Evidence map›Paper›PMID 36576853›Full record

ArticleMedical physics2023

Phantom and methodology for comparison of small lesion detectability in PET.

Scott D Wollenweber, Adam M Alessio, Paul E Kinahan

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Article in Medical physics, 2023. 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

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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

3 authors.

Scott D WollenweberGE Healthcare, Waukesha, Wisconsin, USA.
Adam M AlessioComputational Mathematics, Science and Engineering, IQ Rm. 1116, BioEngineering Facility, East Lansing, Michigan, USA.
Paul E KinahanDepartment of Bioengineering and Physics, Imaging Research Laboratory, Director of PET/CT Physics, UW Medical Center, University of Washington, Seattle, Washington, USA.

Funding

TR&D Project 3: Virtual ReadersP41EB028744 · NIBIB · DUKE UNIVERSITY · PI Ehsan Samei · 2021 to 2026
$7.8M
Characterizing, optimizing, and harmonizing cancer detection with PET imagingR01CA258298 · NCI · UNIVERSITY OF WASHINGTON · PI Paul E. Kinahan · 2022 to 2026
$3.3M
NCI NIH HHS R01 CA258298NIBIB NIH HHS P41 EB028744NIH HHS R01CA258298
6 · The paper itself

Abstract

purposeThe main goal of this work is to describe a phantom design, data acquisition and data analysis methodology enabling comparison of small lesion detectability between PET imaging systems and reconstruction algorithms. Several methods are currently available to characterize intrinsic and image quality performance, but none focus exclusively on small lesion detectability.

methodsWe previously developed a small-lesion detection phantom and described initial results using a head-size phantom. Unlike most fillable nuclear medicine phantoms, this phantom offers a semi-realistic heterogenous background and wall-less contrast features. In this work, the methodology is extended to include (a) the use of both head- and body-sized phantoms and (b) a multi-scan data collection and analysis method. We present an example use case of the phantom and detection estimation methodology, comparing the small-lesion detection performance across four commercial PET/CT systems.

resultsRepeat acquisitions of the phantom enabled estimation of model observer performance and surrogates of detectability. As anticipated, estimated detectability increased with the square root of system sensitivity and TOF offered marked improvement in detectability, especially for the body sized object. The proposed approach characterizing detectability at different times during the decay of the phantom enabled comparison of small lesion detectability at matched activity concentrations (and scan durations) across different scanners.

conclusionThe proposed approach offers a reproducible tool for evaluating relative tradeoffs of system performance on small lesion detectability.

Indexed as

Positron Emission Tomography Computed TomographyTomography, X-Ray ComputedAlgorithmsImage Processing, Computer-AssistedPhantoms, ImagingPositron-Emission Tomographydetectionimage qualitypositron emission tomography (PET)

Identifiers

PMID36576853
PMCPMC10175120

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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.