医学影像学杂志2024，Vol.34Issue(2) ：46-51.

基于DCE-MRI影像组学模型对乳腺NME病变诊断价值的研究

Study on the diagnostic value of radiomics model based on dynamic contrast-enhanced magnetic resonance imaging for non-mass enhancement lesions of breast

李珍 刘磊 仲海 王翠艳
医学影像学杂志2024，Vol.34Issue(2) ：46-51.
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  • 万方数据

基于DCE-MRI影像组学模型对乳腺NME病变诊断价值的研究

Study on the diagnostic value of radiomics model based on dynamic contrast-enhanced magnetic resonance imaging for non-mass enhancement lesions of breast

李珍 1刘磊 2仲海 3王翠艳4
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作者信息

  • 1. 山东大学 山东 济南 250100;山东省立医院医学影像科 山东 济南 250021
  • 2. 山东众阳健康科技集团有限公司 山东 济南 250101
  • 3. 山东大学第二医院医学影像科 山东 济南 250031
  • 4. 山东大学 山东 济南 250100;山东省立医院医学影像科 山东 济南 250021;山东第一医科大学附属省立医院医学影像科 山东 济南 250021
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摘要

目的 探讨结合机器学习早期动态增强磁共振成像(DCE-MRI)的影像组学模型在鉴别良恶性乳腺非肿块强化(NME)病变中的价值.方法 选取行乳腺DCE-MRI检查并获得病理结果的NME病变患者 242 例,分为训练集 163例、测试集 55 例,外部验证集 24 例.基于早期DCE-MRI序列的特征选择,采用支持向量机(SVM)建立组学预测模型;由 2 位放射科医师独立评估MRI特征,建立传统诊断模型,预测病灶的良恶性;运用测试集和外部验证集进行测试和外部验证.采用受试者工作特征(ROC)曲线评价组学模型与放射医师的诊断效能.结果 影像组学模型鉴别乳腺NME病变良恶性达到了与高年资放射医师[曲线下面积(AUC)=0.82,95%CI 0.66,0.89]相当的诊断水平[(AUC=0.82,95%CI 0.67,0.90);P =0.30],均优于低年资放射医师的评估结果(Z=2.63,P=0.01;Z=2.41,P=0.02),同时利用外部验证集进一步验证该模型的预测效能.结论 基于早期DCE-MRI组学模型可以有效地鉴别NME病变的良恶性,与高年资放射医师诊断水平相当,并优于低年资医师诊断水平,可以辅助低年资医师做出更佳诊断.

Abstract

Objective To explore the value of radiomics model combined with machine learning of early dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)in distinguishing benign and malignant breast non-mass enhancement(NME)lesions.Methods 242 patients with NME lesions,who underwent breast DCE-MRI examination and obtained pathological re-sults,were selected anddivided into training set of 163 lesions,testing set of 55 lesions,and external validation set of 24 lesions.Based on feature selection of early DCE-MRI,radiomics model was to established by support vector machine.Two radiologists in-dependently evaluated MRI features,established a traditional diagnostic model,and predicted the benign and malignant lesions.Test sets and external validation sets were used for testing and external validation.The receiver operating characteristic(ROC)curve was used to evaluate the diagnostic efficiency of the radiomics model and radiologists.Results The differentiation of be-nign and malignant breast NME lesions using radiomics models reached a diagnostic level comparable to that of senior radiolo-gists[AUC=0.82,95%confidence interval(CI)0.66,0.89][(AUC=0.82,95%CI 0.67,0.90);P=0.30],both of which were superior to the evaluation results of junior radiologists(Z=2.63,P=0.01;Z=2.41,P=0.02),Meanwhile,external validation sets were used to further validate the predictive performance of the model.Conclusion Based on the early DCE-MRI radiomics model,it can effectively distinguish between benign and malignant NME lesions,which is comparable to the diagnostic level of senior radiologists and superior to the diagnostic level of junior radiologists.This can assist junior radiologists in making better di-agnoses.

关键词

影像组学/磁共振成像/乳腺非肿块强化病变

Key words

Radiomics/Magnetic resonance imaging/Non-mass enhancement lesions of breast

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基金项目

山东省医学会乳腺疾病科研基金项目(YXH2020ZX068)

出版年

2024
医学影像学杂志
山东医学影像学研究会,山东医学影像学研究所

医学影像学杂志

CSTPCD
影响因子：1.157
ISSN：1006-9011
参考文献量16
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