Data Driven Background Estimation in PET Using Event Energy Information

NIH RePORTER · NIH · R56 · $578,570 · view on reporter.nih.gov ↗

Abstract

The objective of this project is to develop methodology for energy-based background estimation that can be applied to clinical data and produce accurate quantitative PET images over challenging imaging situations such as low collected counts, high multiple scatter, and prompt gamma contamination when imaging non-standard PET isotopes. The goal is to enhance the accuracy of PET imaging in situations where current state-of-art scatter estimation techniques are limited in accuracy or perform poorly. In this proposal, we develop a data driven scatter estimation methodology that makes full use of the annihilation photon energy information present to estimate scatter. This method is also extended to provide correction for bias arising from prompt gammas present in data collected form some non-standard PET isotopes. We implement, optimize, and evaluate this algorithm on measured data from a clinical PET scanner for standard and non-standard isotopes, and subsequently apply the methodology to organ- specific scanners (brain and breast). The proposed work will be accomplished through the following specific aims: (i) optimization and evaluation of the EB method for scatter estimation, (ii) extension of the EB methodology to correct for prompt gamma contamination present in data acquired from non-standard PET isotopes, and (iii) application of the EB methodology to dedicated brain and breast PET scanner geometries. In addition to its advantages over existing scatter estimation methodology in situations with low collected counts and/or data with higher level of multiple scatter, the proposed technique is expected to be faster, does not require knowledge of activity distribution outside the imaging field-of-view, and does not require a transmission or CT image. Successful demonstration of this technique may significantly expand the application of quantitative PET/CT in oncology areas such as treatment monitoring with low- dose repeat PET scans, imaging with new biomarkers that use low positron yield radionuclides (e.g. 124I, 86Y, etc.), or acquiring data at high count-rates (as in cardiac imaging or imaging with 124I or 86Y). Beyond oncology, it will also provide improved quantitation in cardiac studies (82Rb, 13NH3, or 11C-actetate). Since, the proposed scatter estimation method does not require a CT image it may have an application in PET/MR imaging as well as clinical studies with some patient motion – both situations where the CT image is either not available or is compromised leading to errors in the traditional way of estimating scatter.

Key facts

NIH application ID
10644161
Project number
1R56EB033585-01
Recipient
UNIVERSITY OF PENNSYLVANIA
Principal Investigator
Suleman Surti
Activity code
R56
Funding institute
NIH
Fiscal year
2022
Award amount
$578,570
Award type
1
Project period
2022-09-01 → 2024-08-31