A Semiautomated Method for Quantification of F 18 Florbetapir PET Images

• Published in: Journal of Nuclear Medicine Vol. 56; no. 11; pp. 1736 - 1741
• Main Authors: Joshi, Abhinay D., Pontecorvo, Michael J., Lu, Ming, Skovronsky, Daniel M., Mintun, Mark A., Devous, Michael D.
• Format: Journal Article
• Language: English
• Published: United States Society of Nuclear Medicine 01.11.2015
• Subjects: Adult; Aged; Aged, 80 and over; Alzheimer Disease - diagnostic imaging; Alzheimer's disease; Amyloidogenic Proteins - metabolism; Amyloidosis - diagnostic imaging; Amyloidosis - pathology; Aniline Compounds; Automation; Autopsy; Biomarkers; Brain; Brain - diagnostic imaging; Cerebellum - diagnostic imaging; Correlation analysis; Ethylene Glycols; Female; Humans; Image Processing, Computer-Assisted - methods; Male; Middle Aged; Neuropathology; Nuclear medicine; Pons - diagnostic imaging; Positron-Emission Tomography - methods; Positron-Emission Tomography - statistics & numerical data; Radiopharmaceuticals; Reproducibility of Results; florbetapir; quantification; Alzheimer’s; PET; neuropathology
• ISSN: 0161-5505; 2159-662X; 1535-5667
• DOI: 10.2967/jnumed.114.153494

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. 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. 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. 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.