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A modified method of 3D-SSP analysis for amyloid PET imaging using [11C]BF-227

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Abstract

Objective

Three-dimensional stereotactic surface projection (3D-SSP) analyses have been widely used in dementia imaging studies. However, 3D-SSP sometimes shows paradoxical results on amyloid positron emission tomography (PET) analyses. This is thought to be caused by errors in anatomical standardization (AS) based on an 18F-fluorodeoxyglucose (FDG) template. We developed a new method of 3D-SSP analysis for amyloid PET imaging, and used it to analyze 11C-labeled 2-(2-[2-dimethylaminothiazol-5-yl]ethenyl)-6-(2-[fluoro]ethoxy)benzoxazole (BF-227) PET images of subjects with mild cognitive impairment (MCI) and Alzheimer’s disease (AD).

Methods

The subjects were 20 with MCI, 19 patients with AD, and 17 healthy controls. Twelve subjects with MCI were followed up for 3 years or more, and conversion to AD was seen in 6 cases. All subjects underwent PET with both FDG and BF-227. For AS and 3D-SSP analyses of PET data, Neurostat (University of Washington, WA, USA) was used. Method 1 involves AS for BF-227 images using an FDG template. In this study, we developed a new method (Method 2) for AS: First, an FDG image was subjected to AS using an FDG template. Then, the BF-227 image of the same patient was registered to the FDG image, and AS was performed using the transformation parameters calculated for AS of the corresponding FDG images. Regional values were normalized by the average value obtained at the cerebellum and values were calculated for the frontal, parietal, temporal, and occipital lobes. For statistical comparison of the 3 groups, we applied one-way analysis of variance followed by the Bonferroni post hoc test. For statistical comparison between converters and non-converters, the t test was applied. Statistical significance was defined as p < 0.05.

Results

Among the 56 cases we studied, Method 1 demonstrated slight distortions after AS of the image in 16 cases and heavy distortions in 4 cases in which the distortions were not observed with Method 2. Both methods demonstrated that the values in AD and MCI patients were significantly higher than those in the controls, in the parietal, temporal, and occipital lobes. However, only Method 2 showed significant differences in the frontal lobes. In addition, Method 2 could demonstrate a significantly higher value in MCI-to-AD converters in the parietal and frontal lobes.

Conclusions

Method 2 corrects AS errors that often occur when using Method 1, and has made appropriate 3D-SSP analysis of amyloid PET imaging possible. This new method of 3D-SSP analysis for BF-227 PET could prove useful for detecting differences between normal groups and AD and MCI groups, and between converters and non-converters.

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References

  1. Minoshima S, Koeppe RA, Frey KA, Kuhl DE. Anatomic standardization: linear scaling and nonlinear warping of functional brain images. J Nucl Med. 1994;35:1528–37.

    PubMed  CAS  Google Scholar 

  2. 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.

    PubMed  CAS  Google Scholar 

  3. Klunk WE, Engler H, Nordberg A, Wang Y, Blomqvist G, Holt DP, et al. Imaging brain amyloid in Alzheimer’s disease with Pittsburgh Compound-B. Ann Neurol. 2004;55:306–19.

    Article  PubMed  CAS  Google Scholar 

  4. Nordberg A. PET imaging of amyloid in Alzheimer’s disease. Lancet Neurol. 2004;3:519–27.

    Article  PubMed  CAS  Google Scholar 

  5. Kudo Y. Development of amyloid imaging PET probes for an early diagnosis of Alzheimer’s disease. Minim Invasive Ther Allied Technol. 2006;15:209–13.

    Article  PubMed  Google Scholar 

  6. Kudo Y, Okamura N, Furumoto S, Tashiro M, Furukawa K, Maruyama M, et al. 2-(2-[2-Dimethylaminothiazol-5-yl]ethenyl)-6-(2-[fluoro]ethoxy)benzoxazole: a novel PET agent for in vivo detection of dense amyloid plaques in Alzheimer’s disease patients. J Nucl Med. 2007;48:553–61.

    Article  PubMed  CAS  Google Scholar 

  7. Friston KJ, Holmes AP, Worsley KJ, Poline JB, Frith C, Frackowiak RSJ. Statistical parametric maps in functional imaging: a general linear approach. Hum Brain Mapp. 1995;2:189–210.

    Article  Google Scholar 

  8. Mikhno A, Devanand D, Pelton G, Cuasay K, Gunn R, Upton N, et al. Voxel-based analysis of 11C-PIB scans for diagnosing Alzheimer’s disease. J Nucl Med. 2008;49:1262–9.

    Article  PubMed  Google Scholar 

  9. Ziolko SK, Weissfeld LA, Klunk WE, Mathis CA, Hoge JA, Lopresti BJ, et al. Evaluation of voxel-based methods for the statistical analysis of PIB PET amyloid imaging studies in Alzheimer’s disease. Neuroimage. 2006;33:94–102.

    Article  PubMed  Google Scholar 

  10. de Leon MJ, Convit A, Wolf OT, Tarshish CY, DeSanti S, Rusinek H, et al. Prediction of cognitive decline in normal elderly subjects with 2-[(18)F]fluoro-2-deoxy-d-glucose/positron-emission tomography (FDG/PET). Proc Natl Acad Sci. 2001;98:10966–71.

    Article  PubMed  Google Scholar 

  11. 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.

    Article  PubMed  CAS  Google Scholar 

  12. Mosconi L, De Santi S, Li Y, Li J, Zhan J, Tsui WH, et al. Visual rating of medial temporal lobe metabolism in mild cognitive impairment and Alzheimer’s disease using FDG-PET. Eur J Nucl Med Mol Imaging. 2006;33:210–21.

    Article  PubMed  Google Scholar 

  13. Maes F, Collignon A, Vandermeulen D, Marchal G, Suetens P. Multimodality image registration by maximization of mutual information. IEEE Trans Med Imaging. 1997;16:187–98.

    Article  PubMed  CAS  Google Scholar 

  14. Maes F, Vandermeulen D, Suetens P. Comparative evaluation of multiresolution optimization strategies for multimodality image registration by maximization of mutual information. Med Image Anal. 1999;3:373–86.

    Article  PubMed  CAS  Google Scholar 

  15. Pluim JP, Maintz JB, Viergever MA. Image registration by maximization of combined mutual information and gradient information. IEEE Trans Med Imaging. 2000;19:809–14.

    Article  PubMed  CAS  Google Scholar 

  16. Pluim JP, Maintz JB, Viergever MA. Mutual-information-based registration of medical images: a survey. IEEE Trans Med Imaging. 2003;22:986–1004.

    Article  PubMed  Google Scholar 

  17. Waragai M, Okamura N, Furukawa K, Tashiro M, Furumoto S, Funaki Y, et al. Comparison study of amyloid PET and voxel-based morphometry analysis in mild cognitive impairment and Alzheimer’s disease. J Neurol Sci. 2009;285:100–8.

    Article  PubMed  Google Scholar 

  18. Furukawa K, Okamura N, Tashiro M, Waragai M, Furumoto S, Iwata R, et al. Amyloid PET in mild cognitive impairment and Alzheimer’s disease with BF-227: comparison to FDG-PET. J Neurol. 2010;257:721–7.

    Article  PubMed  CAS  Google Scholar 

  19. Shao H, Okamura N, Sugi K, Furumoto S, Furukawa K, Tashiro M, et al. Voxel-based analysis of amyloid positron emission tomography probe [C]BF-227 uptake in mild cognitive impairment and alzheimer’s disease. Dement Geriatr Cogn Disord. 2010;30:101–11.

    Article  PubMed  Google Scholar 

  20. Onishi H, Matsutake Y, Kawashima H, Matsutomo N, Amijima H. Comparative study of anatomical normalization errors in SPM and 3D-SSP using digital brain phantom. Ann Nucl Med. 2011;25:59–67.

    Article  PubMed  Google Scholar 

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Acknowledgments

We appreciate the technical assistance provided by Seiichi Watanuki of CYRIC in Tohoku University (Sendai, Japan) and Frank Thiele of Philips Research North America (NY, USA).

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Authors and Affiliations

  1. Department of Diagnostic Radiology, Tohoku University, 1-1 Seiryomachi, Aobaku, Sendai, 980-8574, Japan

    Tomohiro Kaneta & Shoki Takahashi

  2. Department of Pharmacology, Tohoku University Graduate School of Medicine, 4-1 Seiryomachi, Aobaku, Sendai, 980-8575, Japan

    Nobuyuki Okamura, Shozo Furumoto & Kazuhiko Yanai

  3. Department of Radiology, University of Washington, 1959 N.E. Pacific Street, Seattle, WA, 98195-7115, USA

    Satoshi Minoshima

  4. Division of Brain Sciences, Department of Geriatrics and Gerontology, Institute of Development, Aging and Cancer, Tohoku University, 4-1 Seiryomachi, Aobaku, Sendai, 980-8498, Japan

    Katsutoshi Furukawa & Hiroyuki Arai

  5. Division of Cyclotron Nuclear Medicine, Cyclotron and Radioisotope Center, Tohoku University, 6-3 Aoba, Aramaki, Aoba-ku, Sendai, Miyagi, 980-8578, Japan

    Manabu Tashiro

  6. Division of Radiopharmaceutical Chemistry, Cyclotron and Radioisotope Center, Tohoku University, 6-3 Aoba, Aramaki, Aoba-ku, Sendai, Miyagi, 980-8578, Japan

    Ren Iwata

  7. Nuclear Medicine and Radiology, Institute of Development, Aging and Cancer, Tohoku University, 4-1 Seiryomachi, Aobaku, Sendai, 980-8498, Japan

    Hiroshi Fukuda

  8. Department of NeuroImaging Research, Innovation New Biomedical Engineering Center, Tohoku University, 4-1 Seiryomachi, Aobaku, Sendai, 980-8498, Japan

    Yukitsuka Kudo

Authors
  1. Tomohiro Kaneta
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  2. Nobuyuki Okamura
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  3. Satoshi Minoshima
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  4. Katsutoshi Furukawa
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  5. Manabu Tashiro
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  6. Shozo Furumoto
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  7. Ren Iwata
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  8. Hiroshi Fukuda
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  9. Shoki Takahashi
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  10. Kazuhiko Yanai
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  11. Yukitsuka Kudo
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  12. Hiroyuki Arai
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Correspondence to Tomohiro Kaneta.

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Kaneta, T., Okamura, N., Minoshima, S. et al. A modified method of 3D-SSP analysis for amyloid PET imaging using [11C]BF-227. Ann Nucl Med 25, 732–739 (2011). https://doi.org/10.1007/s12149-011-0518-7

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  • DOI: https://doi.org/10.1007/s12149-011-0518-7

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