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Sha SJ, Ghosh PM, Lee SE, et al. Predicting amyloid status in corticobasal syndrome using modified clinical criteria, magnetic resonance imaging and fluorodeoxyglucose positron emission tomography. Alzheimers Res Ther. 2015;7(1):8doi: 10.1186/s13195-014-0093-y.
Sha, S. J., Ghosh, P. M., Lee, S. E., Corbetta-Rastelli, C., Jagust, W. J., Kornak, J., Rankin, K. P., Grinberg, L. T., Vinters, H. V., Mendez, M. F., Dickson, D. W., Seeley, W. W., Gorno-Tempini, M., Kramer, J., Miller, B. L., Boxer, A. L., & Rabinovici, G. D. (2015). Predicting amyloid status in corticobasal syndrome using modified clinical criteria, magnetic resonance imaging and fluorodeoxyglucose positron emission tomography. Alzheimer's research & therapy, 7(1), 8. https://doi.org/10.1186/s13195-014-0093-y
Sha, Sharon J, et al. "Predicting amyloid status in corticobasal syndrome using modified clinical criteria, magnetic resonance imaging and fluorodeoxyglucose positron emission tomography." Alzheimer's research & therapy vol. 7,1 (2015): 8. doi: https://doi.org/10.1186/s13195-014-0093-y
Sha SJ, Ghosh PM, Lee SE, Corbetta-Rastelli C, Jagust WJ, Kornak J, Rankin KP, Grinberg LT, Vinters HV, Mendez MF, Dickson DW, Seeley WW, Gorno-Tempini M, Kramer J, Miller BL, Boxer AL, Rabinovici GD. Predicting amyloid status in corticobasal syndrome using modified clinical criteria, magnetic resonance imaging and fluorodeoxyglucose positron emission tomography. Alzheimers Res Ther. 2015 Mar 02;7(1):8. doi: 10.1186/s13195-014-0093-y. eCollection 2015. PMID: 25733984; PMCID: PMC4346122.
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Alzheimers Res Ther. 2015 Mar 02;7(1):8. doi: 10.1186/s13195-014-0093-y. eCollection 2015.

Predicting amyloid status in corticobasal syndrome using modified clinical criteria, magnetic resonance imaging and fluorodeoxyglucose positron emission tomography.

Alzheimer's research & therapy

Sharon J Sha, Pia M Ghosh, Suzee E Lee, Chiara Corbetta-Rastelli, Willian J Jagust, John Kornak, Katherine P Rankin, Lea T Grinberg, Harry V Vinters, Mario F Mendez, Dennis W Dickson, William W Seeley, Marilu Gorno-Tempini, Joel Kramer, Bruce L Miller, Adam L Boxer, Gil D Rabinovici

Affiliations

  1. Department of Neurology and Neurological Sciences, Stanford University, 300 Pasteur Drive, Rm A343, Stanford, CA 94305 USA.
  2. Department of Neurology, University of California, San Francisco, San Francisco, CA USA ; Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA USA.
  3. Department of Neurology, University of California, San Francisco, San Francisco, CA USA.
  4. Department of Neurology, University of California, San Francisco, San Francisco, CA USA ; Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA USA ; Lawrence Berkeley National Laboratory, Berkeley, CA USA.
  5. Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA USA.
  6. Department of Neurology, University of California, Los Angeles, CA USA ; Department of Pathology and Laboratory Medicine, University of California, Los Angeles, CA USA.
  7. Department of Neurology, University of California, Los Angeles, CA USA.
  8. Department of Laboratory Medicine & Pathology, Mayo Clinic, Jacksonville, FL USA.

PMID: 25733984 PMCID: PMC4346122 DOI: 10.1186/s13195-014-0093-y

Abstract

INTRODUCTION: Group comparisons demonstrate greater visuospatial and memory deficits and temporoparietal-predominant degeneration on neuroimaging in patients with corticobasal syndrome (CBS) found to have Alzheimer's disease (AD) pathology versus those with underlying frontotemporal lobar degeneration (FTLD). The value of these features in predicting underlying AD pathology in individual patients is unknown. The goal of this study is to evaluate the utility of modified clinical criteria and visual interpretations of magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) for predicting amyloid deposition (as a surrogate of Alzheimer's disease neuropathology) in patients presenting with CBS.

METHODS: In total, 25 patients meeting CBS core criteria underwent amyloid (Pittsburgh compound B; PIB) PET scans. Clinical records, MRI, and FDG scans were reviewed blinded to PIB results. Modified clinical criteria were used to classify CBS patients as temporoparietal variant CBS (tpvCBS) or frontal variant CBS (fvCBS). MRI and FDG-PET were classified based on the predominant atrophy/hypometabolism pattern (frontal or temporoparietal).

RESULTS: A total of 9 out of 13 patients classified as tpvCBS were PIB+, compared to 2out of 12 patients classified as fvCBS (P < 0.01, sensitivity 82%, specificity 71% for PIB+ status). Visual MRI reads had 73% sensitivity and 46% specificity for PIB+ status with moderate intra-rater reliability (Cohen's kappa = 0.42). Visual FDG reads had higher sensitivity (91%) for PIB+ status with perfect intra-rater reliability (kappa = 1.00), though specificity was low (50%). PIB results were confirmed in all 8 patients with available histopathology (3 PIB+ with confirmed AD, 5 PIB- with FTLD).

CONCLUSIONS: Splitting CBS patients into frontal or temporoparietal clinical variants can help predict the likelihood of underlying AD, but criteria require further refinement. Temporoparietal-predominant neuroimaging patterns are sensitive but not specific for AD.

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