METHODS: Breast cancer MRI images were classified into BA, BF, BPT, BTA, MDC, MLC, MMC, and MPC using a proposed Deep Learning model with additional 5 fine-tuned Deep learning models consisting of Xception, InceptionV3, VGG16, MobileNet and ResNet50 trained on ImageNet database. The dataset was collected from Kaggle depository for breast cancer detection and classification. That Dataset was boosted using GAN technique. The images in the dataset have 4 magnifications (40X, 100X, 200X, 400X, and Complete Dataset). Thus we evaluated the proposed Deep Learning model and 5 pre-trained models using each dataset individually. That means we carried out a total of 30 experiments. The measurement that was used in the evaluation of all models includes: F1-score, recall, precision, accuracy.
RESULTS: The classification F1-score accuracies of Xception, InceptionV3, ResNet50, VGG16, MobileNet, and Proposed Model (BCCNN) were 97.54%, 95.33%, 98.14%, 97.67%, 93.98%, and 98.28%, respectively.
CONCLUSION: Dataset Boosting, preprocessing and balancing played a good role in enhancing the detection and classification of breast cancer of the proposed model (BCCNN) and the fine-tuned pre-trained models' accuracies greatly. The best accuracies were attained when the 400X magnification of the MRI images due to their high images resolution.
Methods: 80 patients with invasive breast cancer receiving BCS after neoadjuvant chemotherapy were included in this non-randomized case-control study. 40 patients with specimen radiography performed in a standard approach (control group) were compared to 40 patients with use of a radiopaque tissue transfer system (study group).
Results: 19/80 (23.75%) patients required re-excision because of involved margins; among those, 14/40 (35%) were in the control group and 5/40 (12.5%) in the study group. The association between the use of the radiopaque tissue transfer system and the lower re-excision rate was statistically significant (p = 0.023).
Conclusion: Our analysis provides a rationale for the routine use of a radiopaque tissue transfer system for specimen radiography in BCS after neoadjuvant chemotherapy for invasive breast cancer in order to reduce re-excision rates.
METHODS: Patients diagnosed with invasive breast cancer (BC) from 2005 to 2013 at our tertiary institution were included and divided according to race and subtypes. Demographic and clinical information of non-metastatic TNBC patients were analyzed. Log-rank test, univariate and multivariate Cox proportional hazard regression models were used to find associated risk factors related with overall survival (OS) and disease-free survival (DFS).
RESULTS: Among 1227 BC patients, 129 (10.5%) had TNBC. TNBC patients had the worst OS (P: 0.0005) and DFS (P: 0.0016) among the subtypes. However, variations in race did not have any difference in OS or DFS among TNBC patients. Axillary lymph node involvement, invasive lobular histology, larger tumor size, and the presence of lymphovascular invasion (LVI) were factors associated with both poor DFS and OS among TNBC patients.
CONCLUSIONS: Racial variation did not have any impact on the prognosis of the TNBC.
MATERIALS AND METHODS: Twenty-four patients with clinically node-negative breast cancer were recruited. Combined radiotracer and blue dye methods were used for identification of SLNs. The nodes were thinly sliced and embedded. Serial sectioning and immunohistochemical (IHC) staining against AE1/AE3 were performed if initial HandE sections of the blocks were negative.
RESULTS: SLNs were successfully identified in all patients. Ten cases had nodal metastases with 7 detected in SLNs and 3 detected only in axillary nodes (false negative rate, FNR=30%). Some 5 out of 7 metastatic lesions in the SLNs (71.4%) were detected in initial sections of the thinly sliced tissue. Serial sectioning detected the remaining two cases with either micrometastases or isolated tumour cells (ITC).
CONCLUSIONS: Thin slicing of tissue to 3-5mm thickness and serial sectioning improved the detection of micro and macro-metastases but the additional burden of serial sectioning gave low yield of micrometastases or ITC and may not be cost effective. IHC validation did not further increase sensitivity of detection. Therefore its use should only be limited to confirmation of suspicious lesions. False negative cases where SLNs were not involved could be due to skipped metastases to non-sentinel nodes or poor technique during procurement, resulting in missed detection of actual SLNs.
OBJECTIVES: To assess the expression of DDR1 and DVL1 and their association with histological type, grading and hormonal status of IDC and ILC.
MATERIALS AND METHODS: This cross sectional study was conducted on IDC and ILC breast tumours. Tumours were immunohistochemically stained for (DDR1) and (DVL1) as well as estrogen receptor (ER), progesterone receptor (PR) and C-erbB2 receptor. Demographic data including age and ethnicity were obtained from patient records.
RESULTS: A total of 51 cases (30 IDCs and 21 ILCs) were assessed. DDR1 and DVL1 expression was not significantly associated with histological type (p=0.57 and p=0.66 respectively). There was no association between DDR1 and DVL1 expression and tumour grade (p=0.32 and p=1.00 respectively), ER (p=0.62 and 0.50 respectively), PR (p=0.38 and p=0.63 respectively) and C-erbB2 expression (p=0.19 and p=0.33 respectively) in IDC. There was no association between DDR1 and DVL1 expression and tumour grade (p=0.52 and p=0.33 respectively), ER (p=0.06 and p=0.76 respectively), PR (p=0.61 and p=0.43 respectively) and C-erbB2 expression (p=0.58 and p=0.76 respectively) in ILC.
CONCLUSIONS: This study revealed that DDR1 and DVL1 are present in both IDC and ILC regardless of the tumour differentiation. More studies are needed to assess the potential of these two proteins in distinguishing IDC from ILC in breast tumours.
METHODS: We conducted a cross sectional study using 100 samples of archived formalin-fixed paraffin embedded tissue blocks of invasive ductal carcinoma and stained them with immunohistochemistry for PITX2, ER, PR and HER2. All HER2 with scoring of 2+ were confirmed with chromogenic in-situ hybridization (CISH).
RESULTS: PITX2 protein was expressed in 53% of invasive ductal carcinoma and lack of PITX2 expression in 47%. Univariate analysis revealed a significant association between PITX2 expression with PR (p=0.001), ER (p=0.006), gland formation (p=0.044) and marginal association with molecular subtypes of breast carcinoma (p=0.051). Combined ER and PR expression with PITX2 was also significantly associated (p=0.003) especially in double positive cases. Multivariate analysis showed the most significant association between PITX2 and PR (RR 4.105, 95% CI 1.765-9.547, p=0.001).
CONCLUSION: PITX2 is another potential prognostic marker in breast carcinoma adding significant information to established prognostic factors of ER and PR. The expression of PITX2 together with PR may carry a very good prognosis.
MATERIALS AND METHODS: Patients who were treated with first line palliative chemotherapy for de novo MBC from 2002-2011 in UMMC were identified from the UMMC Breast Cancer Registry. Information collected included patient demographics, histopathological features, treatment received, including the different chemotherapy regimens, and presence of FN and TRD. FN was defined as an oral temperature >38.5° or two consecutive readings of >38.0° for 2 hours and an absolute neutrophil count <0.5x109/L, or expected to fall below 0.5x109/L (de Naurois et al, 2010). TRD was defined as death occurring during or within 30 days of the last chemotherapy treatment, as a consequence of the chemotherapy treatment. Statistical analysis was performed using the SPSS version 18.0 software. Survival probabilities were estimated using the Kaplan-Meier method and differences in survival compared using log-rank test.
RESULTS: Between 1st January 2002 and 31st December 2011, 424 patients with MBC were treated in UMMC. A total of 186 out of 221 patients with de novo MBC who received first line palliative chemotherapy were analyzed. The mean age of patients in this study was 49.5 years (range 24 to 74 years). Biologically, ER status was negative in 54.4% of patients and Her-2 status was positive in 31.1%. A 5-flourouracil, epirubicin and cyclophosphamide (FEC) chemotherapy regimen was chosen for 86.6% of the cases. Most patients had multiple metastatic sites (58.6%). The main result of this study showed a FN rate of 5.9% and TRD rate of 3.2%. The median survival (MS) for the entire cohort was 19 months. For those with multiple metastatic sites, liver only, lung only, bone only and brain only metastatic sites, the MS was 18, 24, 19, 24 and 8 months respectively (p-value= 0.319).
CONCLUSIONS: In conclusion, we surmise that FEC is a safe regimen with acceptable FN and TRD rates for de novo MBC.