磁共振成像2026，Vol.17Issue(4)：70-78,9.DOI:10.12015/issn.1674-8034.2026.04.010
基于MRI多病灶生境影像组学预测肝富血供转移瘤的原发灶来源
Prediction of the primary lesion origin of hepatic hypervascular metastases based on MRI multi-lesion habitat radiomics
王荆 1贾平帆 2王效春3
作者信息
- 1. 山西医科大学第一医院磁共振影像科,太原 030001||长治医学院附属和济医院影像科,长治 046000
- 2. 长治医学院附属和平医院影像科,长治 046000
- 3. 山西医科大学第一医院磁共振影像科,太原 030001
- 折叠
摘要
Abstract
Objective:To develop and validate a multi-lesion habitat radiomics(ML-HR)model based on late arterial phase MRI and evaluate its value in non-invasively predicting the gastrointestinal(GI)versus non-GI origin of hypervascular liver metastases(HLM).Materials and Methods:The clinical and contrast-enhanced MRI Data of 111 HLM patients from two centers were retrospectively included and randomly divided into the training set and the validation set in a 7∶3 ratio.The volume of interest(VOI)of all lesions was delineated on the late-stage arterial images.Local radiomics features were extracted and subregions were divided.Fourteen machine learning algorithms were adopted to respectively construct the traditional single-lesion radiomics(SLR)model,the traditional multi-lesion radiomics(MLR)model and the multi-lesion habitat radiomics(ML-HR)model.To identify whether HLM originates from the GI.The optimal algorithm is screened and the best model is determined through the receiver operating characteristic curve.Results:A total of 111 patients(241 lesions)were included,among which the training set(n=77)and the validation set(n=34)were included.Decision tree(DT),radial basis function support vector machine(rbf_SVM),and eXtreme Gradient Boosting(XGBoost)were identified as the optimal algorithms for SLR,MLR,and ML-HR models,respectively.The ML-HR model has the best performance.The AUC of the training set is 0.952(95％confidence interval:0.904 to 0.988),and that of the validation set is 0.901(95％confidence interval:0.765 to 0.997),which is significantly better than the traditional model(P＜0.05).Conclusions:The ML-HR model can effectively and non-invasively predict the GI versus non-GI origin of HLM,providing a reliable imaging basis for clinical personalized medicine.关键词
富血供肝转移瘤/胃肠道/生境影像组学/影像组学/磁共振成像/个体化诊疗Key words
hypervascular liver metastases/gastrointestinal/habitat radiomics/radiomics/magnetic resonance imaging/personalized medicine分类
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王荆,贾平帆,王效春..基于MRI多病灶生境影像组学预测肝富血供转移瘤的原发灶来源[J].磁共振成像,2026,17(4):70-78,9.
