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) application of the EB methodology to dedicated
brain and breast PET scanner geometries, and (iii) extension of the EB methodology to correct for
prompt gamma contamination present in data acquired from non-standard PET isotopes.
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 will significantly
impact routine oncologic imaging where heavy patients with increased scatter, reduced counts and
limited imaging field-of-view will be susceptible to reduced quantitative accuracy. In addition, this
technique can also expand the application of quantitative PET/CT in new oncology imaging 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.