Evidence map›Paper›PMID 37956261›Full record

ArticleMedical physics2024

Energy-based scatter estimation in clinical PET.

James J Hamill, Jorge Cabello, Suleman Surti, Joel S Karp

Open access · bronzeAbstract read
In one paragraph

Article in Medical physics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.6field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

James J HamillSiemens Medical Solutions, Knoxville, Tennessee, USA.
Jorge CabelloSiemens Medical Solutions, Knoxville, Tennessee, USA.
Suleman SurtiDepartment of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Joel S KarpDepartment of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Medical Solutions · GBUniversity of Pennsylvania · US

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
Data Driven Background Estimation in PET Using Event Energy InformationR56EB033585 · NIBIB · UNIVERSITY OF PENNSYLVANIA · PI SURTI, SULEMAN · 2022 to 2022
$579k
NCI NIH HHS R01 CA113941NIBIB NIH HHS R56 EB033585NIH HHS R01-CA113941NIH HHS R56-EB03358
6 · The paper itself

Abstract

backgroundScatter correction (SC) is essential in PET for accurate quantitative imaging. The state-of-the-art SC method is single-scatter simulation (SSS). Although this method is usually robust and accurate, it can fail in some situations, for example when there is motion between the CT and PET scans in PET/CT. Therefore, it is of interest to consider other SC methods. PURPOSE: In this work, an energy-based scatter estimation (EBS) method is described in detail, tested in phantoms and patients, and compared to SSS.

methodsThis version of EBS was developed for list-mode data from Biograph Vision-600 PET/CT scanner. EBS is based on digitized 2D energy histograms in each bin of a coarsely sampled PET sinogram, either with or without time of flight (TOF). The histograms are modeled as a noisy realization of a linear combination of nine basis functions whose parameters were derived from a measurement of the 511-keV photopeak spectrum as well as Monte-Carlo simulations of the scattering process. EBS uses an iterative expectation maximization approach to determine the coefficients in the linear combination, and from this estimates the scatter. The investigation was restricted to

resultsEBS and SSS images were visually similar in all cases except the torso + bladder phantom, where the EBS was much closer to the expected uniform image. The NU2-2018 analysis indicated a 2% scatter residual in EBS images compared to 3% with SSS, and 10% higher background variability, which is a surrogate for image noise. The cardiac phantom scan showed that CR was 98.2% with EBS and 99.6% with SSS, and that the SSS sinogram had values greater than the net-true emission sinogram, indicating a slight overcorrection in the case of SSS. In the lesion SUV comparison in patient scans, EBS correlated strongly (R

conclusionsIn evaluating clinically relevant parameters such as SUV in focal lesions, EBS and SSS give almost the same results. In phantoms, some scatter figures of merit were slightly improved by use of EBS, though an image variability figure of merit was slightly degraded. In typical oncological whole-body PET/CT, EBS may be a suitable replacement for SSS, especially when SSS fails due to technical problems during the scan.

Indexed as

Positron-Emission TomographyPositron Emission Tomography Computed TomographyComputer SimulationHumansImage Processing, Computer-AssistedPhantoms, ImagingPhysical PhenomenaScattering, RadiationenergyPETscatter

Identifiers

PMID37956261
PMCPMC11483182
OpenAlexW4388622912

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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.