Evidence map›Paper›PMID 41929560›Full record

ArticleIEEE transactions on radiation and plasma medical sciences2025

Impact of detector parameters and image resolution modeling on dedicated brain PET imaging.

Min Gao, Samuel Matej, Joel S Karp, Suleman Surti

Abstract read
In one paragraph

Article in IEEE transactions on radiation and plasma medical sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Min GaoUniversity of Pennsylvania, Philadelphia, United States.
Samuel MatejUniversity of Pennsylvania, Philadelphia, United States.
Joel S KarpUniversity of Pennsylvania, Philadelphia, United States.
Suleman SurtiUniversity of Pennsylvania, Philadelphia, United States.

Funding

Time-of-Flight PET for Improved Whole-Body ImagingR01CA113941 · NCI · UNIVERSITY OF PENNSYLVANIA · PI JOEL S KARP, Suleman Surti · 2006 to 2026
$9.8M
NCI NIH HHS R01 CA113941
6 · The paper itself

Abstract

High performance brain PET scanners suitable for accurate and precise measurement of uptake in small regions of the brain require high spatial resolution (1.5-2 mm) together with high system sensitivity. While small cross section crystals are needed to achieve high spatial resolution with pixelated detectors, effective system sensitivity requires long crystals and good time-of-flight (TOF) resolution. In addition, depending on crystal thickness, some level of depth-of-interaction (DOI) capability may also be needed to reduce parallax error. While various methods for DOI measurement can be utilized within the detector, the impact on reconstructed spatial resolution as a function of crystal thickness needs to be carefully evaluated. The focus of this work is to use Monte Carlo simulations to evaluate the impact of crystal size, thickness, and DOI resolution on the reconstructed spatial resolution in a high-resolution brain scanner design. Two crystal cross sections were chosen, 1.6 mm × 1.6 mm and 2 mm × 2 mm, and three different LSO crystal thickness (10 mm, 15 mm, and 20 mm) were evaluated. We evaluated these system designs without DOI capability and with DOI resolution (4-12 mm) for varying crystal thickness. In addition, we evaluated the use of image-space resolution modeling (IRM) techniques, which can mitigate losses in spatial resolution and positioning accuracy due to parallax error and Compton scatter, and to complement the advantages of DOI capability. A brain size elliptical phantom with small spheres was simulated to study the overall benefit in uptake measurements for small objects using the contrast recovery coefficient (CRC) metric. Our results show that a system with 2 mm × 2 mm crystals can provide comparable image quality in terms of CRC measurement than one with 1.6 mm × 1.6 mm crystals. However, crystal thickness has a bigger impact on spatial resolution and CRC with performance degrading with best performance achieved with 10 mm thick crystals. DOI measurement is necessary with longer crystals in order to maintain good imaging performance with high sensitivity. For the 15 mm thick crystals 9 mm DOI resolution is needed to compensate for the loss in spatial resolution compared to 10 mm thick crystals without DOI, but still with lower CRC. A similar conclusion is reached for 20 mm crystals with 4 mm DOI resolution. Alternatively, IRM methods can provide improved and similar performance for all crystal thicknesses studied here, indicating a pathway for achieving our brain scanner design goals without additional cost, complexity, and performance tradeoffs. This work provides a systematic investigation for designing future brain PET systems.

Indexed as

Brain PET designimage resolution modelingspatial resolutionuptake measurement.

Identifiers

PMID41929560
PMCPMC13042831

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.