ArticleFrontiers in nuclear medicine2023
Post-acquisition standardization of positron emission tomography images.
Article in Frontiers in nuclear medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Virtual cutaneous area severity index (vCASI): A comprehensive methodology for quantitative skin disease assessment on positron emission tomography images.European journal of nuclear medicine and molecular imaging · 2025Article
- Brown adipose tissue machine learning nnU-Net V2 network using TriDFusion (3DF).EJNMMI research · 2025Article
- Post-acquisition standardization of positron emission tomography images.Frontiers in nuclear medicine · 2023Article
Corrections and comments
- Update of
Authors and funding
5 authors.
Funding
Abstract
Purpose: Tissue radiotracer activity measured from positron emission tomography (PET) images is an important biomarker that is clinically utilized for diagnosis, staging, prognostication, and treatment response assessment in patients with cancer and other clinical disorders. Using PET image values to define a normal range of metabolic activity for quantification purposes is challenging due to variations in patient-related factors and technical factors. Although the formulation of standardized uptake value (SUV) has compensated for some of these variabilities, significant non-standardness still persists. We propose an image processing method to substantially mitigate these variabilities. Methods: The standardization method is similar for activity concentration (AC) PET and SUV PET images with some differences and consists of two steps. The Results: Our data set consisted of 84 FDG-PET/CT scans of the body torso including 38 normal subjects and two repeat-scans of 23 patients. We utilized one of two objects-liver and spleen-as a reference object and the other for testing. The proposed standardization method reduced Conclusions: The proposed method is automatic, outperforms current standardization methods, and effectively overcomes the residual variation left over in SUV and inter-scanner variations.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.