MRI ‐Derived Lymph Node Characteristics for Risk Stratification of Distant Metastasis in Locoregionally Advanced Nasopharyngeal Carcinoma

BACKGROUND: MRI-derived nodal features may improve prognostication beyond TNM staging, but distant-metastasis risk models remain limited. PURPOSE: To develop and internally validate an MRI model for distant metastasis prediction in locoregionally advanced nasopharyngeal carcinoma (LA-NPC). STUDY TYPE: Retrospective. POPULATION: One thousand five-hundred and forty-one patients with LA-NPC (1103 men and 438 women; mean age, 48 ± 12 years) were split into a training set (n = 1079) and an internal validation set (n = 462). FIELD STRENGTH/SEQUENCE: ) with apparent diffusion coefficient maps, and multiplanar fat-suppressed contrast-enhanced T1-weighted turbo spin-echo. ASSESSMENT: Extranodal extension (ENE), cervical lymph node necrosis (CNN), nodal size, regional lymph node density (RLND), nodal laterality, and clinical variables were assessed. Recursive partitioning analysis (RPA) defined risk groups, which were combined with T and N categories in a nomogram. STATISTICAL TESTS: Cox analyses were performed in training. Performance was assessed by the concordance index (C-index), 3-year time-dependent receiver operating characteristic analysis, and calibration. Two-sided p < 0.05 indicated significance. RESULTS: ENE Grade 3 (HR, 1.92; 95% CI, 1.20-3.07), CNN Grades 3-4 (HR, 2.65; 95% CI, 1.46-4.81), and RLND (per-unit increase: HR, 1.92; 95% CI, 1.29-2.88) were independently associated with shorter distant metastasis-free survival (DMFS). The multivariable model C-index was 0.766 (95% CI, 0.721-0.811). RPA assigned 491, 524, and 64 patients to low-, intermediate-, and high-risk groups, with 3-year DMFS rates of 97.53%, 89.90%, and 60.83%, respectively. Nomogram 3-year AUCs were 0.777 (95% CI, 0.725-0.828) in training and 0.728 (95% CI, 0.645-0.810) in validation; the difference was nonsignificant (p = 0.333). Mean absolute calibration errors were 0.009 and 0.012, respectively. DATA CONCLUSION: MRI-derived nodal features enabled DMFS risk stratification, and the internally validated nomogram showed discrimination and calibration. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 2.

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Journal
Journal of Magnetic Resonance Imaging
Published
2026-11-02
DOI
https://doi.org/10.1002/jmri.70598
Citations
1
Primary Topic
Head and Neck Cancer Studies
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article
Field-Weighted Citation Impact
5.68
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article

MRI ‐Derived Lymph Node Characteristics for Risk Stratification of Distant Metastasis in Locoregionally Advanced Nasopharyngeal Carcinoma

Sufang Qiu, Yubin Hu, Hengyu Guo, Qisi Zhang et al.
1 citations
Journal of Magnetic Resonance Imaging
Head and Neck Cancer Studies
5.68
article

MRI ‐Derived Lymph Node Characteristics for Risk Stratification of Distant Metastasis in Locoregionally Advanced Nasopharyngeal Carcinoma

Sufang Qiu, Yubin Hu, Hengyu Guo, Qisi Zhang, Jiajia Zheng, Yuxing Yu, Lanxin Lin, Jianxian Chen, Haosheng Zhang, Honghong Zhang, Jing Wang
article en
1 citations

Abstract

BACKGROUND: MRI-derived nodal features may improve prognostication beyond TNM staging, but distant-metastasis risk models remain limited. PURPOSE: To develop and internally validate an MRI model for distant metastasis prediction in locoregionally advanced nasopharyngeal carcinoma (LA-NPC). STUDY TYPE: Retrospective. POPULATION: One thousand five-hundred and forty-one patients with LA-NPC (1103 men and 438 women; mean age, 48 ± 12 years) were split into a training set (n = 1079) and an internal validation set (n = 462). FIELD STRENGTH/SEQUENCE: ) with apparent diffusion coefficient maps, and multiplanar fat-suppressed contrast-enhanced T1-weighted turbo spin-echo. ASSESSMENT: Extranodal extension (ENE), cervical lymph node necrosis (CNN), nodal size, regional lymph node density (RLND), nodal laterality, and clinical variables were assessed. Recursive partitioning analysis (RPA) defined risk groups, which were combined with T and N categories in a nomogram. STATISTICAL TESTS: Cox analyses were performed in training. Performance was assessed by the concordance index (C-index), 3-year time-dependent receiver operating characteristic analysis, and calibration. Two-sided p < 0.05 indicated significance. RESULTS: ENE Grade 3 (HR, 1.92; 95% CI, 1.20-3.07), CNN Grades 3-4 (HR, 2.65; 95% CI, 1.46-4.81), and RLND (per-unit increase: HR, 1.92; 95% CI, 1.29-2.88) were independently associated with shorter distant metastasis-free survival (DMFS). The multivariable model C-index was 0.766 (95% CI, 0.721-0.811). RPA assigned 491, 524, and 64 patients to low-, intermediate-, and high-risk groups, with 3-year DMFS rates of 97.53%, 89.90%, and 60.83%, respectively. Nomogram 3-year AUCs were 0.777 (95% CI, 0.725-0.828) in training and 0.728 (95% CI, 0.645-0.810) in validation; the difference was nonsignificant (p = 0.333). Mean absolute calibration errors were 0.009 and 0.012, respectively. DATA CONCLUSION: MRI-derived nodal features enabled DMFS risk stratification, and the internally validated nomogram showed discrimination and calibration. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 2.

Journal of Magnetic Resonance Imaging
Fujian Medical University (CN), Xiamen University (CN), Fujian Provincial Cancer Hospital (CN)
Good health and well-being
Openalex Percentile: Top 3%
Head and Neck Cancer Studies
5.68
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