Vascular Endothelial Growth Factor Expression in Invasive Ductal Carcinoma of Breast

Objective： To detect the expression of VEGF and MVD count in invasive ductal carcinoma of breast to clarify the association of VEGF expression and MVD count with the clinicopathologic features. Methods： The expressions of VEGF, ER, PR, C-erbB-2 and MVD count in 88 cases of invasive ductal carcinoma of breast were examined by immunohistochemistry staining （SP-method）. Results： Sixty-two out of the eighty-eight specimens of breast carcinoma （70.45%） showed positive expression of VEGF. The positive rate of VEGF in cases with lymph node metastasis was higher than that without lymph node metastasis （P〈0.05）. The positive rate of VEGF in stage IIb-Ⅲ was higher than that in stage Ⅰ-Ⅱa （P〈0.05）. The positive rate of VEGF in C-erbB-2 positive group was higher than that in C-erbB-2 negative group （P〈0.05）. Higher expression of VEGF was observed in cases with higher tissue differentiation degree （P〈0.05）. Also, significant higher MVD count was observed in cases with higher tissue differentiation degree （P〈0.01）. The MVD count increased significantly with the increase of the expression of VEGF （P〈0.01）. Conclusion： The result of this study suggested that in invasive ductal carcinoma of breast, angiogenesis and metastasis were mediated mainly by VEGF. The expression of VEGF and MVD might be reference predictors for the biological behavior of breast carcinoma. The antiangiogenic therapy which used VEGF as a target would become a new method to treat patients who were C-erbB-2 positive in the future.

Shear Wave Elastography of Invasive Ductal Carcinoma:Correlations between Shear Wave Velocity and Histological Prognostic Factors

The correlations between shear wave velocity(SWV)calculated from virtual touch tissue imaging quantification(VTIQ)technique and histological prognostic factors of invasive ductal carcinoma was investigated.A total of 76 breast tumors histologically confirmed as invasive ductal carcinomas were included in this study.SWV values were measured by VTIQ for each lesion preoperatively or prior to breast biopsy.The maximum values were recorded for statistical analysis.Medical records were reviewed to determine tumor size,histological grade,lymph node status and immunohistochemical results.Tumor subtypes were categorized as luminal A,luminal B,human epidermal growth factor receptor 2(HER2)positive and triple negative.The correlations between SWV and histological prognostic factors were analyzed.It was found that tumor size showed positive association with SWV(r=0.465,P<0.001).Larger tumors had significantly higher SWV than smaller ones(P=0.001).Histological grade 1 tumors had significantly lower SWV values than those with higher histological grade(P=0.015).The Ki67 expression,tumor subtypes and lymph node status showed no statistically significant correlations with SWV,although triple negative tumors and lymph node-positive tumors showed higher SWV values.It was concluded that tumor size was significantly associated with SWV.Higher histological grade was associated with increased SWV.There was no statistically significant correlations between SWV and other histological prognostic factors.

Enhancing Breast Cancer Diagnosis with Channel-Wise Attention Mechanisms in Deep Learning

Breast cancer,particularly Invasive Ductal Carcinoma(IDC),is a primary global health concern predominantly affecting women.Early and precise diagnosis is crucial for effective treatment planning.Several AI-based tech-niques for IDC-level classification have been proposed in recent years.Processing speed,memory size,and accuracy can still be improved for better performance.Our study presents ECAM,an Enhanced Channel-Wise Attention Mechanism,using deep learning to analyze histopathological images of Breast Invasive Ductal Carcinoma(BIDC).The main objectives of our study are to enhance computational efficiency using a Separable CNN architecture,improve data representation through hierarchical feature aggregation,and increase accuracy and interpretability with channel-wise attention mechanisms.Utilizing publicly available datasets,DataBioX IDC and the BreakHis,we benchmarked the proposed ECAM model against existing state-of-the-art models:DenseNet121,VGG16,and AlexNet.In the IDC dataset,the model based on AlexNet achieved an accuracy rate of 86.81%and an F1 score of 86.94%.On the other hand,DenseNet121 outperformed with an accuracy of 95.60%and an F1 score of 95.75%.Meanwhile,the VGG16 model achieved an accuracy rate of 91.20%and an F1 score of 90%.Our proposed ECAM model outperformed the state-of-the-art,achieving an impressive F1 score of 96.65%and an accuracy rate of 96.70%.The BreakHis dataset,the AlexNet-based model,achieved an accuracy rate of 90.82%and an F1 score of 90.77%.DenseNet121 achieved a higher accuracy rate of 92.66%with an F1 score of 92.72%,while the VGG16 model achieved an accuracy of 92.60%and an F1 score of 91.31%.The proposed ECAM model again outperformed,achieving an F1 score of 96.37%and an accuracy rate of 96.33%.Our model is a significant advancement in breast cancer diagnosis,with high accuracy and potential as an automated grading,especially for IDC.

Metaplastic breast cancer with chondrosarcomatous differentiation combined with concurrent bilateral breast cancer:A case report

BACKGROUND Metaplastic breast carcinoma(MBC)is a rare subtype of invasive breast cancer comprising malignant epithelial and mesenchymal cells.Compared with other invasive breast cancers,MBC is not only histologically distinctly heterogeneous but also has a rapid and aggressive growth pattern,which leads to a significant risk of recurrence and mortality.CASE SUMMARY In this study,we report the case of a patient with a large left breast mass diagnosed with bilateral invasive ductal carcinoma in both breasts after a preoperative core needle aspiration biopsy of the bilateral breast mass.The patient received neoadjuvant chemotherapy and underwent bilateral breast modified radical mastectomy.Postoperative pathology suggested carcinosarcoma with predominantly chondrosarcoma in the left breast and invasive ductal carcinoma(luminal B)in the right breast.As the patient did not achieve complete pathological remission after six cycles of neoadjuvant chemotherapy,we administered six months of intensive capecitabine treatment.Then the patient was switched to continuous treatment with endocrine therapy using letrozole+goserelin,and the patient is currently in stable condition.However,as MBC of the breast is concurrently diagnosed with chondrosarcoma differentiation,our case is sporadic.CONCLUSION Given the variety of immunohistochemical types of bilateral breast cancer,achieving effective chemotherapy should be a key research focus.

Application of Dual-Energy Computed Tomography for Breast Cancer Diagnosis

The present study aimed to investigate the possibility of using dual-energy computed tomography (CT) before therapy to discriminate between normal breast tissue and tumor tissue in patients with breast cancer, without the need to use a contrast medium. The following patient data were extracted by interview and from the hospital’s radiology information system: height, weight, age, menstrual cycle, CT images of normal tissue and tumors with or without contrast medium, and the histopathological diagnosis of the aspiration biopsy. The median age of the 43 participants was 56 years (range, 30 - 80 years). The CT values were evaluated using a clinical analytical program based on the three-material decomposition technique. Breast cancer was classified into ductal carcinoma in situ, invasive ductal carcinoma, invasive lobular carcinoma, fibromatosis-like metaplastic carcinoma, and apocrine carcinoma. In all conditions, regardless of contrast medium, the CT values of tumor tissues were higher than those of normal breast tissue, indicating the effectiveness of dual-energy CT (DE-CT) in the diagnosis of breast cancer. By contrast, DE-CT showed limited potential for distinguishing ductal carcinoma in situ from invasive ductal carcinoma. There have only been a few reports regarding CT examination of breast cancer, and it is expected this study encourage the development of DE-CT imaging to improve tumor detection in patients with breast cancer.

An AAS Dependent Method for Quantitative Analysis of Essential Trace Elements from Blood Samples of Pakistani Female Breast Cancer Patients

Breast cancer is the second leading cancer in the world. The long-term exposure of some metallic compounds induces different forms of cancer, including breast cancer. Trace elements are essential metals for the physiological functions of the cell on a molecular level and also contribute in treatment of many diseases. The aim of study was to compare the level of essential trace elements, sodium, potassium, calcium, iron, and zinc in breast cancer patients with normal healthy adult women. Total forty-five patients (age range from 25 - 73 years) were included in this study and divided into three groups according to three different stages of breast cancer including tumor-II, tumor-III and tumor-IV. Blood was collected from all participants after taking history, clinical data and taking consent. However, about fifteen non-cancer healthy women in age range from 26 - 69 years were subjected to this study. The elemental concentrations were determined through atomic absorption spectrophotometer subsequent to microwave-induced acid digestion. The results of Na, K, Zn, Fe, Ca, were observed to decrease in blood samples of breast cancer patients as compared to non-cancer subjects. The results are reliable with other numerous literature reported studies, the efficiency, and deficiency of these trace metals may contribute an important role in the progress of breast cancer.

Blood Oxygenation Level-dependent Magnetic Resonance Imaging of Breast Cancer： Correlation with Carbonic Anhydrase IX and Vascular Endothelial Growth Factor

Background： Blood oxygenation level-dependent magnetic resonance imaging （BOLD-MRI） is a functional MRI technique which involves using the paramagnetic properties of deoxyhemoglobin to image the local tissue oxygen concentration. The purpose of this study was to investigate whether BOLD-MRI could evaluate hypoxia and angiogenesis of breast invasive ductal carcinoma （IDC）. Methods： Ninety-eight female patients with IDC were retrospectively included in this research. All patients underwent breast BOLD-MRI at 3.0 T before surgery. R2＊ values of BOLD-MR1 were measured. The expression of carbonic anhydrase IX （CA IX） and vascular endothelial growth factor （VEGF） was analyzed by immunohistochemistry. Spearman＇s correlation analysis was used to correlate R2＊ value with CA IX and VEGF levels. Results： Heterogeneous intensity on BOLD-MRI images was the main finding of IDCs. The mean R2＊ value was 52.8 ± 18.6 Hz. The R2＊ values in patients with axillary lymph node metastasis were significantly higher than the R2＊ values in patients without axillary lymph node metastasis （t = 2.882, P = 0.005）. R2＊ values increased with CA IX level and positively correlated with the level of CA 1X （r = 0.616, P 〈 0.001）; however, R2＊ value had no significantly correlation with the level of VEGF （r = 0.110, P = 0.281）. Conclusion： B OLD-MRI could noninvasively evaluate chronic hypoxia of IDC, but not angiogenesis.