scholarly journals Diagnosis and Treatment of the Nasopharyngeal Carcinoma

1987 ◽  
Vol 80 (2) ◽  
pp. 173-173
Keyword(s):  
Nasopharyngeal Carcinoma ◽  
Diagnosis And Treatment

scholarly journals Circulating E pstein– B arr virus micro RNA s mi R‐BART7 and mi R‐BART13 as biomarkers for nasopharyngeal carcinoma diagnosis and treatment

2014 ◽  
Vol 136 (5) ◽  
Author(s):  
Gaohong Zhang ◽  
Jingfeng Zong ◽  
Shaojun Lin ◽  
Rob J.A. Verhoeven ◽  
Shuang Tong ◽  
...  
Keyword(s):  
Nasopharyngeal Carcinoma ◽  
Micro Rna ◽  
Diagnosis And Treatment

scholarly journals The Chinese Society of Clinical Oncology (CSCO) clinical guidelines for the diagnosis and treatment of nasopharyngeal carcinoma

2021 ◽  
Author(s):  
Ling‐Long Tang ◽  
Yu‐Pei Chen ◽  
Chuan‐Ben Chen ◽  
Ming‐Yuan Chen ◽  
Nian‐Yong Chen ◽  
...  
Keyword(s):  
Nasopharyngeal Carcinoma ◽  
Clinical Oncology ◽  
Clinical Guidelines ◽  
Diagnosis And Treatment ◽  
Chinese Society

scholarly journals A Comprehensive Review on Radiomics and Deep Learning for Nasopharyngeal Carcinoma Imaging

Diagnostics ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1523
Author(s):  
Song Li ◽  
Yu-Qin Deng ◽  
Zhi-Ling Zhu ◽  
Hong-Li Hua ◽  
Ze-Zhang Tao
Keyword(s):  
Deep Learning ◽  
Nasopharyngeal Carcinoma ◽  
Large Scale ◽  
Treatment Strategies ◽  
Diagnosis And Treatment ◽  
Future Research ◽  
Malignant Tumours ◽  
Comprehensive Overview ◽  
Network Methods ◽  
Imaging Research

Nasopharyngeal carcinoma (NPC) is one of the most common malignant tumours of the head and neck, and improving the efficiency of its diagnosis and treatment strategies is an important goal. With the development of the combination of artificial intelligence (AI) technology and medical imaging in recent years, an increasing number of studies have been conducted on image analysis of NPC using AI tools, especially radiomics and artificial neural network methods. In this review, we present a comprehensive overview of NPC imaging research based on radiomics and deep learning. These studies depict a promising prospect for the diagnosis and treatment of NPC. The deficiencies of the current studies and the potential of radiomics and deep learning for NPC imaging are discussed. We conclude that future research should establish a large-scale labelled dataset of NPC images and that studies focused on screening for NPC using AI are necessary.

scholarly journals Radiomics for Diagnosis and Radiotherapy of Nasopharyngeal Carcinoma

2022 ◽  
Vol 11 ◽  
Author(s):  
Yu-mei Zhang ◽  
Guan-zhong Gong ◽  
Qing-tao Qiu ◽  
Yun-wei Han ◽  
He-ming Lu ◽  
...  
Keyword(s):  
Nasopharyngeal Carcinoma ◽  
Southern China ◽  
Nasal Congestion ◽  
Clinical Manifestations ◽  
Diagnosis And Treatment ◽  
Radiotherapy Planning ◽  
Nasal Discharge ◽  
Target Delineation ◽  
Positron Emission ◽  
Magnetic Resonance Imaging Mri

Nasopharyngeal carcinoma (NPC) is a malignant tumor of the head and neck. The primary clinical manifestations are nasal congestion, blood-stained nasal discharge, headache, and hearing loss. It occurs frequently in Southeast Asia, North Africa, and especially in southern China. Radiotherapy is the main treatment, and currently, imaging examinations used for the diagnosis, treatment, and prognosis of NPC include computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET)-CT, and PET-MRI. These methods play an important role in target delineation, radiotherapy planning design, dose evaluation, and outcome prediction. However, the anatomical and metabolic information obtained at the macro level of images may not meet the increasing accuracy required for radiotherapy. As a technology used for mining deep image information, radiomics can provide further information for the diagnosis and treatment of NPC and promote individualized precision radiotherapy in the future. This paper reviews the application of radiomics in the diagnosis and treatment of nasopharyngeal carcinoma.

scholarly journals Circulating tumor cells with karyotyping as a novel biomarker for diagnosis and treatment of nasopharyngeal carcinoma

BMC Cancer ◽  
2018 ◽  
Vol 18 (1) ◽  
Author(s):  
Jing Zhang ◽  
Huashan Shi ◽  
Tingting Jiang ◽  
Zhe Liu ◽  
Peter P. Lin ◽  
...  
Keyword(s):  
Nasopharyngeal Carcinoma ◽  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Diagnosis And Treatment

scholarly journals Design of InnoPrimers-Duplex Real-Time PCR for Detection and Treatment Response Prediction of EBV-Associated Nasopharyngeal Carcinoma Circulating Genetic Biomarker

Diagnostics ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1761
Author(s):  
Mai Abdel Haleem Abu Salah ◽  
Siti Asma Binti Hassan ◽  
Norhafiza Mat Lazim ◽  
Baharudin Abdullah ◽  
Wan Fatihah Binti Wan Sohaimi ◽  
...  
Keyword(s):  
Nasopharyngeal Carcinoma ◽  
Early Diagnosis ◽  
Treatment Response ◽  
Southern China ◽  
Response Prediction ◽  
Diagnosis And Treatment ◽  
Immune Recognition ◽  
Epithelial Tumor ◽  
Genetic Biomarker ◽  
Treatment Response Prediction

Nasopharyngeal carcinoma (NPC) is an epithelial tumor with high prevalence in southern China and Southeast Asia. NPC is well associated with the Epstein-Barr virus (EBV) latent membrane protein 1 (LMP1) 30 bp deletion by having its vital role in increased tumorigenicity and decreased immune recognition of EBV-related tumors. This study developed an InnoPrimers-duplex qPCR for detection of NPC blood circulating LMP1 30 bp deletion genetic biomarker for early diagnosis and treatment response prediction of NPC patients. The analytical and diagnostic evaluation and treatment response prediction were conducted using NPC patients’ whole blood (WB) and tissue samples and non-NPC cancer patients and healthy individuals’ WB samples. The assay was able to detect as low as 20 ag DNA per reaction (equivalent to 173 copies) with high specificity against broad reference microorganisms and archive NPC biopsy tissue and FNA samples. The diagnostic sensitivity and specificity were 83.3% and 100%, respectively. The 30 bp deletion genetic biomarker was found to be a good prognostic biomarker associated with overall clinical outcome of NPC WHO type III patients. This sensitive and specific assay can help clinicians in early diagnosis and treatment response prediction of NPC patients, which will enhance treatment outcome and lead to better life-saving.

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