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利用功能磁共振成像对乳腺癌亚型进行鉴别及其与生物学状态的相关性:与酰胺质子转移加权成像和扩散加权成像的比较

Differentiation of breast cancer subtypes and correlation with biological status using functional magnetic resonance imaging: comparison with amide proton transfer-weighted imaging and diffusion-weighted imaging.

作者信息

Xu Mingzhe, Shan Dongqiu, Zhang Renzhi, Li Jing, Guo Lanwei, Chen Xuejun, Qu Jinrong

机构信息

Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China.

Department of Radiology, National Cancer Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

出版信息

Quant Imaging Med Surg. 2025 Jul 1;15(7):6102-6117. doi: 10.21037/qims-24-2174. Epub 2025 Jun 25.


DOI:10.21037/qims-24-2174
PMID:40727362
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12290727/
Abstract

BACKGROUND: Differentiating molecular subtypes and identifying biological markers in breast cancer (BC) are essential for prognostic stratification and treatment selection. This study aimed to compare the effectiveness of amide proton transfer-weighted imaging (APTWI) and diffusion-weighted imaging (DWI) in differentiating molecular subtypes and predicting the biological status of BC. METHODS: This retrospective study included 109 women (aged 50.8±10.8 years) with BC who underwent 3T APTWI and DWI between May 2023 and January 2024. Patients were categorized by molecular subtypes and expression levels of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and Ki-67. Magnetization transfer ratio asymmetry (MTRasym) and apparent diffusion coefficient (ADC) values were measured. The area under the receiver operating characteristic (ROC) curve (AUC) was used to assess the performance of MTRasym and ADC values in distinguishing subtypes. Pearson's correlation analysis was used to examine the relationship between MTRasym, ADC values, and the Ki-67 proliferation index. RESULTS: Triple-negative (TN) cancers (3.03%±0.56%) had significantly higher MTRasym values than luminal A (2.25%±1.00%) and luminal B (2.39%±0.81%) cancers (P=0.006, 0.012). HER2-enriched cancers (2.93%±0.71%) also had significantly higher MTRasym than luminal A cancers (P=0.039). MTRasym and ADC values were significantly higher in ER-negative (ER-) than they were in ER-positive (ER+) cancers (P<0.001, P=0.040), and MTRasym values were higher in PR-negative (PR-) and high-Ki-67 cancers (P<0.001, P=0.013). AUC values for MTRasym ranged from 0.699 to 0.799, depending on the subtype and biological marker comparison. MTRasym and ADC values showed a weak positive correlation with the Ki-67 index (r=0.37, P<0.001, and r=0.31, P=0.003). CONCLUSIONS: APTWI is more effective than DWI for differentiating BC subtypes and predicting biological markers, providing valuable insights for clinical management.

摘要

背景:区分乳腺癌(BC)的分子亚型并识别生物标志物对于预后分层和治疗选择至关重要。本研究旨在比较酰胺质子转移加权成像(APTWI)和扩散加权成像(DWI)在区分BC分子亚型和预测其生物学状态方面的有效性。 方法:这项回顾性研究纳入了2023年5月至2024年1月期间接受3T APTWI和DWI检查的109例BC女性患者(年龄50.8±10.8岁)。根据雌激素受体(ER)、孕激素受体(PR)、人表皮生长因子受体2(HER2)和Ki-67的分子亚型和表达水平对患者进行分类。测量磁化转移率不对称性(MTRasym)和表观扩散系数(ADC)值。采用受试者操作特征(ROC)曲线下面积(AUC)评估MTRasym和ADC值区分亚型的性能。采用Pearson相关分析检验MTRasym、ADC值与Ki-67增殖指数之间的关系。 结果:三阴性(TN)癌(3.03%±0.56%)的MTRasym值显著高于管腔A型(2.25%±1.00%)和管腔B型(2.39%±0.81%)癌(P=0.006,0.012)。HER2富集型癌(2.93%±0.71%)的MTRasym也显著高于管腔A型癌(P=0.039)。ER阴性(ER-)癌的MTRasym和ADC值显著高于ER阳性(ER+)癌(P<0.001,P=0.040),PR阴性(PR-)和高Ki-67癌的MTRasym值更高(P<0.001,P=0.013)。根据亚型和生物标志物比较,MTRasym的AUC值在0.699至0.799之间。MTRasym和ADC值与Ki-67指数呈弱正相关(r=0.37,P<0.001;r=0.31,P=0.003)。 结论:APTWI在区分BC亚型和预测生物标志物方面比DWI更有效,为临床管理提供了有价值的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c34/12290727/4b05be502d42/qims-15-07-6102-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c34/12290727/81dc1ae120ea/qims-15-07-6102-f1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c34/12290727/af2a16e60980/qims-15-07-6102-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c34/12290727/f44ab2344c25/qims-15-07-6102-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c34/12290727/4b05be502d42/qims-15-07-6102-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c34/12290727/81dc1ae120ea/qims-15-07-6102-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c34/12290727/6de7bf40b1bf/qims-15-07-6102-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c34/12290727/37de50e84126/qims-15-07-6102-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c34/12290727/3c5eedc0724c/qims-15-07-6102-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c34/12290727/af2a16e60980/qims-15-07-6102-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c34/12290727/f44ab2344c25/qims-15-07-6102-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c34/12290727/4b05be502d42/qims-15-07-6102-f7.jpg

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本文引用的文献

[1]
Evaluation of functional magnetic resonance APT and DKI imaging for breast cancer.

Cancer Cell Int. 2024-12-18

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Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.

CA Cancer J Clin. 2024

[3]
Radiomic Nomogram for Predicting Axillary Lymph Node Metastasis in Patients with Breast Cancer.

Acad Radiol. 2024-3

[4]
Predicting histopathological types and molecular subtype of breast tumors: A comparative study using amide proton transfer-weighted imaging, intravoxel incoherent motion and diffusion kurtosis imaging.

Magn Reson Imaging. 2024-1

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Sci Rep. 2023-10-20

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Human Epidermal Growth Factor Receptor 2 Testing in Breast Cancer: ASCO-College of American Pathologists Guideline Update.

J Clin Oncol. 2023-8-1

[10]
Breast Amide Proton Transfer Imaging at 3 T: Diagnostic Performance and Association With Pathologic Characteristics.

J Magn Reson Imaging. 2023-3

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