| [1] |
Albuainain RY,Bunajem FY,Abdulla HA. Assessment of Tumor Response to Neoadjuvant Chemotherapy in Breast Cancer Using MRI and(18)F-FDG PET/CT[J]. Eur J Breast Health,2025,21(1):46-51.
|
| [2] |
Chen Y,Chen S,Tang W,et al. Multiparametric MRI Radiomics With Machine Learning for Differentiating HER2-Zero,-Low,and -Positive Breast Cancer: Model Development,Testing,and Interpretability Analysis[J]. AJR Am J Roentgenol,2025,224(1):e2431717.
|
| [3] |
Shigematsu H,Fujimoto M,Kobayashi Y,et al. Prognostic Value of MRI Assessment of Residual Peritumoral Edema in Breast Cancer Treated With Neoadjuvant Chemotherapy[J]. J Magn Reson Imaging,2025,61(2):944-955.
|
| [4] |
Ren W,Xi X,Zhang X,et al. Predicting molecular subtypes of breast cancer based on multi-parametric MRI dataset using deep learning method[J]. Magn Reson Imaging,2025,117:110305.
|
| [5] |
Jacob S,Christofferson A,Fisch S,et al. Regional lymph node changes on breast MRI in patients with early-stage breast cancer receiving neoadjuvant chemo-immunotherapy[J]. Breast Cancer Res Treat,2025,209(1):147-159.
|
| [6] |
郭雯,任谊,魏庆忠. 改良VSD装置在乳腺癌改良根治术后腋窝引流中的临床应用价值[J/OL]. 中华普外科手术学杂志(电子版),2025,19(5):555-558.
|
| [7] |
Javadinia SA,Valizadeh N,Saeedian A. Editorial for "Prognostic Value of MRI Assessment of Residual Peritumoral Edema in Breast Cancer Treated With Neoadjuvant Chemotherapy"[J]. J Magn Reson Imaging,2025,61(2):956-957.
|
| [8] |
刘小娜,史博慧,马晓霞,等. 乳腺癌不同手术方式对术后并发症及康复影响的对比观察[J/OL]. 中华普外科手术学杂志(电子版),2025,19(5):551-554.
|
| [9] |
Lyu S,Wang B,Xie T,et al. Multiparametric MRI for differentiating idiopathic granulomatous mastitis from invasive breast cancer:Improving radiologists' diagnostic accuracy[J]. Eur J Radiol,2025,184:111958.
|
| [10] |
Kwon M,Ko EY,Lee JE,et al. Prediction model for individualized precision surgery in breast cancer patients with complete response on MRI and residual calcifications on mammography after neoadjuvant chemotherapy[J]. Breast Cancer,2025,32(1):109-119.
|
| [11] |
Aloufi AS,Khoumais N,Ahmed F,et al. Accuracy of Abbreviated Breast MRI in Diagnosing Breast Cancer in Women with Dense Breasts Compared with Standard Imaging Modalities[J]. Saudi J Med Med Sci,2025,13(1):7-17.
|
| [12] |
Yamaguchi K,Nakazono T,Egashira R,et al. Relationship between kinetic parameters of ultrafast dynamic contrast-enhanced(DCE)MRI and tumor-infiltrating lymphocytes(TILs)in breast cancer[J]. Jpn J Radiol,2025,43(1):43-50.
|
| [13] |
Ahmed KA,Kim Y,Armaghani AJ,et al. Phase II Trial of Brain MRI Surveillance in Stage IV Breast Cancer[J]. Neuro Oncol,2025,11(7):54-63.
|
| [14] |
Ozcan BB,Mootz AR,Polat DS,et al. Association of preoperative MRI with breast cancer treatment and survival: A single institution observational study[J]. Magn Reson Imaging,2025,118:110343.
|
| [15] |
Wang J,Wang L,Yang Z,et al. Application of machine learning in the analysis of multiparametric MRI data for the differentiation of treatment responses in breast cancer: retrospective study[J]. Eur J Cancer Prev,2025,34(1):56-65.
|
| [16] |
Janssen LM,de Vries BBLP,Janse MHA,et al. Tumor infiltrating lymphocytes and change in tumor load on MRI to assess response and prognosis after neoadjuvant chemotherapy in breast cancer[J]. Breast Cancer Res Treat,2025,209(1):167-175.
|
| [17] |
Shen F,Liu Q,Wang Y,et al. Comparison of[(18)F]FDG PET/CT and[(18)F]FDG PET/MRI in the Detection of Distant Metastases in Breast Cancer: A Meta-Analysis[J]. Clin Breast Cancer,2025,25(2):e113-e123.
|
| [18] |
Liao J,Xu Z,Xie Y,et al. Assessing Axillary Lymph Node Burden and Prognosis in cT1-T2 Stage Breast Cancer Using Machine Learning Methods: A Retrospective Dual-Institutional MRI Study[J]. J Magn Reson Imaging,2025,61(3):1221-1231.
|
| [19] |
鲁果果,王轩轩,马爱珍. 最小表观扩散系数值与浸润性乳腺癌生物学预后因子的关系分析[J]. 中国CT和MRI杂志,2024,22(6):85-87.
|
| [20] |
王巍巍,刘艳超,李颖,等. DCE-MRI预测乳腺癌NAC治疗后病理完全缓解的可行性研究[J]. 中国CT和MRI杂志,2024,22(7):114-117.
|
| [21] |
梁云,肖运平,主晓磊,等. 多模式MRI联合CA125、CA153、CA199预测乳腺癌术后复发转移的临床价值研究[J]. 中国CT和MRI杂志,2024,22(2):92-94.
|