Literature DB >> 26338898

A Semiautomated Method for Quantification of F 18 Florbetapir PET Images.

Abhinay D Joshi1, Michael J Pontecorvo2, Ming Lu2, Daniel M Skovronsky2, Mark A Mintun2, Michael D Devous2.   

Abstract

UNLABELLED: PET amyloid imaging is increasingly used in research trials related to Alzheimer disease and has potential as a quantitative biomarker. This study had 3 objectives: first, to describe a semiautomated quantitative method that does not require subject-specific MR imaging scans for estimating F 18 Florbetapir plaque binding using 10-min PET images; second, to evaluate the method's accuracy for identifying positive and negative scans; and third, to correlate derived standardized uptake value ratios to neuropathologic measures of amyloid.
METHODS: The F 18 Florbetapir PET images are initially converted to Montreal Neurologic Institute brain atlas space using an internally developed PET target F 18 Florbetapir template. Subsequently, a single mean cortical standardized uptake value ratio (mcSUVr) is calculated from the mean standardized uptake value of 6 cortical regions normalized to a reference region. Four reference regions were explored: whole cerebellum, cerebellar gray matter, pons, and centrum semiovale. The performance of the resultant mcSUVrs were evaluated in 74 young cognitively normal subjects (age < 50 y) with a negligible likelihood of amyloid β pathology, and in 59 deceased subjects with autopsy-based amyloid β neuritic plaque measure who underwent F 18 Florbetapir PET imaging before death.
RESULTS: Significant correlations were obtained between mcSUVrs and 3 different pathologic measures of amyloid deposition at autopsy using all 4 reference regions, with the whole-cerebellum mcSUVr correlating most strongly across pathologic measures (r = 0.71-0.75, P < 0.0001). Using the whole-cerebellum mcSUVr and a threshold mcSUVr of less than 1.10, 100% of young cognitively normal subjects were correctly classified as amyloid-negative (mcSUVr range, 0.87-1.08). Similarly, 20 of 20 autopsy-negative subjects showed mcSUVrs of 1.10 or less, whereas 38 of 39 pathology-verified amyloid-positive subjects had mcSUVrs of more than 1.10.
CONCLUSION: This semiautomated F 18 Florbetapir PET quantification method yielded mcSUVrs that significantly correlated with measures of amyloid pathology at autopsy. The method also effectively discriminated autopsy-identified amyloid-positive and -negative cases using a whole-cerebellum mcSUVr threshold of 1.10.
© 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Entities:  

Keywords:  Alzheimer’s; PET; florbetapir; neuropathology; quantification

Mesh:

Substances:

Year:  2015        PMID: 26338898     DOI: 10.2967/jnumed.114.153494

Source DB:  PubMed          Journal:  J Nucl Med        ISSN: 0161-5505            Impact factor:   10.057


  22 in total

1.  A Fully Automatic Technique for Precise Localization and Quantification of Amyloid-β PET Scans.

Authors:  Mouna Tahmi; Wassim Bou-Zeid; Qolamreza R Razlighi
Journal:  J Nucl Med       Date:  2019-06-06       Impact factor: 10.057

2.  Quantitation of PET signal as an adjunct to visual interpretation of florbetapir imaging.

Authors:  Michael J Pontecorvo; Anupa K Arora; Marybeth Devine; Ming Lu; Nick Galante; Andrew Siderowf; Catherine Devadanam; Abhinay D Joshi; Stephen L Heun; Brian F Teske; Stephen P Truocchio; Michael Krautkramer; Michael D Devous; Mark A Mintun
Journal:  Eur J Nucl Med Mol Imaging       Date:  2017-01-07       Impact factor: 9.236

3.  Yes we can analyse amyloid images - Now What?

Authors:  Henryk Barthel; John Seibyl; Osama Sabri
Journal:  Eur J Nucl Med Mol Imaging       Date:  2017-05       Impact factor: 9.236

4.  A Novel Cognitive Stress Test for the Detection of Preclinical Alzheimer Disease: Discriminative Properties and Relation to Amyloid Load.

Authors:  David A Loewenstein; Rosie E Curiel; Maria T Greig; Russell M Bauer; Marian Rosado; Dawn Bowers; Meredith Wicklund; Elizabeth Crocco; Michael Pontecorvo; Abhinay D Joshi; Rosemarie Rodriguez; Warren W Barker; Jacqueline Hidalgo; Ranjan Duara
Journal:  Am J Geriatr Psychiatry       Date:  2016-04-04       Impact factor: 4.105

5.  A new integrated dual time-point amyloid PET/MRI data analysis method.

Authors:  Diego Cecchin; Henryk Barthel; Davide Poggiali; Annachiara Cagnin; Solveig Tiepolt; Pietro Zucchetta; Paolo Turco; Paolo Gallo; Anna Chiara Frigo; Osama Sabri; Franco Bui
Journal:  Eur J Nucl Med Mol Imaging       Date:  2017-07-04       Impact factor: 9.236

6.  Correlation between two methods of florbetapir PET quantitative analysis.

Authors:  Christopher Breault; Jonathan Piper; Abhinay D Joshi; Sara D Pirozzi; Aaron S Nelson; Ming Lu; Michael J Pontecorvo; Mark A Mintun; Michael D Devous
Journal:  Am J Nucl Med Mol Imaging       Date:  2017-07-15

Review 7.  Amyloid Imaging: Poised for Integration into Medical Practice.

Authors:  Keshav Anand; Marwan Sabbagh
Journal:  Neurotherapeutics       Date:  2017-01       Impact factor: 7.620

8.  18F-florbetapir Positron Emission Tomography-determined Cerebral β-Amyloid Deposition and Neurocognitive Performance after Cardiac Surgery.

Authors:  Rebecca Y Klinger; Olga G James; Salvador Borges-Neto; Tiffany Bisanar; Yi-Ju Li; Wenjing Qi; Miles Berger; Niccolò Terrando; Mark F Newman; P Murali Doraiswamy; Joseph P Mathew
Journal:  Anesthesiology       Date:  2018-04       Impact factor: 7.892

9.  Optimisation and usefulness of quantitative analysis of 18F-florbetapir PET.

Authors:  Daniel Fakhry-Darian; Neva Hiten Patel; Sairah Khan; Tara Barwick; William Svensson; Sameer Khan; Richard J Perry; Paresh Malhotra; Christopher J Carswell; Kuldip S Nijran; Zarni Win
Journal:  Br J Radiol       Date:  2019-05-14       Impact factor: 3.039

10.  Validation of the Alzheimer Disease Dementia Conversion-Related Pattern as an ATN Biomarker of Neurodegeneration.

Authors:  Ganna Blazhenets; Lars Frings; Yilong Ma; Arnd Sörensen; David Eidelberg; Jens Wiltfang; Philipp T Meyer
Journal:  Neurology       Date:  2021-01-06       Impact factor: 9.910

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