*Result*: Image Quality Standardization in Radiomics: A Systematic Review of Artifacts, Variability, and Feature Stability.

Title:
Image Quality Standardization in Radiomics: A Systematic Review of Artifacts, Variability, and Feature Stability.
Authors:
Felicetti F; Department of Computer Engineering, Modeling, Electronics and Systems Engineering, University of Calabria, Ponte P. Bucci, 87036 Rende, Italy., Lamonaca F; Department of Computer Engineering, Modeling, Electronics and Systems Engineering, University of Calabria, Ponte P. Bucci, 87036 Rende, Italy.; Institute of Nanotechnology (CNR-NANOTEC), National Research Council of Italy, 87036 Rende, Italy., Carnì DL; Department of Computer Engineering, Modeling, Electronics and Systems Engineering, University of Calabria, Ponte P. Bucci, 87036 Rende, Italy., Costanzo S; Department of Computer Engineering, Modeling, Electronics and Systems Engineering, University of Calabria, Ponte P. Bucci, 87036 Rende, Italy.; Consorzio Nazionale Interuniversitario per le Telecomunicazioni, 43124 Parma, Italy.; Inter-University National Research Center on Interactions Between Electromagnetic Fields and Biosystems (ICEmB), 16126 Genova, Italy.
Source:
Sensors (Basel, Switzerland) [Sensors (Basel)] 2026 Feb 05; Vol. 26 (3). Date of Electronic Publication: 2026 Feb 05.
Publication Type:
Journal Article; Systematic Review; Review
Language:
English
Journal Info:
Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220 (Electronic) Linking ISSN: 14248220 NLM ISO Abbreviation: Sensors (Basel) Subsets: MEDLINE
Imprint Name(s):
Original Publication: Basel, Switzerland : MDPI, c2000-
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Grant Information:
RADIOAMICA- Open Network per la RADIOm- 446 ica/rAdiogenoMIca Cooperativa basata su intelligenza Artificiale Italian Ministry for Research
Contributed Indexing:
Keywords: artifacts; feature extraction; image quality assessment; measurements; personalized medicine; radiomics; standardization
Entry Date(s):
Date Created: 20260213 Date Completed: 20260213 Latest Revision: 20260216
Update Code:
20260216
PubMed Central ID:
PMC12900098
DOI:
10.3390/s26031039
PMID:
41682554
Database:
MEDLINE

*Further Information*

*This paper explores the role of metrology in the assessment of image quality in the field of radiomics. Image Quality Assessment (IQA) is central to ensuring the reliability and reproducibility of radiomic analyses, as it directly affects the accuracy of feature extraction and segmentation, ultimately impacting diagnostic outcomes. From the analysis of approximately 20,000 papers sourced from three databases (PubMed, Scopus, IEEE Xplore), last searched in December 2025, the need for standardized imaging protocols and quality control measures emerges as a critical theme. Studies were included if they involved radiomic feature extraction and evaluated the impact of image quality variations on feature robustness and no formal risk-of-bias assessment was performed. A total of 105 studies were included, covering different medical imaging modalities. Across the included studies, noise, motion, acquisition and reconstruction parameters, and other artifacts consistently emerged as major sources of radiomic feature instability. Indeed, in most papers, IQA is neglected, while the effect of poor-quality images is reported. This research identifies and discusses the relevant issues reported in clinical practice, as well as the main metrics adopted for image quality evaluation. Through a comprehensive review of current literature and an analysis of emerging trends, this paper highlights the urgent need for innovative solutions in image quality metrics tailored to radiomics applications.*