首页|期刊导航|医疗卫生装备|超声影像组学与卵巢癌临床病理特征的关系及对Ki-67阳性表达的预测价值

超声影像组学与卵巢癌临床病理特征的关系及对Ki-67阳性表达的预测价值OA

Relationship between ultrasound radiomics and clinicopathological characteristics of ovarian cancer and its predictive value for positive expression of Ki-67

中文摘要英文摘要

目的:探究超声影像组学与卵巢癌临床病理特征的关系及对Ki-67阳性表达的预测价值.方法:回顾性选取2021年7月—2024年7月于某院接受治疗的126例卵巢癌患者作为训练集,根据患者Ki-67表达情况将训练集分为阳性组(n=93)和阴性组(n=33).另选取同期于该院接受治疗的80例卵巢癌患者作为测试集.比较训练集和测试集的临床资料,并对阳性组和阴性组的临床病理特征及常规超声特征、影像组学特征进行组间比较.通过多因素Logistic回归分析Ki-67阳性表达的影响因素,并将其纳入Logistic回归进行模型拟合,得到临床参数模型.将组内相关系数>0.8 的超声影像组学特征纳入最小绝对收缩和选择算子(least absolute shrinkage and selection operator,LASSO)回归进行降维并筛选出最终的超声影像组学特征,将最终筛选出的特征纳入多元Logistic回归分析构建超声影像组学模型.基于超声影像组学评分Rad-score和临床病理特征构建联合模型.绘制ROC曲线、校准曲线、临床决策曲线评价3个模型的预测效能.采用Spearman相关性检验分析Rad-score与临床病理特征的相关性.使用SPSS 22.0软件进行统计学分析.结果:训练集与测试集临床资料比较差异无统计学意义(P>0.05).阳性组中,国际妇产科联合会(International Federation of Gynecology and Obstetrics,FIGO)分期为Ⅲ~Ⅳ期、有淋巴结转移、有远处或周边组织浸润、分化程度为低分化、肿瘤最大径≥10 cm的患者明显多于阴性组,差异有统计学意义(P<0.05).在边界不清晰、形态不规则、有血流信号方面,阳性组患者明显多于阴性组,阳性组患者的阻力指数高于阴性组,差异有统计学意义(P<0.05).多因素Logistic回归分析结果表明,有远处或周边组织浸润、有淋巴结转移、FIGO分期为Ⅲ~Ⅳ期、肿瘤最大径≥10 cm、分化程度为低分化是卵巢癌患者Ki-67阳性表达的危险因素(P<0.05).ROC曲线显示,临床参数模型、超声影像组学模型、联合模型AUC值分别为0.805、0.856、0.927,均具有较高的区分度,且联合模型优于单一模型;校准曲线显示,3个模型的预测值与观测值拟合良好,联合模型的准确性较好;临床决策曲线分析结果显示,3种模型的净获益值均较高,联合模型的有效性更优.Rad-score与临床病理特征呈负相关,Rad-score与FIGO分期(r=-0.59,P<0.001)、有无淋巴结转移(r=-0.87,P<0.001)、有无远处或周边组织浸润(r=-0.82,P<0.001)、分化程度(r=-0.58,P<0.001)、肿瘤最大径(r=-0.78,P<0.001)的相关性较高.结论:卵巢癌患者超声影像组学特征与临床病理特征具备相关性,且基于临床参数与超声影像组学构建的联合模型对Ki-67阳性表达具有较好的预测价值.

Objective To explore the relationship between ultrasound radiomics and clinicopathological characteristics of ovarian cancer and its predictive value for positive expression of Ki-67.Methods A retrospective cohort of 126 ovarian cancer patients treated at a certain hospital between July 2021 and July 2024 was included into a training set.Based on the Ki-67 expression status,the training set was divided into a positive group(n=93)and a negative group(n=33).An additional 80 ovarian cancer patients treated at the same hospital during the same period were enrolled into a test set.The clinical data of the training and test sets were compared,and inter-group comparison between the positive and negative groups was carried out in terms of clinicopathological and conventional ultrasound characteristics,radiomics characteristics.The factors influencing Ki-67 positive expression were investigated with the multivariate regression analysis,which were incorporated into a logistic regression model for fitting to yield a clinical parameter model.The ultrasound radiomics characteristics with intra-group correlation coefficients>0.8 were included in least absolute shrinkage and selection operator(LASSO)regression for dimensionality reduction and final feature selection,then the selected characteristics were integrated into multiple logistic regression analysis to construct an ultrasound radiomics model.A combined model was established based on the ultrasound radiomics scores(Rad-score)and clinicopathological characteristics.Receiver operating characteristic(ROC)curves,calibration curves and clinical decision curves were plotted to evaluate the predictive performance of the three models.Spearman's correlation analysis was used to examine the relationship between Rad-score and clinicopathological characteristics.Statistical analysis was performed using SPSS 22.0 software.Results There was no statistically significant difference in clinical data between the training set and the test set(P>0.05).In the positive group the patients with FIGO stage Ⅲ-Ⅳ cancer,lymph node metastasis,distant or peripheral tissue infiltration,low differentiation and tumor maximum diameter≥10 cm were more than those in the negative group,with the difference being significant(P<0.05).There were more patients with unclear boundaries,irregular morphology and blood flow signals in the positive group than in the negative group,and the patients in the positive group had higher resistance indexes than those in the negative group,with the differences being statistically significant(P<0.05).Multivariate logistic regression analysis revealed the risk factors for Ki-67 positive expression in ovarian cancer patients included distant or peripheral tissue infiltration,lymph node metastasis,FIGO stage Ⅲ-Ⅳ cancer,tumor maximum diameter≥10 cm and low differentiation(P<0.05).The ROC curves showed the AUC values for the clinical parameter model,ultrasound radiomics model and combined model were 0.805,0.856 and 0.927 respectively,all demonstrating high discriminatory power,and the combined model outperformed the individual models;the calibration curves proved the predicted values from all the three models had high agreement with the observed values,and the combined model gained higher accuracy than the others;the clinical decision curve analysis indicated the three models were gifted with high net benefit values,and the combined model behaved better than the others.Rad-scores was negatively correlated with clinicopathological characteristics,and the Rad-score showed high correlations with FIGO staging(r=-0.59,P<0.001),presence of lymph node metastasis(r=-0.87,P<0.001),presence of peripheral tissue infiltration(r=-0.82,P<0.001),differentiation(r=-0.58,P<0.001)and tumor maximum diameter(r=-0.78,P<0.001).Conclusion Ultrasound radiomics characteristics in ovarian cancer patients correlate with clinicopathological characteristics,and the combined model incorporating clinical parameters and ultrasound radiomics demonstrates high predictive value for Ki-67 positive expression.[Chinese Medical Equipment Journal,2026,47(4):73-81]

李红莲;程进波

福建医科大学附属南平第一医院超声科,福建 南平 353000福建医科大学附属南平第一医院超声科,福建 南平 353000

医药卫生

超声影像组学卵巢癌Ki-67阳性表达临床病理特征

ultrasound radiomicsovarian cancerKi-67 positive expressionclinicopathological characteristic

《医疗卫生装备》 2026 (4)

73-81,9

10.19745/j.1003-8868.2026060

评论