MRI ‐Based Habitat Analysis for Predicting Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer: A Multicenter Study

乳腺癌 医学 列线图 肿瘤科 新辅助治疗 接收机工作特性 化疗 内科学 放射科 病态的 威尔科克森符号秩检验 临床试验 熵(时间箭头) 病理 临床意义 分割 阶段(地层学) 磁共振成像 膀胱癌 癌症 核医学 精确检验 放化疗 完全响应 曲线下面积
作者
Huijuan Zhu,Baiyun Zhang,danni peng,Siyi Song,Lixia Huang,Ye Zhang,Xiu Wu
出处
期刊:Journal of Magnetic Resonance Imaging [Wiley]
卷期号:63 (6): 1769-1779 被引量:1
标识
DOI:10.1002/jmri.70285
摘要

BACKGROUND: Habitat imaging has been widely used to assess tumor treatment response; however, the role of MRI-based habitat analysis in identifying pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer remains an unresolved issue. OBJECTIVES: To evaluate the utility of dynamic contrast-enhanced MRI (DCE-MRI)-based habitat imaging in identifying pCR after NAC in breast cancer patients. STUDY TYPE: Retrospective. FIELD STRENGTH/SEQUENCE: 1.5 T or 3.0 T, DCE-MRI (Gradient echo). SUBJECTS: Three hundred and sixty-three women with biopsy-confirmed breast cancer from Center A (n = 249, training set) and Center B and Center C (n = 114, external validation set). ASSESSMENT: DCE-MRI peak-enhancement images were used to generate habitat maps via supervoxel segmentation and K-means clustering. Two intratumoral heterogeneity (ITH) metrics (Volume Entropy and Intensity Entropy) were extracted to quantify the structural and signal complexity of tumors. Three discriminative models were developed: a clinical model based on clinicopathologic variables, an ITH model incorporating Volume Entropy and Intensity Entropy, and an integrated nomogram combining both feature sets. STATISTICAL TESTS: , Fisher exact test, and receiver operating characteristic curve analysis. Significance was set at p < 0.05. RESULTS: Volume Entropy and Intensity Entropy were significantly lower in pCR versus non-pCR groups. HR status, HER2 status, and both ITH features were independent indicators of pCR. The nomogram showed superior performance (AUC = 0.849 in the training set and 0.825 in the validation set), outperforming the clinical model (DeLong test). Subgroup analysis across four molecular subtypes showed AUCs ranging from 0.762 to 0.890. An interactive online tool was developed for clinical application. DATA CONCLUSION: MRI-based habitat analysis offers a simple, interpretable, and clinically applicable approach for noninvasive identification of pCR to NAC in breast cancer. TECHNICAL EFFICACY: Stage 3.
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