Search results for: breast fillet

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: Remi Safi, Aline Hamade, Najat Bteich, Jamal El Saghir, Mona Diab Assaf, Marwan El-Sabban, Fadia Najjar

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Estrogen is considered a risk factor for breast cancer since it promotes breast-cell proliferation. The jaesckeanadiol-3-p-hydroxyphenylpropanoate, a hemi-synthetic analogue of the natural phytoestrogen ferutinin (jaesckeanadiol-p-hydroxybenzoate), is designed to be devoid of estrogenic activity. This analogue induces a cytotoxic effect 30 times higher than that of ferutinin towards MCF-7 breast cancer cell line. We compared these two compounds with respect to their effect on proliferation, cell cycle distribution and cancer stem-like cells in the MCF-7 cell line. Treatment with ferutinin (30 μM) and its analogue (1 μM) produced a significant accumulation of cells at the pre G0/G1 cell cycle phase and triggered apoptosis. Importantly, this compound retains its anti-proliferative activity against breast cancer stem/progenitor cells that are naturally insensitive to ferutinin at the same dose. These results position ferutinin analogue as an effective compound inhibiting the proliferation of estrogen-dependent breast cancer cells and consistently targeting their stem-like cells.

Keywords: ferutinin, hemi-synthetic analogue, breast cancer, estrogen, stem/progenitor cells

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Authors: Ayyaz Hussain, Tariq Sadad

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Breast cancer (BC) is one of the widespread ailments among females globally. The early prognosis of BC can decrease the mortality rate. Exact findings of benign tumors can avoid unnecessary biopsies and further treatments of patients under investigation. However, due to variations in images, it is a tough job to isolate cancerous cases from normal and benign ones. The machine learning technique is widely employed in the classification of BC pattern and prognosis. In this research, a deep convolution neural network (DCNN) called AlexNet architecture is employed to get more discriminative features from breast tissues. To achieve higher accuracy, K-nearest neighbor (KNN) classifiers are employed as a substitute for the softmax layer in deep learning. The proposed model is tested on a widely used breast image database called MIAS dataset for experimental purposes and achieved 99% accuracy.

Keywords: breast cancer, DCNN, KNN, mammography

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Authors: Devadrita Dey Sarkar

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Regardless of the many technologic advances in the past decade, increased training and experience, and the obvious benefits of uniform standards, the false-negative rate in screening mammography remains unacceptably high .A computer aided neural network classification of regions of suspicion (ROS) on digitized mammograms is presented in this abstract which employs features extracted by a new technique based on independent component analysis. CAD is a concept established by taking into account equally the roles of physicians and computers, whereas automated computer diagnosis is a concept based on computer algorithms only. With CAD, the performance by computers does not have to be comparable to or better than that by physicians, but needs to be complementary to that by physicians. In fact, a large number of CAD systems have been employed for assisting physicians in the early detection of breast cancers on mammograms. A CAD scheme that makes use of lateral breast images has the potential to improve the overall performance in the detection of breast lumps. Because breast lumps can be detected reliably by computer on lateral breast mammographs, radiologists’ accuracy in the detection of breast lumps would be improved by the use of CAD, and thus early diagnosis of breast cancer would become possible. In the future, many CAD schemes could be assembled as packages and implemented as a part of PACS. For example, the package for breast CAD may include the computerized detection of breast nodules, as well as the computerized classification of benign and malignant nodules. In order to assist in the differential diagnosis, it would be possible to search for and retrieve images (or lesions) with these CAD systems, which would be reliable and useful method for quantifying the similarity of a pair of images for visual comparison by radiologists.

Keywords: CAD(computer-aided design), lesions, neural network, ROS(region of suspicion)

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Authors: Huma Naqeeb

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Epidemiological studies have shown the robust link between breast cancer and dietary pattern. There has been no previous study conducted in Pakistan, which specifically focuses on dietary patterns among breast cancer women. This study aims to examine the association of breast cancer with dietary patterns among Pakistani women. This case-control research was carried in multiple tertiary care facilities. Newly diagnosed primary breast cancer patients were recruited as cases (n = 408); age matched controls (n = 408) were randomly selected from the general population. Data on required parameters were systematically collected using subjective and objective tools. Factor and Principal Component Analysis (PCA) techniques were used to extract women’s dietary patterns. Four dietary patterns were identified based on eigenvalue >1; (i) veg-ovo-fish, (ii) meat-fat-sweet, (iii) mix (milk and its products, and gourds vegetables) and (iv) lentils - spices. Results of the multiple regressions were displayed as adjusted odds ratio (Adj. OR) and their respective confidence intervals (95% CI). After adjusted for potential confounders, veg-ovo-fish dietary pattern was found to be robustly associated with a lower risk of breast cancer among women (Adj. OR: 0.68, 95%CI: (0.46-0.99, p<0.01). The study findings concluded that attachment to the diets majorly composed of fresh vegetables, and high quality protein sources may contribute in lowering the risk of breast cancer among women.

Keywords: breast cancer, dietary pattern, women, principal component analysis

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Authors: Nadia H. Mohammed, Anmar Al-Taie, Fadia H. Al-Sultany

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Although breast cancer prevalence continues to increase, mortality has been decreasing as a result of early detection and improvement in adjuvant systemic therapy. Nevertheless, this disease required further efforts to understand and identify the associated potential risk factors that could play a role in the prevalence of this malignancy among Iraqi women. The objective of this study was to assess the perception of certain predictive risk factors on the prevalence of breast cancer types among a sample of Iraqi women diagnosed with breast cancer. This was a retrospective observational study carried out at National Cancer Research Center in College of Medicine, Baghdad University from November 2017 to January 2018. Data of 100 patients with breast cancer whose biopsies examined in the National Cancer Research Center were included in this study. Data were collected to structure a detailed assessment regarding the patients’ demographic, medical and cancer records. The majority of study participants (94%) suffered from ductal breast cancer with mean age 49.57 years. Among those women, 48.9% were obese with body mass index (BMI) 35 kg/m². 68.1% of them had positive family history of breast cancer and 66% had low parity. 40.4% had stage II ductal breast cancer followed by 25.5% with stage III. It was found that 59.6% and 68.1% had positive oestrogen receptor sensitivity and positive human epidermal growth factor (HER2/neu) receptor sensitivity respectively. In regard to the impact of prediction of certain variables on the incidence of ductal breast cancer, positive family history of breast cancer (P < 0.0001), low parity (P< 0.0001), stage I and II breast cancer (P = 0.02) and positive HER2/neu status (P < 0.0001) were significant predictive factors among the study participants. The results from this study provide relevant evidence for a significant positive and potential association between certain risk factors and the prevalence of breast cancer among Iraqi women.

Keywords: Ductal Breast Cancer, Hormone Sensitivity, Iraq, Risk Factors

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Authors: H. Tayefih, F. farajzade ahari, F. Zarghami, V. Zeighamian, N. Zarghami, Y. Pilehvar-soltanahmadi

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Breast cancer is the most frequently occurring cancer among women throughout the world. Natural compounds such as curcumin hold promise to treat a variety of cancers including breast cancer. However, curcumin's therapeutic application is limited, due to its rapid degradation and poor aqueous solubility. On the other hand, previous studies have stated that drug delivery using nanoparticles might improve the therapeutic response to anticancer drugs. Poly (N-isopropylacrylamide-co-methacrylic acid) (PNIPAAm–MAA) is one of the hydrogel copolymers utilized in the drug delivery system for cancer therapy. The aim of this study was to examine the cytotoxic potential of curcumin encapsulated within the NIPAAm-MAA nanoparticle, on the MCF-7 breast cancer cell line. In this work, polymeric nanoparticles were synthesized through the free radical mechanism, and curcumin was encapsulated into NIPAAm-MAA nanoparticles. Then, the cytotoxic effect of curcumin-loaded NIPAAm-MAA on the MCF-7 breast cancer cell line was measured by MTT assays. The evaluation of the results showed that curcumin-loaded NIPAAm-MAA has more cytotoxic effect on the MCF-7 cell line and efficiently inhibited the growth of the breast cancer cell population, compared with free curcumin. In conclusion, this study indicates that curcumin-loaded NIPAAm-MAA suppresses the growth of the MCF-7 cell line. Overall, it is concluded that encapsulating curcumin into the NIPAAm-MAA copolymer could open up new avenues for breast cancer treatment.

Keywords: PNIPAAm-MAA, breast cancer, curcumin, drug delivery

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Authors: Jasminka Mujic, Karin Milde-Langosch, Volkmar Mueller, Mirza Suljagic, Tea Becirevic, Jozo Coric, Daria Ler

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MACC1 (metastasis associated in colon cancer-1) is a prognostic biomarker for tumor progression, metastasis, and survival of a variety of solid cancers. MACC1 also causes tumor growth in xenograft models and acts as a master regulator of the HGF/MET signaling pathway. In breast cancer, the expression of MACC1 determined by immunohistochemistry was significantly associated with positive lymph node status and advanced clinical stage. The aim of the present study was to further investigate the prognostic or predictive value of MACC1 expression in breast cancer using western blot analysis and immunohistochemistry. The results of our study have shown that high MACC1 expression in breast cancer is associated with shorter disease-free survival, especially in node-negative tumors. The MACC1 might be a suitable biomarker to select patients with a higher probability of recurrence which might benefit from adjuvant chemotherapy. Our results support a biologic role and potentially open the perspective for the use of MACC1 as predictive biomarker for treatment decision in breast cancer patients.

Keywords: breast cancer, biomarker, HGF/MET, MACC1

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Authors: Ahmad Jawad Fardin

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Over 60% of patients with breast cancer in Afghanistan present late with advanced stage III and IV, a major cause for the poor survival rate. The objectives of this study were to identify the contributing factors for the diagnosis and treatment delay and its outcome. This cross-sectional study was conducted on 318 patients with histologically confirmed breast cancer in the oncology department of Jamhoriat hospital, which is the first and only national cancer center in Afghanistan; data were collected from medical records and interviews conducted with women diagnosed with breast cancer, linear regression and logistic regression were used for analysis. Patient delay was defined as the time from first recognition of symptoms until first medical consultation and doctor form first consultation with a health care provider until histological confirmation of breast cancer. The mean age of patients was 49.2+_ 11.5years. The average time for the final diagnosis of breast cancer was 8.5 months; most patients had ductal carcinoma 260.7 (82%). Factors associated with delay were low education level 76% poor socioeconomic and cultural conditions 81% lack of cancer center 73% lack of screening 19%. The stage distribution was as follows stage IV 4 22% stage III 44.4% stage II 29.3% stage I 4.3%. Complex associated factors were identified to delayed the diagnosis of breast cancer and increased adverse outcomes consequently. Raising awareness and education in women, the establishment of cancer centers and providing accessible diagnosis service and screening, training of general practitioners; required to promote early detection, diagnosis and treatment.

Keywords: delayed diagnosis and poor outcome, breast cancer in Afghanistan, poor outcome of delayed breast cancer treatment, breast cancer delayed diagnosis and treatment in Afghanistan

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Authors: Talita Kato, Moises Grespan, Elza I. Ida, Massami Shimokomaki, Adriana L. Soares

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White Striping (WS) is becoming a concern for the poultry industry, as it affects the look of breast broiler chicken meat leading it to rejection by the consumers. It is characterized by the appearance of varying degrees of white striations on the Pectoralis major muscle surface following the direction of the muscle fiber. The etiology of this myopathy is still unknown, however it is suggested to be associated with increased weight gain rate and age of the bird, attributing the phenomenon to the genetically bird’s selection for efficiently higher meat production. The aim of this study was to evaluate the occurrence of Pectoralis major WS in a commercial plant in southern Brazil and its chemical characterization. The breast meat samples (n=660) from birds of 47 days of age, were classified as: Normal NG (no apparent white striations), Moderate MG (when the fillets present thin lines <1 mm) and Severe SG (white striations present ˃1 mm thick covering a large part of the fillet surface). Thirty samples (n = 10 for each level of severity) were analyzed for pH, color (L*, a*, b*), proximate chemical composition (moisture, protein, ash and lipids contents) and hydroxyproline in order to determine the collagen content. The results revealed the occurrence for NG group was 16.97%, 51.67% for MG group and 31.36% for SG group. Although the total protein content did not differ significantly, the collagen index was 42% higher in favor to SG in relation to NG. Also the lipid fraction was 27% higher for SG group. The NG presented the lowest values of the parameters L* and a* (P ≤ 0.05), as there was no white striations on its surface and highest b* value in SG, because of the maximum lipid contents. These results indicate there was a contribution of the SG muscle cells to oversynthesize connective tissue components on the muscle fascia. In conclusion, this study revealed a high incidence of White Striping on broiler commercial line in Brazil thus, there is a need to identify the causes of this abnormality in order to diminish or to eliminate it.

Keywords: collagen content, commercial line, pectoralis major muscle, proximate composition

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Authors: Zahra Khalid, Gul Muhammad Khan, Arbab Masood Ahmad

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Cartesian Genetic Programming (CGP) is explored to design an optimal circuit capable of early stage breast cancer detection. CGP is used to evolve simple multiplexer circuits for detection of malignancy in the Fine Needle Aspiration (FNA) samples of breast. The data set used is extracted from Wisconsins Breast Cancer Database (WBCD). A range of experiments were performed, each with different set of network parameters. The best evolved network detected malignancy with an accuracy of 99.14%, which is higher than that produced with most of the contemporary non-linear techniques that are computational expensive than the proposed system. The evolved network comprises of simple multiplexers and can be implemented easily in hardware without any further complications or inaccuracy, being the digital circuit.

Keywords: breast cancer detection, cartesian genetic programming, evolvable hardware, fine needle aspiration

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Authors: Ali Berkan Ural

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This paper presents the analysis, evaluation, and pre-diagnosis of early stage breast based diagnostic problems (breast cancer, nodulesorlumps) by Computer Aided Diagnosing (CAD) system from mammogram radiological images. According to the statistics, the time factor is crucial to discover the disease in the patient (especially in women) as possible as early and fast. In the study, a new algorithm is developed using advanced image processing and deep learning method to detect and classify the problem at earlystagewithmoreaccuracy. This system first works with image processing methods (Image acquisition, Noiseremoval, Region Growing Segmentation, Morphological Operations, Breast BorderExtraction, Advanced Segmentation, ObtainingRegion Of Interests (ROIs), etc.) and segments the area of interest of the breast and then analyzes these partly obtained area for cancer detection/lumps in order to diagnosis the disease. After segmentation, with using the Spectrogramimages, 5 different deep learning based methods (specified Convolutional Neural Network (CNN) basedAlexNet, ResNet50, VGG16, DenseNet, Xception) are applied to classify the breast based problems.

Keywords: computer aided diagnosis, breast cancer, region growing, segmentation, deep learning

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Authors: Abuelquasim. M. Hassan, Namarig .S. Mohammed, Samah F. Mohammed, Wafaa. A. Mohammed, Wafaa M. Edriss, Amel A. Ahmed, Elfadil M. Abass

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Introduction: Cytomegalovirus (CMV), a common virus, usually causes asymptomatic infections in immunocompetent hosts; however, it may lead to serious complications especially in cancer patients. Objectives: This study was conducted to determine the seroprevalence of human cytomegalovirus (HCMV) among leukemia, breast and prostate cancer patients attending at Radiation Isotope-Center-Khartoum (RICK) from April to August 2016. Material and Methods: A total of 91 subjects were included: 30 leukemic, 22 breast cancer and 29 prostate cancer patients.10 of them were healthy and used as control group, serum samples were collected and tested for CMV IgG & IgM using enzyme-linked immune sorbent assay (ELISA). Result: Of the control group, 9/10 (9.9%) were seropositive for CMV IgG and 1/10 (1.09%) were sero positive for IgM. Also, all cancer groups demonstrated presence of IgG antibody classes as: The percentage of positive results in prostate, breast cancer and leukemia were 35.8 %, 37.2%, and 35.3% respectively. Conclusion: There was no significant correlation between leukemia, breast, prostate and HCMV.

Keywords: cytomegalovirus, serodiagnostic, breast cancer, leukemia

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Authors: Sam Khozama, Ali M. Mayya

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Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data needs a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM) and ensemble learning with hyper parameters optimization are used, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: machine learning, deep learning, cancer prediction, breast cancer, LSTM, fusion

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Authors: Rana F. Obeidat, Suzanne S. Dickerson, Gregory G. Homish, Nesreen M. Alqaissi, Robin M. Lally

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Background: Despite the fact that breast cancer is the most prevalent cancer among Jordanian women, practically nothing is known about their perceptions of early stage breast cancer and surgical treatment. Objective: To gain understanding of the diagnosis and surgical treatment experience of Jordanian women diagnosed with early stage breast cancer. Methods: An interpretive phenomenological approach was used for this study. A purposive sample of 28 Jordanian women who were surgically treated for early stage breast cancer within 6 months of the interview was recruited. Data were collected using individual interviews and analyzed using Heideggerian hermeneutical methodology. Results: Fear had a profound effect on Jordanian women’s stories of diagnosis and surgical treatment of early stage breast cancer. Women’s experience with breast cancer and its treatment was shaped by their pre-existing fear of breast cancer, the disparity in the quality of care at various health care institutions, and sociodemographic factors (e.g., education, age). Conclusions: Early after the diagnosis, fear was very strong and women lost perspective of the fact that this disease was treatable and potentially curable. To control their fears, women unconditionally trusted God, the health care system, surgeons, family, friends, and/or neighbors, and often accepted treatment offered by their surgeons without questioning. Implications for practice: Jordanian healthcare providers have a responsibility to listen to their patients, explore meanings they ascribe to their illness, and provide women with proper education and support necessary to help them cope with their illness.

Keywords: breast cancer, early stage, Jordanian, experience, phenomenology

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Authors: Mina Jafari, Kobra Hamraee, Saied Hossein Hosseini

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The prediction of breast cancer disease is one of the challenges in medicine. In this paper we collected 528 records of women’s information who live in Kabul including demographic, life style, diet and pregnancy data. There are many classification algorithm in breast cancer prediction and tried to find the best model with most accurate result and lowest error rate. We evaluated some other common supervised algorithms in data mining to find the best model in prediction of breast cancer disease among afghan women living in Kabul regarding to momography result as target variable. For evaluating these algorithms we used Cross Validation which is an assured method for measuring the performance of models. After comparing error rate and accuracy of three models: Decision Tree, Naive Bays and Rule Induction, Decision Tree with accuracy of 94.06% and error rate of %15 is found the best model to predicting breast cancer disease based on the health care records.

Keywords: decision tree, breast cancer, probability, data mining

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Authors: M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani, S. Zolghadri, S. Kakaei

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Despite the appropriate characteristics of ¹⁷⁷Lu and DOTATOC, to our best knowledge, the therapeutic benefit of ¹⁷⁷Lu-DOTATOC complex in breast cancer has not been reported until now. In this study, biodistribution of ¹⁷⁷Lu-DOTA-TOC in mouse tumor model for evaluation of possible utilization of this complex in breast cancer treatment was investigated.¹⁷⁷Lu was prepared with the specific activity of 2.6-3 GBq.mg^-1 and radionuclidic purity higher than 99%. The radiolabeled complex was prepared in the optimized conditions with the radiochemical purity higher than 99%. The final solution was injected to the BALB/c mice with adenocarcinoma breast cancer. The biodistribution results showed major accumulation in the kidneys as the major excretion route and the somatostatin receptor-positive tissues such as pancreas compared with the other tissues. Also, significant uptake was observed in tumor even in longer time after injection. According to the results obtained in this research study, somatostatin receptors expressed in breast cancers can be targeted with DOTATOC analogues especially with ¹⁷⁷Lu-DOTATOC as an ideal therapeutic agent.

Keywords: ¹⁷⁷Lu, adenocarcinoma breast cancer, DOTATOC, BALB/c mice

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Authors: Dusanee Suwankhong, Pranee Liamputtong

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Breast surgery leaves undesirable scars to all women who experienced mastectomy, despite the fact that this could be a principle approach to save one life. This paper explores how Thai women living with breast cancer perceived and experienced a scarred body after breast surgery. In-depth interviews and drawing methods were employed among 20 women diagnosed with breast cancer. The interviewed data were analysed using thematic analysis method. The results showed that all women with breast cancer who underwent breast surgery perceived and experienced scar as a persisting and visible side-effect. This disfigurement appearance presented a negative image of feminine identity and led to emotional burdens among women. They responded to being scarred in different ways relating to their perceptions of body and changes. The older group had less embarrassed feelings towards being scarred comparing to the younger one. All women tried to seek means to cope with such physical impairment and keep balance life related to their condition. For example, they relied on Buddhism practice and tried to heal the keloid using natural products. Scars appeared to be an unpleasant effect for women who underwent breast mastectomy. Nurses and health care professionals in the local health service sectors need to pay close attention to how the women see the scarred body and their experiences of living with the distorted feminine appearance, and to provide sensitive support that meets the needs of these vulnerable women. The suitable supports can reduce the sense of embarrassment and increase their sense of self-confidence about their social femininity.

Keywords: breast surgery, emotional response, qualitative study, scars, Thai women

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Authors: Oluwaponmile D. Alao

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In this paper, two models have been developed to ascertain the best network needed for diagnosis of breast cancer. Breast cancer has been a disease that required the attention of the medical practitioner. Experience has shown that misdiagnose of the disease has been a major challenge in the medical field. Therefore, designing a system with adequate performance for will help in making diagnosis of the disease faster and accurate. In this paper, two models: backpropagation neural network and support vector machine has been developed. The performance obtained is also compared with other previously obtained algorithms to ascertain the best algorithms.

Keywords: breast cancer, data mining, neural network, support vector machine

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Authors: Navkiran Kaur, Apoorva Mathur, Abhishree Agarwal, Sakshi Gupta, Tuhin Rashmi

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Aim: Breast cancer is the most common cancer in women worldwide, and resistance to the current therapeutics, often concurrently, is an increasing clinical challenge. Glycosylation of proteins is one of the most important post-translational modifications. It is widely known that aberrant glycosylation has been implicated in many different diseases due to changes associated with biological function and protein folding. Alterations in cell surface glycosylation, can promote invasive behavior of tumor cells that ultimately lead to the progression of cancer. In breast cancer, there is an increasing evidence pertaining to the role of glycosylation in tumor formation and metastasis. In the present study, an attempt has been made to study the disease associated sialoglycoproteins in breast cancer by using bioinformatics tools. The sequence will be retrieved from UniProt database. A database in the form of a word document was made by a collection of FASTA sequences of breast cancer gene sequence. Glycosylation was studied using yinOyang tool on ExPASy and Differential genes expression and protein analysis was done in context of breast cancer metastasis. The number of residues predicted O-glc NAc threshold containing 50 aberrant glycosylation sites or more was detected and recorded for individual sequence. We found that the there is a significant change in the expression profiling of glycosylation patterns of various proteins associated with breast cancer. Differential aberrant glycosylated proteins in breast cancer cells with respect to non-neoplastic cells are an important factor for the overall progression and development of cancer.

Keywords: breast cancer, bioinformatics, cancer, metastasis, glycosylation

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Authors: Tolulope Allo, Mofoluwake P. Ajayi, Adenike E. Idowu, Emmanuel O. Amoo, Fadeke Esther Olu-Owolabi

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Breast cancer which was more prevalent in Europe and America in the past is gradually being mirrored across the world today with greater economic burden on low and middle income countries (LMCs). Breast cancer is the most common cancer among women globally and current studies have shown that a woman dies with the diagnosis of breast cancer every thirteen minutes. The economic cost of breast cancer is overwhelming particularly for developing economies. While it causes billion of dollar in losses of national income, it pushes millions of people below poverty line. This study examined the economic burden of breast cancer on Nigerian women, its impacts on their standard of living and its effects on Nigeria’s socio economic development. The study adopts a qualitative research approach using the in-depth interview technique to elicit valuable information from respondents with cancer experience from the Southern part of Nigeria. Respondents constituted women in their reproductive age (15-49 years) that have experienced and survived cancer and also those that are currently receiving treatment. Excerpts from the interviews revealed that the cost of treatment is one of the major factors contributing to the late presentation of breast cancer incidences among women as many of them could not afford to pay for their own treatment. The study also revealed that many women prefer to explore other options such as herbal treatments and spiritual consultations which is less expensive and affordable. The study therefore concludes that breast cancer diagnosis and treatment should be subsidized by the government in order to facilitate easy access and affordability thereby promoting early detection and reducing the economic burden of treatment on women.

Keywords: breast cancer, development, economic burden, women

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Authors: Shuge Lei, Haonan Hu, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Yan Tong

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It remains challenging to measure reliability from classification results from different machine learning models. This paper proposes a reliable soup optimization algorithm based on the model weight fusion algorithm Model Soup, aiming to improve reliability by using dual-channel reliability as the objective function to fuse a series of weights in the breast ultrasound classification models. Experimental results on breast ultrasound clinical datasets demonstrate that reliable soup significantly enhances the reliability of breast ultrasound image classification tasks. The effectiveness of the proposed approach was verified via multicenter trials. The results from five centers indicate that the reliability optimization algorithm can enhance the reliability of the breast ultrasound image classification model and exhibit low multicenter correlation.

Keywords: breast ultrasound image classification, feature attribution, reliability assessment, reliability optimization

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Authors: Seyda Can, Meryem Unulu

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Objective: Breast milk is the most fundamental nutritional element for the healthy growth and development of newborns as they supply all the necessary components. Various obstacles such as diseases of mother and child, allergies of the baby, and insufficient breastmilk affect breast-feeding adversely. The wet nursery or breast milk banking is the most important source in providing the nutrients closest to the ideal for the newborn. Despite increasing opinions about its benefits, breast milk banking practice is controversial because of reasons such as ethical problems, traditional beliefs and attitudes, security concerns of families and lack of knowledge. It is thought that the results of this study will create the data for studies to raise the awareness of the society regarding wet nursery, and milk banks. Method: The study was planned and performed in descriptive type. The population of the study consists of mothers that gave birth between October-November 2017 in a public hospital in Turkey, and the sample consisted of 205 mothers chosen by improbable sampling method from the population and accepted to participate in the study. While gathering data, a survey consisting of 33 questions designed to determine the socio-demographic characteristics and their views on wet nursery and breast milk banking. Written ethical committee and institution permit was taken. Before the interview, participants were informed about the purpose and content of the study and oral permit was taken. Result: When the distribution of 205 mothers according to their individual characteristics, it was detected that their age average was 28,16±5,23 and 63,4 of mothers (n=130) had normal delivery. It was determined that clear majority of mothers, 75,6% (n=155) had no breast-feeding problems and 75,1% (n=154) fed the baby only with breast milk. It was detected that 18,5% (n=38) would accept a stranger to be a wet nurse and 60% (n=123) would donate milk if there is a breast milk bank. It was detected 33,2 % (n=68) of participant mothers want to make use of breast milk bank if there is a situation that prevents breast feeding, 38,5 % (n=79) of mothers think breast milk bank would be problematic religiously. Statistical difference was detected between the educational status of women and the rate of wanting breast milk bank practice. As the educational status of mothers increased, their rate of wanting breast milk bank practice increased. Conclusion: It is essential that every baby is breastfed by its mother primarily. However, when this is not possible, in order to implement wet nursery and breast milk banking as an extension of national breast-feeding policy, regulations need to be made and worries should be eased. Also, organizing training programs are also really important to raise awareness of the society and mothers.

Keywords: breast feeding, breast milk, milk banks, wet nursery

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Authors: Asma Zaib, Saeed Khan, Ayaz Ahmed Noonari, Sehrish Bint-e-Mohsin

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Breast cancer is the most common cancer among females worldwide and is estimated that more than 450,000 deaths are reported each year. It accounts for about 14% of all female cancer deaths. Angiogenesis plays an essential role in Breast cancer development, invasion, and metastasis. Breast cancer predominantly begins in luminal epithelial cells lining the normal breast ducts. Breast carcinoma likely requires coordinated efforts of both increased proliferation and increased motility to progress to metastatic stages.Resveratrol: a natural stilbenoid, has anti-inflammatory and anticancer effects that inhibits proliferation of variety of human cancer cell lines, including breast, prostate, stomach, colon, pancreatic, and thyroid cancers.The objective of this study is:To investigate anti-neoangiogenesis effects of Resveratrol in breast cancer and to analyze inhibitory effects of resveratrol on aromatase, Erα, HER2/neu, and VEGFR.Docking is the computational determination of binding affinity between molecule (protein structure and ligand).We performed molecular docking using Swiss-Dock and to determine docking effects of (1) Resveratrol with Aromatase, (2) Resveratrol with ERα (3) Resveratrol with HER2/neu and (4) Resveratrol with VEGFR2.Docking results of resveratrol determined inhibitory effects on aromatase with binding energy of -7.28 kcal/mol which shows anticancerous effects on estrogen dependent breast tumors. Resveratrol also show inhibitory effects on ERα and HER2/new with binging energy -8.02, and -6.74 respectively; which revealed anti-cytoproliferative effects upon breast cancer. On the other hand resveratrol v/s VEGFR showed potential inhibitory effects on neo-angiogenesis with binding energy -7.68 kcal/mol, angiogenesis is the important phenomenon that promote tumor development and metastasis. Resveratrol is an anti-breast cancer agent conformed by in silico studies, it has been identified that resveratrol can inhibit breast cancer cells proliferation by acting as competitive inhibitor of aromatase, ERα and HER2 neo, while neo-angiogemesis is restricted by binding to VEGFR which authenticates the anti-carcinogenic effects of resveratrol against breast cancer.

Keywords: angiogenesis, anti-cytoproliferative, molecular docking, resveratrol

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Authors: Viacheslav Sushko, Viktor Sushko

Abstract:

Pre-cancerous breast diseases are pathological changes that precede the appearance of adenocarcinoma. The most common benign breast disease is mastopathy. We examined the life and disease history of 114 women aged 58-69 who were diagnosed with adenocarcinoma of the breast at different stages of development. They filled out the Reeder Scale to determine the level of stress. The results of the study revealed that 62 of them had mastopathy at the age of 30-45 years old. These women refused surgical treatment for mastopathy. Five to six years before their diagnosis of adenocarcinoma of the mammary gland, 84 women had experienced severe stress (death of a beloved close relative, torture accompanied by rape, prolonged stay in extreme conditions (under bombardment and bombardment). In the assessment of data from completed Reeder scales, 114 women had a high level of mental stress, with a score from 1-1.72. The 84 women who suffered from severe stress showed overeating or a significant decrease in food intake, insomnia, apathy, increased irritability and restlessness, loss of interest in sexual relationships, forgetfulness, difficulty in performing routine work, prolonged uncontrollable headaches, unexplained fatigue, heart pain, reduced capacity for work. In conclusion, it is important to provide psychotherapy for breast cancer patients as the diagnosis, and the different stages of treatment are very stressful. It is also advisable to see a psychiatrist at an early stage and prevent distress and treat precancerous breast disease.

Keywords: breast cancer, distress, mastopathy, severe stress

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Authors: F. Ghazalnaz Sharifonnasabi, Iman Makhdoom

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Breast cancer is a serious health concern that affects many people around the world. According to a study published in the Breast journal, the global burden of breast cancer is expected to increase significantly over the next few decades. The number of deaths from breast cancer has been increasing over the years, but the age-standardized mortality rate has decreased in some countries. It’s important to be aware of the risk factors for breast cancer and to get regular check- ups to catch it early if it does occur. Machin learning techniques have been used to aid in the early detection and diagnosis of breast cancer. These techniques, that have been shown to be effective in predicting and diagnosing the disease, have become a research hotspot. In this study, we consider two deep learning approaches including: Multi-Layer Perceptron (MLP), and Convolutional Neural Network (CNN). We also considered the five-machine learning algorithm titled: Decision Tree (C4.5), Naïve Bayesian (NB), Support Vector Machine (SVM), K-Nearest Neighbors (KNN) Algorithm and XGBoost (eXtreme Gradient Boosting) on the Breast Cancer Wisconsin Diagnostic dataset. We have carried out the process of evaluating and comparing classifiers involving selecting appropriate metrics to evaluate classifier performance and selecting an appropriate tool to quantify this performance. The main purpose of the study is predicting and diagnosis breast cancer, applying the mentioned algorithms and also discovering of the most effective with respect to confusion matrix, accuracy and precision. It is realized that CNN outperformed all other classifiers and achieved the highest accuracy (0.982456). The work is implemented in the Anaconda environment based on Python programing language.

Keywords: breast cancer, multi-layer perceptron, Naïve Bayesian, SVM, decision tree, convolutional neural network, XGBoost, KNN

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Authors: Laila Seada, Ashraf Ibrahim, Amjad Al Shammari

Abstract:

Background and Objectives: Breast carcinoma is the most common cancer of females in Hail region, accounting for 31% of all diagnosed cancer cases followed by thyroid carcinoma (25%) and colorectal carcinoma (13%). Methods: In the present retrospective study, all cases of breast lesions received at the histopathology department in King Khalid Hospital, Hail, during the period from May 2011 to April 2016 have been retrieved from department files. For all cases, a trucut biopsy, lumpectomy, or modified radical mastectomy was available for histopathologic diagnosis, while 105/140 (75%) had, as well, preoperative fine needle aspirates (FNA). Results: 49 cases out of 140 (35%) breast lesions were carcinomas: 44/49 (89.75%) was invasive ductal, 2/49(4.1%) invasive lobular carcinomas, 1/49(2.05%) intracystic low grade papillary carcinoma and 2/49 (4.1%) ductal carcinoma in situ (DCIS). Mean age for malignant cases was 45.06 (+/-10.58): 32.6% were below the age of 40 and 30.6 below 50 years, 18.3% below 60 and 16.3% below 70 years. For the benign group, mean age was 32.52 (+/10.5) years. Benign lesions were in order of frequency: 34 fibroadenomas, 14 fibrocystic disease, 12 chronic mastitis, five granulomatous mastitis, three intraductal papillomas, and three benign phyllodes tumor. Tubular adenoma, lipoma, skin nevus, pilomatrixoma, and breast reduction specimens constituted the remaining specimens. Conclusion: Breast lesions are common in our series and invasive carcinoma accounts for more than 1/3^rd of the lumps, with 63.2% incidence in pre-menopausal ladies, below the age of 50 years. FNA as a non-invasive procedure, proved to be an effective tool in diagnosing both benign and malignant/suspicious breast lumps and should continue to be used as a first assessment line of palpable breast masses.

Keywords: age incidence, breast carcinoma, fine needle aspiration, hail region

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Authors: Saad Al-Shibli, Nasser Amjad, Muna Al Kubaisi, Norra Harun, Shaikh Mizan

Abstract:

Leptin is a multifunctional hormone produced mainly by adipocyte. Leptin and its receptor have long been found associated with breast cancer. The main aim of this study is to investigate the correlation between Leptin/Leptin receptor and the clinicopathological features of breast cancer. Blood samples for ELISA, tissue samples from tumors and adjacent breast tissue were taken from 51 women with breast cancer with a control group of 40 women with a negative mammogram. Leptin and Leptin receptor in the tissues were estimated by immunohistochemistry (IHC). They were localized at the subcellular level by immunocytochemistry using transmission electron microscopy (TEM). Our results showed significant difference in serum leptin level between control and the patient group, but no difference between pre and post-operative serum leptin levels in the patient group. By IHC, we found that the majority of the breast cancer cells studied, stained positively for leptin and leptin receptors with co-expression of leptin and its receptors. No significant correlation was found between leptin/leptin receptors expression with the race, menopausal status, lymph node metastasis, estrogen receptor expression, progesterone receptor expression, HER2 expression and tumor size. Majority of the patients with distant metastasis were associated with high leptin and leptin receptor expression. TEM views both Leptin and Leptin receptor were found highly concentrated within and around the nucleus of the cancer breast cells, indicating nucleus is their principal seat of actions while the adjacent breast epithelial cells showed that leptin gold particles are scattered all over the cell with much less than that of the cancerous cells. However, presence of high concentration of leptin does not necessarily prove its over-expression, because it could be internalized from outside by leptin receptor in the cells. In contrast, leptin receptor is definitely over-expressed in the ductal breast cancer cells. We conclude that reducing leptin levels, blocking its downstream tissue specific signal transduction, and/or blocking the upstream leptin receptor pathway might help in prevention and therapy of breast cancer.

Keywords: breast cancer, expression, leptin, leptin receptors

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Authors: Amdy Moustapha Drame, Ilya V. Germashev, E. A. Markushevskaya

Abstract:

Among the main problems of medicine is breast cancer, from which a significant number of women around the world are constantly dying. Therefore, the detection of malignant breast tumors is an urgent task. For many years, various technologies for detecting these tumors have been used, in particular, in thermal imaging in order to determine different levels of breast cancer development. These periodic screening methods are a diagnostic tool for women and may have become an alternative to older methods such as mammography. This article proposes a model for the identification of malignant neoplasms of the mammary glands by the asymmetry of internal and external thermal imaging fields.

Keywords: asymmetry, breast cancer, tumors, deep learning, thermogram, convolutional transformation, classification

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Authors: Sally Shepherd, Craig Murphy

Abstract:

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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