three institutions included in the study.

Conclusion

Using the CTAC-NDB, the findings in the vicinity of the cranium became increasingly clear, whereas those in the medial surface of the brain became less defined or remained unchanged. These findings were confirmed via a semiquantitative analysis. Moreover, similar changes in the reduction pattern were observed in the three institutions. Therefore, the new database with CTAC might be applicable in other institutions. Data collected in this study may serve as a CTAC-NDB.

Keywords

Dementia IMP Brain perfusion SPECT CTAC Normal database 

Notes

Acknowledgements

This work was performed by the working group of Japanese Society of Nuclear Medicine (JSNM) in 2013–2015 and 2017–2018 and was supported partly by JSNM. No potential conflicts of interest were disclosed.

Funding

None.

References

  1. 1.
    Jack CR Jr, Albert MS, Knopman DS, McKhann GM, Sperling RA, Carrillo MC, et al. Introduction to the recommendations from the National Institute on Aging—Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7:257–62.CrossRefGoogle Scholar
  2. 2.
    McKeith IG, Dickson DW, Lowe J, Emre M, O’Brien JT, Feldman H, et al. Diagnosis and management of dementia with Lewy bodies: third report of the DLB Consortium. Neurology. 2005;65:1863–72.CrossRefGoogle Scholar
  3. 3.
    Morinaga A, Ono K, Ikeda T, Ikeda Y, Shima K, Noguchi-Shinohara M, et al. A comparison of the diagnostic sensitivity of MRI, CBF-SPECT, FDG-PET and cerebrospinal fluid biomarkers for detecting Alzheimer’s disease in a memory clinic. Dement Geriatr Cogn Disord. 2010;30:285–92.CrossRefGoogle Scholar
  4. 4.
    Jagust W, Thisted R, Devous MD Sr, Van Heertum R, Mayberg H, Jobst K, et al. SPECT perfusion imaging in the diagnosis of Alzheimer’s disease: a clinical-pathologic study. Neurology. 2001;56:950–6.CrossRefGoogle Scholar
  5. 5.
    Minoshima S, Frey KA, Koeppe RA, Foster NL, Kuhl DE. A diagnostic approach in Alzheimer’s disease using three-dimensional stereotactic surface projections of fluorine-18-FDG PET. J Nucl Med. 1995;36:1238–48.Google Scholar
  6. 6.
    Friston KJ. Analyzing brain images: principles and overview. In: Frackowiak RSJ, Friston KJ, Frith CD, et al., editors. Human brain function. San Diego: Academic Press; 1997. p. 25–41.Google Scholar
  7. 7.
    Chang LT. A method for attenuation correction in radionuclide computed tomography. IEEE Trans Nucl Sci. 1977;25:638–43.CrossRefGoogle Scholar
  8. 8.
    Ichihara T, Ogawa K, Motomura N, Kubo A, Hashimoto S. Compton scatter compensation using the triple-energy window method for single- and dual-isotope SPECT. J Nucl Med. 1993;34:2216–21.Google Scholar
  9. 9.
    Hayashi M, Deguchi K, Utsunomiya K, Yamada M, Komori T, Takeuchi M, et al. Comparison of methods of attenuation and scatter correction in brain perfusion SPECT. J Nucl Med Technol. 2005;33:224–9.Google Scholar
  10. 10.
    Inui Y, Ichihara T, Uno M, Ishiguro M, Ito K, Kato K, et al. CT-based attenuation correction and resolution compensation for I-123 IMP brain SPECT normal database: a multicenter phantom study. Ann Nucl Med. 2018;32:311–8.CrossRefGoogle Scholar
  11. 11.
    Matsuda H, Murata M, Mukai Y, Sako K, Ono H, Toyama H, et al. Japanese multicenter database of healthy controls for [123I]FP-CIT SPECT. Eur J Nucl Med Mol Imaging. 2018;45:1405–16.CrossRefGoogle Scholar
  12. 12.
    Ito K, Mori E, Fukuyama H, Ishii K, Washimi Y, Asada T, et al. Prediction of outcomes in MCI with (123)I-IMP-CBF SPECT: a multicenter prospective cohort study. Ann Nucl Med. 2013;27:898–906.CrossRefGoogle Scholar
  13. 13.
    Mizumura S, Kumita S, Cho K, Ishihara M, Nakajo H, Toba M, et al. Development of quantitative analysis method for stereotactic brain image: assessment of reduced accumulation in extent and severity using anatomical segmentation. Ann Nucl Med. 2003;17:289–95.CrossRefGoogle Scholar
  14. 14.
    Morano GN, Seibyl JP. Technical overview of brain SPECT imaging: improving acquisition and processing of data. J Nucl Med Technol. 2003;31:191–5.Google Scholar
  15. 15.
    Ishii K, Hanaoka K, Okada M, Kumano S, Komeya Y, Tsuchiya N, et al. Impact of CT attenuation correction by SPECT/CT in brain perfusion images. Ann Nucl Med. 2012;26:241–7.CrossRefGoogle Scholar
  16. 16.
    Minoshima S, Giordani B, Berent S, Frey KA, Foster NL, Kuhl DE. Metabolic reduction in the posterior cingulate cortex in very early Alzheimer’s disease. Ann Neurol. 1997;42:85–94.CrossRefGoogle Scholar
  17. 17.
    Gillen R, Firbank MJ, Lloyd J, O’Brien JT. CT-based attenuation and scatter correction compared with uniform attenuation correction in brain perfusion SPECT imaging for dementia. Phys Med Biol. 2015;60:6775–877.CrossRefGoogle Scholar
  18. 18.
    Lange C, Seese A, Schwarzenböck K, Steinhoff K, Umland-Seidler B, Krause BJ, et al. CT-based attenuation correction inI-123-ioflupane SPECT. PLoS ONE. 2014;9:e108328.CrossRefGoogle Scholar
  19. 19.
    Farid K, Petras S, Poullias X, Caillat-Vigneron N. Clinical impact of nonuniform CT-based attenuation correction in brain perfusion SPECT/CT using (99m)Tc-ECD. Clin Nucl Med. 2014;39:343–5.CrossRefGoogle Scholar
  20. 20.
    Akamatsu M, Yamashita Y, Akamatsu G, Tsutsui Y, Ohya N, Nakamura Y, et al. Influences of reconstruction and attenuation correction in brain SPECT images obtained by the hybrid SPECT/CT device: evaluation with a 3-dimensional brain phantom. Asia Ocean J Nucl Med Biol. 2014;2:24–9.Google Scholar

Copyright information

© The Japanese Society of Nuclear Medicine 2019

Authors and Affiliations

  • Takahiro Yamazaki
    • 1
    • 2
    Email author
  • Yoshitaka Inui
    • 1
  • Takashi Ichihara
    • 3
  • Masaki Uno
    • 4
  • Seiichiro Ota
    • 1
  • Akihiro Toyoda
    • 3
  • Masanobu Ishiguro
    • 3
  • Takashi Kato
    • 5
  • Kengo Ito
    • 5
  • Hiroshi Toyama
    • 1
  1. 1.Department of RadiologyFujita Health University School of MedicineToyoakeJapan
  2. 2.Department of PsychiatryMatsukage Senior HospitalNagoyaJapan
  3. 3.Department of Artificial Intelligence in Medical Imaging DevelopmentFujita Health University School of MedicineToyoakeJapan
  4. 4.Department of RadiologyFujita Health University HospitalToyoakeJapan
  5. 5.Department of Clinical and Experimental NeuroimagingNational Center for Geriatrics and GerontologyObuJapan

Personalised recommendations