Search results for: breast and thoracic surgery

Authors: E. M. D. Akuoko, Eliana Vasquez Osorio, Marcel Van Herk, Marianne Aznar

Abstract:

Radiotherapy is an integral part of treatment for many patients with breast cancer. However, side effects can occur, e.g., fibrosis or erythema. If patients at higher risks of radiation-induced side effects could be identified before treatment, they could be given more individual information about the risks and benefits of radiotherapy. We hypothesize that breast density is correlated with the risk of side effects and present a novel method for automatic evaluation based on radiotherapy planning CT scans. Methods: 799 supine CT scans of breast radiotherapy patients were available from the REQUITE dataset. The methodology was first established in a subset of 114 patients (cohort 1) before being applied to the whole dataset (cohort 2). All patients were scanned in the supine position, with arms up, and the treated breast (ipsilateral) was identified. Manual experts contour available in 96 patients for both the ipsilateral and contralateral breast in cohort 1. Breast tissue was segmented using atlas-based automatic contouring software, ADMIRE® v3.4 (Elekta AB, Sweden). Once validated, the automatic segmentation method was applied to cohort 2. Breast density was then investigated by thresholding voxels within the contours, using Otsu threshold and pixel intensity ranges based on Hounsfield units (-200 to -100 for fatty tissue, and -99 to +100 for fibro-glandular tissue). Volumetric breast density (VBD) was defined as the volume of fibro-glandular tissue / (volume of fibro-glandular tissue + volume of fatty tissue). A sensitivity analysis was performed to verify whether calculated VBD was affected by the choice of breast contour. In addition, we investigated the correlation between volumetric breast density (VBD) and patient age and breast size. VBD values were compared between ipsilateral and contralateral breast contours. Results: Estimated VBD values were 0.40 (range 0.17-0.91) in cohort 1, and 0.43 (0.096-0.99) in cohort 2. We observed ipsilateral breasts to be denser than contralateral breasts. Breast density was negatively associated with breast volume (Spearman: R=-0.5, p-value < 2.2e-16) and age (Spearman: R=-0.24, p-value = 4.6e-10). Conclusion: VBD estimates could be obtained automatically on a large CT dataset. Patients’ age or breast volume may not be the only variables that explain breast density. Future work will focus on assessing the usefulness of VBD as a predictive variable for radiation-induced side effects.

Keywords: breast cancer, automatic image segmentation, radiotherapy, big data, breast density, medical imaging

Procedia PDF Downloads 108

Authors: Elyce Cardonick, Shistri Dhar, Linsdey Seidman

Abstract:

Background: When breast cancer is diagnosed during pregnancy, the prognosis is comparable to non-pregnant women matched for prognostic indicators when pregnant women receive treatment without delay. Chemotherapy, including taxanes, can be given during pregnancy with normal neonatal development in exposed fetuses. Methods: Cases of primary breast cancer were extracted from the Cancer and Pregnancy Registry and longitudinal study at Cooper Medical School, which collects cases of pregnant women diagnosed and treated for cancer into a single database. Obstetrical, oncology and pediatric records were reviewed, including annual neonatal developmental, behavioral and medical assessments. Results: 270 pregnant women were diagnosed with primary breast cancer at a mean gestational age of 14.7+9weeks. Mean maternal age at diagnosis 34.5+4.5 years. Receptor status is comparable to non-pregnant women of reproductive age. Forty-nine women were advised to terminate. Two hundred two women underwent surgery;244 women received chemotherapy in pregnancy after the first trimester; the majority of Doxorubucin/Cytoxan; 81 of the cases included a taxane. At a mean of 90 months, follow up obtained on 255 newborns.192/255 newborns are meeting developmental milestones. Respiratory illnesses, including asthma, and bronchiolitis, were reported in 64 newborns, the most common medical condition reported. Thirty-one children are undergoing treatment for GERD, 11 for urinary tract infections, and 7 are undergoing treatment for anemia. Twenty-six children with expressive or articulation language delays, 21/26 are mild. Eleven children with gross/ 7 with fine motor delays. Eight children are treated for ADHD, 4 for anxiety and 4 have social skill impairment. The majority of children with developmental, language or motor delays were born preterm. Conclusion: After chemotherapy exposure in utero for breast cancer, the majority of newborns are meeting developmental milestones and are medically healthy. The goal for treating pregnant women with breast cancer is to aim for delivery close to the term.

Keywords: breast cancer, pregnancy, chemotherapy, newborn

Procedia PDF Downloads 90

Authors: Swathi Gopakumar, Sruthi Krishna, Shivasubramani Krishnamoorthy

Abstract:

Contactless, painless and radiation-free thermal imaging technology is one of the preferred screening modalities for detection of breast cancer. However, poor signal to noise ratio and the inexorable need to preserve edges defining cancer cells and normal cells, make the segmentation process difficult and hence unsuitable for computer-aided diagnosis of breast cancer. This paper presents key findings from a research conducted on the appraisal of two promising techniques, for the detection of breast cancer: (I) marker-controlled, Level-set segmentation of anisotropic diffusion filtered preprocessed image versus (II) Segmentation using marker-controlled level-set on a Gaussian-filtered image. Gaussian-filtering processes the image uniformly, whereas anisotropic filtering processes only in specific areas of a thermographic image. The pre-processed (Gaussian-filtered and anisotropic-filtered) images of breast samples were then applied for segmentation. The segmentation of breast starts with initial level-set function. In this study, marker refers to the position of the image to which initial level-set function is applied. The markers are generally placed on the left and right side of the breast, which may vary with the breast size. The proposed method was carried out on images from an online database with samples collected from women of varying breast characteristics. It was observed that the breast was able to be segmented out from the background by adjustment of the markers. From the results, it was observed that as a pre-processing technique, anisotropic filtering with level-set segmentation, preserved the edges more effectively than Gaussian filtering. Segmented image, by application of anisotropic filtering was found to be more suitable for feature extraction, enabling automated computer-aided diagnosis of breast cancer.

Keywords: anisotropic diffusion, breast, Gaussian, level-set, thermograms

Procedia PDF Downloads 354

Authors: Jaewoo Choi, Ki-Tae Hwang, Eunyoung Ko

Abstract:

Backgrounds/Aims: Patients with breast cancer are currently classified according to TNM stage. Nevertheless, the actual volume would be mis-estimated, and it would bring on inappropriate diagnosis. Tridimensional volume-stage derived from the ellipsoid formula was presented as useful measure. Methods: The medical records of 480 consecutive breast cancer between January 2001 and March 2013 were retrospectively reviewed. All patients were divided into three groups according to tumor volume by receiver operating characteristic analysis, and the ranges of each volume-stage were that V1 was below 2.5 cc, V2 was exceeded 2.5 and below 10.9 cc, and V3 was exceeded 10.9 cc. We analyzed outcomes of volume-stage and compared disease-free survival (DFS) and overall survival (OS) between size-stage and volume-stage with variant intrinsic factor. Results: In the T2 stage, there were patients who had a smaller volume than 4.2 cc known as maximum value of T1. These findings presented that patients in T1c had poorer DFS than T2-lesser (mean of DFS 48.7 vs. 51.8, p = 0.011). Such is also the case in OS (mean of OS 51.1 vs. 55.3, p = 0.006). The cumulative survival curves for V1, V2 compared T1, T2 showed similarity in DFS (HR 1.9 vs. 1.9), and so did it for V3 compared T3 (HR 3.5 vs. 2.6) significantly. Conclusion: This study demonstrated that tumor volume had good feasibility on the prognosis of patients with breast cancer. We proposed that volume-stage should be considered for an additional stage indicator, particularly in early breast cancer.

Keywords: breast cancer, tridimensional volume of tumor, TNM stage, volume stage

Procedia PDF Downloads 378

Authors: S. Sudhakar, Geetha Manjunath, Siva Teja Kakileti, Himanshu Madhu

Abstract:

Diagnosis of breast cancer at early stages has seen better clinical and survival outcomes. Survival rates in developing countries like India are very low due to accessibility and affordability issues of screening tests such as Mammography. In addition, Mammography is not much effective in younger women with dense breasts. This leaves a gap in current screening methods. Thermalytix is a new technique for detecting breast abnormality in a non-contact, non-invasive way. It is an AI-enabled computer-aided diagnosis solution that automates interpretation of high resolution thermal images and identifies potential malignant lesions. The solution is low cost, easy to use, portable and is effective in all age groups. This paper presents the results of a retrospective comparative analysis of Thermalytix over Mammography and Clinical Breast Examination for breast cancer screening. Thermalytix was found to have better sensitivity than both the tests, with good specificity as well. In addition, Thermalytix identified all malignant patients without palpable lumps.

Keywords: breast cancer screening, radiology, thermalytix, artificial intelligence, thermography

Procedia PDF Downloads 244

Authors: Segen Asayehegn

Abstract:

Introduction: In Tigray, Ethiopia, next to cervical cancer, breast cancer is one of the most common cancer health problems for women. Objectives: This article is proposed to identify the prospective and potential risk factors affecting the time-to-first-recurrence of breast cancer patients in Tigray, Ethiopia. Methods: The data were taken from the patient’s medical record that registered from January 2010 to January 2020. The study considered a sample size of 1842 breast cancer patients. Powerful non-parametric and parametric shared frailty survival regression models (FSRM) were applied, and model comparisons were performed. Results: Out of 1842 breast cancer patients, about 1290 (70.02%) recovered/cured the disease. The median cure time from breast cancer is found at 12.8 months. The model comparison suggested that the lognormal parametric shared a frailty survival regression model predicted that treatment, stage of breast cancer, smoking habit, and marital status significantly affects the first recurrence of breast cancer. Conclusion: Factors like treatment, stages of cancer, and marital status were improved while smoking habits worsened the time to cure breast cancer. Recommendation: Thus, the authors recommend reducing breast cancer health problems, the regional health sector facilities need to be improved. More importantly, concerned bodies and medical doctors should emphasize the identified factors during treatment. Furthermore, general awareness programs should be given to the community on the identified factors.

Keywords: acceleration factor, breast cancer, Ethiopia, shared frailty survival models, Tigray

Procedia PDF Downloads 110

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

Abstract:

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

Procedia PDF Downloads 159

Authors: Ayyaz Hussain, Tariq Sadad

Abstract:

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

Procedia PDF Downloads 107

Authors: Devadrita Dey Sarkar

Abstract:

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)

Procedia PDF Downloads 435

Authors: Huma Naqeeb

Abstract:

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

Procedia PDF Downloads 91

Authors: Marketa Kotova, Jana Kolarova, Ludek Zalud, Petr Dobsak

Abstract:

A game for training of breath (TRABR) for continuous monitoring of pulmonary ventilation during the patients’ therapy focuses especially on monitoring of their ventilation processes. It is necessary to detect, monitor and differentiate abdominal and thoracic breathing during the therapy. It is a fun form of rehabilitation where the patient plays and also practicing isolated breathing. Finally the game to practice breath was designed to evaluate whether the patient uses two types of breathing or not.

Keywords: pulmonary ventilation, thoracic breathing, abdominal breathing, breath monitoring using pressure sensors, game TRABR TRAining of BReath)

Procedia PDF Downloads 465

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

Abstract:

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

Procedia PDF Downloads 108

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

Abstract:

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

Procedia PDF Downloads 352

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

Abstract:

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

Procedia PDF Downloads 200

Authors: Ahmad Jawad Fardin

Abstract:

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

Procedia PDF Downloads 154

Authors: A-Reum Shin, Heon-Seock Cynn, Ji-Hyun Lee, Da-Eun Kim

Abstract:

Round shoulder posture (RSP) is a position of scapular protraction and elevation, which may appear as scapular winging, and humeral internal rotation. Flexed posture (FP) may also affect RSP because FP is characterized by hyperkyphosis, forward head posture, and height reduction. The aim of this study was to investigate the effect of scapular posterior tilting exercise with prone trunk extension on round shoulder posture, activities of lower trapezius and serratus anterior, flexed posture, and thoracic erector spinae activity in subjects with round shoulder posture. Fifteen subjects with round shoulder posture were recruited in this study. Activities of lower trapezius, serratus anterior and thoracic erector spinae were measured during both scapular posterior tilting exercise and scapular posterior tilting exercise with prone trunk extension using electromyography, and round shoulder posture and flexed posture were measured immediately after each exercises using caliper. When the prone trunk extension was applied, the round shoulder posture and flexed posture significantly decreased, activities of lower trapezius and thoracic erector spinae significantly increased (p < 0.05) compared with the scapular posterior tilting exercise alone. There was no significant difference in serratus anterior activity between two exercises. Thus, prone trunk extension could be effective method to improve round shoulder posture during scapular posterior tilting exercise in subjects with round shoulder posture.

Keywords: flexed posture, prone trunk extension, round shoulder posture, scapular posterior tilting

Procedia PDF Downloads 187

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

Abstract:

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

Procedia PDF Downloads 181

Authors: Ali Berkan Ural

Abstract:

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

Procedia PDF Downloads 64

Authors: Ahmed Gonnah, Omar Masoud, Mohamed Abdel-Wahab, Ahmed ElMosalamy, Abdulrahman Al-Naseem

Abstract:

Introduction: Fibroadenomas are solid, mobile, and non-tender benign breast lumps, with the highest prevalence amongst young women aged between 15 and 35. Symptoms can include discomfort, and they can become problematic, particularly when they enlarge, resulting in many referrals for biopsies, with fibroadenomas accounting for 30-75% of the cases. Diagnosis is based on triple assessment that involves a clinical examination, ultrasound imaging and mammography, as well as core needle biopsies. Current management includes observation for 6-12 months, with the indication of definitive surgery, in cases that are older than 35 years or with fibroadenoma persistence. Serious adverse effects of surgery might include nipple-areolar distortion, scarring and damage to the breast tissue, as well as the risks associated with surgery and anesthesia, making it a non-feasible option. Methods: A literature search was performed on the databases EMBASE. MEDLINE/PubMed, Google scholar and Ovid, for English language papers published between 1st of January 2000 and 17th of March 2021. A structured protocol was employed to devise a comprehensive search strategy with keywords and Boolean operators defined by the research question. The keywords used for the search were ‘HIFU’, ‘High-Intensity Focused Ultrasound’, ‘Fibroadenoma’, ‘Breast’, ‘Lesion’. This review was carried out in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: Recently, a thermal ablative technique, High Intensity Focused Ultrasound (HIFU), was found to be a safe, non-invasive, and technically successful alternative, having displayed promising outcomes in reducing the volume of fibroadenomas, pain experienced by patients, and the length of hospitalization. Quality of life improvement was also evidenced, exhibited by the disappearance of symptoms, and enhanced physical activity post-intervention, in addition to patients’ satisfaction with the cosmetic results and future recommendation of the procedure to other patients. Conclusion: Overall, HIFU is a well-tolerated treatment associated with a low risk of complications that can potentially include erythema, skin discoloration and bruising, with the majority of this self-resolving shortly after the procedure.

Keywords: ultrasound, HIFU, breast, efficacy, side effects, fibroadenoma

Procedia PDF Downloads 184

Authors: L. C. Prasanna, Antony Sylvan D’Souza, Kumar M. R. Bhat

Abstract:

Although life as a conjoined twin would seem intolerable, there has recently been an increased interest in this subject because of the increasing number of cases where attempts have been made to separate them surgically. We have reviewed articles on cardiovascular anomalies in conjoined twins and presenting rarest anomaly in dicephalus parapagus fetus having two heads attached to one body from the neck or upper chest downwards, with a pair of limbs and a set of reproductive organs. Both the twins shared a common thoracic cavity with a single sternum. When the thoracic cavity was opened, a common anterior mediastinum was found. On opening the pericardium, two separate, closely apposed hearts were exposed. The two cardia are placed side by side. The left heart was slightly larger than the right and were joined at the atrial levels. Four atrial appendages were present, two for each twin. The atrial complex was a common chamber posterior to the ventricles. A single large tributary which could be taken as inferior vena cava drains into the common atrial chamber. In this case, the heart could not be assigned to either twin and therefore, it is referred to as the shared heart within a common pericardial sac. The right and left descending thoracic aorta have joined with each other just above the diaphragm to form a common descending thoracic aorta which has an opening in the diaphragm to be continued as common abdominal aorta which has a normal branching pattern. Upon an interior dissection, it is observed that the two atria have a wide communication which could be a wide patent foramen ovale and this common atrial cavity has a communication with a remnant of a possible common sinus venosus.

Keywords: atrium, congenital anomaly, conjoined twin, sinus venosus

Procedia PDF Downloads 368

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

Abstract:

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

Procedia PDF Downloads 344

Authors: Sam Khozama, Ali M. Mayya

Abstract:

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

Procedia PDF Downloads 132

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

Abstract:

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

Procedia PDF Downloads 297

Authors: Mina Jafari, Kobra Hamraee, Saied Hossein Hosseini

Abstract:

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

Procedia PDF Downloads 109

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

Abstract:

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

Procedia PDF Downloads 197

Authors: Muneeb Nasir, Misbah Masood, Farrukh Rashid, Abubabakar Shahid

Abstract:

Introduction: Neo-adjuvant chemotherapy is a potent option for triple negative breast cancer (TNBC) as these tumours lack a clearly defined therapeutic target. Several recent studies lend support that pathological complete remission (pCR) is associated with improved disease free survival (DFS) and overall survival (OS) and could be used as surrogate marker for DFS and OS in breast cancer patients. Methods: We have used a four-drug protocol in T3 and T4 TNBC patients either N+ or N- in the neo-adjuvant setting. The 15 patients enrolled in this study had a median age of 45 years. 12 patients went on to complete four planned cycles of B-CAT protocol. The chemotherapy regimen included inj. Bevacizumab 5mg/kg D1, inj. Adriamycin 50mg/m2 D1 and Docetaxel 65mg/m2 on D1. Inj. Cisplatin 60mg/m2 on D2. All patients received GCF support from D4 to D9 of each cycle. Results: Radiological assessment using ultrasound and PET-CT revealed a high percentage of responses. Radiological CR was documented in half of the patients (6/12) after four cycles. Remaining patients went on to receive 2 more cycles before undergoing radical surgery. pCR was documented in 7/12 patients and 3 more had a good partial response. The regimen was toxic and grade ¾ neutropenia was seen in 58% of patients. Four episodes of febrile neutropenia were reported and managed. Non-hematatological toxicities were common with mucositis, diarrhea, asthenia and neuropathy topping the list. Conclusion: B-CAT is a very active combination with very high pCR rates in TNBC. Toxicities though frequent, were manageable on outpatient basis. This protocol warrants further investigation.

Keywords: B-CAT:bevacizumab, cisplatin, adriamycin, taxotere, CR: complete response, pCR: pathological complete response, TNBC: triple negative breast cancer

Procedia PDF Downloads 239

Authors: Oluwaponmile D. Alao

Abstract:

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

Procedia PDF Downloads 305

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

Abstract:

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

Procedia PDF Downloads 269

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

Abstract:

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

Procedia PDF Downloads 332

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

Abstract:

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

Procedia PDF Downloads 52