PET amyloid in normal aging: direct comparison of visual and automatic processing methods

Haller, Sven; Montandon, Marie Louise; Lilja, Johan; Rodriguez, Cristelle; Garibotto, Valentina; Herrmann, Françoís; Giannakopoulos, Pantéleimon

doi:10.1038/s41598-020-73673-1

Cited by 14 publications

(11 citation statements)

References 55 publications

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“…To date, in the clinical field, Aβ positivity of PET is generally determined by experienced clinicians based on visual rating. However, visual rating can be operator-and Aβ tracer-dependent, thus are prone to intra-and inter-rater discrepancies [8]. Interestingly, we found that the iterative outlier method-derived cutoff value had a higher concordance rate of Aβ positivity between the two tracers than that of the visual assessment.…”

Section: Discussionmentioning

confidence: 69%

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Finding the optimal cutoff value for amyloid β positivity using the iterative outlier method and concordance rate

et al. 2021

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Purpose: The purpose of this study was to calculate the cutoff value for amyloid β (Aβ) positron emission tomography (PET) positivity using the iterative outlier method and to evaluate its validity based on the concordance rate. Methods: We performed the iterative outlier method on 373 cognitively unimpaired (CU) subjects and calculated the optimal cutoff value for Aβ positivity. The validation was performed using the independent dataset, comprising 83 subjects (27 CU, 27 amnestic mild cognitive impairment, and 29 Alzheimer's dementia). We evaluated the validity of the Aβ cutoff value by calculating its concordance rate with the visual assessment and between two different Aβ tracers performed in the same subject. Results: The concordance rate of Aβ cutoff values with the visual assessment ranged from 84.3% to 91.5%, depending on the reference regions. The concordance rate of the cutoff values between the two Aβ tracers ranged from 90.3% to 97.5%, all of which were higher than that of the visual assessment (86.7%). Conclusion:We demonstrated that the iterative outlier method could identify the cutoff value for Aβ PET positivity.

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Section: Discussionmentioning

confidence: 69%

“…Until now, the validity of these cutoffs has often been evaluated with the standard-of-truth (SOT) based on either histological findings of brain autopsy or visual assessment of PET images. However, visual assessment is operator-dependent [8] and it is difficult to obtain postmortem data.…”

Section: Introductionmentioning

confidence: 99%

Finding the optimal cutoff value for amyloid β positivity using the iterative outlier method and concordance rate

et al. 2021

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“…Quantification of amyloid PET has shown strong concordance with binary visual assessment in several studies [ 25 , 57 , 63 , 65 , 66 , 97 , 107 , 109 , 173 , 174 , 185 ]. Amyloid PET tracers available in clinical and research settings have all demonstrated comparable cross-sectional amyloid SUVr results [ 186 – 188 ].…”

Section: Why Is Amyloid Pet Quantification Valuable and Clinically Be...mentioning

confidence: 75%

“…The Aβ index has not been widely used to date. Nonetheless, it was recently used in a study comparing visual read and automated methods for amyloid PET processing, where an optimal cut-off score of −0.36 achieved a sensitivity of 97% based on visual read in 155 elderly controls over a 4.5 year follow up [ 173 ].…”

Section: Methodsmentioning

confidence: 99%

Quantification of amyloid PET for future clinical use: a state-of-the-art review

Pemberton

Collij

Heeman

et al. 2022

Eur J Nucl Med Mol Imaging

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Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer’s disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be determined in vivo using positron emission tomography (PET), for which three fluorine-18 labelled radiotracers have been approved for clinical use. In clinical practice, trained readers will categorise scans as either Aβ positive or negative, based on visual inspection. Diagnostic decisions are often based on these reads and patient selection for clinical trials is increasingly guided by amyloid status. However, tracer deposition in the grey matter as a function of amyloid load is an inherently continuous process, which is not sufficiently appreciated through binary cut-offs alone. State-of-the-art methods for amyloid PET quantification can generate tracer-independent measures of Aβ burden. Recent research has shown the ability of these quantitative measures to highlight pathological changes at the earliest stages of the AD continuum and generate more sensitive thresholds, as well as improving diagnostic confidence around established binary cut-offs. With the recent FDA approval of aducanumab and more candidate drugs on the horizon, early identification of amyloid burden using quantitative measures is critical for enrolling appropriate subjects to help establish the optimal window for therapeutic intervention and secondary prevention. In addition, quantitative amyloid measurements are used for treatment response monitoring in clinical trials. In clinical settings, large multi-centre studies have shown that amyloid PET results change both diagnosis and patient management and that quantification can accurately predict rates of cognitive decline. Whether these changes in management reflect an improvement in clinical outcomes is yet to be determined and further validation work is required to establish the utility of quantification for supporting treatment endpoint decisions. In this state-of-the-art review, several tools and measures available for amyloid PET quantification are summarised and discussed. Use of these methods is growing both clinically and in the research domain. Concurrently, there is a duty of care to the wider dementia community to increase visibility and understanding of these methods.

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“…Most of these studies were cross-sectional, explored one imaging modality, and mainly included MCI and AD cases. In the last years, we have focused our research on the very early phases of cognitive decrement that are still compatible with normal aging (Haller et al, 2019(Haller et al, , 2020Montandon et al, 2020b). In a recent study using qualitative MRI markers in the context of a 4.5-year longitudinal study in older communitydwellers, we reported that the accumulation of four CMB or more at baseline as well as increase of visually assessed right MTA at follow-up (but not Fazekas score, amyloid positivity or abnormal FDG-PET patterns) were the only qualitative imaging markers to be independently associated with progressive deterioration of cognitive performance within the age-adjusted norms (Montandon et al, 2020b).…”

Section: Introductionmentioning

confidence: 99%

Prediction of Subtle Cognitive Decline in Normal Aging: Added Value of Quantitative MRI and PET Imaging

Giannakopoulos

Montandon

Rodriguez

et al. 2021

Front. Aging Neurosci.

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Quantitative imaging processing tools have been proposed to improve clinic-radiological correlations but their added value at the initial stages of cognitive decline is still a matter of debate. We performed a longitudinal study in 90 community-dwelling elders with three neuropsychological assessments during a 4.5 year follow-up period, and visual assessment of medial temporal atrophy (MTA), white matter hyperintensities, cortical microbleeds (CMB) as well as amyloid positivity, and presence of abnormal FDG-PET patterns. Quantitative imaging data concerned ROI analysis of MRI volume, amyloid burden, and FDG-PET metabolism in several AD-signature areas. Multiple regression models, likelihood-ratio tests, and areas under the receiver operating characteristic curve (AUC) were used to compare quantitative imaging markers to visual inspection. The presence of more or equal to four CMB at inclusion and slight atrophy of the right MTL at follow-up were the only parameters to be independently related to the worst cognitive score explaining 6% of its variance. This percentage increased to 24.5% when the ROI-defined volume loss in the posterior cingulate cortex, baseline hippocampus volume, and MTL metabolism were also considered. When binary classification of cognition was made, the area under the ROC curve increased from 0.69 for the qualitative to 0.79 for the mixed imaging model. Our data reveal that the inclusion of quantitative imaging data significantly increases the prediction of cognitive changes in elderly controls compared to the single consideration of visual inspection.

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PET amyloid in normal aging: direct comparison of visual and automatic processing methods

Cited by 14 publications

References 55 publications

Finding the optimal cutoff value for amyloid β positivity using the iterative outlier method and concordance rate

Finding the optimal cutoff value for amyloid β positivity using the iterative outlier method and concordance rate

Quantification of amyloid PET for future clinical use: a state-of-the-art review

Prediction of Subtle Cognitive Decline in Normal Aging: Added Value of Quantitative MRI and PET Imaging

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