CT影像组学模型对肾上腺腺瘤亚型鉴别的价值  

The value of CT-based radiomics models in differentiating adrenal adenoma subtypes

作　　者：吴春梅 李轩昂 王尉丞 薛林雁[4] 殷小平[1,3] WU Chunmei;LI Xuanang;WANG Weicheng;XUE Linyan;YIN Xiaoping(Department of Radiology,Affiliated Hospital of Hebei University,Baoding 071000,China;College of Clinical Medical of Hebei University;Hebei Key Laboratory of precise imaging of inflammation related tumors;College of Quality and Technical Supervision,Hebei University)

机构地区：[1]河北大学附属医院影像科,保定071000 [2]河北大学临床医学院 [3]河北省炎症相关肿瘤精准影像诊断学重点实验室 [4]河北大学质量技术监督学院

出　　处：《国际医学放射学杂志》2024年第3期274-279,287,共7页International Journal of Medical Radiology

摘　　要：目的探讨基于多期相CT影像组学模型鉴别肾上腺腺瘤亚型的临床价值。方法回顾性收集经术后病理证实为肾上腺腺瘤的病人195例,均于术前行肾上腺CT平扫及增强检查。将病人按8∶2比例随机分成训练集(156例)和验证集(39例)。根据激素分泌水平将病人分为功能性肾上腺腺瘤组(70例)和无功能性肾上腺腺瘤组(125例)。基于病人CT平扫及增强影像提取1521个影像组学特征,通过随机森林算法筛选保留8个最优影像组学特征,采用支持向量机(SVM)算法并经5折交叉验证,分别构建平扫期、动脉期、静脉期、延迟期及各期融合的影像组学模型。2组间临床和CT影像特征的比较采用t检验、Mann-Whitney U检验、卡方检验。绘制受试者操作特征(ROC)曲线,计算ROC曲线下面积(AUC)、准确度、敏感度、特异度以评估模型效能。结果功能性肾上腺腺瘤组的血钾低于无功能性肾上腺腺瘤组,而高血压病人占比高于无功能性肾上腺腺瘤组(均P<0.05)。验证集中,平扫期影像组学模型的诊断效能(AUC=0.813)、准确度(0.759)、特异度(0.814)均最高。结论基于CT不同期相的影像组学特征结合SVM构建的影像组学模型可无创性鉴别肾上腺腺瘤亚型,具有一定的临床价值,有助于临床决策。Objective To investigate the clinical value of multiphase CT radiomics models in differentiating adrenal adenoma subtypes.Methods A retrospective collection of 195 patients with pathologically confirmed adrenal adenomas who underwent preoperative non-contrast and contrast-enhanced CT scans was conducted.Patients were randomly divided into a training set(156 cases)and a validation set(39 cases)in an 8∶2 ratio.Based on the hormone secretion level,the adrenal adenomas were divided into functional adrenal adenoma group(70 cases)and non-functional adrenal adenoma group(125 cases).Based on hormone secretion levels,patients were divided into a functional adrenal adenoma group(70 cases)and a non-functional adrenal adenoma group(125 cases).A total of 1521 radiomics features were extracted from the patients’non-contrast and contrast-enhanced CT images.Using the random forest algorithm,the top 8 optimal radiomics features were selected.Radiomics models were constructed using the support vector machine(SVM)algorithm with 5-fold cross-validation for the non-contrast phase,arterial phase,venous phase,delayed phase,and a model combining all phases.Clinical and CT imaging features were compared between the two groups using t-tests,Mann-Whitney U tests,and chi-square tests.The receiver operating characteristic(ROC)curve was plotted,and the area under the curve(AUC),accuracy,sensitivity,and specificity were calculated to evaluate the model's performance.Results The functional adrenal adenoma group had lower blood potassium levels and a higher proportion of patients with hypertension compared to the non-functional adrenal adenoma group(both P<0.05).In the validation set,the non-contrast phase radiomics model showed the highest diagnostic performance with an AUC of 0.813,accuracy of 0.759,and specificity of 0.814.Conclusion The radiomics model based on CT radiomics features from different phases combined with SVM can non-invasively differentiate adrenal adenoma subtypes.This model has significant clinical value and can aid in cl

关 键 词：肾上腺腺瘤 影像组学 机器学习 支持向量机 随机森林 体层摄影术 X线计算机 

分 类 号：R814.42[医药卫生—影像医学与核医学] R816.7[医药卫生—放射医学]