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James M. Mountz

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YNICL Journal 2015 Journal Article

Comparison of qualitative and quantitative imaging characteristics of [11C]PiB and [18F]flutemetamol in normal control and Alzheimer's subjects

  • James M. Mountz
  • Charles M. Laymon
  • Ann D. Cohen
  • Zheng Zhang
  • Julie C. Price
  • Sanaa Boudhar
  • Eric McDade
  • Howard J. Aizenstein

INTRODUCTION: Neuritic amyloid plaques and neurofibrillary tangles, the hallmark pathologic lesions of Alzheimer's disease, are thought to develop before the symptoms of brain failure are clinically detectable. Imaging methods capable of detecting the presence of neuritic amyloid plaques should improve a clinician's ability to identify Alzheimer's disease during the earliest symptomatic phase and to identify at-risk individuals presymptomatically. Currently the best studied amyloid imaging ligand is [(11)C]Pittsburgh Compound B ([(11)C]PiB). However, the 20-minute half-life of this radiotracer limits its use. This study is designed to evaluate the performance characteristics of [(18)F]flutemetamol and to independently compare results to [(11)C]PiB in the same subjects. METHODS: Twenty-three subjects, 15 cognitively normal (NL) and 8 with a clinical diagnosis of Alzheimer's Dementia (AD), underwent [(11)C]PiB and [(18)F]flutemetamol PET scans within 28 days of study enrollment. We studied both normal and AD subjects to assess the uptake characteristics across a range of amyloid positivity. Blinded visual reads were conducted by five raters. Correlation analyses were performed between cortical SUVR for the two tracers and also between rater scores and SUVR for each tracer. Overall reader accuracy for classifying scans as amyloid positive or negative was determined for each tracer using SUVR classification as the standard. RESULTS: The linear correlation coefficient between global cortical SUVR for the two tracers was R(2) = 0.85, indicating that both tracers have similar retention characteristics. The two tracers were well correlated for rater-determined AD-like positivity (Cohen κ = 0.82). Averaged visual ratings and global cortical SUVR disagreed on their classification in 2/23 [(11)C]PiB scans and 4/23 [(18)F]flutemetamol scans. CONCLUSIONS: [(11)C]PiB and [(18)F]flutemetamol have similar retention characteristics across a range of amyloid negative to positive subjects. Both tracers performed similarly when a standardized visual read technique was used to classify scans as amyloid-positive or amyloid-negative and correlated well with SUVR classifications. However, care in visual interpretation of amyloid positive versus amyloid negative regions should be taken, particularly in the case of [(18)F]flutemetamol when considering cortical vs. white-matter retention.

YNIMG Journal 2013 Journal Article

Classification of amyloid-positivity in controls: Comparison of visual read and quantitative approaches

  • Ann D. Cohen
  • Wenzhu Mowrey
  • Lisa A. Weissfeld
  • Howard J. Aizenstein
  • Eric McDade
  • James M. Mountz
  • Robert D. Nebes
  • Judith A. Saxton

An important research application of amyloid imaging with positron emission tomography (PET) is detection of the earliest evidence of fibrillar amyloid-beta (Aβ) deposition. Use of amyloid PET for this purpose, requires a reproducible method for defining a cutoff that separates individuals with no significant Aβ deposition from those in which Aβ deposition has begun. We previously reported the iterative outlier approach (IO) for the analysis of Pittsburgh Compound-B (PiB) PET data. Developments in amyloid imaging since the initial report of IO have led us to re-examine the generalizability of this method. IO was developed using full-dynamic atrophy-corrected PiB PET data obtained from a group of control subjects with a fairly distinct separation between PiB-positive [PiB(+)] and PiB-negative [PiB(−)] subjects. Methods We tested the performance of IO using late-summed tissue ratio data with atrophy correction or with an automated template method without atrophy correction and tested the robustness of the method when applied to a cohort of older subjects in which separation between PiB(+) and PiB(−) subjects was not so distinct. Results The IO method did not perform consistently across analyses and performed particularly poorly when separation was less clear. We found that a sparse k-means (SKM) cluster analysis approach performed significantly better; performing more consistently across methods and subject cohorts. We also compared SKM to a consensus visual read approach and found very good correspondence. Conclusion The visual read and SKM methods, applied together, may optimize the identification of early Aβ deposition. These methods have the potential to provide a standard approach to the detection of PiB-positivity that is generalizable across centers.

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