International consensus statement on allergy and rhinology: sinonasal tumors

EC Kuan, EW Wang, ND Adappa… - International forum of …, 2024 - Wiley Online Library
Background Sinonasal neoplasms, whether benign and malignant, pose a significant
challenge to clinicians and represent a model area for multidisciplinary collaboration in …

Current opinions on diagnosis and treatment of adenoid cystic carcinoma

Y Fang, Z Peng, Y Wang, K Gao, Y Liu, R Fan, H Zhang… - Oral Oncology, 2022 - Elsevier
Adenoid cystic carcinoma (ACC) is a rare malignant tumor derived mainly from the salivary
glands, representing approximately 1% of all head and neck carcinomas and 10% of all …

PET/CT imaging in treatment planning and surveillance of sinonasal neoplasms

S Akay, JH Pollard, A Saad Eddin, A Alatoum… - Cancers, 2023 - mdpi.com
Simple Summary Sinonasal cancers are rare types of cancer that are often detected at a late
stage, making them difficult to treat. To monitor these cancers closely, advanced imaging …

Sinonasal squamous cell carcinoma, a narrative reappraisal of the current evidence

M Ferrari, S Taboni, ALC Carobbio, E Emanuelli… - Cancers, 2021 - mdpi.com
Simple Summary Sinonasal squamous cell carcinomas are a group of diverse tumors
affecting the nasal cavity and paranasal sinuses. As a direct consequence of their rarity and …

Clinical management of emerging sinonasal malignancies

KJ Contrera, NM Woody, M Rahman, R Sindwani… - Head & …, 2020 - Wiley Online Library
Several emerging sinonasal malignancies have recently been described in the pathology
literature. Although not all distinctly classified by the World Health Organization, these rare …

Machine learning to differentiate small round cell malignant tumors and non-small round cell malignant tumors of the nasal and paranasal sinuses using apparent …

C Chen, Y Qin, H Chen, J Cheng, B He, Y Wan… - European …, 2022 - Springer
Objective We used radiomics feature–based machine learning classifiers of apparent
diffusion coefficient (ADC) maps to differentiate small round cell malignant tumors (SRCMTs) …

Texture analysis of fat-suppressed T2-weighted magnetic resonance imaging and use of machine learning to discriminate nasal and paranasal sinus small round …

C Chen, Y Qin, J Cheng, F Gao, X Zhou - Frontiers in oncology, 2021 - frontiersin.org
Objective We used texture analysis and machine learning (ML) to classify small round cell
malignant tumors (SRCMTs) and Non-SRCMTs of nasal and paranasal sinus on fat …

Radiological features of human papillomavirus-related multiphenotypic sinonasal carcinoma: systematic review and case series

A Baba, R Kurokawa, T Fukuda, H Fujioka… - Neuroradiology, 2022 - Springer
Purpose To comprehensively summarize the radiological characteristics of human
papillomavirus (HPV)-related multiphenotypic sinonasal carcinomas (HMSCs). Methods We …

Quantitative analysis of DCE-MRI and RESOLVE-DWI for differentiating nasopharyngeal carcinoma from nasopharyngeal lymphoid hyperplasia

JY Yu, D Zhang, XL Huang, J Ma, C Yang, XJ Li… - Journal of Medical …, 2020 - Springer
To explore the ability of quantitative dynamic contrast-enhanced magnetic resonance
imaging (DCE-MRI) analysis and readout segmentation of long variable echo-trains …

Development and validation of apparent diffusion coefficient histogram-based nomogram for predicting malignant transformation of sinonasal inverted papilloma

M Qi, Z Xia, F Zhang, Y Sha, J Ren - Dentomaxillofacial …, 2023 - academic.oup.com
Objectives: To develop and validate a nomogram based on whole-tumour histograms of
apparent diffusion coefficient (ADC) maps for predicting malignant transformation (MT) in …