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Park YJ, Moon SY, Yoon JK, Lee SJ, An YS. Establishing cutoff values for visual amyloid positivity in [ 18F]flutemetamol PET. EJNMMI Res 2025; 15:1. [PMID: 39776383 PMCID: PMC11711603 DOI: 10.1186/s13550-024-01193-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2024] [Accepted: 12/29/2024] [Indexed: 01/11/2025] Open
Abstract
BACKGROUND This study aimed to establish the optimal cutoff values for visual amyloid positivity using standardized uptake value ratios (SUVRs) in [18F]flutemetamol (FMM) positron emission tomography (PET) imaging. Given the variability in amyloid assessment, our goal was to determine cutoff values that enhance diagnostic accuracy and assist clinicians in reliably identifying amyloid positivity. RESULTS The identified cutoff values for visual amyloid positivity were > 1.6 for the cerebellar gray matter, > 1.38 for the whole cerebellum, and > 0.63 for the pons, yielding high sensitivity (95.5%, 94.5%, and 95.8%, respectively) and specificity (91.2%, 94.3%, and 95.2%, respectively). CONCLUSIONS The SUVR cutoff values demonstrated excellent diagnostic performance, supporting their clinical use in assessing visual amyloid positivity in [18F]FMM PET imaging.
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Affiliation(s)
- Yong-Jin Park
- Department of Nuclear Medicine and Molecular Imaging, Ajou University School of Medicine, Suwon, Korea
| | - So Young Moon
- Department of Neurology, Ajou University School of Medicine, Suwon, Korea
| | - Joon-Kee Yoon
- Department of Nuclear Medicine and Molecular Imaging, Ajou University School of Medicine, Suwon, Korea
| | - Su-Jin Lee
- Department of Nuclear Medicine and Molecular Imaging, Ajou University School of Medicine, Suwon, Korea
| | - Young-Sil An
- Department of Nuclear Medicine and Molecular Imaging, Ajou University School of Medicine, Suwon, Korea.
- Department of Nuclear Medicine and Molecular Imaging, School of Medicine, Ajou University, 206, World cup-ro, Yeongtong-gu, Suwon-si, Gyeonggi-do, Suwon, 16499, Korea.
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Kim S, Wang SM, Kang DW, Um YH, Han EJ, Park SY, Ha S, Choe YS, Kim HW, Kim REY, Kim D, Lee CU, Lim HK. A Comparative Analysis of Two Automated Quantification Methods for Regional Cerebral Amyloid Retention: PET-Only and PET-and-MRI-Based Methods. Int J Mol Sci 2024; 25:7649. [PMID: 39062892 PMCID: PMC11276670 DOI: 10.3390/ijms25147649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2024] [Revised: 07/06/2024] [Accepted: 07/10/2024] [Indexed: 07/28/2024] Open
Abstract
Accurate quantification of amyloid positron emission tomography (PET) is essential for early detection of and intervention in Alzheimer's disease (AD) but there is still a lack of studies comparing the performance of various automated methods. This study compared the PET-only method and PET-and-MRI-based method with a pre-trained deep learning segmentation model. A large sample of 1180 participants in the Catholic Aging Brain Imaging (CABI) database was analyzed to calculate the regional standardized uptake value ratio (SUVR) using both methods. The logistic regression models were employed to assess the discriminability of amyloid-positive and negative groups through 10-fold cross-validation and area under the receiver operating characteristics (AUROC) metrics. The two methods showed a high correlation in calculating SUVRs but the PET-MRI method, incorporating MRI data for anatomical accuracy, demonstrated superior performance in predicting amyloid-positivity. The parietal, frontal, and cingulate importantly contributed to the prediction. The PET-MRI method with a pre-trained deep learning model approach provides an efficient and precise method for earlier diagnosis and intervention in the AD continuum.
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Affiliation(s)
- Sunghwan Kim
- Department of Psychiatry, College of Medicine, Yeouido St. Mary’s Hospital, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea
| | - Sheng-Min Wang
- Department of Psychiatry, College of Medicine, Yeouido St. Mary’s Hospital, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea
| | - Dong Woo Kang
- Department of Psychiatry, College of Medicine, Seoul St. Mary’s Hospital, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea
| | - Yoo Hyun Um
- Department of Psychiatry, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea
| | - Eun Ji Han
- Division of Nuclear Medicine, Department of Radiology, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea
| | - Sonya Youngju Park
- Division of Nuclear Medicine, Department of Radiology, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea
| | - Seunggyun Ha
- Division of Nuclear Medicine, Department of Radiology, Seoul St. Mary’s Hospital, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea
| | - Yeong Sim Choe
- Research Institute, Neurophet Inc., Seoul 06234, Republic of Korea (R.E.K.)
| | - Hye Weon Kim
- Research Institute, Neurophet Inc., Seoul 06234, Republic of Korea (R.E.K.)
| | - Regina EY Kim
- Research Institute, Neurophet Inc., Seoul 06234, Republic of Korea (R.E.K.)
| | - Donghyeon Kim
- Research Institute, Neurophet Inc., Seoul 06234, Republic of Korea (R.E.K.)
| | - Chang Uk Lee
- Department of Psychiatry, College of Medicine, Seoul St. Mary’s Hospital, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea
| | - Hyun Kook Lim
- Department of Psychiatry, College of Medicine, Yeouido St. Mary’s Hospital, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea
- CMC Institute for Basic Medical Science, The Catholic Medical Center of The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea
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3
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Li Y, Zhang X, Zhao H, Wang Y, Zhang D, Wang X, Dong R, Yan XX, Wu J, Sui Y, Zhang J, Cui M. Screening of [ 18F]Florbetazine for Aβ Plaques and a Head-to-Head Comparison Study with [ 11C]Pittsburgh Compound-B ([ 11C]PiB) in Human Subjects. ACS Pharmacol Transl Sci 2024; 7:2054-2062. [PMID: 39022359 PMCID: PMC11249633 DOI: 10.1021/acsptsci.4c00149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2024] [Revised: 06/05/2024] [Accepted: 06/11/2024] [Indexed: 07/20/2024]
Abstract
Positron emission tomography (PET) imaging of amyloid-β (Aβ) has emerged as a crucial strategy for early diagnosis and monitoring of therapeutic advancements targeting Aβ. In our previous first-in-human study, we identified that [18F]Florbetazine ([18F]92), featuring a diaryl-azine scaffold, exhibits higher cortical uptake in Alzheimer's disease (AD) patients compared to healthy controls (HC). Building upon these promising findings, this study aimed to characterize the diagnostic potential of [18F]92 and its dimethylamino-modified tracer [18F]91 and further compare them with the benchmark [11C]PiB in the same cohort of AD patients and age-matched HC subjects. The cortical accumulation of these tracers was evident, with no significant radioactivity retention observed in the cortex of HC subjects, consistent with [11C]PiB images (correlation coefficient of 0.9125 and 0.7883 between [18F]Florbetazine/[18F]91 and [11C]PiB, respectively). Additionally, quantified data revealed higher standardized uptake value ratios (SUVR) (with the cerebellum as the reference region) of [18F]Florbetazine/[18F]91 in AD patients compared to the HC group ([18F]Florbetazine: 1.49 vs 1.16; [18F]91: 1.33 vs 1.20). Notably, [18F]Florbetazine exhibited less nonspecific bindings in myelin-rich regions, compared to the dimethylamino-substituted [18F]91, akin to [11C]PiB. Overall, this study suggests that [18F]Florbetazine displays superior characteristics to [18F]91 in identifying Aβ pathology in AD. Furthermore, the close agreement between the uptakes in nontarget regions for [18F]Florbetazine and [11C]PiB in this head-to-head comparison study underscores its suitability for both clinical and research applications.
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Affiliation(s)
- Yuying Li
- Key
Laboratory of Radiopharmaceuticals, Ministry of Education, Beijing Normal University, Beijing 100875, China
| | - Xiaojun Zhang
- Department
of Nuclear Medicine, Chinese PLA General
Hospital, Beijing 100853, China
| | | | - Yan Wang
- Department
of Anatomy and Neurobiology, Xiangya School of Medicine, Central South University, Changsha, Changsha 410013, China
| | - Dandan Zhang
- Center
for Advanced Quantum Studies and Department of Physics, Beijing Normal University, Beijing 100875, China
| | | | - Ruilin Dong
- HighTech
Atom Co., Ltd., Beijing 102413, China
| | - Xiao-xin Yan
- Department
of Anatomy and Neurobiology, Xiangya School of Medicine, Central South University, Changsha, Changsha 410013, China
| | - Jing Wu
- Center
for Advanced Quantum Studies and Department of Physics, Beijing Normal University, Beijing 100875, China
| | - Yanying Sui
- HighTech
Atom Co., Ltd., Beijing 102413, China
| | - Jinming Zhang
- Department
of Nuclear Medicine, Chinese PLA General
Hospital, Beijing 100853, China
| | - Mengchao Cui
- Key
Laboratory of Radiopharmaceuticals, Ministry of Education, Beijing Normal University, Beijing 100875, China
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Wagatsuma K, Sakata M, Miwa K, Hamano Y, Kawakami H, Kamitaka Y, Yamao T, Miyaji N, Ishibashi K, Tago T, Toyohara J, Ishii K. Phantom and clinical evaluation of the Bayesian penalised likelihood reconstruction algorithm Q.Clear without PSF correction in amyloid PET images. EJNMMI Phys 2024; 11:37. [PMID: 38647924 PMCID: PMC11035535 DOI: 10.1186/s40658-024-00641-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 04/12/2024] [Indexed: 04/25/2024] Open
Abstract
PURPOSE Bayesian penalised likelihood (BPL) reconstruction, which incorporates point-spread-function (PSF) correction, provides higher signal-to-noise ratios and more accurate quantitation than conventional ordered subset expectation maximization (OSEM) reconstruction. However, applying PSF correction to brain PET imaging is controversial due to Gibbs artefacts that manifest as unpredicted cortical uptake enhancement. The present study aimed to validate whether BPL without PSF would be useful for amyloid PET imaging. METHODS Images were acquired from Hoffman 3D brain and cylindrical phantoms for phantom study and 71 patients administered with [18F]flutemetamol in clinical study using a Discovery MI. All images were reconstructed using OSEM, BPL with PSF correction, and BPL without PSF correction. Count profile, %contrast, recovery coefficients (RCs), and image noise were calculated from the images acquired from the phantoms. Amyloid β deposition in patients was visually assessed by two physicians and quantified based on the standardised uptake value ratio (SUVR). RESULTS The overestimated radioactivity in profile curves was eliminated using BPL without PSF correction. The %contrast and image noise decreased with increasing β values in phantom images. Image quality and RCs were better using BPL with, than without PSF correction or OSEM. An optimal β value of 600 was determined for BPL without PSF correction. Visual evaluation almost agreed perfectly (κ = 0.91-0.97), without depending on reconstruction methods. Composite SUVRs did not significantly differ between reconstruction methods. CONCLUSION Gibbs artefacts disappeared from phantom images using the BPL without PSF correction. Visual and quantitative evaluation of [18F]flutemetamol imaging was independent of the reconstruction method. The BPL without PSF correction could be the standard reconstruction method for amyloid PET imaging, despite being qualitatively inferior to BPL with PSF correction for [18F]flutemetamol amyloid PET imaging.
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Affiliation(s)
- Kei Wagatsuma
- School of Allied Health Sciences, Kitasato University, 1-15-1 Kitazato, Minami-ku, Sagamihara, Kanagawa, 252-0373, Japan.
- Research Team for Neuroimaging, Tokyo Metropolitan Institute for Geriatrics and Gerontology, 35-2, Sakae-cho, Itabashi-ku, Tokyo, 173-0015, Japan.
| | - Muneyuki Sakata
- Research Team for Neuroimaging, Tokyo Metropolitan Institute for Geriatrics and Gerontology, 35-2, Sakae-cho, Itabashi-ku, Tokyo, 173-0015, Japan
| | - Kenta Miwa
- Department of Radiological Sciences, School of Health Sciences, Fukushima Medical University, 10-6 Sakaemachi, Fukushima-shi, Fukushima, 960-8516, Japan
| | - Yumi Hamano
- School of Allied Health Sciences, Kitasato University, 1-15-1 Kitazato, Minami-ku, Sagamihara, Kanagawa, 252-0373, Japan
| | - Hirofumi Kawakami
- GE HealthCare Japan, 4-7-127 Asahigaoka, Hino-shi, Tokyo, 191-8503, Japan
| | - Yuto Kamitaka
- Research Team for Neuroimaging, Tokyo Metropolitan Institute for Geriatrics and Gerontology, 35-2, Sakae-cho, Itabashi-ku, Tokyo, 173-0015, Japan
| | - Tensho Yamao
- Department of Radiological Sciences, School of Health Sciences, Fukushima Medical University, 10-6 Sakaemachi, Fukushima-shi, Fukushima, 960-8516, Japan
| | - Noriaki Miyaji
- Department of Radiological Sciences, School of Health Sciences, Fukushima Medical University, 10-6 Sakaemachi, Fukushima-shi, Fukushima, 960-8516, Japan
| | - Kenji Ishibashi
- Research Team for Neuroimaging, Tokyo Metropolitan Institute for Geriatrics and Gerontology, 35-2, Sakae-cho, Itabashi-ku, Tokyo, 173-0015, Japan
| | - Tetsuro Tago
- Research Team for Neuroimaging, Tokyo Metropolitan Institute for Geriatrics and Gerontology, 35-2, Sakae-cho, Itabashi-ku, Tokyo, 173-0015, Japan
| | - Jun Toyohara
- Research Team for Neuroimaging, Tokyo Metropolitan Institute for Geriatrics and Gerontology, 35-2, Sakae-cho, Itabashi-ku, Tokyo, 173-0015, Japan
| | - Kenji Ishii
- Research Team for Neuroimaging, Tokyo Metropolitan Institute for Geriatrics and Gerontology, 35-2, Sakae-cho, Itabashi-ku, Tokyo, 173-0015, Japan
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Roh HW, Son SJ, Hong CH, Moon SY, Lee SM, Seo SW, Choi SH, Kim EJ, Cho SH, Kim BC, Park S, Song S, An YS. Comparison of automated quantification of amyloid deposition between PMOD and Heuron. Sci Rep 2023; 13:9891. [PMID: 37336977 DOI: 10.1038/s41598-023-36986-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 06/13/2023] [Indexed: 06/21/2023] Open
Abstract
Several programs are widely used for clinical and research purposes to automatically quantify the degree of amyloid deposition in the brain using positron emission tomography (PET) images. Given that very few studies have investigated the use of Heuron, a PET image quantification software approved for clinical use, this study aimed to compare amyloid deposition values quantified from 18F-flutemetamol PET images using PMOD and Heuron. Amyloid PET data obtained from 408 patients were analysed using each quantitative program; moreover, the standardized uptake value ratios (SUVRs) of target areas were obtained by dividing the standardized uptake value (SUV) of the target region by the SUV of cerebellar grey matter as a reference. Compared with PMOD, Heuron yielded significantly higher SUVRs for all target areas (paired sample t-test, p < 0.001), except for the PC/PCC (p = 0.986). However, the Bland-Altman plot analysis indicated that the two quantitative methods may be used interchangeably. Moreover, receiver operating characteristic curve analysis revealed no significant between-method difference in the performance of the SUVRs in evaluating the visual positivity of amyloid deposits (p = 0.948). In conclusion, Heuron and PMOD have comparable performance in quantifying the degree of amyloid deposits in PET images.
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Affiliation(s)
- Hyun Woong Roh
- Department of Psychiatry, School of Medicine, Ajou University, Suwon, Korea
| | - Sang Joon Son
- Department of Psychiatry, School of Medicine, Ajou University, Suwon, Korea
| | - Chang Hyung Hong
- Department of Psychiatry, School of Medicine, Ajou University, Suwon, Korea
| | - So Young Moon
- Department of Neurology, School of Medicine, Ajou University, Suwon, Korea
| | - Sun Min Lee
- Department of Neurology, School of Medicine, Ajou University, Suwon, Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, Korea
| | - Seong Hye Choi
- Department of Neurology, School of Medicine, Inha University, Incheon, Korea
| | - Eun-Joo Kim
- Department of Neurology, Pusan National University Hospital, Medical Research Institute, Pusan National University School of Medicine, Busan, Korea
| | - Soo Hyun Cho
- Department of Neurology, Chonnam National University Medical School, Chonnam National University Hospital, Gwangju, Korea
| | - Byeong Chae Kim
- Department of Neurology, Chonnam National University Medical School, Chonnam National University Hospital, Gwangju, Korea
| | | | | | - Young-Sil An
- Department of Nuclear Medicine and Molecular Imaging, School of Medicine, Ajou University, 206, World cup-ro, Yeongtong-gu, Suwon-si, Gyeonggi-do, Suwon, 16499, Korea.
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Pemberton HG, Buckley C, Battle M, Bollack A, Patel V, Tomova P, Cooke D, Balhorn W, Hegedorn K, Lilja J, Brand C, Farrar G. Software compatibility analysis for quantitative measures of [ 18F]flutemetamol amyloid PET burden in mild cognitive impairment. EJNMMI Res 2023; 13:48. [PMID: 37225974 DOI: 10.1186/s13550-023-00994-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 05/05/2023] [Indexed: 05/26/2023] Open
Abstract
RATIONALE Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease pathogenesis. In clinical practice, trained readers will visually categorise positron emission tomography (PET) scans as either Aβ positive or negative. However, adjunct quantitative analysis is becoming more widely available, where regulatory approved software can currently generate metrics such as standardised uptake value ratios (SUVr) and individual Z-scores. Therefore, it is of direct value to the imaging community to assess the compatibility of commercially available software packages. In this collaborative project, the compatibility of amyloid PET quantification was investigated across four regulatory approved software packages. In doing so, the intention is to increase visibility and understanding of clinically relevant quantitative methods. METHODS Composite SUVr using the pons as the reference region was generated from [18F]flutemetamol (GE Healthcare) PET in a retrospective cohort of 80 amnestic mild cognitive impairment (aMCI) patients (40 each male/female; mean age = 73 years, SD = 8.52). Based on previous autopsy validation work, an Aβ positivity threshold of ≥ 0.6 SUVrpons was applied. Quantitative results from MIM Software's MIMneuro, Syntermed's NeuroQ, Hermes Medical Solutions' BRASS and GE Healthcare's CortexID were analysed using intraclass correlation coefficient (ICC), percentage agreement around the Aβ positivity threshold and kappa scores. RESULTS Using an Aβ positivity threshold of ≥ 0.6 SUVrpons, 95% agreement was achieved across the four software packages. Two patients were narrowly classed as Aβ negative by one software package but positive by the others, and two patients vice versa. All kappa scores around the same Aβ positivity threshold, both combined (Fleiss') and individual software pairings (Cohen's), were ≥ 0.9 signifying "almost perfect" inter-rater reliability. Excellent reliability was found between composite SUVr measurements for all four software packages, with an average measure ICC of 0.97 and 95% confidence interval of 0.957-0.979. Correlation coefficient analysis between the two software packages reporting composite z-scores was strong (r2 = 0.98). CONCLUSION Using an optimised cortical mask, regulatory approved software packages provided highly correlated and reliable quantification of [18F]flutemetamol amyloid PET with a ≥ 0.6 SUVrpons positivity threshold. In particular, this work could be of interest to physicians performing routine clinical imaging rather than researchers performing more bespoke image analysis. Similar analysis is encouraged using other reference regions as well as the Centiloid scale, when it has been implemented by more software packages.
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Affiliation(s)
- Hugh G Pemberton
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK.
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK.
- UCL Queen Square Institute of Neurology, University College London, London, UK.
| | | | - Mark Battle
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Ariane Bollack
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK
| | - Vrajesh Patel
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
| | - Petya Tomova
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
| | | | | | | | | | - Christine Brand
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
| | - Gill Farrar
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
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Quantitative comparative analysis of amyloid PET images using three radiopharmaceuticals. Ann Nucl Med 2023; 37:271-279. [PMID: 36749463 PMCID: PMC10129914 DOI: 10.1007/s12149-023-01824-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 01/31/2023] [Indexed: 02/08/2023]
Abstract
OBJECTIVE Amyloid positron emission tomography (PET) with F-18 florbetaben (FBB), F-18 flutemetamol (FMM), and F-18 florapronol (FPN) is being used clinically for the evaluation of dementia. These radiopharmaceuticals are commonly used to evaluate the accumulation of beta-amyloid plaques in the brain, but there are structural differences between them. We investigated whether there are any differences in the imaging characteristics. METHODS A total of 605 subjects were enrolled retrospectively in this study, including healthy subjects (HS) and patients with mild cognitive impairment or Alzheimer's disease. Participants underwent amyloid PET imaging using one of the three radiopharmaceuticals. The PET images were analyzed visually and semi-quantitatively using a standardized uptake value ratio (SUVR). In addition, we calculated and compared the cut-off SUVR of the representative regions for each radiopharmaceutical that can distinguish between positive and negative scans. RESULTS In the negative images of the HS group, the contrast between the white matter and the gray matter was high in the FMM PET images, while striatal uptake was relatively higher in the FPN PET images. The SUVR showed significant differences across the radiopharmaceuticals in all areas except the temporal lobe, but the range of differences was relatively small. Accuracy levels for the global cut-off SUVR to discriminate between positive and negative images were highest in FMM PET, with a value of 0.989. FBB PET also showed a high value of 0.978, while FPN PET showed a relatively low value of 0.901. CONCLUSIONS Negative amyloid PET images using the three radiopharmaceuticals showed visually and quantitatively similar imaging characteristics except in the striatum. Binary classification using the cut-off of the global cortex showed high accuracy overall, although there were some differences between the three PET images.
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8
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Peira E, Poggiali D, Pardini M, Barthel H, Sabri O, Morbelli S, Cagnin A, Chincarini A, Cecchin D. A comparison of advanced semi-quantitative amyloid PET analysis methods. Eur J Nucl Med Mol Imaging 2022; 49:4097-4108. [PMID: 35652962 PMCID: PMC9525368 DOI: 10.1007/s00259-022-05846-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 05/18/2022] [Indexed: 11/25/2022]
Abstract
PURPOSE To date, there is no consensus on how to semi-quantitatively assess brain amyloid PET. Some approaches use late acquisition alone (e.g., ELBA, based on radiomic features), others integrate the early scan (e.g., TDr, which targets the area of maximum perfusion) and structural imaging (e.g., WMR, that compares kinetic behaviour of white and grey matter, or SI based on the kinetic characteristics of the grey matter alone). In this study SUVr, ELBA, TDr, WMR, and SI were compared. The latter - the most complete one - provided the reference measure for amyloid burden allowing to assess the efficacy and feasibility in clinical setting of the other approaches. METHODS We used data from 85 patients (aged 44-87) who underwent dual time-point PET/MRI acquisitions. The correlations with SI were computed and the methods compared with the visual assessment. Assuming SUVr, ELBA, TDr, and WMR to be independent measures, we linearly combined them to obtain more robust indices. Finally, we investigated possible associations between each quantifier and age in amyloid-negative patients. RESULTS Each quantifier exhibited excellent agreement with visual assessment and strong correlation with SI (average AUC = 0.99, ρ = 0.91). Exceptions to this were observed for subcortical regions with ELBA and WMR (ρELBA = 0.44, ρWMR = 0.70). The linear combinations showed better performances than the individual methods. Significant associations were observed between TDr, WMR, SI, and age in amyloid-negative patients (p < 0.05). CONCLUSION Among the other methods, TDr came closest to the reference with less implementation complexity. Moreover, this study suggests that combining independent approaches gives better results than the individual procedure, so efforts should focus on multi-classifier systems for amyloid PET. Finally, the ability of techniques integrating blood perfusion to depict age-related variations in amyloid load in amyloid-negative subjects demonstrates the goodness of the estimate.
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Affiliation(s)
- Enrico Peira
- INFN - National Institute of Nuclear Physics, via Dodecaneso 33, 16146, Genoa, Italy.
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Child and Maternal Health (DINOGMI), University of Genoa, Genoa, Italy.
| | - Davide Poggiali
- PNC - Padua Neuroscience Center, University of Padua, Padua, Italy
| | - Matteo Pardini
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Child and Maternal Health (DINOGMI), University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Henryk Barthel
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | - Osama Sabri
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | - Silvia Morbelli
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Nuclear Medicine Unit, Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
| | - Annachiara Cagnin
- Neurology Unit, Department of Neurology, University Hospital of Padua, Padua, Italy
| | - Andrea Chincarini
- INFN - National Institute of Nuclear Physics, via Dodecaneso 33, 16146, Genoa, Italy
| | - Diego Cecchin
- PNC - Padua Neuroscience Center, University of Padua, Padua, Italy
- Nuclear Medicine Unit, Department of Medicine - DIMED, University Hospital of Padua, Padua, Italy
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9
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Müller EG, Edwin TH, Strand BH, Stokke C, Revheim ME, Knapskog AB. Is Amyloid Burden Measured by 18F-Flutemetamol PET Associated with Progression in Clinical Alzheimer's Disease? J Alzheimers Dis 2021; 85:197-205. [PMID: 34776444 PMCID: PMC8842772 DOI: 10.3233/jad-215046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: Patients with Alzheimer’s disease (AD) show heterogeneity in clinical progression rate, and we have limited tools to predict prognosis. Amyloid burden from 18F-Flutemetamol positron emission tomography (PET), as measured by standardized uptake value ratios (SUVR), might provide prognostic information. Objective: We investigate whether 18F-Flutemetamol PET composite or regional SUVRs are associated with trajectories of clinical progression. Methods: This observational longitudinal study included 94 patients with clinical AD. PET images were semi-quantified with normalization to pons. Group-based trajectory modeling was applied to identify trajectory groups according to change in the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) over time. Multinomial logistic regression models assessed the association of SUVRs with trajectory group membership. Results: Three trajectory groups were identified. In the regression models, neither composite nor regional SUVRs were associated with trajectory group membership. Conclusion: There were no associations between CDR progression and 18F-Flutemetamol PET-derived composite SUVRs or regional SUVRs in clinical AD.
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Affiliation(s)
- Ebba Gløersen Müller
- Division of Radiology and Nuclear Medicine, Department of Nuclear Medicine, Oslo University Hospital, Oslo, Norway.,Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Trine Holt Edwin
- Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway.,Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway.,Norwegian National Advisory Unit on Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway
| | - Bjørn Heine Strand
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway.,Norwegian National Advisory Unit on Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway.,Department of Chronic Diseases and Ageing, Norwegian Institute of Public Health, Oslo, Norway
| | - Caroline Stokke
- Division of Radiology and Nuclear Medicine, Department of Nuclear Medicine, Oslo University Hospital, Oslo, Norway.,Department of Physics, University of Oslo, Oslo, Norway
| | - Mona Elisabeth Revheim
- Division of Radiology and Nuclear Medicine, Department of Nuclear Medicine, Oslo University Hospital, Oslo, Norway.,Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
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