CT 放射组学列线图预测头颈部鳞状细胞癌的 Ki-67 指数。
CT radiomics nomogram for prediction of the Ki-67 index in head and neck squamous cell carcinoma.
机构信息
Health Management Center, The Affiliated Hospital of Qingdao University, Qingdao, China.
Deapartment of Neurology, Jinan Central Hospital Affiliated to Shandong First Medical University, Jinan, China.
出版信息
Eur Radiol. 2023 Mar;33(3):2160-2170. doi: 10.1007/s00330-022-09168-6. Epub 2022 Oct 12.
OBJECTIVES
To construct and validate a contrast-enhanced computed tomography (CECT)-based radiomics nomogram to predict Ki-67 expression level in head and neck squamous cell carcinoma (HNSCC).
METHODS
A total of 217 patients with HNSCC who underwent CECT scans and immunohistochemical examination of their Ki-67 index were enrolled in this study. The patients were divided into a training set (n = 140; Ki-67: ≥ 50% [n = 72] and < 50% [n = 68]) and an external test set (n = 77; Ki-67: ≥ 50% [n = 38] and < 50% [n = 39]). The least absolute shrinkage and selection operator method was used to select key features for a CECT-image-based radiomics signature and a radiomics score (Rad-score) was calculated. A clinical model was established using clinical data and CT findings. The independent clinical factors and Rad-score were then combined to construct a radiomics nomogram. The performance characteristics of the Rad-score, clinical model, and nomogram were assessed using ROCs and decision curve analysis.
RESULTS
Twenty features were finally selected to construct the Rad-score. The radiomics nomogram incorporating the Rad-score, low histological grade, and lymphatic spread showed higher predictive value for the Ki-67 index (≥ 50% vs. < 50%) than the clinical model on both the training (AUC, 0.919 vs. 0.648, p < 0.001) and test (AUC, 0.832 vs. 0.685, p = 0.030) sets. Decision curve analysis demonstrated that the radiomics nomogram was more clinically useful than the clinical model.
CONCLUSIONS
A CECT-based radiomics nomogram was constructed to predict the expression of Ki-67 in HNSCC. This model showed favorable predictive efficacy and might be useful for prognostic evaluation and clinical decision-making in patients with HNSCC.
KEY POINTS
• Accurate pre-treatment prediction of Ki-67 index in HNSCC is crucial. • A CECT-based radiomics nomogram showed favorable predictive efficacy in estimation of Ki-67 expression status in HNSCC patients.
目的
构建并验证基于增强 CT（CECT）的放射组学列线图，以预测头颈部鳞状细胞癌（HNSCC）中 Ki-67 的表达水平。
方法
本研究共纳入 217 例接受 CECT 扫描和 Ki-67 免疫组化检查的 HNSCC 患者。将患者分为训练集（n=140；Ki-67：≥50%[n=72]和<50%[n=68]）和外部测试集（n=77；Ki-67：≥50%[n=38]和<50%[n=39]）。采用最小绝对收缩和选择算子方法选择 CECT 图像的关键特征，并计算放射组学评分（Rad-score）。使用临床数据和 CT 结果建立临床模型。然后将独立的临床因素和 Rad-score 结合起来构建放射组学列线图。使用 ROC 和决策曲线分析评估 Rad-score、临床模型和列线图的性能特征。
结果
最终选择了 20 个特征来构建 Rad-score。包含 Rad-score、低组织学分级和淋巴扩散的放射组学列线图在训练集（AUC，0.919 对 0.648，p<0.001）和测试集（AUC，0.832 对 0.685，p=0.030）上对 Ki-67 指数（≥50%对<50%）的预测价值均高于临床模型。决策曲线分析表明，放射组学列线图比临床模型更具临床实用性。
结论
构建了基于 CECT 的放射组学列线图来预测 HNSCC 中 Ki-67 的表达。该模型显示出良好的预测效果，可能有助于 HNSCC 患者的预后评估和临床决策。
关键点
• 准确预测 HNSCC 中 Ki-67 指数对于治疗前的决策至关重要。• 基于 CECT 的放射组学列线图在预测 HNSCC 患者 Ki-67 表达状态方面具有良好的预测效果。
Zotero 插件