Evidence map›Paper›PMID 37064407›Full record

ArticleQuantitative imaging in medicine and surgery2023

Multicenter quantitative

Habibeh Vosoughi, Mehdi Momennezhad, Farshad Emami, Mohsen Hajizadeh, Arman Rahmim, Parham Geramifar

Abstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2023. 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
–field-weighted citation impact
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.

  1. Article
  2. Automated segmentation of lesions and organs at risk on [Cancer imaging : the official publication of the International Cancer Imaging Society · 2024
    Article
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

6 authors.

Habibeh VosoughiDepartment of Medical Physics, Mashhad University of Medical Science, Mashhad, Iran.
Mehdi MomennezhadNuclear Medicine Research Center, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Farshad EmamiNuclear Medicine and Molecular Imaging Department, Imam Reza International University, Razavi Hospital, Mashhad, Iran.
Mohsen HajizadehDepartment of Medical Physics, Mashhad University of Medical Science, Mashhad, Iran.
Arman RahmimDepartment of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada.
Parham GeramifarResearch Center for Nuclear Medicine, Tehran University of Medical Science, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Harmonization methods reduce variability between different make and models of positron emission tomography (PET) scanners. The study aims to explore harmonization strategies that lead to comparable and robust quantitative metrics in a multicenter setting. Methods: NEMA IEC Phantom data acquisition was performed for low and high spheres-to-background ratios (SBR4:1 and 10:1) on six PET/CT (computed tomography) scanners. Different reconstruction sets, including the number of sub-iterations, number of subsets, and full width at half maximum (FWHM) for each scanner, were evaluated towards optimized and harmonized reconstruction settings. Recovery coefficients (RCs) of four quantitative metrics, including standardized uptake value (SUV) Results: A significant difference (P value <0.0001) was observed in the aforementioned quantitative metrics between SBR10 and SBR4. Reconstruction parameter sets with the smallest RMSE and RC values within 10% bias were identified as the best candidate for harmonization. The coefficient of variation of the mean value of RCs (CV Conclusions: Harmonizing PET/CT systems with and without point spread function/time of flight (PSF/TOF) using various vendor-developed image reconstruction algorithms improves the quantification reproducibility. RC

Indexed as

18F-fluorodeoxyglucose positron emission tomography/computer tomography (18F-FDG PET/CT)harmonizationquantificationreproducibility

Identifiers

PMID37064407
PMCPMC10102741

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Registered trials

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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.