基于MRI的淋巴结特征用于局部晚期鼻咽癌远处转移风险分层。
MRI-Derived Lymph Node Characteristics for Risk Stratification of Distant Metastasis in Locoregionally Advanced Nasopharyngeal Carcinoma.
文献信息
| PMID | 42969888 |
|---|---|
| 原文 | 在 PubMed 查看原文 ↗ |
| 发表日期 | 2026 |
| 作者 | Jing Wang |
| 作者单位 | Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China. |
| 期刊 | Journal of magnetic resonance imaging : JMRI |
| SCI 分区 | Q1 |
| IF | 4.6 |
| 研究类型 | 临床研究 · 临床 |
| 所属专科 | 鼻咽癌 |
中文摘要
背景： 基于MRI的淋巴结特征可能改善TNM分期之外的预后判断，但远处转移风险模型仍然有限。
目的： 开发并内部验证一个用于预测局部晚期鼻咽癌（LA-NPC）远处转移的MRI模型。
研究类型： 回顾性。
人群： 共1541例LA-NPC患者（男性1103例，女性438例；平均年龄48±12岁），分为训练集（n=1079）和内部验证集（n=462）。
场强/序列： 3.0-T MRI，采用轴位T1加权涡轮自旋回波、轴位T2加权短tau反转恢复、扩散加权成像（b=0和800 s/mm2）及表观扩散系数图，以及多平面脂肪抑制对比增强T1加权涡轮自旋回波。
评估： 评估结外延伸（ENE）、颈部淋巴结坏死（CNN）、淋巴结大小、区域淋巴结密度（RLND）、淋巴结侧别及临床变量。采用递归分割分析（RPA）定义风险组，并将其与T和N分期类别结合构建列线图。
统计检验： 在训练集中进行Cox分析。通过一致性指数（C-index）、3年时间依赖受试者工作特征分析及校准评估性能。双侧p<0.05表示有统计学意义。
结果： ENE 3级（HR，1.92；95% CI，1.20-3.07）、CNN 3-4级（HR，2.65；95% CI，1.46-4.81）及RLND（每单位增加：HR，1.92；95% CI，1.29-2.88）与较短的无远处转移生存期（DMFS）独立相关。多变量模型C-index为0.766（95% CI，0.721-0.811）。RPA将491、524和64例患者分别归入低、中和高风险组，3年DMFS率分别为97.53%、89.90%和60.83%。列线图3年AUC在训练集中为0.777（95% CI，0.725-0.828），在验证集中为0.728（95% CI，0.645-0.810）；差异无统计学意义（p=0.333）。平均绝对校准误差分别为0.009和0.012。
数据结论： 基于MRI的淋巴结特征能够实现DMFS风险分层，内部验证的列线图显示出区分度和校准度。
证据水平： 4。
技术效能： 2期。
英文摘要
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: 3.0-T MRI using axial T1-weighted turbo spin-echo, axial T2-weighted short-tau inversion recovery, diffusion-weighted imaging (b = 0 and 800 s/mm2) 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.