ArticleTomography (Ann Arbor, Mich.)2021
Stability of Radiomic Features across Different Region of Interest Sizes-A CT and MR Phantom Study.
Article in Tomography (Ann Arbor, Mich.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 2 of them syntheses that pooled it.
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Who cites it
34 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Deep learning models for pancreatic cancer detection on CT: a meta-analysis.Frontiers in medicine · 2026Pooled it
- Diagnostic Performance of Computed Tomography-Based Artificial Intelligence for Early Recurrence of Cholangiocarcinoma: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Bridging radiomics and histopathology: cross-modality consistency of radiomic features from CT to micro-CT in NSCLC.European radiology experimental · 2026Article
- An MRI-based radiomics model for precision subtyping of hereditary spastic paraplegia: discriminating SPG4 from SPG5.Neuroradiology · 2026Article
- Reproducibility of Optical Coherence Tomography Radiomics after Cataract Surgery: Effects of Media Opacity, Signal Strength, and Region of Interest Selection.Korean journal of ophthalmology : KJO · 2026Article
- Feasibility of automated AI-based contouring and stable radiomic feature assessment by HyperSight-CBCT Imaging for adaptive high-precision radiotherapy of prostate cancer.Scientific reports · 2026Article
- Article
- Computed Tomography Radiomics and Machine Learning for Prediction of Histology-Based Hepatic Steatosis Scores.Diagnostics (Basel, Switzerland) · 2025Article
- Effects of parametric feature maps on the reproducibility of radiomics from different fields of view in cardiac magnetic resonance cine images- a clinical and experimental study setting.The international journal of cardiovascular imaging · 2025Article
- Radiomics-driven spectral profiling of six kidney stone types with monoenergetic CT reconstructions in photon-counting CT.European radiology · 2025Article
- Photon-Counting CT Scan Phantom Study: Stability of Radiomics Features.Diagnostics (Basel, Switzerland) · 2025Article
- Deciphering Breast Cancer Complexity: A Study on the Predictive Power of MRI Texture Analysis for Tumor Characterization and Treatment Response.Journal of the Belgian Society of Radiology · 2025Article
- Textural heterogeneity of liver lesions in CT imaging - comparison of colorectal and pancreatic metastases.Abdominal radiology (New York) · 2024Article
- Decoding Radiomics: A Step-by-Step Guide to Machine Learning Workflow in Hand-Crafted and Deep Learning Radiomics Studies.Diagnostics (Basel, Switzerland) · 2024Review
- Can we predict pathology without surgery? Weighing the added value of multiparametric MRI and whole prostate radiomics in integrative machine learning models.European radiology · 2024Article
- Characterization of renal masses with MRI-based radiomics: assessment of inter-package and inter-observer reproducibility in a prospective pilot study.Abdominal radiology (New York) · 2024Article
- CT Texture Analysis of Perihilar Cholangiocarcinoma-Associations With Tumor Grading, Tumor Markers and Clinical Outcome.Cancer reports (Hoboken, N.J.) · 2024Article
- Article
- Letter to the editor on "Segmentation methods applied to MRI-derived radiomic analysis for the prediction of placenta accreta spectrum in patients with placenta previa".Abdominal radiology (New York) · 2023Article
- Interobserver Agreement in Automatic Segmentation Annotation of Prostate Magnetic Resonance Imaging.Bioengineering (Basel, Switzerland) · 2023Article
Corrections and comments
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6 authors.
Funding
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Abstract
We aimed to evaluate radiomic features' stability across different region of interest (ROI) sizes in CT and MR images. We chose a phantom with a homogenous internal structure so no differences for a feature extracted from ROIs of different sizes would be expected. For this, we scanned a plastic cup filled with sodium chloride solution ten times in CT and per MR sequence (T1-weighted-gradient-echo and T2-weighted-turbo-inversion-recovery-magnitude). We placed sphere-shaped ROIs of different diameters (4, 8, and 16 mm, and 4, 8, and 16 pixels) into the phantom's center. Features were extracted using PyRadiomics. We assessed feature stability across ROI sizes with overall concordance correlation coefficients (OCCCs). Differences were tested for significance with the Mann-Whitney U-test. Of 93 features, 87 T1w-derived, 87 TIRM-derived, and 70 CT-derived features were significantly different between ROI sizes. Among MR-derived features, OCCCs showed excellent (>0.90) agreement for mean, median, and root mean squared for ROI sizes between 4 and 16 mm and pixels. We further observed excellent agreement for 10th and 90th percentile in T1w and 10th percentile in T2w TIRM images. There was no excellent agreement among the OCCCs of CT-derived features. In summary, many features indicated significant differences and only few showed excellent agreement across varying ROI sizes, although we examined a homogenous phantom. Since we considered a small phantom in an experimental setting, further studies to investigate this size effect would be necessary for a generalization. Nevertheless, we believe knowledge about this effect is crucial in interpreting radiomics studies, as features that supposedly discriminate disease entities may only indicate a systematic difference in ROI size.
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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.