ArticleEJNMMI physics2023
Harmonization of standard uptake values across different positron emission tomography/computed tomography systems and different reconstruction algorithms: validation in oncology patients.
Article in EJNMMI physics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 11 citations in OpenAlex.
- A deep learning framework for lesion-level treatment response prediction in hodgkin lymphoma using PET/CT tensor radiomics.EJNMMI physics · 2026Article
- A Practical, Short, [Journal of clinical medicine · 2025Article
- Article
- Usefulness of pre- and post-treatment volumetric PET/CT parameters in predicting prognosis and evaluating recurrence for chemoradiotherapy-treated hypopharyngeal cancer.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2025Article
- A comprehensive review of the role of bone marrow biopsy and PET-CT in the evaluation of bone marrow involvement in adults newly diagnosed with DLBCL.Frontiers in oncology · 2024Review
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundEQ.PET is a software package that overcomes the reconstruction-dependent variation of standard uptake values (SUV). In this study, we validated the use of EQ.PET for harmonizing SUVs between different positron emission tomography/computed tomography (PET/CT) systems and reconstruction algorithms.
methodsIn this retrospective study, 49 patients with various cancers were scanned on a Biograph mCT (mCT) or Gemini TF 16 (Gemini) after [
resultsIn Group 1, the consistency of SUV and TBR between different reconstruction algorithms improved when the EQ.PET filter was applied. In Group 2, by comparing ΔSUV, ΔSUV%, ΔTBR, and ΔTBR% with and without the EQ.PET, the results showed significant differences (P < 0.05). In Group 3, Bland-Altman analysis of ΔSUV with EQ.PET showed an improved consistency relative to that without EQ.PET.
conclusionsEQ.PET is an efficient tool to harmonize SUVs and TBRs across different reconstruction algorithms. Patients could benefit from the harmonized SUV, ΔSUV, and ΔSUV% for therapy responses and follow-up evaluations.
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