Chinese expert consensus on imaging examination and diagnosis of nasal cavity and paranasal sinus tumors
The complex anatomy and diverse tissue composition of the nasal cavity and paranasal sinuses contribute to a wide variety of tumor pathologies in this region, posing significant diagnostic challenges in clinical practice. Evaluation with computed tomography (CT) and magnetic resonance imaging (MRI)...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-08-01
|
| Series: | Frontiers in Oncology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2025.1626584/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | The complex anatomy and diverse tissue composition of the nasal cavity and paranasal sinuses contribute to a wide variety of tumor pathologies in this region, posing significant diagnostic challenges in clinical practice. Evaluation with computed tomography (CT) and magnetic resonance imaging (MRI) is critical for the diagnosis and management of patients with sinonasal tumors. Radiologists should be proficient in the indications and contraindications for CT and MRI examinations of sinonasal tumors, along with standardized scanning protocols and image quality control requirements. Particular attention must be paid to radiation protection principles for infants, children, and pregnant patients, alongside contrast agent safety guidelines for pregnant and lactating females. Furthermore, radiologists require a thorough understanding of the intricate anatomy of the sinonasal region, the spectrum of common benign and malignant tumor pathologies, and their characteristic imaging manifestations, especially recognizing tumor-specific imaging signs. Finally, adopting a long-term perspective, radiologists should prioritize multidisciplinary collaboration. Integrating clinical practice with emerging technologies-such as multimodal imaging, molecular diagnostics, and artificial intelligence (AI)-is critical for addressing diagnostic complexities, refining therapeutic strategies, and improving patient prognoses. Advancing research in these domains not only strengthens disease management but also deepens the understanding of pathogenesis and treatment response, ultimately enhancing diagnostic accuracy and long-term outcomes. |
|---|---|
| ISSN: | 2234-943X |