Non-invasive Estimation of the Arterial Input Function in PET Studies using Whole-Body Physiological Models

NIH RePORTER · NIH · R21 · $167,500 · view on reporter.nih.gov ↗

Abstract

Project Summary/Abstract Positron Emission Tomography (PET) is an imaging modality that can be used to asses many physiological or pathological process through the use of a variety of specific tracers. Currently, the most important clinical application is in oncology using the tracer 18F-FDG to detect tumors and metastases and assess treatment response. PET can be a fully quantitative imaging modality able to accurately measure a physiological property such as the glucose metabolic rate, blood flow, or various protein distribution in various part of the body. However, semi-quantitative indexes such as standard uptake values (SUV) are more routinely used in clinical settings, and even some research settings. They are two main obstacles to use the fully quantitative approach more frequently. The first one is the need for dynamic scans. The second is the need to measure the arterial input function (AIF) in order to apply kinetic modeling. This AIF measurement is invasive, and complex, especially for tracers that are metabolized. The goal of this study is to develop novel methods to estimate the input function directly from the PET images, including the metabolite correction, when a whole-body scan is performed, which is often already needed for the research or clinical application. We propose to develop whole-body physiological models (WBP models) to describe the in vivo distribution, metabolism and elimination of PET tracers and algorithms to estimate the arterial input function, including the metabolite-correction, non- invasively using these WBP models. We will apply these new methods to 18F-FDG and a variety of other tracers, including the radiotracer 11C-PBR28 used to measure inflammation, using retrospective analysis of existing data and newly acquired data to test and validate the methods. For 18F-FDG we will also apply these WBP models to improve the quantification of static whole-body scans routinely used in clinical practice by providing SUV values corrected for variability in the input function, and new semi-quantitative indexes of glucose metabolic rate more accurate that the SUV-based rates currently used clinically.

Key facts

NIH application ID
10239015
Project number
5R21EB026759-03
Recipient
YALE UNIVERSITY
Principal Investigator
jean-dominique gallezot
Activity code
R21
Funding institute
NIH
Fiscal year
2022
Award amount
$167,500
Award type
5
Project period
2019-09-16 → 2025-06-30