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A magnetic resonance imaging-based lymph node regression grading scheme for nasopharyngeal carcinoma after radiotherapy
Hui Yang1; Liang, Zhiying1; Liang, Jiahui1; Cao, Di1; Cao, Qin2; Zhao, Feng1; Zhang, Weijing1; Kou, Kit Ian3; Cui, Chunyan1; Liu, Lizhi1; Li, Haojiang1; Peng, Zexue4; Zhu, Siyu1
2024-07
Source PublicationQuant Imaging Med Surg
ISSN2223-4292
Volume14Issue:8Pages:5513-5525
Abstract

 

Background: Among patients with nasopharyngeal carcinoma (NPC), there is no established method to distinguish between patients with residual disease that may eventually progress and those who have achieved cured. We thus aimed to assess the prognostic value of magnetic resonance imaging (MRI)-based lymph node regression grade (LRG) in the risk stratification of patients with NPC following radiotherapy (RT). Methods: This study retrospectively enrolled 387 patients newly diagnosed with NPC between January 2010 and January 2013. A four-category MRI-LRG system based on the areal analysis of RT-induced fibrosis and residual tumor was established. Univariate analysis was performed using the Kaplan-Meier method, and comparisons were conducted via the log-rank test. Multivariate analyses were conducted using Cox regression models to calculate the hazard ratios (HRs) with 95% confidence intervals (CIs) and adjusted P values. Survival curves were calculated using the Kaplan-Meier method and compared using the log-rank test. Results: The sum of MRI-LRG scores (LRG-sum) was an independent prognostic factor for progressionfree survival (PFS) (HR 2.50, 95% CI: 1.28-4.90; P<0.001). LRG-sum <= 9 and >9 showed a poorer 5-year PFS rate than did LRG-sum <= 2 (66.1%, 42.9%, and 77.6%, respectively; P<0.001). A survival clustering analysis-based decision tree model showed more complex interactions among LRG-sum and pretreatment and post-RT Epstein-Barr virus (EBV) DNA, yielding four patient clusters with differentiated disease progression risks (5-year PFS rates of 89.5%, 76.4%, 57.6%, and 27.8%, respectively), which showed better risk stratification than did post-RT EBV DNA alone (P<0.001). Conclusions: The MRI-LRG system adds prognostic information and is a potentially reliable, noninvasive means to stratify treatment modalities for patients with NPC.

KeywordNasopharyngeal Carcinoma (Npc) Risk Stratification Lymph Node Regression Grade (Lrg) Epstein Barr Virus Dna (Ebv Dna) Postradiotherapy
DOI10.21037/qims-24-275
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaRadiology, Nuclear Medicine & Medical Imaging
WOS SubjectRadiology, Nuclear Medicine & Medical Imaging
WOS IDWOS:001312968100019
PublisherAME PUBLISHING COMPANY, FLAT-RM C 16F, KINGS WING PLAZA 1, NO 3 KWAN ST, SHATIN, HONG KONG 00000, PEOPLES R CHINA
Scopus ID2-s2.0-85200359088
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Document TypeJournal article
CollectionFaculty of Science and Technology
Corresponding AuthorPeng, Zexue; Zhu, Siyu
Affiliation1.Sun Yat Sen Univ Canc Ctr, Guangdong Prov Clin Res Ctr Canc, State Key Lab Oncol South China, Guangdong Key Lab Nasopharyngeal Carcinoma Diag &, 651 Dongfeng Rd East, Guangzhou 510060, Peoples R China
2.Peoples Hosp Yingcheng, Dept Hepatobiliary Oncol, Yingcheng, Peoples R China
3.Univ Macau, Fac Sci & Technol, Dept Math, Taipa, Macao, Peoples R China
4.Xiangya Changde Hosp, Dept Radiol, 1688 Moon Ave, Changde 415000, Peoples R China
Recommended Citation
GB/T 7714
Hui Yang,Liang, Zhiying,Liang, Jiahui,et al. A magnetic resonance imaging-based lymph node regression grading scheme for nasopharyngeal carcinoma after radiotherapy[J]. Quant Imaging Med Surg, 2024, 14(8), 5513-5525.
APA Hui Yang., Liang, Zhiying., Liang, Jiahui., Cao, Di., Cao, Qin., Zhao, Feng., Zhang, Weijing., Kou, Kit Ian., Cui, Chunyan., Liu, Lizhi., Li, Haojiang., Peng, Zexue., & Zhu, Siyu (2024). A magnetic resonance imaging-based lymph node regression grading scheme for nasopharyngeal carcinoma after radiotherapy. Quant Imaging Med Surg, 14(8), 5513-5525.
MLA Hui Yang,et al."A magnetic resonance imaging-based lymph node regression grading scheme for nasopharyngeal carcinoma after radiotherapy".Quant Imaging Med Surg 14.8(2024):5513-5525.
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