Hiroshi Matsuda1,2,3, Kengo Ito4, Kazunari Ishii5,6, Eku Shimosegawa7, Hidehiko Okazawa8, Masahiro Mishina9, Sunao Mizumura10, Kenji Ishii11, Kyoji Okita1, Yoko Shigemoto2,3, Takashi Kato12, Akinori Takenaka12, Hayato Kaida5,6, Kohei Hanaoka13, Keiko Matsunaga7, Jun Hatazawa13, Masamichi Ikawa14, Tetsuya Tsujikawa8, Miyako Morooka10, Kenji Ishibashi11, Masashi Kameyama15, Tensho Yamao1,3,16, Kenta Miwa1,16, Masayo Ogawa1, Noriko Sato2. 1. Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Kodaira, Japan. 2. Department of Radiology, National Center of Neurology and Psychiatry, Kodaira, Japan. 3. Cyclotron and Drug Discovery Research Center, Southern TOHOKU Research Institute for Neuroscience, Koriyama, Japan. 4. Innovation Center for Clinical Research, National Center for Geriatrics and Gerontology, Obu, Japan. 5. Department of Radiology, Kindai University Faculty of Medicine, Osakasayama, Japan. 6. Division of Positron Emission Tomography, Institute of Advanced Clinical Medicine, Kindai University Hospital, Osakasayama, Japan. 7. Department of Molecular Imaging in Medicine, Osaka University Graduate School of Medicine, Suita, Japan. 8. Biomedical Imaging Research Center, University of Fukui, Fukui, Japan. 9. Department of Neuro-Pathophysiological Imaging, Graduate School of Medicine, Nippon Medical School, Kawasaki, Japan. 10. Department of Radiology, Medical Centre Omori, Toho University, Tokyo, Japan. 11. Team for Neuroimaging Research, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan. 12. Department of Radiology, National Center for Geriatrics and Gerontology, Obu, Japan. 13. Joint Research Division for the Quantum Cancer Therapy, Research Center for Nuclear Physics, Osaka University, Osaka, Japan. 14. Department of Neurology, Faculty of Medical Sciences, Fukui, Japan. 15. Department of Radiology, Tokyo Metropolitan Geriatric Hospital, Tokyo, Japan. 16. Preparing Section for New Faculty of Medical Science, Fukushima Medical University, Fukushima, Japan.
Abstract
Background: In clinical practice, equivocal findings are inevitable in visual interpretation of whether amyloid positron emission tomography (PET) is positive or negative. It is therefore necessary to establish a more objective quantitative evaluation method for determining the indication for disease-modifying drugs currently under development. Aims: We aimed to determine cutoffs for positivity in quantitative analysis of 18F-flutemetamol PET in patients with cognitive impairment and suspected Alzheimer's disease (AD). We also evaluated the clinical efficacy of amyloid PET in the diagnosis of AD. This study was registered in the Japan Registry of Clinical Trials (jRCTs, 031180321). Methods: Ninety-three patients suspected of having AD underwent 18F-flutemetamol PET in seven institutions. A PET image for each patient was visually assessed and dichotomously rated as either amyloid-positive or amyloid-negative by two board-certified nuclear medicine physicians. If the two readers obtained different interpretations, the visual rating was rerun until they reached consensus. The PET images were quantitatively analyzed using the standardized uptake value ratio (SUVR) and standardized Centiloid (CL) scale with the whole cerebellum as a reference area. Results: Visual interpretation obtained 61 positive and 32 negative PET scans. Receiver operating characteristic analysis determined the best agreement of quantitative assessments and visual interpretation of PET scans to have an area under curve of 0.982 at an SUVR of 1.13 and a CL of 16. Using these cutoff values, there was high agreement between the two approaches (kappa = 0.88). Five discordant cases had SUVR and CL values ranging from 1.00 to 1.22 and from 1 to 26, respectively. In these discordant cases, either diffuse or mildly focal elevation of cortical activity confused visual interpretation. The amyloid PET outcome significantly altered the diagnosis of AD (χ2 = 51.3, p < 0.0001). PET imaging elevated the proportions of the very high likelihood category from 20.4 to 46.2% and the very low likelihood category from 0 to 22.6%. Conclusion: Quantitative analysis of amyloid PET using 18F-flutemetamol can objectively evaluate amyloid positivity using the determined cutoffs for SUVR and CL. Moreover, amyloid PET may have added value over the standard diagnostic workup in dementia patients with cognitive impairment and suspected AD.
Background: In clinical practice, equivocal findings are inevitable in visual interpretation of whether amyloid positron emission tomography (PET) is positive or negative. It is therefore necessary to establish a more objective quantitative evaluation method for determining the indication for disease-modifying drugs currently under development. Aims: We aimed to determine cutoffs for positivity in quantitative analysis of 18F-flutemetamol PET in patients with cognitive impairment and suspected Alzheimer's disease (AD). We also evaluated the clinical efficacy of amyloid PET in the diagnosis of AD. This study was registered in the Japan Registry of Clinical Trials (jRCTs, 031180321). Methods: Ninety-three patients suspected of having AD underwent 18F-flutemetamol PET in seven institutions. A PET image for each patient was visually assessed and dichotomously rated as either amyloid-positive or amyloid-negative by two board-certified nuclear medicine physicians. If the two readers obtained different interpretations, the visual rating was rerun until they reached consensus. The PET images were quantitatively analyzed using the standardized uptake value ratio (SUVR) and standardized Centiloid (CL) scale with the whole cerebellum as a reference area. Results: Visual interpretation obtained 61 positive and 32 negative PET scans. Receiver operating characteristic analysis determined the best agreement of quantitative assessments and visual interpretation of PET scans to have an area under curve of 0.982 at an SUVR of 1.13 and a CL of 16. Using these cutoff values, there was high agreement between the two approaches (kappa = 0.88). Five discordant cases had SUVR and CL values ranging from 1.00 to 1.22 and from 1 to 26, respectively. In these discordant cases, either diffuse or mildly focal elevation of cortical activity confused visual interpretation. The amyloid PET outcome significantly altered the diagnosis of AD (χ2 = 51.3, p < 0.0001). PET imaging elevated the proportions of the very high likelihood category from 20.4 to 46.2% and the very low likelihood category from 0 to 22.6%. Conclusion: Quantitative analysis of amyloid PET using 18F-flutemetamol can objectively evaluate amyloid positivity using the determined cutoffs for SUVR and CL. Moreover, amyloid PET may have added value over the standard diagnostic workup in dementiapatients with cognitive impairment and suspected AD.
Authors: Hugh G Pemberton; Lyduine E Collij; Fiona Heeman; Ariane Bollack; Mahnaz Shekari; Gemma Salvadó; Isadora Lopes Alves; David Vallez Garcia; Mark Battle; Christopher Buckley; Andrew W Stephens; Santiago Bullich; Valentina Garibotto; Frederik Barkhof; Juan Domingo Gispert; Gill Farrar Journal: Eur J Nucl Med Mol Imaging Date: 2022-04-07 Impact factor: 10.057