基于光子计数CT的前庭导水管轨迹分析用于评估梅尼埃病内型与听力损失
Photon-counting CT based vestibular aqueduct trajectory analysis for the assessment of Ménière's disease endotypes and hearing loss.
文献信息
| PMID | 42874222 |
|---|---|
| 原文 | 在 PubMed 查看原文 ↗ |
| 发表日期 | 2026 |
| 作者 | Jie Wang |
| 作者单位 | Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Zhejiang Key Laboratory of Imaging and Interventional Medicine, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China. |
| 期刊 | European journal of radiology |
| SCI 分区 | Q1 |
| IF | 3.7 |
| 研究类型 | 临床研究 · 临床 |
| 所属专科 | 耳科 |
中文摘要
背景： 梅尼埃病（MD）是一种异质性内耳疾病，基于影像学的内型识别可能有助于预后判断和个体化管理。前庭导水管（VA）是一种候选影像生物标志物，而光子计数CT（PCCT）能够高分辨率显示颞骨微解剖结构。本研究评估了PCCT衍生的VA形态学参数作为MD内型识别和听力损失评估的影像生物标志物。
方法： 在这项回顾性研究中，106例患者（212耳）接受了颞骨PCCT和3.0-T 3D-FLAIR MRI检查。PCCT参数包括VA的角轨迹（ATVA）、VA可见度分级、形态学亚型、中点宽度、VA长度以及后半规管-后颅窝距离。两名神经放射科医生独立评估了所有图像。通过AUC及留一患者交叉验证（LOPOCV）评估了六项临床驱动任务的诊断性能；采用带聚类稳健标准误的多变量线性回归评估与纯音平均（PTA）的关联。
结果： 观察者间一致性极好（ICC，0.84-0.91）。VA可见度分级识别发育不良内型的AUC为0.860（LOPOCV，0.812）；结合VA形态学和中点宽度区分退化内型的AUC为0.784（LOPOCV，0.736）。多变量回归确定ATVA是PTA的独立预测因子（β = 0.238，p = 0.023）。
结论： 尽管存在临床异质性，PCCT衍生的VA形态学参数仍能实现MD内型识别，并与听力损失严重程度相关，支持其作为MD管理影像生物标志物的潜在作用。
英文摘要
BACKGROUND: Ménière's disease (MD) is a heterogeneous inner ear disorder, and imaging-based endotype identification may inform prognosis and personalized management. The vestibular aqueduct (VA) is a candidate imaging biomarker, and photon-counting CT (PCCT) offers high-resolution depiction of temporal bone microanatomy. This study evaluated PCCT-derived VA morphometric parameters as imaging biomarkers for MD endotype identification and hearing loss assessment.
METHODS: In this retrospective study, 106 patients (212 ears) underwent temporal bone PCCT and 3.0-T 3D-FLAIR MRI. PCCT parameters included angular trajectory of the VA (ATVA), VA visibility grade, morphologic subtype, midpoint width, VA length, and posterior semicircular canal-posterior fossa distance. Two neuroradiologists independently evaluated all images. Diagnostic performance for six clinically motivated tasks was assessed by AUC with leave-one-patient-out cross-validation (LOPOCV); associations with pure-tone average (PTA) were evaluated by multivariable linear regression with cluster-robust standard errors.
RESULTS: Interobserver agreement was excellent (ICC, 0.84-0.91). VA visibility grading identified the hypoplastic endotype with an AUC of 0.860 (LOPOCV, 0.812); combined VA morphology and midpoint width distinguished the degenerated endotype with an AUC of 0.784 (LOPOCV, 0.736). Multivariable regression identified ATVA as an independent PTA predictor (β = 0.238, p = 0.023).
CONCLUSIONS: PCCT-derived VA morphometric parameters enabled MD endotype identification despite clinical heterogeneity and were associated with hearing loss severity, supporting their potential role as imaging biomarkers for MD management.