# Energy-Based Scatter Estimation Algorithm for Accurate Quantitative PET Imaging

> **NIH NIH R21** · UNIVERSITY OF PENNSYLVANIA · 2020 · $193,900

## Abstract

The objective of this project is to develop methodology for energy-based scatter estimation that can be
applied to clinical data and produce accurate quantitative PET images over challenging imaging
situations such as low collected counts and/or data acquisition at high count-rates. 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 scatter estimation
methodology that makes full use of the annihilation photon energy information present in the emission
PET data together with a simple energy calibration acquired with a physical phantom. We implement,
optimize, and evaluate this algorithm on measured data from a clinical PET scanner over all imaging
protocols. Our final goal is to implement it on clinical PET/CT and evaluate its impact on real patient data.
 The proposed work will be accomplished through the following specific aims: (i) Using realistic Monte
Carlo simulations to fully implement the proposed algorithm as it will be applied to measured data,
followed by parameter optimization and evaluation in reconstructed images, and (ii) evaluating the
methodology on measured data (phantoms as well as patient studies) followed by its extension to high
count-rate data acquisition situations.
 In addition to its advantages over existing scatter estimation methodology in situations with low
collected counts and/or data acquisition at high count-rates, the proposed technique is expected to be
faster and also 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:** 9975773
- **Project number:** 5R21CA239177-02
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Suleman Surti
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $193,900
- **Award type:** 5
- **Project period:** 2019-07-10 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9975773

## Citation

> US National Institutes of Health, RePORTER application 9975773, Energy-Based Scatter Estimation Algorithm for Accurate Quantitative PET Imaging (5R21CA239177-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9975773. Licensed CC0.

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