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1. 复旦大学附属肿瘤医院放射诊断科,复旦大学上海医学院肿瘤学系,上海 200032
2. 上海市质子重离子医院放射诊断科,上海 201315
3. 上海市放射肿瘤学重点实验室,上海 201321
4. 上海质子重离子放射治疗工程技术研究中心,上海 201321
[ "向诗语(ORCID: 0000-0001-7732-5215),博士在读,主治医师。" ]
吴斌(ORCID: 0009-0000-6056-2759),博士,副主任医师。
收稿:2025-03-26,
修回:2025-07-06,
纸质出版:2025-07-30
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向诗语, 李桥, 沈长青, 等. 基于血管移位的诊断评分和诺莫图在鉴别颈部迷走神经鞘瘤和颈部交感神经鞘瘤中的应用[J]. 中国癌症杂志, 2025,35(7):695-701.
Shiyu XIANG, Qiao LI, Changqing SHEN, et al. Preoperative differentiation of vagal nerve cervical schwannomas from sympathetic chain cervical schwannomas based on diagnosis score and vascular displacement nomogram[J]. China Oncology, 2025, 35(7): 695-701.
向诗语, 李桥, 沈长青, 等. 基于血管移位的诊断评分和诺莫图在鉴别颈部迷走神经鞘瘤和颈部交感神经鞘瘤中的应用[J]. 中国癌症杂志, 2025,35(7):695-701. DOI: 10.19401/j.cnki.1007-3639.2025.07.008.
Shiyu XIANG, Qiao LI, Changqing SHEN, et al. Preoperative differentiation of vagal nerve cervical schwannomas from sympathetic chain cervical schwannomas based on diagnosis score and vascular displacement nomogram[J]. China Oncology, 2025, 35(7): 695-701. DOI: 10.19401/j.cnki.1007-3639.2025.07.008.
背景与目的:
颈部迷走神经鞘瘤(vagal nerve cervical schwannomas,VNCS)和颈部交感神经鞘瘤(sympathetic chain cervical schwannomas,SCCS)的术后并发症不同,术前准确鉴别VNCS与SCCS具有重要的临床意义。本研究旨在构建并验证基于血管移位情况建立的诊断评分和诺莫图模型,用于术前区分VNCS与SCCS。
方法:
本研究为横断面研究。回顾性分析2017年1月—2022年4月复旦大学附属肿瘤医院收治的经病理学检查证实的VNCS和SCCS患者资料,本研究经复旦大学附属肿瘤医院伦理委员会批准(伦理编号:1612167-18)。纳入标准:① 经活检或手术病理学检查证实的VNCS和SCCS;② 临床数据完整;③ 在术前进行增强计算机体层成像(computed tomography,CT)或磁共振成像(magnetic resonance imaging,MRI)检查。排除标准:① 对比剂过敏者;② 扫描图像质量差者;③ 图像伪影严重者;④ 扫描方式不符合要求者。所有患者以7∶3的比例随机分配到训练集和验证集。基于患者术前CT或MRI图像评估肿瘤的位置、大小及血管移位情况,由放射诊断科1名住院医师和1名主治医师分别独立阅片评估。使用Lasso回归分析筛选出独立预测因子,建立诊断评分和诺莫图,通过受试者工作特征(receiver operating characteristic,ROC)曲线评估模型性能。
结果:
共纳入患者110例,训练集77例,验证集33例,年龄24~78岁,平均(51.22±12.36)岁。两组患者的年龄、性别、肿瘤位置及大小等基线资料差异均无统计学意义(
P
>
0.05)。影像学分析显示,颈内动脉(internal carotid artery,ICA)与颈外动脉(external carotid artery,ECA)的分离状态与SCCS显著相关(
P
<
0.001),而ICA与颈内静脉(internal jugular vein,IJV)的分离则与VNCS显著相关(
P
<
0.001)。ICA后外侧移位与SCCS显著相关(
P
<
0.001),而ICA前内侧移位与VNCS显著相关(
P
<
0.001)。基于肿瘤大小、ICA移位方向、IJV移位方向、ICA/ECA分离及ICA/IJV分
离5个影像学特征构建的诊断评分模型与诺莫图,在区分VNCS与SCCS时表现出显著效能,训练集与验证集的ROC曲线的曲线下面积(area under curve,AUC)分别为0.953(95% CI:0.912~0.994)和0.939(95% CI:0.885~0.993)。
结论:
基于血管移位的诊断评分和诺莫图模型在鉴别VNCS与SCCS中表现出良好的预测效能,可能有助于临床决策。
Background and purpose:
Accurate preoperative differentiation between vagal nerve cervical schwannomas (SCCS) and sympathetic chain cervical schwannomas (SCCS) in the neck is crucial because of their different postoperative complication. This study aimed to construct and validate a Diagnosis Score and vascular displacement nomogram for the preoperative differentiation of VNCS from SCCS in the neck.
Methods:
This cross-sectional study retrospectively analyzed patients with pathologically confirmed VNCS and SCCS at Fudan University Shanghai Cancer Center from January 2017 to April 2022. This study was approved by the medical ethics committee of Fudan University Shanghai Cancer Center (approval number: 1612167-18). Inclusion criteria: ① histopathological diagnosis of VNCS or SCCS through biopsy or surgical resection; ② patients with complete clinic data; ③ availability of preoperative contrast-enhanced computed tomography (CT) or magnetic resonance imaging (MRI) examinations. Patients were excluded for: ① contrast agent contraindications; ② poor image quality; ③ severe artifacts; ④ non-standard scanning protocols. The cohort was randomly divided into training and validation sets in a 7∶3 ratio. Two radiologists (one resident and one attending physician) independently evaluated tumor characteristics (location
size and vascular displacement patterns) on preoperative imaging. Independent predictors were selected using LASSO regression analysis to construct a diagnostic scoring system and nomogram
with model performance evaluated by the receiver operating characteristic (ROC) curve.
Results:
A total of 110 patients were enrolled
with 77 cases allocated to the training set and 33 cases to t
he validation set. The age range was 24-78 years
and the mean age was (51.22±12.36) years. There were no statistically significant differences in baseline characteristics including age
gender
tumor location and size between the two patient groups (
P
>
0.05). ICA/ECA splaying was significantly associated with SCCS (
P
<
0.001)
while the ICA/IJV splaying was significantly associated with VNCS (
P
<
0.001). Lateral and posterior ICA displacement were significantly associated with SCCS (
P
<
0.001)
and medial and anterior ICA displacement were significantly associated with VNCS (
P
<
0.001). Five features including tumor size
ICA displacement direction
IJV displacement direction
ICA/ECA splaying and ICA/IJV splaying were used to establish the Diagnosis Score and nomogram. The nomogram combined imaging features showed favorable preference value for differentiating VNCS from SCCS
with area under curve (AUC) values of 0.953 (95% CI: 0.912-0.994) and 0.939 (95% CI: 0.885-0.993) for the training and validation cohorts
respectively.
Conclusion:
The Diagnosis Score and vascular displacement nomogram showed favorable predictive efficacy for differentiating VNCS from SCCS in the neck
and might be useful for clinical decision-making.
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