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Radiomics of the Paranasal Sinuses: A Systematic Review of Computer-Assisted Techniques to Assess Computed Tomography
Rhea Darbari Kaul1,2,3, Peta-Lee Sacks1, Cedric Thiel1
1Rhinology and Skull Base Research Group, Applied Medical Research Centre, University of New South Wales, Sydney, Australia.
Radiomics analysis of paranasal sinus CT scans is emerging in rhinology. Current studies show potential but have limited clinical utility due to minimal quality.
Area of Science:
- Medical Imaging
- Artificial Intelligence
- Rhinology
Background:
- Radiomics offers quantitative analysis of medical imaging data.
- Artificial intelligence (AI) methods are used to analyze radiomic data for clinical applications.
- Computed tomography (CT) imaging is crucial in rhinology for diagnosis and treatment assessment.
Purpose of the Study:
- To systematically review techniques for analyzing radiomic data from paranasal sinus CT scans.
Main Methods:
- Systematic literature search of Ovid MEDLINE and EMBASE databases (Jan 2019 - Mar 2024).
- Adherence to PRISMA checklist and Cochrane Library guidelines.
- Risk of bias assessed using QUADAS-2 and PROBAST tools.
Main Results:
- 10 articles met eligibility criteria from 1456 initial records.
- Studies included diagnostic (7) and prognostic (3) analyses.
- Analysis employed statistical methods or machine learning (AI); diagnostic/prognostic utility varied, with some rated excellent (AUC-ROC).
Conclusions:
- Radiomics shows promise for advancing rhinology disease understanding.
- Current studies are limited in quality and clinical utility.
- Further high-quality research is needed to enhance clinical application.
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