Correlation Analysis of Breast Cancer DWI Combined with DCE-MRI Imaging Features with Molecular Subtypes and Prognostic Factors

2019 ◽  
Vol 43 (4) ◽  
Author(s):  
Congru Yuan ◽  
Feng Jin ◽  
Xiuling Guo ◽  
Sheng Zhao ◽  
Wei Li ◽  
...  
2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Shuang Liu ◽  
Min Tang ◽  
Shuqin Ruan ◽  
Feng Wei ◽  
Jiaxi Lu

This study was to analyze the clinical application value of magnetic resonance imaging (MRI) image features based on intelligent algorithms in the diagnosis and treatment of breast cancer and to provide an effective reference assessment for breast cancer diagnosis. The MRI diagnosis model (ACO-MRI) based on the ant colony algorithm (ACO) was proposed, which was compared with the diagnosis methods based on support vector machine (SVM) and proximity (KNN) algorithm, and the proposed algorithm was applied to MRI images to diagnose breast cancer. The results showed that the accuracy, sensitivity, and specificity of the ACO-MRI model were greater than those of the KNN and SVM algorithm. Moreover, the specificity was statistically considerable compared with the two algorithms of KNN and SVM ( P < 0.05 ). By comparing 1/5 number of ants and the average gray path of the ACO-MRI model under 1/8 number of ants, it was found that the average gray path value of 1/8 number of ants was greatly higher than the average gray path value of 1/5 number of ants ( P < 0.05 ). The differences in the overall distribution of breast MRI imaging features among Luminal A, Luminal B, HER-2 overexpression, and TN were compared. There were considerable differences in the overall distribution of the three breast MRI imaging features of the boundaries, morphology, and enhancement methods among the four groups ( P < 0.05 ). In short, MRI image based on the intelligent algorithm ACO-MRI diagnosis model can effectively improve the diagnosis effect of breast cancer. Its image feature boundaries, morphology, and enhancement methods had good imaging features in the diagnosis of breast cancer.


Author(s):  
Rong Sun ◽  
Zi-jun Meng ◽  
Xuewen Hou ◽  
Yang Chen ◽  
Yi-feng Yang ◽  
...  

2020 ◽  
Vol 38 (11) ◽  
pp. 1062-1074
Author(s):  
Junlin Huang ◽  
Qing Lin ◽  
Chunxiao Cui ◽  
Jie Fei ◽  
Xiaohui Su ◽  
...  

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 11599-11599
Author(s):  
Sherry X. Yang ◽  
Eric Polley

11599 Background: It is unclear whether survival varies among breast cancer molecular subtypes without systemic and locoregional therapy. This study aims to evaluate the survival profile by molecular subtypes after surgery. Methods: In total, we evaluated 301 women with invasive breast cancer with stage I, II or III disease. Patients were classified into four major breast cancer subtypes by immunohistochemistry/FISH classifiers: luminal-A (ER+ and/or PR+/HER2-), luminal-B (ER+ and/or PR+/HER2+), HER2-enriched (HER2+/ER-/PR-) or basal-like (ER-/PR-/HER2-; triple-negative). Overall survival (OS) was analyzed by Kaplan-Meier analysis, and log-rank test for differences. Association between clinical outcome and subtype adjusting for breast cancer prognostic factors was assessed by multivariable Cox proportional hazards model. Results: All patients did not receive systemic chemotherapy and hormone therapy as well as radiation therapy. Luminal A was the most common subtype (N = 224), followed by basal-like (N = 43), luminal B (N = 21) and HER2-enriched (N = 13). Median follow-up for OS was 197 months (range: 1 – 273 months). Age at diagnosis was statistically different among the subtypes, with basal-like and luminal B having high proportions less than 50 years (P = 0.047). Patients with basal-like and HER2-enriched had more high grade tumors (P < 0.001). Notably, there was no difference in OS among the four subtypes (log-rank P = 0.983). In multivariable analysis, the adjusted hazard ratio (HR) was 1.1 for luminal A vs. luminal B (P = 0.781), 0.62 in luminal A vs. HER2-enriched (P = 0.273), or 0.67 in luminal A vs. basal-like (P = 0.158). In contrast, the adjusted HR were 2.2 in age less than 50 years (P = 0.0017), and 1.1 for number of positive nodes (P = 0.00074). Conclusions: OS, through long-term clinical follow-up, is not significantly different among molecular subtypes if not controlling for other prognostic factors in patients who only received surgery. Age and number of positive nodes are independent prognostic factors in patients with no systemic and locoregional treatments.


Author(s):  
Karen S Johnson ◽  
Emily F Conant ◽  
Mary Scott Soo

Abstract Gene expression profiling has reshaped our understanding of breast cancer by identifying four molecular subtypes: (1) luminal A, (2) luminal B, (3) human epidermal growth factor receptor 2 (HER2)-enriched, and (4) basal-like, which have critical differences in incidence, response to treatment, disease progression, survival, and imaging features. Luminal tumors are most common (60%–70%), characterized by estrogen receptor (ER) expression. Luminal A tumors have the best prognosis of all subtypes, whereas patients with luminal B tumors have significantly shorter overall and disease-free survival. Distinguishing between these tumors is important because luminal B tumors require more aggressive treatment. Both commonly present as irregular masses without associated calcifications at mammography; however, luminal B tumors more commonly demonstrate axillary involvement at diagnosis. HER2-enriched tumors are characterized by overexpression of the HER2 oncogene and low-to-absent ER expression. HER2+ disease carries a poor prognosis, but the development of anti-HER2 therapies has greatly improved outcomes for women with HER2+ breast cancer. HER2+ tumors most commonly present as spiculated masses with pleomorphic calcifications or as calcifications alone. Basal-like cancers (15% of all invasive breast cancers) predominate among “triple negative” cancers, which lack ER, progesterone receptor (PR), and HER2 expression. Basal-like cancers are frequently high-grade, large at diagnosis, with high rates of recurrence. Although imaging commonly reveals irregular masses with ill-defined or spiculated margins, some circumscribed basal-like tumors can be mistaken for benign lesions. Incorporating biomarker data (histologic grade, ER/PR/HER2 status, and multigene assays) into classic anatomic TNM staging can better inform clinical management of this heterogeneous disease.


PLoS ONE ◽  
2017 ◽  
Vol 12 (2) ◽  
pp. e0171683 ◽  
Author(s):  
Ming Fan ◽  
Hui Li ◽  
Shijian Wang ◽  
Bin Zheng ◽  
Juan Zhang ◽  
...  

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