ArticleJournal of applied clinical medical physics2019
Reliability of CT-based texture features: Phantom study.
Article in Journal of applied clinical medical physics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed, 67 citations in OpenAlex.
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- Finding Reproducible and Prognostic Radiomic Features in Variable Slice Thickness Contrast Enhanced CT of Colorectal Liver Metastases.The journal of machine learning for biomedical imaging · 2025Article
- [Diagnostics (Basel, Switzerland) · 2024Review
- A reference framework for standardization and harmonization of CT radiomics features on cadaveric sample.Scientific reports · 2024Article
- Impact of quantitative CT texture analysis on the outcome of CT-guided bone biopsy.Journal of bone oncology · 2024Article
- Investigating the role of imaging factors in the variability of CT-based texture analysis metrics.Journal of applied clinical medical physics · 2024Article
- Technical and clinical considerations of a physical liver phantom for CT radiomics analysis.Journal of applied clinical medical physics · 2024Article
- Radiomics model versus 2017 revised international consensus guidelines for predicting malignant intraductal papillary mucinous neoplasms.European radiology · 2024Article
- Impacts of Adaptive Statistical Iterative Reconstruction-V and Deep Learning Image Reconstruction Algorithms on Robustness of CT Radiomics Features: Opportunity for Minimizing Radiomics Variability Among Scans of Different Dose Levels.Journal of imaging informatics in medicine · 2024Article
- Imageless navigation system (Naviswiss) provides accurate component position in total hip arthroplasty with lateral decubitus position for end-stage hip osteoarthritis: a prospective cohort study with CT-validation.Arthroplasty (London, England) · 2024Article
- Surface-based anthropomorphic bone structures for use in high-resolution simulated medical imaging.Physics in medicine and biology · 2023Article
- CT validation of intraoperative imageless navigation (Naviswiss) for component positioning accuracy in primary total hip arthroplasty in supine patient position: a prospective observational cohort study in a single-surgeon practice.Arthroplasty (London, England) · 2023Article
- Predicting Soft Tissue Sarcoma Response to Neoadjuvant Chemotherapy Using an MRI-Based Delta-Radiomics Approach.Molecular imaging and biology · 2023Article
- Performance of CT radiomics in predicting the overall survival of patients with stage III clear cell renal carcinoma after radical nephrectomy.La Radiologia medica · 2022Article
- Test-Retest Data for the Assessment of Breast MRI Radiomic Feature Repeatability.Journal of magnetic resonance imaging : JMRI · 2022Article
- Radiomics in Oncological PET Imaging: A Systematic Review-Part 2, Infradiaphragmatic Cancers, Blood Malignancies, Melanoma and Musculoskeletal Cancers.Diagnostics (Basel, Switzerland) · 2022Review
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo determine the intra-, inter- and test-retest variability of CT-based texture analysis (CTTA) metrics. MATERIALS AND
methodsIn this study, we conducted a series of CT imaging experiments using a texture phantom to evaluate the performance of a CTTA panel on routine abdominal imaging protocols. The phantom comprises of three different regions with various textures found in tumors. The phantom was scanned on two CT scanners viz. the Philips Brilliance 64 CT and Toshiba Aquilion Prime 160 CT scanners. The intra-scanner variability of the CTTA metrics was evaluated across imaging parameters such as slice thickness, field of view, post-reconstruction filtering, tube voltage, and tube current. For each scanner and scanning parameter combination, we evaluated the performance of eight different types of texture quantification techniques on a predetermined region of interest (ROI) within the phantom image using 235 different texture metrics. We conducted the repeatability (test-retest) and robustness (intra-scanner) test on both the scanners and the reproducibility test was conducted by comparing the inter-scanner differences in the repeatability and robustness to identify reliable CTTA metrics. Reliable metrics are those metrics that are repeatable, reproducible and robust.
resultsAs expected, the robustness, repeatability and reproducibility of CTTA metrics are variably sensitive to various scanner and scanning parameters. Entropy of Fast Fourier Transform-based texture metrics was overall most reliable across the two scanners and scanning conditions. Post-processing techniques that reduce image noise while preserving the underlying edges associated with true anatomy or pathology bring about significant differences in radiomic reliability compared to when they were not used.
conclusionFollowing large-scale validation, identification of reliable CTTA metrics can aid in conducting large-scale multicenter CTTA analysis using sample sets acquired using different imaging protocols, scanners etc.
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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.