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Role of MRI-Based Radiomics in Sinonasal Cancer Management: A Scoping Review
Andrea Migliorelli1, Marianna Manuelli1, Andrea Ciorba1
1ENT & Audiology Unit, Department of Neurosciences, University Hospital of Ferrara, 44100 Ferrara, Italy.
Cancers
|October 29, 2025
Summary
Radiomics shows promise in predicting outcomes for malignant sinonasal tumors. This technique may help identify patients at high risk for recurrence, guiding personalized treatment strategies.
Area of Science:
- Oncology
- Radiology
- Medical Imaging
Background:
- Malignant sinonasal tumors are rare head and neck cancers with limited survival rates.
- Local recurrence is a primary cause of treatment failure in sinonasal cancer.
- Preoperative risk stratification is crucial for optimizing treatment strategies.
Purpose of the Study:
- To review recent literature on radiomics applications in malignant sinonasal tumors.
- To assess the potential of radiomics in improving patient outcomes.
Main Methods:
- Comprehensive literature review adhering to PRISMA criteria.
- Searched PubMed/MEDLINE, EMBASE, and Cochrane Library databases.
- Included studies published from 2020 to July 2025.
Main Results:
- Analysis of five articles involving 629 patients.
- Radiomics is currently used for Ki-67 expression prediction.
- Applications include early recurrence risk assessment and chemotherapy response evaluation.
Conclusions:
- Radiomics demonstrates potential in managing malignant sinonasal tumors.
- Further research is needed to validate these findings and clinical utility.
Keywords:
artificial intelligencedeep learningmachine learningradiomicssinonasal cancersinonasal tumor
