Imaging evaluation of sinonasal tract neoplasms

The objectives of this article are to review the essential anatomy of the paranasal sinuses, describe computed tomography (CT) and magnetic resonance (MR) imaging approaches to the evaluation of paranasal sinus neoplasms, discuss imaging features of common sinonasal tract tumors, and examine systemic staging and surveillance of sinonasal neoplasms using FDG PET/CT and DOTATATE PET/CT.

Authors

Institutions

Publication Details

Journal
Mini-invasive Surgery
Published
2025-08-29
DOI
https://doi.org/10.20517/2574-1225.2024.75
Primary Topic
Head and Neck Surgical Oncology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Imaging evaluation of sinonasal tract neoplasms

Shirley Y. Su, V. P. Singh, Alexander Khalaf, Kim O. Learned et al.
Mini-invasive Surgery
Head and Neck Surgical Oncology
article

Imaging evaluation of sinonasal tract neoplasms

Shirley Y. Su, V. P. Singh, Alexander Khalaf, Kim O. Learned, Kuang-chun Jim Hsieh, Richard Fagan, Giang-Kim Nguyen
article en

Abstract

The objectives of this article are to review the essential anatomy of the paranasal sinuses, describe computed tomography (CT) and magnetic resonance (MR) imaging approaches to the evaluation of paranasal sinus neoplasms, discuss imaging features of common sinonasal tract tumors, and examine systemic staging and surveillance of sinonasal neoplasms using FDG PET/CT and DOTATATE PET/CT.

Mini-invasive Surgery
Baylor College of Medicine (US)
Openalex Percentile: Top 63%
Head and Neck Surgical Oncology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.