PURPOSE: We investigated whether the reproducibility of standard visual reporting (STD method) in flutemetamol (FMM) PET can be improved using a newly introduced method that uses grey matter edges derived from the perfusion phase (GM-EDGE method). METHODS: Two-phase FMM PET was performed in 121 patients with mild cognitive impairment. Five nuclear medicine physicians blindly and independently evaluated all late-phase scans, initially employing the STD method and later the GM-EDGE method. A five-point scale was used to express the degree of amyloid positivity, and a binary classification (positive/negative) was used in combination with subjective confidence (five-point scale). Multirater Fleiss' kappa, intraclass correlation coefficient (ICC) and inter-rater reliability (Cohen's kappa) were determined for the STD and GM-EDGE methods. RESULTS: The weighted Cohen's kappa values for the five-point measure of amyloid positivity ranged from 0.63 to 0.73 (median 0.70) for the STD method and from 0.76 to 0.89 (median 0.80) for the GM-EDGE method (ICC 0.84, 95% CI 0.79-0.88, for the STD method; 0.91, 95% CI 0.89-0.94, for the GM-EDGE method). The nonweighted Cohen's kappa value for the binary classification ranged from 0.73 to 0.93 (median 0.82) for the STD method and 0.90 to 0.97 (median 0.93) for the GM-EDGE method (Fleiss' kappa 0.82, 95% CI 0.77-0.88, for the STD method; 0.93, 95% CI 0.87-0.99, for the GM-EDGE method). The GM-EDGE method resulted in significantly greater subjective confidence in the readings of four physicians (p < 0.010). The binary classification was concordant among all five physicians in 80.8% of the scans using the STD method and in 91.6% of the scans using the GM-EDGE method (p = 0.016). CONCLUSION: The newly introduced GM-EDGE method was associated with significantly higher inter-rater agreement among physicians and higher subjective confidence in the reading. The method is easy to implement in clinical practice, especially when the perfusion phase is utilized clinically.

Department of Nuclear Medicine PET Centre Na Homolce Hospital Roentgenova 37 2 150 30 Prague 5 Czech Republic

Zobrazit více v PubMed

Zhou L, Salvado O, Dore V, Bourgeat P, Raniga P, Macaulay SL, et al. MR-less surface-based amyloid assessment based on 11C PiB PET. PLoS One. 2014;9(1):e84777. doi: 10.1371/journal.pone.0084777. PubMed DOI PMC

Rosario BL, Weissfeld LA, Laymon CM, Mathis CA, Klunk WE, Berginc MD, et al. Inter-rater reliability of manual and automated region-of-interest delineation for PiB PET. Neuroimage. 2011;55(3):933–941. doi: 10.1016/j.neuroimage.2010.12.070. PubMed DOI PMC

Knešaurek K, Warnock G, Kostakoglu L, Burger C. Comparison of standardized uptake value ratio calculations in amyloid positron emission tomography brain imaging. World J Nucl Med. 2018;17(1):21–6. 10.4103/wjnm.WJNM_5_17. PubMed PMC

Joshi AD, Pontecorvo MJ, Lu M, Skovronsky DM, Mintun MA, Devous MD., Sr A semiautomated method for quantification of F18 florbetapir PET images. J Nucl Med. 2015;56(11):1736–1741. doi: 10.2967/jnumed.114.153494. PubMed DOI

Lundqvist R, Lilja J, Thomas BA, Lötjönen J, Villemagne VL, Rowe CC, et al. Implementation and validation of an adaptive template registration method for 18F-flutemetamol imaging data. J Nucl Med. 2013;54(8):1472–1478. doi: 10.2967/jnumed.112.115006. PubMed DOI

Thurfjell L, Lilja J, Lundqvist R, Buckley C, Smith A, Vandenberghe R, et al. Automated quantification of 18F-flutemetamol PET activity for categorizing scans as negative or positive for brain amyloid: concordance with visual image reads. J Nucl Med. 2014;55(10):1623–1628. doi: 10.2967/jnumed.114.142109. PubMed DOI

Su Y, Blazey TM, Snyder AZ, Raichle ME, Marcus DS, Ances BM, et al. Partial volume correction in quantitative amyloid imaging. Neuroimage. 2015;107:55–64. doi: 10.1016/j.neuroimage.2014.11.058. PubMed DOI PMC

Klunk WE, Koeppe RA, Price JC, Benzinger TL, Devous MD, Sr, Jagust WJ, et al. The Centiloid project: standardizing quantitative amyloid plaque estimation by PET. Alzheimers Dement. 2015;11(1):1-15.e1–1-15.e4. doi: 10.1016/j.jalz.2014.07.003. PubMed DOI PMC

Vandenberghe R, Nelissen N, Salmon E, Ivanoiu A, Hasselbalch S, Andersen A, et al. Binary classification of 18F-flutemetamol PET using machine learning: comparison with visual reads and structural MRI. Neuroimage. 2013;64:517–525. doi: 10.1016/j.neuroimage.2012.09.015. PubMed DOI

Blomquist G, Engler H, Nordberg A, Ringheim A, Wall A, Forsberg A, et al. Unidirectional influx and net accumulation of PIB. Open Neuroimag J. 2008;2:114–125. doi: 10.2174/1874440000802010114. PubMed DOI PMC

Hsiao IT, Huang CC, Hsieh CJ, Hsu WC, Wey SP, Yen TC, et al. Correlation of early phase 18F-florbetapir (AV-45/Amyvid) PET images to FDG images: preliminary studies. Eur J Nucl Med Mol Imaging. 2012;39(4):613–620. doi: 10.1007/s00259-011-2051-2. PubMed DOI

Lin KJ, Hsiao IT, Hsu JL, Huang CC, Huang KL, Hsieh CJ, et al. Imaging characteristic of dual-phase (18)F-florbetapir (AV-45/Amyvid) PET for the concomitant detection of perfusion deficits and beta-amyloid deposition in Alzheimer’s disease and mild cognitive impairment. Eur J Nucl Med Mol Imaging. 2016;43(7):1304–1314. doi: 10.1007/s00259-016-3359-8. PubMed DOI

Valentina G, Silvia M, Marco P. Dual-phase amyloid PET: hitting two birds with one stone. Eur J Nucl Med Mol Imaging. 2016;43(7):1300–1303. doi: 10.1007/s00259-016-3393-6. PubMed DOI

Belohlavek O, Jaruskova M. An easy way to increase confidence in beta-amyloid PET evaluation. Nucl Med Rev. 2017;20(2):107–109. doi: 10.5603/NMR.2017.0019. PubMed DOI

GE Healthcare. Vizamyl. Summary of product characteristics. European Medicines Agency; 2014. http://www.ema.europa.eu/docs/en_GB/document_library/EPAR_-_Product_Information/human/002557/WC500172950.pdf. Accessed 23 Aug 2018.

McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR, Jr, Kawas CH, et al. The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7(3):263–269. doi: 10.1016/j.jalz.2011.03.005. PubMed DOI PMC

Randolph JJ. Online kappa calculator. 2008. http://justusrandolph.net/kappa. Accessed 23 Aug 2018.

Harn NR, Hunt SL, Hill J, Vidoni E, Perry M, Burns JM. Augmenting amyloid PET interpretations with quantitative information improves consistency of early amyloid detection. Clin Nucl Med. 2017;42(8):577–581. doi: 10.1097/RLU.0000000000001693. PubMed DOI PMC

Buckley CJ, Sherwin PF, Smith AP, Wolber J, Weick SM, Brooks DJ. Validation of an electronic image reader training programme for interpretation of [18F] flutemetamol β-amyloid PET brain images. Nucl Med Commun. 2017;38(3):234–241. doi: 10.1097/MNM.0000000000000633. PubMed DOI PMC

Yamane T, Ishii K, Sakata M, Ikari Y, Nishio T, Ishii K, et al. Inter-rater variability of visual interpretation and comparison with quantitative evaluation of 11C-PiB PET amyloid images of the Japanese Alzheimer’s Disease Neuroimaging Initiative (J-ADNI) multicenter study. Eur J Nucl Med Mol Imaging. 2017;44(5):850–857. doi: 10.1007/s00259-016-3591-2. PubMed DOI

Spatial navigation questionnaires as a supportive diagnostic tool in early Alzheimer's disease

Mild behavioral impairment in early Alzheimer's disease and its association with APOE and BDNF risk genetic polymorphisms

Different Profiles of Spatial Navigation Deficits In Alzheimer's Disease Biomarker-Positive Versus Biomarker-Negative Older Adults With Amnestic Mild Cognitive Impairment