ArticleAcademic radiology2021
Quantification of Minimum Detectable Difference in Radiomics Features Across Lesions and CT Imaging Conditions.
Article in Academic radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Value of radiomics model based on enhanced computed tomography in risk grade prediction of gastrointestinal stromal tumors.Scientific reports · 2021Trial
- ESR Essentials: a step-by-step guide of segmentation for radiologists-practice recommendations by the European Society of Medical Imaging Informatics.European radiology · 2025Review
- Classification of carotid artery plaques: promising alternative methods to computed tomography angiography through radiomics approach using neck non-contrast computed tomography.Quantitative imaging in medicine and surgery · 2025Article
- The potential of photon-counting CT for the improved precision of lung nodule radiomics.Physics in medicine and biology · 2025Article
- Protocol selection formalism for minimizing detectable differences in morphological radiomics features of lung lesions in repeated CT acquisitions.Journal of medical imaging (Bellingham, Wash.) · 2024Article
- Spectral segmentation and radiomic features predict carotid stenosis and ipsilateral ischemic burden from DECT angiography.Diagnostic and interventional radiology (Ankara, Turkey) · 2022Article
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4 authors.
Funding
Abstract
RATIONALE AND
objectivesThe 3-fold purpose of this study was to (1) develop a method to relate measured differences in radiomics features in different computed tomography (CT) scans to one another and to true feature differences; (2) quantify minimum detectable change in radiomics features based on measured radiomics features from pairs of synthesized CT images acquired under variable CT scan settings, and (3) ascertain and inform the recommendations of the Quantitative Imaging Biomarkers Alliance (QIBA) for nodule volumetry. MATERIALS AND
methodsImages of anthropomorphic lung nodule models were simulated using resolution and noise properties for 297 unique imaging conditions. Nineteen morphology features were calculated from both the segmentation masks derived from the imaged nodules and from ground truth nodules. Analysis was performed to calculate minimum detectable difference of radiomics features as a function of imaging protocols in comparison to QIBA guidelines.
resultsThe minimum detectable differences ranged from 1% to 175% depending on the specific feature and set of imaging protocols. The results showed that QIBA protocol recommendations result in improved minimum detectable difference as compared to the range of possible protocols. The results showed that the minimum detectable differences may be improved from QIBA's current recommendation by further restricting the slice thickness requirement to be between 0.5 mm and 1 mm.
conclusionMinimum detectable differences of radiomics features were quantified for lung nodules across a wide range of possible protocols. The results can be used prospectively to inform decision-making about imaging protocols to provide superior quantification of radiomics features.
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