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Quantification of (11)C-PIB kinetics in cardiac amyloidosis
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Medicinal Chemistry, Preparative Medicinal Chemistry.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
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2018 (English)In: Journal of Nuclear Cardiology, ISSN 1071-3581, EISSN 1532-6551Article in journal (Refereed) Epub ahead of print
Abstract [en]

BACKGROUND: The purpose of this work was to determine the optimal tracer kinetic model of (11)C-PIB and to validate the use of the simplified methods retention index (RI) and standardized uptake value (SUV) for quantification of cardiac (11)C-PIB uptake in amyloidosis. METHODS AND RESULTS: Single-tissue, reversible and irreversible two-tissue models were fitted to data from seven cardiac amyloidosis patients who underwent (11)C-PIB PET scans and arterial blood sampling for measurement of blood radioactivity and metabolites. The irreversible two-tissue model (2Tirr) best described cardiac (11)C-PIB uptake. RI and SUV showed high correlation with the rate of irreversible binding (Ki) from the 2Tirr model (r(2 )=0.95 and r(2 )=0.94). Retrospective data from 10 amyloidosis patients and 5 healthy controls were analyzed using RI, SUV, as well as compartment modelling with a population-average metabolite correction. All measures were higher in amyloidosis patients than in healthy controls (p=.001), but with an overlap between groups for Ki. CONCLUSION: An irreversible two-tissue model best describes the (11)C-PIB uptake in cardiac amyloidosis. RI and SUV correlate well with Ki from the 2Tirr model. RI and SUV discriminate better between amyloidosis patients and controls than Ki based on population-average metabolite correction.

Place, publisher, year, edition, pages
2018.
Keywords [en]
11c-pib, Cardiac amyloidosis, absolute quantification, retention index, standardized uptake value
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:uu:diva-356695DOI: 10.1007/s12350-018-1349-xISBN: 1532-6551 (Electronic) 1071-3581 (Linking) OAI: oai:DiVA.org:uu-356695DiVA, id: diva2:1236574
Note

Kero, Tanja Sorensen, Jens Antoni, Gunnar Wilking, Helena Carlson, Kristina Vedin, Ola Rosengren, Sara Wikstrom, Gerhard Lubberink, Mark eng J Nucl Cardiol. 2018 Jul 23. pii: 10.1007/s12350-018-1349-x. doi: 10.1007/s12350-018-1349-x.

Available from: 2018-08-03 Created: 2018-08-03 Last updated: 2018-10-25Bibliographically approved
In thesis
1. Methodological aspects of quantitative cardiac molecular imaging
Open this publication in new window or tab >>Methodological aspects of quantitative cardiac molecular imaging
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The objective of this research was to facilitate the use of quantitative cardiac molecular imaging by developing and validating methods and applications. More specifically:

we determined the optimal tracer kinetic model for analysis of 11C-PIB and evaluated the performance of two simpler measures, retention index (RI) and standardized uptake value (SUV), in the quantification of cardiac 11C-PIB uptake in amyloidosis. An irreversible two-tissue (2Tirr) model best described the 11C-PIB uptake in cardiac amyloidosis. RI and SUV showed high correlation with quantitative results from this kinetic model and also a better discrimination between amyloidosis patients and controls than a 2Tirr model with population averaged metabolite correction. RI and SUV are furthermore more feasible for use in clinical routine and therefore the preferred measure to use in PET diagnosis of cardiac amyloidosis. We also tested the feasibility of a semiautomatic software to analyze RI and visualize cardiac uptake of 11C-PIB in amyloidosis. The RI values were comparable with RI based on manual segmentation, showing significantly higher 11C-PIB RI in amyloidosis patients than in healthy volunteers. A fast and accurate semiautomatic analysis process is thus feasible to use for PET in cardiac amyloidosis instead of the laborious manual analyses that were used so far.

Furthermore, we assessed the quantitative accuracy of cardiac perfusion measurements with 15O-water PET in a digital time-of-flight PET-MR scanner. A high correlation and agreement between PET-MR based and PET-CT based MBF was found; cardiac perfusion measurements with 15O-water can therefore be performed accurately with the fully integrated Signa PET-MR scanner. 

Finally, we assessed the quantitative accuracy of cardiac perfusion measurements using dynamic contrast-enhanced MRI with simultaneous 15O-water PET as reference at rest and during adenosine-induced hyperemia with a fully integrated PET-MR scanner. The correlations between global and regional MRI- and PET-based MBF values were good and the biases were negliable for both global and regional MBF comparisons, but the limits of agreement were wide for both global and regional MBF, with larger variability for high MBF-values indicating that MRI-based quantitative MBF measurement based on widely available acquisition protocols is not yet ready for clinical introduction.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2018. p. 84
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1484
Keywords
PET, cardiac amyloidosis, 11C-PIB, retention index, standardized uptake value, PET-MR, MRI, myocardial blood flow, 15O-water, quantification, quantitative modeling
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-356721 (URN)978-91-513-0404-5 (ISBN)
Public defence
2018-09-28, Skoogsalen, ing 78/79, Akademiska sjukhuset, Sjukhusvägen 5B, Uppsala, 09:00 (English)
Opponent
Supervisors
Available from: 2018-09-07 Created: 2018-08-05 Last updated: 2018-10-02

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