Search results for: women with breast cancer

Authors: Farah Naja, Romy Abi Fadel, Yasmin Aridi, Aya Zarif, Dania Hariri, Mohammad Alameddine, Anas Mugharbel, Maya Khalil, Zeina Nahleh, Arafat Tfayli

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The objective of this study is to assess the prevalence and determinants of CAM use among breast cancer patients in Beirut, Lebanon. A secondary objective is to evaluate the association between CAM use and quality of life (QOL). A cross-sectional survey was conducted on 180 breast cancer patients recruited from two major referral centers in Beirut. In a face to face interview, participants completed a questionnaire comprised of three sections: socio-demographic and lifestyle characteristics, breast cancer condition, and CAM use. The assessment of QOL was carried using the FACT-B Arabic version. Prevalence of CAM use since diagnosis was 40%. CAM use was negatively associated with age, treatment at a philanthropic hospital and positively associated with having an advanced stage of disease. The most commonly used CAM was ‘Special food’ followed by ‘Herbal teas’. Only 4% of CAM users cited health care professionals as influencing their choice of CAM. One in four patients disclosed CAM use to their treating physician. There was no significant association between CAM use and QOL. The use of CAM therapies among breast cancer patients is prevalent in Lebanon. Efforts should be dedicated at educating physicians to discuss CAM use with their patients and advising patients to disclose of their use with their physicians.

Keywords: breast cancer, complementary and aLternative medicine, Lebanon, quality of life

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Authors: Mahdi Bazarganigilani

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Computer-aided diagnosis (CAD) systems can play crucial roles in diagnosing crucial diseases such as breast cancer at the earliest. In this paper, a CAD system for the diagnosis of breast cancer was introduced and evaluated. This CAD system was developed by using spatio-temporal analysis of data on a set of consecutive thermographic images by employing wavelet transformation. By using this analysis, a very accurate machine learning model using random forest was obtained. The final results showed a promising accuracy of 91% in terms of the F1 measure indicator among 200 patients' sample data. The CAD system was further extended to obtain a detailed analysis of the effect of smaller sub-areas of each breast on the occurrence of cancer.

Keywords: computer-aided diagnosis systems, thermographic analysis, spatio-temporal analysis, image processing, machine learning

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Authors: Wooseok Byon, Eunyoung Kim, Junseong Kwon, Byung Joo Song, Chan Heun Park

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Purpose: 18F Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) is a noninvasive imaging modality that can identify nodal metastases in women with primary breast cancer. The aim of this study was to compare the accuracy of FDG-PET with MRI and sonography scanning to determine axillary lymph node status in patients with breast cancer undergoing sentinel lymph node biopsy or axillary lymph node dissection. Patients and Methods: Between January and December 2012, ninety-nine patients with breast cancer and clinically negative axillary nodes were evaluated. All patients underwent FDG-PET, MRI, ultrasound followed by sentinel lymph node biopsy (SLNB) or axillary lymph node dissection (ALND). Results: Using axillary lymph node assessment as the gold standard, the sensitivity and specificity of FDG-PET were 51.4% (95% CI, 41.3% to 65.6%) and 92.2% (95% CI, 82.7% to 97.4%) respectively. The sensitivity and specificity of MRI and ultrasound were 57.1% (95% CI, 39.4% to 73.7%), 67.2% (95% CI, 54.3% to 78.4%) and 42.86% (95% CI, 26.3% to 60.7%), 92.2% (95% CI, 82.7% to 97.4%). Stratification according to hormone receptor status showed an increase in specificity when negative (FDG-PET: 42.3% to 77.8%, MRI 50% to 77.8%, ultrasound 34.6% to 66.7%). Also, positive HER2 status was associated with an increase in specificity (FDG-PET: 42.9% to 85.7%, MRI 50% to 85.7%, ultrasound 35.7% to 71.4%). Conclusions: The sensitivity and specificity of FDG-PET compared with MRI and ultrasound was high. However, FDG-PET is not sufficiently accurate to appropriately identify lymph node metastases. This study suggests that FDG-PET scanning cannot replace histologic staging in early-stage breast cancer, but might have a role in evaluating axillary lymph node status in hormone receptor negative or HER-2 overexpressing subtypes.

Keywords: axillary lymph node metastasis, FDG-PET, MRI, ultrasound

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Authors: Sally Shepherd, Craig Murphy

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Introduction: The uterus or cervix are unusual locations as metastatic sites for cancers. It is further unusual for it to be a site of metastasis, whilst the primary malignancy remains occult. Case Report: A 63-year-old female with three months of altered bowel habits underwent a CT scan of the abdomen and pelvis, revealing a bulky uterus and left ovary, nonspecific colonic thickening, and diffuse peritoneal changes. She underwent colposcopy, which revealed a large endocervical polyp that was excised, revealing strongly hormone-positive metastatic invasive lobular breast cancer. She subsequently underwent a PET scan, which showed moderately diffuse activity in the cervix and left adnexa. Breast examination was unremarkable, and screening mammography, ultrasound, and MRI of the breast did not identify any lesions. Her blood tests revealed a Ca 15-3 of 934, CA-125 of 220, and CEA of 27. She was commenced on letrozole and ribociclib with an improvement in her symptoms. Conclusion: It is rare for occult breast cancer to be established and diagnosed by pelvic imaging and biopsy. Suspicion of uterine or cervical metastasis should be heightened in patients with an active or past history of breast cancer.

Keywords: occult breast cancer, cervical metastasis, invasive lobular carcinoma, metastasis

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Authors: Jiwan Kumar, Pooja, Sandeep Negi, Anjum Rouf, Amit Kumar, Naveen Lakra

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In modern times where, health issues are increasing day by day, breast cancer is also one of them, which is very crucial and really important to find in the early stages. Doctors can use this model in order to tell their patients whether a cancer is not harmful (benign) or harmful (malignant). We have used the knowledge of machine learning in order to produce the model. we have used algorithms like Logistic Regression, Random forest, support Vector Classifier, Bayesian Network and Radial Basis Function. We tried to use the data of crucial parts and show them the results in pictures in order to make it easier for doctors. By doing this, we're making ML better at finding breast cancer, which can lead to saving more lives and better health care.

Keywords: Bayesian network, radial basis function, ensemble learning, understandable, data making better, random forest, logistic regression, breast cancer

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Authors: Ika Wulansari, Yati Afiyanti, Indang Trihandini

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Sleeping disorder experienced by patients with breast cancer can affect the physical, mental, health, and well-being. This study examines the effect of progressive muscle relaxation training and sleep hygiene education to change sleep quality scores of the patient with breast cancer. The study design using quasi-experiment with pre-post test within the control group, involving 62 breast cancer patients using consecutive sampling method in Jakarta. Statistical test results with independent t-test showed a significant difference in score of sleep quality between in intervention group and the control group (6,66±3,815; 9,30±3,334, p-value = 0,005). Progressive muscle relaxation exercise and sleep hygiene education proven to be affective to change the patients sleeping quality, so that it can be an alternative therapeutic option to overcome sleeping disorders.

Keywords: sleeping disorders, breast cancer, progressive muscle relaxation, sleep hygiene education

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Authors: Jing Chen, Jun-E Liu, Peng Yue

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Objective: The objective of this study was to develop a psychological adjustment and adaptation status scale for breast cancer survivors, and to examine the reliability and validity of the scale. Method: 37 breast cancer survivors were recruited in qualitative research; a five-subject theoretical framework and an item pool of 150 items of the scale were derived from the interview data. In order to evaluate and select items and reach a preliminary validity and reliability for the original scale, the suggestions of study group members, experts and breast cancer survivors were taken, and statistical methods were used step by step in a sample of 457 breast cancer survivors. Results: An original 24-item scale was developed. The five dimensions “domestic affections”, “interpersonal relationship”, “attitude of life”, “health awareness”, “self-control/self-efficacy” explained 58.053% of the total variance. The content validity was assessed by experts, the CVI was 0.92. The construct validity was examined in a sample of 264 breast cancer survivors. The fitting indexes of confirmatory factor analysis (CFA) showed good fitting of the five dimensions model. The criterion-related validity of the total scale with PTGI was satisfactory (r=0.564, p<0.001). The internal consistency reliability and test-retest reliability were tested. Cronbach’s alpha value (0.911) showed a good internal consistency reliability, and the intraclass correlation coefficient (ICC=0.925, p<0.001) showed a satisfactory test-retest reliability. Conclusions: The scale was brief and easy to understand, was suitable for breast cancer patients whose physical strength and energy were limited.

Keywords: breast cancer survivors, rehabilitation, psychological adaption and adjustment, development of scale

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Authors: Leila Anoosheh

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Aim: The aim of this study was to assess The effects of aerobic training on microRNA let-7a expression and levels of tumor tissue IL-6 in mice with breast cancer. Method: Twenty BALB/c c mice (4-5 weeks,17 gr mass) were cancerous by injection of estrogen-dependent receptor breast cancer cells MC4-L2 and divided into two groups: tumor-training(TT) and tumor-control(TC) group. Then TT group completed aerobic training for 6 weeks, 5 days per week (14-18 m/min). After tumor emersion, tumor width and length were measured by digital caliper every week. 48 hours after the last exercise subjects were killed. Tissue sampling were collected and stored in -70ᵒ. Tumor tissue was homogenized and let-7a expression and IL-6 levels were accounted with Real time-PCR and ELISA Kit respectively. Statistical analysis of let-7a was conducted by the REST software. Repeated measures and independent tests were used to assess tumor size and IL-6, respectively. Results: Tumor size and IL-6 levels were significantly decreased in TT group compare with TC group (p<0.05). microRNA let-7a was increased significantly in TT against control group respectively (p=0/000). Conclusion: Reduction in tumor size, followed by aerobic exercise can be attributed to the loss of inflammatory factors such as IL-6; It seems that regarding to up regulation effects of aerobic exercise training on let-7a and down regulation effects of that on IL-6 in mice with breast cancer, This type of training can be used as adjuvant therapy in conjunction with other therapies for breast cancer.

Keywords: breast cancer, aerobic training, microRNA let-7a, IL-6

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Authors: Siddhant Rao

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Studies estimate that there will be 266,120 new cases of invasive breast cancer and 40,920 breast cancer induced deaths in the year of 2018 alone. Despite the pervasiveness of this affliction, the current process to obtain an accurate breast cancer prognosis is tedious and time consuming. It usually requires a trained pathologist to manually examine histopathological images and identify the features that characterize various cancer severity levels. We propose MITOS-RCNN: a region based convolutional neural network (RCNN) geared for small object detection to accurately grade one of the three factors that characterize tumor belligerence described by the Nottingham Grading System: mitotic count. Other computational approaches to mitotic figure counting and detection do not demonstrate ample recall or precision to be clinically viable. Our models outperformed all previous participants in the ICPR 2012 challenge, the AMIDA 2013 challenge and the MITOS-ATYPIA-14 challenge along with recently published works. Our model achieved an F- measure score of 0.955, a 6.11% improvement in accuracy from the most accurate of the previously proposed models.

Keywords: breast cancer, mitotic count, machine learning, convolutional neural networks

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Authors: Marta E. Hernandez-Caballero, Veronica Borgonio-Cuadra, Antonio Miranda-Duarte, Xochitl Rojas-Toledo, Normand Garcia-Hernandez, Maura Cardenas-Garcia, Teresa Abad-Camacho

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Breast cancer (BC) is the most common tumor in women over the world. DNA methylation is an epigenetic modification critical in CpG sites, aberrant methylation of CpG islands in promoters is a hallmark of cancer. So, gene expression can be regulated by alterations in DNA methylation. In cell lines DACT2 gene reduces the growth and migration of tumor cells by its participation in the suppression of TGFb/SMAD2/3. PHF20L1 is involved in histone acetylation therefore, it regulates transcription. Our aim was to analyze the methylation status of the DACT2 and PHF20L1 promoter regions in tumoral and healthy mammary tissue from women with BC in different progression states. The study included 77 patients from Centro Medico Nacional La Raza in Mexico City. After identifying a CpG island in DACT2 and PHF20L1 promoters, DNA methylation status was analyzed through sodium bisulfite with subsequent amplification using methylation-specific PCR. Results revealed no changes in methylation status of PHF20L1 and cancer stages (II y III) or in comparison to healthy tissues, it was demethylated. DACT2 promoter methylation was no significant between tumoral stages (II, P = 0.37; III, P = 0.17) or with healthy tissue. Previous data reported DACT2 methylated in nasopharyngeal carcinoma but in this study promoter methylation was not observed. PHF20L1 protein contains N-terminal Tudor and C-terminal plant homeodomain domains, it has been suggested that can stabilize DNMT1 regulating DNA methylation, therefore, was associated with poor prognostic in BC. We found no evidence of methylation in patients and controls in PHF20L1 promoter, so its association with BC may have no direct relation with promoter methylation. More studies including other methylation sites in these genes in BC are necessary.

Keywords: bisulfite conversion, breast cancer, DACT2, DNA methylation, PHF20L1, tumoral status

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Authors: S. Sushma, S. Balasubramanian, K. C. Latha, R. Sridhar

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Structural texture measures are used to address the aspect of breast cancer risk assessment in screening mammograms. The current study investigates whether texture properties characterized by local Fractal Dimension (FD) and lacunarity contribute to assess breast cancer risk. Fractal Dimension represents the complexity while the lacunarity characterize the gap of a fractal dimension. In this paper, we present our result confirming that the lacunarity value resulted in algorithm using mammogram images states that level of lacunarity will be low when the Fractal Dimension value will be high.

Keywords: breast cancer, fractal dimension, image analysis, lacunarity, mammogram

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Authors: Jean Paul M. Milambo

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Purpose: Aromatase inhibitors (AIs) are indicated in the treatment of hormone-receptive breast cancer in postmenopausal women in various settings. Studies have shown cardiovascular events in some developed countries. To date the data is sparce for evidence-based recommendations in African clinical settings due to lack of cancer registries, capacity building and surveillance systems. Therefore, this study was conducted to assess the feasibility of HyBeacon® probe genotyping adjunctive to standard care for timely prediction and diagnosis of Aromatase inhibitors (AIs) associated adverse events in breast cancer survivors in Africa. Methods: Cross sectional study was conducted to assess the knowledge of POCT among six African countries using online survey and telephonically contacted. Incremental cost effectiveness ratio (ICER) was calculated, using diagnostic accuracy study. This was based on mathematical modeling. Results: One hundred twenty-six participants were considered for analysis (mean age = 61 years; SD = 7.11 years; 95%CI: 60-62 years). Comparison of genotyping from HyBeacon® probe technology to Sanger sequencing showed that sensitivity was reported at 99% (95% CI: 94.55% to 99.97%), specificity at 89.44% (95% CI: 87.25 to 91.38%), PPV at 51% (95%: 43.77 to 58.26%), and NPV at 99.88% (95% CI: 99.31 to 100.00%). Based on the mathematical model, the assumptions revealed that ICER was R7 044.55. Conclusion: POCT using HyBeacon® probe genotyping for AI-associated adverse events maybe cost effective in many African clinical settings. Integration of preventive measures for early detection and prevention guided by different subtype of breast cancer diagnosis with specific clinical, biomedical and genetic screenings may improve cancer survivorship. Feasibility of POCT was demonstrated but the implementation could be achieved by improving the integration of POCT within primary health cares, referral cancer hospitals with capacity building activities at different level of health systems. This finding is pertinent for a future envisioned implementation and global scale-up of POCT-based initiative as part of risk communication strategies with clear management pathways.

Keywords: breast cancer, diagnosis, point of care, South Africa, aromatase inhibitors

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Authors: A. D. Zikiryahodjaev, L. V. Bolotina, A. S. Sukhotko

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Purpose. To evaluate the expediency and timeliness of performance of surgical treatment as a component of multi-therapy treatment of patients with stage IV breast cancers. Materials and Methods. This investigation comparatively analyzed the results of complex treatment with or without surgery in patients with metastatic breast cancer. We analyzed retrospectively treatment experience of 196 patients with generalized breast cancer in the department of oncology and breast reconstructive surgery of P.A. Herzen Moscow Cancer Research Institute from 2000 to 2012. The average age was (58±1,1) years. Invasive ductul carcinoma was verified in128 patients (65,3%), invasive lobular carcinoma-33 (16,8%), complex form - 19 (9,7%). Complex palliative care involving drug and radiation therapies was performed in two patient groups. The first group includes 124 patients who underwent surgical intervention as complex treatment, the second group includes 72 patients with only medical therapy. Standard systemic therapy was given to all patients. Results. Overall, 3-and 5-year survival in fist group was 43,8 and 21%, in second - 15,1 and 9,3% respectively [p=0,00002 log-rank]. Median survival in patients with surgical treatment composed 32 months, in patients with only systemic therapy-21. The factors having influencing an influence on the prognosis and the quality of life outcomes for of patients with generalized breast cancer were are also studied: hormone-dependent tumor, Her2/neu hyper-expression, reproductive function status (age, menopause existence). Conclusion.Removing primary breast tumor in patients with generalized breast cancer improve long-term outcomes. Three- and five-year survival increased by 28,7 and 16,3% respectively, and median survival–for 11 months. These patients may benefit from resection of the breast tumor. One explanation for the effect of this resection is that reducing the tumor load influences metastatic growth.

Keywords: breast cancer, combination therapy, factors of prognosis, primary tumor

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Authors: Alisher Ibragimov, Sofya Senotrusova, Aleksandra Beliaeva, Egor Ushakov, Yuri Markin

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Mammography plays a critical role in screening for breast cancer in women, and artificial intelligence has enabled the automatic detection of diseases in medical images. Many of the current techniques used for mammogram analysis focus on a single view (mediolateral or craniocaudal view), while in clinical practice, radiologists consider multiple views of mammograms from both breasts to make a correct decision. Consequently, computer-aided diagnosis (CAD) systems could benefit from incorporating information gathered from multiple views. In this study, the introduce a method based on a Siamese neural network (SNN) model that simultaneously analyzes mammographic images from tri-view: bilateral and ipsilateral. In this way, when a decision is made on a single image of one breast, attention is also paid to two other images – a view of the same breast in a different projection and an image of the other breast as well. Consequently, the algorithm closely mimics the radiologist's practice of paying attention to the entire examination of a patient rather than to a single image. Additionally, to the best of our knowledge, this research represents the first experiments conducted using the recently released Vietnamese dataset of digital mammography (VinDr-Mammo). On an independent test set of images from this dataset, the best model achieved an AUC of 0.87 per image. Therefore, this suggests that there is a valuable automated second opinion in the interpretation of mammograms and breast cancer diagnosis, which in the future may help to alleviate the burden on radiologists and serve as an additional layer of verification.

Keywords: breast cancer, computer-aided diagnosis, deep learning, multi-view mammogram, siamese neural network

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Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

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Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: breast cancer, diagnosis, machine learning, biomarker classification, neural network

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Authors: Wooseok Byon, Eunyoung Kim, Junseong Kwon, Byung Joo Song, Chan Heun Park

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Background/Purpose: Previous preclinical and clinical data suggest that increased lymphocytic infiltration would be associated with good prognosis and benefit from immunogenic chemotherapy especially in triple-negative breast cancer (TNBC). We investigated a single-center experience of TNBC and relationship with lymphocytic infiltration. Methods: From January 2004 to December 2012, at the Department of Surgery, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, we retrospectively reviewed 897 breast cancer patients-clinical outcomes, clinicopathological characteristics, breast cancer subtypes. And we reviewed lymphocytic infiltration of TNBC specimens by two pathologists. Statistical analysis of risk factors associated with recurrence was performed. Results: A total of 897 patients, 76 were TNBC (8.47%). Mean age of TNBC patients were 50.95 (SD10.42) years, mean follow-up periods was 40.06 months. We reviewed 49 slides, and there were 8 recurrent breast cancer patients (16.32%), and 4 patients were expired (8.16%). There were 9 lymphocytic predominant breast cancers (LPBC)-carcinomas with either intratumoral lymphocytes in >60% of tumor cell nests. 1 patient of LPBC was recurred and 8 were not. In multivariate logistic regression, the odds ratio of lymphocytic infiltration was 0.59 (p=0.643). Conclusion: In a single-center experience of TNBC, the lymphocytic infiltration in tumor cell nest might be a good trend on the prognosis but there was not statistically significant.

Keywords: tumor-infiltrating lymphocytes, triple negative breast cancer, medical and health sciences

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Authors: Dina Fatmawati, Sofia Mubarika, Mae Sri Wahyuningsih

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Chemotherapy for breast cancer is largely ineffective, but innovative combinations of chemotherapeutic agents and natural compounds represent a promising strategy. In our previous study, the combination of Doxorubicin (Dox) and ethanolic extract of Dioscorea esculenta tuber ((EED) was found to have a synergistic effect on T47D human breast cancer cell line. In this study, we investigated the apoptotic effect of the combination on T47D human breast cancer cells and normal fibroblasts cell line and its effects on the expression of Caspase-3 and cleaved poly (ADP-Ribose) Polymerase-1 (cPARP-1) protein. T47D cell lines and fibroblasts cells were treated with the combination of Dox and EED. Apoptotic effect of the combination was determined using flow cytrometry assay. Protein expressions were determined by immunocytochemistry staining. The percentage of apoptotic cells were significantly higher in T47D cell lines (75%) than that of in fibroblast cells (23%). The expression of Caspase 3 (84.53%) and cPARP-1 (83.36%) were significantly higher in the cancer cell lines than those of normal cells. These results indicate that the combination of doxorubicin and Dioscorea esculenta is a promising candidate for the treatment of breast cancer cells.

Keywords: Dioscorea esculenta, Doxorubicin, apoptosis, immunocytochemistry, cancer cells

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Authors: Mai Ashraf Talaat

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Objectives: The aim of this review article is to assess the success of dental implants in breast cancer patients receiving bisphosphonate therapy and to evaluate the risk of developing bisphosphonate-related osteonecrosis of the jaw following dental implant surgery. Materials and Methods: A thorough search was conducted, with no time or language restriction, using: PubMed, PubMed Central, Web of Science, and ResearchGate electronic databases. Medical Subject Headings (MeSH) terms such as “bisphosphonate”, “dental implant”, “bisphosphonate-related osteonecrosis of the jaw (BRONJ)”, “osteonecrosis”, “breast cancer, MRONJ”, and their related entry terms were used. Eligibility criteria included studies and clinical trials that evaluated the impact of bisphosphonates on dental implants. Conclusion: Breast cancer patients undergoing bisphosphonate therapy may receive dental implants. However, the risk of developing BRONJ and implant failure is high. Risk factors such as the type of BP received, the route of administration, and the length of treatment prior to surgery should be considered. More randomized controlled trials with long-term follow-ups are needed to draw more evidence-based conclusions.

Keywords: dental implants, breast cancer, bisphosphonates, osteonecrosis, bisphosphonate-related osteonecrosis of the jaw

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Authors: Douglas Dunn, Ricahrd Walton, Matthew Warner-Smith, Chirag Mistry, Kan Ren, David Roder

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Introduction: Breast density is a risk factor for breast cancer, both due to increased fibro glandular tissue that can harbor malignancy and the masking of lesions on mammography. Therefore, evaluation of breast density measurement is useful for risk stratification on an individual and population level. This study investigates the performance of Lunit INSIGHT MMG for automated breast density measurement. We analyze the reliability of Lunit compared to breast radiologists, explore density variations across the BreastScreen NSW population, and examine the impact of breast implants on density measurements. Methods: 15,518 mammograms were utilized for a comparative analysis of intra- and inter-reader reliability between Lunit INSIGHT MMG and breast radiologists. Subsequently, Lunit was used to evaluate 624,113 mammograms for investigation of density variations according to age and birth country, providing insights into diverse population subgroups. Finally, we compared breast density in 4,047 clients with implants to clients without implants, controlling for age and birth country. Results: Inter-reader variability between Lunit and Breast Radiologists weighted kappa coefficient was 0.72 (95%CI 0.71-0.73). Highest breast densities were seen in women with a North-East Asia background, whilst those of Aboriginal background had the lowest density. Across all backgrounds, density was demonstrated to reduce with age, though at different rates according to country of birth. Clients with implants had higher density relative to the age-matched no-implant strata. Conclusion: Lunit INSIGHT MMG demonstrates reasonable inter- and intra-observer reliability for automated breast density measurement. The scale of this study is significantly larger than any previous study assessing breast density due to the ability to process large volumes of data using AI. As a result, it provides valuable insights into population-level density variations. Our findings highlight the influence of age, birth country, and breast implants on density, emphasizing the need for personalized risk assessment and screening approaches. The large-scale and diverse nature of this study enhances the generalisability of our results, offering valuable information for breast cancer screening programs internationally.

Keywords: breast cancer, screening, breast density, artificial intelligence, mammography

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Authors: Chia-Hui Chen, Chien-Kuo Wang

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Background: Full field digital mammography (FFDM) is widely used in diagnosis of breast cancer. Digital breast tomosynthesis (DBT) has recently been introduced into the clinic and is being used for screening for breast cancer in the general population. Hence, the radiation dose delivered to the patients involved in an imaging protocol is of utmost concern. Aim: To compare the surface radiation dose (ESD) of digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) by using breast phantoms. Method: We analyzed the average entrance surface dose (ESD) of FFDM and DBT by using breast phantoms. Optically Stimulated luminescent Dosimeters (OSLD) were placed in a tissue-equivalent Breast phantom at difference sites of interest. Absorbed dose measurements were obtained after digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) exposures. Results: An automatic exposure control (AEC) is proposed for surface dose measurement during DBT and FFDM. The mean ESD values for DBT and FFDM were 6.37 mGy and 3.51mGy, respectively. Using of OSLD measured for surface dose during DBT and FFDM. There were 19.87 mGy and 11.36 mGy, respectively. The surface exposure dose of DBT could possibly be increased by two times with FFDM. Conclusion: The radiation dose from DBT was higher than that of FFDM and the difference in dose between AEC and OSLD measurements at phantom surface.

Keywords: full-field digital mammography, digital breast tomosynthesis, optically stimulated luminescent dosimeters, surface dose

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Authors: Beom-Seok Ko, Yoo-Seok Kim, Woo-Sung Lim, Ku-Sang Kim, Hyun-Ah Kim, Jin-Sun Lee, An-Bok Lee, Jin-Gu Bong, Tae-Hyun Kim, Sei-Hyun Ahn

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Background: Breast conserving surgery (BCS) followed by radiation therapy is today standard therapy for early breast cancer. It is safe therapeutic procedure in early breast cancers, because it provides the same level of overall survival as mastectomy. There are a number of different types of incisions used to BCS. Avoiding scars on the breast is women’s desire. Numerous minimal approaches have evolved due to this concern. Periareolar incision is often used when the small tumor relatively close to the nipple. But periareolar incision has a disadvantages include limited exposure of the surgical field. In plastic surgery, various methods such as zigzag incisions have been recommended to achieve satisfactory esthetic results. Periareolar zigzag incision has the advantage of not only good surgical field but also contributed to better surgical scars. The purpose of this study was to evaluate the oncological safety of procedures by studying the status of the surgical margins of the excised tumor specimen and reduces the need for further surgery. Methods: Between January 2016 and September 2016, 148 women with breast cancer underwent BCS or mastectomy by the same surgeon in ASAN medical center. Patients with exclusion criteria were excluded from this study if they had a bilateral breast cancer or underwent resection of the other tumors or taken axillary dissection or performed other incision methods. Periareolar zigzag incision was performed and excision margins of the specimen were identified frozen sections and paraffin-embedded or permanent sections in all patients in this study. We retrospectively analyzed tumor characteristics, the operative time, size of specimen, the distance from the tumor to nipple. Results: A total of 148 patients were reviewed, 72 included in the final analysis, 76 excluded. The mean age of the patients was 52.6 (range 25-19 years), median tumor size was 1.6 cm (range, 0.2-8.8), median tumor distance from the nipple was 4.0 cm (range, 1.0-9.0), median excised specimen sized was 5.1 cm (range, 2.8-15.0), median operation time was 70.0 minute (range, 39-138). All patients were discharged with no sign of infection or skin necrosis. Free resection margin was confirmed by frozen biopsy and permanent biopsy in all samples. There were no patients underwent reoperation. Conclusions: We suggest that periareolar zigzag incision can provide a good surgical field to remove a relatively large tumor and may provide cosmetically good outcomes.

Keywords: periareolar zigzag incision, breast conserving surgery, breast cancer, resection margin

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Authors: Lakmali Anthony, Madeline Gillies

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Purpose: Decreasing mortality has led to increased focus on patient-reported outcomes such as quality of life (QoL) in breast cancer. Breast cancer patients often have decreased QoL even after treatment is complete. This systematic review of the literature aims to identify psychosocial factors associated with decreased QoL in post-treatment breast cancer patients. Methodology: This systematic review was performed in accordance with the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses recommendations. The search was conducted in MEDLINE, EMBASE, and PsychINFO using MeSH headings. The two authors screened studies for relevance and extracted data. Results: Seventeen studies were identified, including 3,150 total participants (mean = 197) with a mean age of 51.9 years. There was substantial heterogeneity in measures of QoL. The most common was the European Organisation for Research and Treatment of Cancer QLQ-C30 (n=7, 41.1%). Most studies (n=12, 70.5%) found that emotional distress correlated with poor QoL, while 3 found no significant association. The most common measure of emotional distress was the Hospital Anxiety and Depression Scale (n=12, 70.5%). Other psychosocial factors associated with QoL were unmet needs, problematic social support, and negative affect. Clinicopathologic determinants included mastectomy without reconstruction, stage IV disease, and adjuvant chemotherapy. Conclusion: This systematic review provides a summary of the psychosocial determinants of poor QoL in post-treatment breast cancer patients, as well as the most commonly reported measures of these. An understanding of these potentially modifiable determinants of poor outcome is pivotal to the provision of quality, patient-centred care in surgical oncology.

Keywords: breast cancer, quality of life, psychosocial determinants, cancer surgery

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Authors: Nouf A. Aldarmahi, Nesrin I. Tarbiah, Nuha A. Alkhattabi, Huda F. Alshaibi

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Nigella sativa which is known as dark cumin is a well-known example for a widely applicable herbal medicine. Nigella sativa can be effective in a variety of diseases such as hypertension, diabetes, bronchitis, gastrointestinal upset, and cancer. The anticancer effect of Nigella sativa appeared to be mediated by immune-modulatory effect through stimulating human natural killer (NK) cells. This is a type of lymphocytes which is part of the innate immunity, also known as the first line of defense in the body against pathogens. This study investigated the effect of thymoquinone as a major component of Nigella sativa on the molecular cytotoxic pathway of NK cell and the role of thymoquinone therapeutic effect on NK cells. NK cells were cultured with breast tumor cells in different ways and cultured media was collected and the concentration of perforin, granzyme B and interferon-α were measured by ELISA. The cytotoxic effect of NK cells on breast tumor cells was enhanced in the presence of thymoquinone, with increased activity of perforin in NK cells. This improved anticancer effect of thymoquinone on breast cancer cells.

Keywords: breast cancer, cancer cells, natural killer cells, thymoquinone

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Authors: Shradha Parsekar, Suma Nair, Ajay Bailey, Binu V. S.

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Background: Concealing of cancer-related information is seen in many low-and-middle-income countries and may be associated with multiple factors. Comparatively, there is lack of information about, how breast cancers diagnosed women disclose cancer-related information to their social contacts and vice versa. To get more insights on the participant’s experience, opinions, expectations, and attitudes, a qualitative study is a suitable approach. Therefore, this study involving in-depth interviews was planned to lessen this gap. Methods: Interviews were conducted separately among breast cancer patients and their caregivers with semi-structured qualitative interview guide. Purposive and convenient sampling was being used to recruit patients and caregivers, respectively. Ethical clearance and permission from the tertiary hospital were obtained and participants were selected from the Udupi district, Karnataka, India. After obtaining a list of breast cancer diagnosed cases, participants were contacted in person and their willingness to take part in the study was taken. About 39 caregivers and 35 patients belonging to different breast cancer stages were recruited. Interviews were recorded with prior permission. Data was managed by Atlas.ti 8 software. The recordings were transcribed, translated and coded in two cycles. Most of the patients belonged to stage II and III cancer. Codes were grouped together into to whom breast cancer status was concealed to and underneath reason for the same. Main findings: followings are the codes and code families which emerged from the data. 1) Concealing the breast cancer status from social contacts other than close family members (such as extended family, neighbor and friends). Participants perceived the reasons as, a) to avoid questions which people probe (which doesn’t have answers), b) to avoid people paying courtesy visit (to inquire about the health as it is Indian culture to visit the sick person) making it inconvenient for patient and caregivers have to offer something and talk to them, c) to avoid people getting shocked (react as if cancer is different from other diseases) or getting emotional/sad, or getting fear of death d) to avoid getting negative suggestion or talking anything in front of patient as it may affect patient negatively, e) to avoid getting stigmatized, f) to avoid getting obstacle in child’s marriage. 2) Participant concealed the breast cancer status of young children as they perceived that it may a) affect studies, b) affect emotionally, c) children may get scared. 3) Concealing the breast cancer status from patients as the caregivers perceived that they have fear of a) worsening patient’s health, b) patient getting tensed, c) patient getting shocked, and d) patient getting scared. However, some participants stressed important in disclosing the cancer status to social contact/patient to make the people aware of the disease. Conclusion: The news of breast cancer spreads like electricity in the wire, therefore, patient or family avoid it for many reasons. Although, globally, due to physicians’ ethical obligations, there is an inclination towards more disclosure of cancer diagnosis and status of prognosis to the patient. However, it is an ongoing argument whether patient/social contacts should know the status especially in a country like India.

Keywords: breast cancer, concealing cancer status, India, qualitative study

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Authors: Janet Wing-Chong Wai, Alex Chiu-Wing Lee, Hailey Hoi-Ching Tsang, Jeffrey Chiu, Kwok-Wing Tang

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Background: Mammography has limited sensitivity and specificity though it is the primary imaging technique for detection of early breast cancer. Ultrasound imaging and contrast-enhanced MRI are useful adjunct tools to mammography. The advantage of breast MRI is high sensitivity for invasive breast cancer. Therefore, indications for and use of breast magnetic resonance imaging have increased over the past decade. Objectives: 1. Cases demonstration on different indications for breast MR imaging. 2. To review of the common artifacts and pitfalls in breast MR imaging. Materials and Methods: This is a retrospective study including all patients underwent dynamic contrast-enhanced breast MRI examination in our centre, performed from Jan 2011 to Dec 2017. The clinical data and radiological images were retrieved from the EPR (electronic patient record), RIS (Radiology Information System) and PACS (Picture Archiving and Communication System). Results and Discussion: Cases including (1) Screening of the contralateral breast in patient with a new breast malignancy (2) Breast augmentation with free injection of unknown foreign materials (3) Finding of axillary adenopathy with an unknown site of primary malignancy (4) Neo-adjuvant chemotherapy: before, during, and after chemotherapy to evaluate treatment response and extent of residual disease prior to operation. Relevant images will be included and illustrated in the presentation. As with other types of MR imaging, there are different artifacts and pitfalls that can potentially limit interpretation of the images. Because of the coils and software specific to breast MR imaging, there are some other technical considerations that are unique to MR imaging of breast regions. Case demonstration images will be available in presentation. Conclusion: Breast MR imaging is a highly sensitive and reasonably specific method for the detection of breast cancer. Adherent to appropriate clinical indications and technical optimization are crucial for achieving satisfactory images for interpretation.

Keywords: MRI, breast, clinical, cancer

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Authors: John Joseph S. Martis, Rohanchandra R. Gatty, Aaron Jose Fernandes, Rahul P. Nambiar

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Introduction: Surgery for breast cancer is either mastectomy or breast conservation surgery. The most commonly used incision for modified radical mastectomy is the transverse Stewart incision. But this incision may have the disadvantage of causing disparity between the closure lines of superior and inferior skin flaps in mastectomy and can cause overhanging of soft tissue below and behind the axilla. The curvizigzag incision, on principle, may help in this regard and can prevent scar migration beyond the anterior axillary line. This study aims to compare the two incisions in this regard. Methods: 100 patients with cancer of breast were included in the study after satisfying inclusion and exclusion criteria. They underwent surgery at Father Muller Medical College, Mangalore, India, between November 2019 to September 2021. The patients were divided into two groups. Group A patients were subjected to modified radical mastectomy with curvizigzag incision and group B patients with transverse Stewart incision. Results: Seroma on postoperative day1, day 2 was 0% in both the groups. Seroma on postoperative day 30 was present in 14% of patients in group B. 60% of patients in group B had sag of soft tissue below and behind the axilla, and none of the patients in group A had this problem. In 64% of the patients in group B, the incision crossed the anterior axillary fold, 64% of the patients in group B had tension in the incision site while approximation of the skin flaps. Conclusion: Curvizigzag incision is statistically better with lesser complications when compared to the transverse Stewart incision for modified radical mastectomy for carcinoma breast.

Keywords: breast cancer, curvizigzag incision, transverse Stewart incision, seroma, modified radical mastectomy

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Authors: R. Sonda, F. Pellini, A. Invento, S. Mirandola, F. Riolfatti, D. Grigolato, G. P. Pollini

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The purpose of study is to assess utility of 18F-FDG PET/CT in patients with breast heteroplasia and possibility of changing the surgery/therapeutic treatment. Among these "under fourty-five" candidated for NAC, the prevalence of change in therapeutic approach in comparison with first and second level exams has been: 43.75%, while by 22% among the "over forty-five". The surgical timing according to first-level exams have been deferred in 31.46% cases; PET/CT has led to a change in therapeutic treatment of 48.31% on the previous given; then the addition of MRI has led to a similar variation. For all the total patients, the prevalent choice was found to the debulking approach by increasing from a prevalence of 12.92% to 15.17%, resulting in a reduction of conservative one.The present study set itself the objective to demonstrate how the FDG PET/CT could improve on breast imaging according to a more appropriate surgery.

Keywords: breast cancer, FGD PET/CT, preoperative staging, surgical approach

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Authors: Surita Maini, Sanjay Dhanka

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Machine learning (ML) involves developing algorithms and statistical models that enable computers to learn and make predictions or decisions based on data without being explicitly programmed. Because of its unlimited abilities ML is gaining popularity in medical sectors; Medical Imaging, Electronic Health Records, Genomic Data Analysis, Wearable Devices, Disease Outbreak Prediction, Disease Diagnosis, etc. In the last few decades, many researchers have tried to diagnose Breast Cancer (BC) using ML, because early detection of any disease can save millions of lives. Working in this direction, the authors have proposed a hybrid ML technique RBF SVM, to predict the BC in earlier the stage. The proposed method is implemented on the Breast Cancer UCI ML dataset with 569 instances and 32 attributes. The authors recorded performance metrics of the proposed model i.e., Accuracy 98.24%, Sensitivity 98.67%, Specificity 97.43%, F1 Score 98.67%, Precision 98.67%, and run time 0.044769 seconds. The proposed method is validated by K-Fold cross-validation.

Keywords: breast cancer, support vector classifier, machine learning, hyper parameter tunning

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Authors: Jahanshah Ashkani, Kevin J. Naidoo

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Glycosylation is the major posttranslational modification (PTM) process in cellular development. In tumour development, it is marked by structural alteration of carbohydrates (glycans) that is the result of aberrant glycosylation. Altered glycan structures affect cell surface ligand-receptor interactions that interfere with the regulation of cell adhesion, migration, and proliferation. The resulting changes in glycan biosynthesis pathways originate from altered expression of glycosyltransferases and glycosidases. While the alteration in glycosylation patterns is a recognized “hallmark of cancer”, the influential overview of the biology of cancer proposes eight hallmarks with no explicit suggestion to connectivity with glycosylation. Recently, we have discovered a connection between the glycosyltransferase gene expression and cancer type and subtype. Here we present an association between aberrant glycosylation and the biological hallmarks of breast cancer by exploring the common regulatory mechanisms at the genomic scale. The result of this study bridges the glycobiological and biological pathways that are accepted hallmarks of cancer by connecting their common regulatory pathways. This is an impetus for further investigation as target therapies of breast cancer are very likely to be uncovered from this.

Keywords: aberrant glycosylation, biological hallmarks, breast cancer, regulatory mechanism

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Authors: Leah Ning

Abstract:

This paper discusses the development of a machine learning algorithm that accurately detects metastatic breast cancer (cancer has spread elsewhere from its origin part) in selected images that come from pathology scans of lymph node sections. Being able to develop an accurate artificial intelligence (AI) algorithm would help significantly in breast cancer diagnosis since manual examination of lymph node scans is both tedious and oftentimes highly subjective. The usage of AI in the diagnosis process provides a much more straightforward, reliable, and efficient method for medical professionals and would enable faster diagnosis and, therefore, more immediate treatment. The overall approach used was to train a convolution neural network (CNN) based on a set of pathology scan data and use the trained model to binarily classify if a new scan were benign or malignant, outputting a 0 or a 1, respectively. The final model’s prediction accuracy is very high, with 100% for the train set and over 70% for the test set. Being able to have such high accuracy using an AI model is monumental in regard to medical pathology and cancer detection. Having AI as a new tool capable of quick detection will significantly help medical professionals and patients suffering from cancer.

Keywords: breast cancer detection, AI, machine learning, algorithm

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