New PET Model for Quantifying Cardiac Amyloidosis Allows for More Accurate Diagnosis and Monitoring

June 25, 2023

Chicago, Illinois (Embargoed until 1:33 p.m. CDT, Sunday, June 25, 2023)—Researchers have identified the optimal tracer kinetic model to quantify 18F-flutemetamol myocardial uptake in patients with transthyretin (ATTR) cardiac amyloidosis. Presented at the 2023 Society of Nuclear Medicine and Molecular Imaging Annual Meeting, this method allows physicians to obtain a fully quantitative measurement of cardiac amyloidosis burden and response to treatment for the first time.

ATTR cardiac amyloidosis is a rare, life-threatening disorder caused by the buildup of abnormal proteins, called amyloid plaques, in the heart tissue. As the proteins build up, it becomes harder for the heart to function properly and can eventually lead to heart failure.

Recent studies have shown the promise of 18F-flutemetamol PET imaging for detecting ATTR cardiac amyloidosis. “Static PET data analysis methods for 18F-flutemetamol are time sensitive, due to patient-dependent tracer washout from the myocardium.  As a result, these methods can only provide physicians with a limited read-out,” stated Qiong Liu, a PhD student at Yale University in New Haven, Connecticut. “New methods to obtain fully quantitative myocardial volume of distribution with this tracer are needed.”

To determine the optimal method for quantifying 18F-flutemetamol myocardial uptake, Liu and colleagues performed kinetic modeling on dynamic 18F-flutemetamol PET scans of six ATTR cardiac amyloidosis patients. Dynamic images were reconstructed, and several compartmental models were tested. Parametric images of the volume of distribution were then generated and analyzed.

Researchers found that the kinetics of 18F-flutemetamol are best quantified using a two-tissue reversible compartment model. The simplified graphical Logan plot identified the volume of distribution parameter generated from the first 30-minute dynamic scan as a quantitative parameter that is potentially useful for diagnosing and evaluating treatment in patients with ATTR cardiac amyloidosis.

“These findings suggest that commonly employed semiquantitative methodologies, such as standardized uptake values used for 18F-FDG, are not optimal for 18F-flutemetamol. Using parametric modeling to fully quantify volume of distribution may provide clinicians with a more accurate and robust method for assessing the presence and progression of amyloid plaques in the myocardium, ultimately improving patient care,” said Liu.

The study underscores the importance of understanding the fundamental kinetics of tracers in the target organ of interest, which is especially important to the optimal use of any new tracer. Similar approaches using dynamic and parametric imaging may also be beneficial for other tracers.

Figure 6. VT images for six patients generated from 30 minutes of dynamic data. Mean VT values of myocardium are shown on the bottom right.

Abstract 270. “Dynamic Imaging and Tracer Kinetic Modeling of 18F-flutemetamol PET for ATTR Cardiac Amyloidosis Patients.” Qiong Liu, Tiantian Shi, Paul Gravel, Ramesh Fazzone-Chettiar, Xueqi Guo, Huidong Xie, Xiongchao Chen, Yi-Hwa Liu, Richard E. Carson, Chi Liu, and Edward J. Miller, Yale University, New Haven, Connecticut; and Koen Van Laere, University Hospital Leuven, Leuven, Belgium.


Link to Session

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All 2023 SNMMI Annual Meeting abstracts can be found online.

About the Society of Nuclear Medicine and Molecular Imaging

The Society of Nuclear Medicine and Molecular Imaging (SNMMI) is an international scientific and medical organization dedicated to advancing nuclear medicine and molecular imaging—vital elements of precision medicine that allow diagnosis and treatment to be tailored to individual patients in order to achieve the best possible outcomes.

SNMMI’s members set the standard for molecular imaging and nuclear medicine practice by creating guidelines, sharing information through journals and meetings and leading advocacy on key issues that affect molecular imaging and therapy research and practice. For more information, visit www.snmmi.org.