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Global and regional changes in cerebral blood flow (CBF) can result in biased quantitative estimates of amyloid load by PET imaging. Therefore, the current simulation study assessed effects of these changes on amyloid quantification using a reference tissue approach for [18F]flutemetamol and [18F]florbetaben. Previously validated pharmacokinetic rate constants were used to simulate time-activity curves (TACs) corresponding to full dynamic and dual-time-window acquisition protocols. CBF changes were simulated by varying the tracer delivery (K1) from +25 to -25%. The standardized uptake value ratio (SUVr) was computed and TACs were fitted using reference Logan (RLogan) and the simplified reference tissue model (SRTM) to obtain the relative delivery rate (R1) and volume of distribution ratio (DVR). RLogan was least affected by CBF changes (χ2 = 583 p 0.95) and SUVr's sensitivity to CBF changes improved for later uptake-times, with the exception of [18F]flutemetamol cortical changes. In conclusion, RLogan is the preferred method for amyloid quantification of [18F]flutemetamol and [18F]florbetaben studies and SRTM could be additionally used for obtaining a CBF proxy. ; The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: the project leading to this application has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 115952. This Joint Undertaking receives the support from the European Union's Horizon 2020 research and innovation programme and EFPIA http://www.imi.europa.eu. JDG holds a 'Ramón y Cajal' fellowship (RYC-2013-13054) from the Spanish Ministry of Science, Innovation and Universities.

Quality control (QC) of medical imaging devices is essential to ensure their proper function and to gain accurate and quantitative results. Therefore, several international bodies have published QC guidelines and recommendations for a wide range of imaging modalities to ensure adequate performance of the systems. Hybrid imaging systems such as positron emission tomography/computed tomography (PET/CT) or PET/magnetic resonance imaging (PET/MRI), in particular, present additional challenges caused by differences between the combined modalities. However, despite the increasing use of this hybrid imaging modality in recent years, there are no dedicated QC recommendations for PET/MRI. Therefore, this work aims at collecting information on QC procedures across a European PET/MRI network, presenting quality assurance procedures implemented by PET/MRI vendors and achieving a consensus on PET/MRI QC procedures across imaging centers. Users of PET/MRI systems at partner sites involved in the HYBRID consortium were surveyed about local frequencies of QC procedures for PET/MRI. Although all sites indicated that they perform vendor-specific daily QC procedures, significant variations across the centers were observed for other QC tests and testing frequencies. Likewise, variations in available recommendations and guidelines and the QC procedures implemented by vendors were found. Based on the available information and our clinical expertise within this consortium, we were able to propose a minimum set of PET/MRI QC recommendations including the daily QC, cross-calibration tests, and an image quality (IQ) assessment for PET and coil checks and MR image quality tests for MRI. Together with regular checks of the PET–MRI alignment, proper PET/MRI performance can be ensured. ; This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 764458. The work reflects only the author's view, and the Agency is not responsible for any use ...

Background: Detecting subtle-to-moderate biomarker changes such as those in amyloid PET imaging becomes increasingly relevant in the context of primary and secondary prevention of Alzheimer's disease (AD). This work aimed to determine if and when distribution volume ratio (DVR; derived from dynamic imaging) and regional quantitative values could improve statistical power in AD prevention trials. Methods: Baseline and annualized % change in [11C]PIB SUVR and DVR were computed for a global (cortical) and regional (early) composite from scans of 237 cognitively unimpaired subjects from the OASIS-3 database ( www.oasis-brains.org ). Bland-Altman and correlation analyses were used to assess the relationship between SUVR and DVR. General linear models and linear mixed effects models were used to determine effects of age, sex, and APOE-ε4 carriership on baseline and longitudinal amyloid burden. Finally, differences in statistical power of SUVR and DVR (cortical or early composite) were assessed considering three anti-amyloid trial scenarios: secondary prevention trials including subjects with (1) intermediate-to-high (Centiloid > 20.1), or (2) intermediate (20.1 < Centiloid ≤ 49.4) amyloid burden, and (3) a primary prevention trial focusing on subjects with low amyloid burden (Centiloid ≤ 20.1). Trial scenarios were set to detect 20% reduction in accumulation rates across the whole population and in APOE-ε4 carriers only. Results: Although highly correlated to DVR (ρ = .96), cortical SUVR overestimated DVR cross-sectionally and in annual % change. In secondary prevention trials, DVR required 143 subjects per arm, compared with 176 for SUVR. Both restricting inclusion to individuals with intermediate amyloid burden levels or to APOE-ε4 carriers alone further reduced sample sizes. For primary prevention, SUVR required less subjects per arm (n = 855) compared with DVR (n = 1508) and the early composite also provided considerable sample size reductions (n = 855 to n = 509 for SUVR, n = 1508 to n = 734 for DVR). Conclusion: Sample sizes in AD secondary prevention trials can be reduced by the acquisition of dynamic PET scans and/or by restricting inclusion to subjects with intermediate amyloid burden or to APOE-ε4 carriers only. Using a targeted early composite only leads to reductions of sample size requirements in primary prevention trials. These findings support strategies to enable smaller Proof-of-Concept Phase II clinical trials to better streamline drug development. ; Main authors of this paper have received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 115952. This Joint Undertaking receives the support from the European Union's Horizon 2020 research and innovation program and EFPIA. Data were provided by OASIS-3: Principal Investigators: T. Benzinger, D. Marcus, J. Morris; NIH P50AG00561, P30NS09857781, P01AG026276, P01AG003991, R01AG043434, UL1TR000448, and R01EB009352.

Imaging biomarkers (IBs) are integral to the routine management of patients with cancer. IBs used daily in oncology include clinical TNM stage, objective response and left ventricular ejection fraction. Other CT, MRI, PET and ultrasonography biomarkers are used extensively in cancer research and drug development. New IBs need to be established either as useful tools for testing research hypotheses in clinical trials and research studies, or as clinical decision-making tools for use in healthcare, by crossing 'translational gaps' through validation and qualification. Important differences exist between IBs and biospecimen-derived biomarkers and, therefore, the development of IBs requires a tailored 'roadmap'. Recognizing this need, Cancer Research UK (CRUK) and the European Organisation for Research and Treatment of Cancer (EORTC) assembled experts to review, debate and summarize the challenges of IB validation and qualification. This consensus group has produced 14 key recommendations for accelerating the clinical translation of IBs, which highlight the role of parallel (rather than sequential) tracks of technical (assay) validation, biological/clinical validation and assessment of cost-effectiveness; the need for IB standardization and accreditation systems; the need to continually revisit IB precision; an alternative framework for biological/clinical validation of IBs; and the essential requirements for multicentre studies to qualify IBs for clinical use. ; Development of this roadmap received support from Cancer Research UK and the Engineering and Physical Sciences Research Council (grant references A/15267, A/16463, A/16464, A/16465, A/16466 and A/18097), the EORTC Cancer Research Fund, and the Innovative Medicines Initiative Joint Undertaking (grant agreement number 115151), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and European Federation of Pharmaceutical Industries and Associations (EFPIA) companies' in kind contribution.