The role of PET quantification in neurological imaging: FDG and amyloid imaging in dementia

Herholz, Karl

doi:10.1007/s40336-014-0073-z

Cited by 13 publications

(8 citation statements)

References 78 publications

(70 reference statements)

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“…Positron emission tomography (PET) coupled with computed tomography (CT) is an established quantitative imaging technique playing a key role in clinical oncology [1,2]. In particular, quantitative or semi-quantitative 18 F-FDG-PET/CT examinations cover a large part of PET indications, such as oncological, cardiac, and neurological imaging [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Phantom-based image quality assessment of clinical 18F-FDG protocols in digital PET/CT and comparison to conventional PMT-based PET/CT

et al. 2020

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Background: We assessed and compared image quality obtained with clinical 18 F-FDG whole-body oncologic PET protocols used in three different, state-of-the-art digital PET/ CT and two conventional PMT-based PET/CT devices. Our goal was to evaluate an improved trade-off between administered activity (patient dose exposure/signal-to-noise ratio) and acquisition time (patient comfort) while preserving diagnostic information achievable with the recently introduced digital detector technology compared to previous analogue PET technology. Methods: We performed list-mode (LM) PET acquisitions using a NEMA/IEC NU2 phantom, with activity concentrations of 5 kBq/mL and 25 kBq/mL for the background (9.5 L) and sphere inserts, respectively. For each device, reconstructions were obtained varying the image statistics (10, 30, 60, 90, 120, 180, and 300 s from LM data) and the number of iterations (range 1 to 10) in addition to the employed local clinical protocol setup. We measured for each reconstructed dataset: the quantitative cross-calibration, the image noise on the uniform background assessed by the coefficient of variation (COV), and the recovery coefficients (RCs) evaluated in the hot spheres. Additionally, we compared the characteristic time-activity-product (TAP) that is the product of scan time per bed position × mass-activity administered (in min•MBq/kg) across datasets. Results: Good system cross-calibration was obtained for all tested datasets with < 6% deviation from the expected value was observed. For all clinical protocol settings, image noise was compatible with clinical interpretation (COV < 15%). Digital PET showed an improved background signal-to-noise ratio as compared to conventional PMT-based PET. RCs were comparable between digital and PMTbased PET datasets. Compared to PMT-based PET, digital systems provided comparable image quality with lower TAP (from~40% less and up to 70% less). Conclusions: This study compared the achievable clinical image quality in three state-of-the-art digital PET/CT devices (from different vendors) as well as in two conventional PMT-based PET. Reported results show that a comparable image quality is achievable with a TAP reduction of~40% in digital PET. This could lead to a significant reduction of the administered mass-activity and/or scan time with direct benefits in terms of dose exposure and patient comfort.

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Section: Introductionmentioning

confidence: 99%

Phantom-based image quality assessment of clinical 18F-FDG protocols in digital PET/CT and comparison to conventional PMT-based PET/CT

et al. 2020

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“…Quantifying the metabolic decline of the brain as it ages is important in order to better understand not only the relationship between aging-related cognitive and metabolic changes in the brain but also the difference between normal and pathological brain aging (Cunnane et al, 2016c). Indeed, brain glucose hypometabolism is well-known to be present in Alzheimer’s disease (AD) itself (Herholz, 1995, 2014) and in conditions associated with increased risk of AD including mild cognitive impairment (MCI; Albin et al, 2010; Pagani et al, 2015), carriers of the apolipoprotein E4 (APOE4) allele (Mosconi et al, 2008a), a family history of AD (Reiman et al, 2004; Mosconi et al, 2007a), and type 2 diabetes (Baker et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Links Between Metabolic and Structural Changes in the Brain of Cognitively Normal Older Adults: A 4-Year Longitudinal Follow-Up

Castellano

Hudon

Croteau

et al. 2019

Front. Aging Neurosci.

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We aimed to longitudinally assess the relationship between changing brain energy metabolism (glucose and acetoacetate) and cognition during healthy aging. Participants aged 71 ± 5 year underwent cognitive evaluation and quantitative positron emission tomography (PET) and magnetic resonance imaging (MRI) scans at baseline ( N = 25) and two ( N = 25) and four ( N = 16) years later. During the follow-up, the rate constant for brain extraction of glucose (K glc ) declined by 6%–12% mainly in the temporo-parietal lobes and cingulate gyri ( p ≤ 0.05), whereas brain acetoacetate extraction (Kacac) and utilization remained unchanged in all brain regions ( p ≥ 0.06). Over the 4 years, cognitive results remained within the normal age range but an age-related decline was observed in processing speed. K glc in the caudate was directly related to performance on several cognitive tests ( r = +0.41 to +0.43, all p ≤ 0.04). Peripheral insulin resistance assessed by the homeostasis model assessment of insulin resistance (HOMA-IR) was significantly inversely related to K glc in the thalamus ( r = −0.44, p = 0.04) and in the caudate ( r = −0.43, p = 0.05), and also inversely related to executive function, attention and processing speed ( r = −0.45 to −0.53, all p ≤ 0.03). We confirm in a longitudinal setting that the age-related decline in K glc is directly associated with declining performance on some tests of cognition but does not significantly affect Kacac.

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“…In these cases, the use of standardized uptake value ratio (SUVr) quantification is usually suggested instead of visual inspection. SUVr utilizes static imaging and is evaluated in respect to a region without altered metabolism or with mildly affected metabolism in AD [ 168 ].…”

Section: Emerging Ad “Dry” Biomarkers: Structural and Functional Tmentioning

confidence: 99%

Molecular and Imaging Biomarkers in Alzheimer’s Disease: A Focus on Recent Insights

Clara

Lavitrano

Salvatore

et al. 2020

JPM

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Alzheimer’s disease (AD) is the most common neurodegenerative disease among the elderly, affecting millions of people worldwide and clinically characterized by a progressive and irreversible cognitive decline. The rapid increase in the incidence of AD highlights the need for an easy, efficient and accurate diagnosis of the disease in its initial stages in order to halt or delay the progression. The currently used diagnostic methods rely on measures of amyloid-β (Aβ), phosphorylated (p-tau) and total tau (t-tau) protein levels in the cerebrospinal fluid (CSF) aided by advanced neuroimaging techniques like positron emission tomography (PET) and magnetic resonance imaging (MRI). However, the invasiveness of these procedures and the high cost restrict their utilization. Hence, biomarkers from biological fluids obtained using non-invasive methods and novel neuroimaging approaches provide an attractive alternative for the early diagnosis of AD. Such biomarkers may also be helpful for better understanding of the molecular mechanisms underlying the disease, allowing differential diagnosis or at least prolonging the pre-symptomatic stage in patients suffering from AD. Herein, we discuss the advantages and limits of the conventional biomarkers as well as recent promising candidates from alternative body fluids and new imaging techniques.

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The role of PET quantification in neurological imaging: FDG and amyloid imaging in dementia

Cited by 13 publications

References 78 publications

Phantom-based image quality assessment of clinical 18F-FDG protocols in digital PET/CT and comparison to conventional PMT-based PET/CT

Phantom-based image quality assessment of clinical 18F-FDG protocols in digital PET/CT and comparison to conventional PMT-based PET/CT

Links Between Metabolic and Structural Changes in the Brain of Cognitively Normal Older Adults: A 4-Year Longitudinal Follow-Up

Molecular and Imaging Biomarkers in Alzheimer’s Disease: A Focus on Recent Insights

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