Search results for: Cancer ovarian

Authors: D. A. Binas, M. Konidari, C. Bourgioti, L. Angela Moulopoulou, T. L. Economopoulos, G. K. Matsopoulos

Abstract:

High grade ovarian epithelial cancer (OEC) is the most fatal gynecological cancer and poor prognosis of this entity is closely related to considerable intratumoral genetic heterogeneity. By examining imaging data, it is possible to assess the heterogeneity of tumorous tissue. This study presents a methodology for aligning, segmenting and finally visualizing information from various magnetic resonance imaging series, in order to construct 3D models of heterogeneity maps from the same tumor in OEC patients. The proposed system may be used as an adjunct digital tool by health professionals for personalized medicine, as it allows for an easy visual assessment of the heterogeneity of the examined tumor.

Keywords: K-means segmentation, ovarian epithelial cancer, quantitative characteristics, registration, tumor visualization.

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Authors: Simone C. F. Neves, Lúcio F. A. Campos, Ewaldo Santana, Ginalber L. O. Serra, Allan K. Barros

Abstract:

We propose a method for discrimination and classification of ovarian with benign, malignant and normal tissue using independent component analysis and neural networks. The method was tested for a proteomic patters set from A database, and radial basis functions neural networks. The best performance was obtained with probabilistic neural networks, resulting I 99% success rate, with 98% of specificity e 100% of sensitivity.

Keywords: Cancer ovarian, Proteomic patterns in serum, independent component analysis and neural networks.

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Authors: Amaneh Javid, Shahin Ahmadian, Ali A. Saboury, Saeed Rezaei-Zarchi

Abstract:

This study determines the effect of naked and heparinbased super-paramagnetic iron oxide nanoparticles on the human cancer cell lines of A2780. Doxorubicin was used as the anticancer drug, entrapped in the SPIO-NPs. This study aimed to decorate nanoparticles with heparin, a molecular ligand for 'active' targeting of cancerous cells and the application of modified-nanoparticles in cancer treatment. The nanoparticles containing the anticancer drug DOX were prepared by a solvent evaporation and emulsification cross-linking method. The physicochemical properties of the nanoparticles were characterized by various techniques, and uniform nanoparticles with an average particle size of 110±15 nm with high encapsulation efficiencies (EE) were obtained. Additionally, a sustained release of DOX from the SPIO-NPs was successful. Cytotoxicity tests showed that the SPIO-DOX-HP had higher cell toxicity than the individual HP and confocal microscopy analysis confirmed excellent cellular uptake efficiency. These results indicate that HP based SPIO-NPs have potential uses as anticancer drug carriers and also have an enhanced anticancer effect.

Keywords: Heparin, A2780 cells, ovarian cancer, nanoparticles, doxorubicin.

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Authors: Marcela Capcarova, Adriana Kolesarova, Marina Medvedova, Peter Petruska, Alexander V. Sirotkin

Abstract:

The aim of this study was to determine the activity of superoxide dismutase (SOD), glutathione peroxidase (GPx), total antioxidant status (TAS) and accumulation of Hsp70 in porcine ovarian granulosa cells after deoxynivalenol (DON) and zearalenone (ZEA) exposure in vitro. Porcine ovarian granulosa cells were incubated with DON/ZEA administrations as follows: group A (10/10 ng/mL), group B (100/100 ng/mL), group C (1000/1000 ng/mL), and the control group without any additions for 24h. In this study mycotoxins developed stress reaction of porcine ovarian granulosa cells and increased accumulation of Hsp70 what resulted in increasing activities of SOD and GPx in groups with lower doses of mycotoxins. High dose of DON and ZEA had opposite effect on GPx activity than the lower doses. Slight increase in TAS of porcine granulosa cells was observed after mycotoxins exposure. These results contribute towards the understanding of cellular stress and its response.

Keywords: Deoxynivalenol, zearalenone, antioxidants, Hsp70, granulosa cells.

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Authors: A. Taqaddas

Abstract:

Magnetic Nanoparticles (MNPs) have great potential to overcome many of the shortcomings of the present diagnostic and therapeutic approaches used in cancer diagnosis and treatment. This Literature review discusses the use of Magnetic Nanoparticles focusing mainly on Iron oxide based MNPs in cancer imaging using MRI.

Keywords: Cancer, Imaging, Magnetic Nanoparticles, MRI.

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Authors: Shabbar Naqvi, Jonathan M. Garibaldi

Abstract:

Breast cancer is one of the most frequent occurring cancers in women throughout the world including U.K. The grading of this cancer plays a vital role in the prognosis of the disease. In this paper we present an overview of the use of advanced computational method of fuzzy inference system as a tool for the automation of breast cancer grading. A new spectral data set obtained from Fourier Transform Infrared Spectroscopy (FTIR) of cancer patients has been used for this study. The future work outlines the potential areas of fuzzy systems that can be used for the automation of breast cancer grading.

Keywords: Breast cancer, FTIR, fuzzy inference system, principal component analysis

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Authors: Amir Ghasemlouei, Alireza Khalaj

Abstract:

Breast cancer is in the top rate of cancer. We analyzed the prevalence of obesity and its association with breast cancer and finally we reviewed 25 article that 320 patient and 320 control which enrolled to our study. The distribution of breast cancer patients and controls with respect to their anthropometric indices in patients with higher weight, which was statistically significant (60.2 ± 10.2 kg) compared with control group (56.1 ± 11.3 kg). The body mass index of patients was (26.06+/-3.42) and significantly higher than the control group (24.1+/-1.7). Obesity leads to increased levels of adipose tissue in the body that can be stored toxins and carcinogens to produce a continuous supply. Due to the high level of fat and the role of estrogen in a woman which is endogenous estrogen of the tumor and regulates the activities of growth steroids, obesity has confirmed as a risk factor for breast cancer. Our study and other studies have shown that obesity is a risk factor for breast cancer. And it can be prevented with a weight loss intervention for breast cancer in the future.

Keywords: Breast cancer, review study, obesity, overweight.

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Authors: Michael Netzer, Michael Seger, Mahesh Visvanathan, Bernhard Pfeifer, Gerald H. Lushington, Christian Baumgartner

Abstract:

Lung cancer accounts for the most cancer related deaths for men as well as for women. The identification of cancer associated genes and the related pathways are essential to provide an important possibility in the prevention of many types of cancer. In this work two filter approaches, namely the information gain and the biomarker identifier (BMI) are used for the identification of different types of small-cell and non-small-cell lung cancer. A new method to determine the BMI thresholds is proposed to prioritize genes (i.e., primary, secondary and tertiary) using a k-means clustering approach. Sets of key genes were identified that can be found in several pathways. It turned out that the modified BMI is well suited for microarray data and therefore BMI is proposed as a powerful tool for the search for new and so far undiscovered genes related to cancer.

Keywords: lung cancer, micro arrays, data mining, feature selection.

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Authors: [email protected]

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 need 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), ensemble learning with hyper parameters optimization, 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, Score-Level Fusion.

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Authors: F. Bakiri, T. Rexha, A. Mitre

Abstract:

The aim of our study was to compare knowledge of regarding HPV and cervical cancer in female student of 18 to 26 years old, with or without sexual intercourse. We conducted a questionnaire survey of the students (N=568), in Faculty of Natural Sciences, Tirana, Albania. Sexually experienced students were more likely to have heard of risk factors such as multiple sex partners, sexual intercourse before age 18, having contracted any sexually transmitted diseases, having genital warts, smoking cigarettes, use of oral contraceptive, poor diet or nutrition and using tampons. No significant sexually experience differences were observed in knowledge of the way of transmission of the virus associated with cervical cancer knowledge, the virus associated with cervical cancer knowledge, the prevention of cervical cancer knowledge. On the other hand strong significant sexually experience differences were observed in knowledge of the diagnostic way of cervical cancer and what HPV can cause knowledge.

Keywords: Risk factors, HPV, Cervical cancer, Albanian students.

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Authors: Chunling Cong, Chris.P.Tsokos

Abstract:

The objective of the present research manuscript is to perform parametric, nonparametric, and decision tree analysis to evaluate two treatments that are being used for breast cancer patients. Our study is based on utilizing real data which was initially used in “Tamoxifen with or without breast irradiation in women of 50 years of age or older with early breast cancer" [1], and the data is supplied to us by N.A. Ibrahim “Decision tree for competing risks survival probability in breast cancer study" [2]. We agree upon certain aspects of our findings with the published results. However, in this manuscript, we focus on relapse time of breast cancer patients instead of survival time and parametric analysis instead of semi-parametric decision tree analysis is applied to provide more precise recommendations of effectiveness of the two treatments with respect to reoccurrence of breast cancer.

Keywords: decision tree, breast cancer treatments, parametricanalysis, non-parametric analysis

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Authors: Marios Poulos, Eirini Maliagani, Minas Paschopoulos, George Bokos

Abstract:

The purpose of my research proposal is to demonstrate that there is a relationship between EEG and endometrial cancer. The above relationship is based on an Aristotelian Syllogism; since it is known that the 14-3-3 protein is related to the electrical activity of the brain via control of the flow of Na+ and K+ ions and since it is also known that many types of cancer are associated with 14-3-3 protein, it is possible that there is a relationship between EEG and cancer. This research will be carried out by well-defined diagnostic indicators, obtained via the EEG, using signal processing procedures and pattern recognition tools such as neural networks in order to recognize the endometrial cancer type. The current research shall compare the findings from EEG and hysteroscopy performed on women of a wide age range. Moreover, this practice could be expanded to other types of cancer. The implementation of this methodology will be completed with the creation of an ontology. This ontology shall define the concepts existing in this research-s domain and the relationships between them. It will represent the types of relationships between hysteroscopy and EEG findings.

Keywords: Bioinformatics, Protein 14-3-3, EEG, Endometrial cancer, Ontology.

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Authors: S. Usha, S. Arumugam

Abstract:

Cancer affects people globally with breast cancer being a leading killer. Breast cancer is due to the uncontrollable multiplication of cells resulting in a tumour or neoplasm. Tumours are called ‘benign’ when cancerous cells do not ravage other body tissues and ‘malignant’ if they do so. As mammography is an effective breast cancer detection tool at an early stage which is the most treatable stage it is the primary imaging modality for screening and diagnosis of this cancer type. This paper presents an automatic mammogram classification technique using wavelet and Gabor filter. Correlation feature selection is used to reduce the feature set and selected features are classified using different decision trees.

Keywords: Breast Cancer, Mammogram, Symlet Wavelets, Gabor Filters, Decision Trees

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Authors: Phannee Saengkaew, Weerasak Ussawawongaraya, Sasiphan Khaweerat, Supagorn Rugmai, Sirisart Ouajai, Jiraporn Luengviriya, Sakuntam Sanorpim, Manop Tirarattanasompot, Somboon Rhianphumikarakit

Abstract:

We present a preliminary x-ray study on human-hair microstructures for a health-state indicator, in particular a cancer case. As an uncomplicated and low-cost method of x-ray technique, the human-hair microstructure was analyzed by wide-angle x-ray diffractions (XRD) and small-angle x-ray scattering (SAXS). The XRD measurements exhibited the simply reflections at the d-spacing of 28 Å, 9.4 Å and 4.4 Å representing to the periodic distance of the protein matrix of the human-hair macrofibrous and the diameter and the repeated spacing of the polypeptide alpha helixes of the photofibrils of the human-hair microfibrous, respectively. When compared to the normal cases, the unhealthy cases including to the breast- and ovarian-cancer cases obtained higher normalized ratios of the x-ray diffracting peaks of 9.4 Å and 4.4 Å. This likely resulted from the varied distributions of microstructures by a molecular alteration. As an elemental analysis by x-ray fluorescence (XRF), the normalized quantitative ratios of zinc(Zn)/calcium(Ca) and iron(Fe)/calcium(Ca) were determined. Analogously, both Zn/Ca and Fe/Ca ratios of the unhealthy cases were obtained higher than both of the normal cases were. Combining the structural analysis by XRD measurements and the elemental analysis by XRF measurements exhibited that the modified fibrous microstructures of hair samples were in relation to their altered elemental compositions. Therefore, these microstructural and elemental analyses of hair samples will be benefit to associate with a diagnosis of cancer and genetic diseases. This functional method would lower a risk of such diseases by the early diagnosis. However, the high-intensity x-ray source, the highresolution x-ray detector, and more hair samples are necessarily desired to develop this x-ray technique and the efficiency would be enhanced by including the skin and fingernail samples with the human-hair analysis.

Keywords: Human-hair analysis, XRD, SAXS, breast cancer, health-state indicator

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Authors: Nilubon Kurubanjerdjit, Nattakarn Iam-On, Ka-Lok Ng

Abstract:

MicroRNAs are small non-coding RNA found in many different species. They play crucial roles in cancer such as biological processes of apoptosis and proliferation. The identification of microRNA-target genes can be an essential first step towards to reveal the role of microRNA in various cancer types. In this paper, we predict miRNA-target genes for lung cancer by integrating prediction scores from miRanda and PITA algorithms used as a feature vector of miRNA-target interaction. Then, machine-learning algorithms were implemented for making a final prediction. The approach developed in this study should be of value for future studies into understanding the role of miRNAs in molecular mechanisms enabling lung cancer formation.

Keywords: MicroRNA, miRNAs, lung cancer, machine learning, Naïve Bayes, SVM.

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Authors: Maria L. McLeod

Abstract:

This study examines the ways in which cancer patient narratives are portrayed and framed on the websites of three leading U.S. cancer care centers – The University of Texas MD Anderson Cancer Center in Houston, Memorial Sloan Kettering Cancer Center in New York, and Seattle Cancer Care Alliance. Thirty patient stories, 10 from each cancer center website blog, were analyzed using qualitative and quantitative textual analysis of unstructured data, documenting common themes and other elements of story structure and content. Patient narratives were coded using grounded theory as the basis for conducting emergent qualitative research. As part of a systematic, inductive approach to collecting and analyzing data, recurrent and unique themes were examined and compared in terms of positive and negative framing, patient agency, and institutional praise. All three of these cancer care centers are teaching hospitals, with university affiliations, that emphasize an evidence-based scientific approach to treatment that utilizes the latest research and cutting-edge techniques and technology. The featured cancer stories suggest positive outcomes based on anecdotal narratives as opposed to the science-based treatment models employed by the cancer centers. An analysis of 30 sample stories found skewed representation of the “cancer experience” that emphasizes positive outcomes while minimizing or excluding more negative realities of cancer diagnosis and treatment. The stories also deemphasize patient agency, instead focusing on deference and gratitude toward the cancer care centers, which are cast in the role of savior.  

Keywords: Cancer framing, cancer narratives, survivor stories, patient narratives.

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Authors: Faten A. Khorshid

Abstract:

Breast cancer is the most common malignancy in the world among women. Many therapies have been designed to treat this disease. Mamectomy, chemotherapy and radiotherapy are still the main therapies of breast cancer. However, the results were unsatisfactory and still far from the ideal treatment. PM 701is a natural product, has anticancer activity. The bioactive fraction PMF and subfraction PMFK had been isolated from PM701. PM 701 and its fractions were proved to have a cytotoxic properties against different cancer cell lines. This article is directed for the further examination of lyophilized PM701 and its active fractions on the growth of breast cancer cells (MCF-7). PM 701, PMF or PMFK were adding to the cultural medium, where MCF-7 is incubated. PM 701, PMF or PMFK were able to inhibit significantly the proliferation of MCF-7 cells, Moreover these new agents were proved to induce apoptosis of the breast cancer cells; through its direct effect on the nuclei.

Keywords: Anticancer agent, breast carcinoma, MCF-7 cell line, PM 701

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Authors: M. Caramihai, Irina Severin, H. Balan, A. Blidaru, V. Balanica

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Accurate assessment of the primary tumor response to treatment is important in the management of breast cancer. This paper introduces a new set of treatment evaluation indicators for breast cancer cases based on the computational process of three known metrics, the Euclidian, Hamming and Levenshtein distances. The distance principals are applied to pairs of mammograms and/or echograms, recorded before and after treatment, determining a reference point in judging the evolution amount of the studied carcinoma. The obtained numerical results are indeed very transparent and indicate not only the evolution or the involution of the tumor under treatment, but also a quantitative measurement of the benefit in using the selected method of treatment.

Keywords: Breast cancer, Distance metrics, Cancer treatment evaluation.

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Authors: Zhang Linan, Jihwan Song, Dongchoul Kim

Abstract:

In this study, a three-dimensional haptotaxis model to simulate the migration of a population of cancer cells has been proposed. The invasion of cancer cells is related with the hapto-attractant and the effect of the interface energies between the cells and the ECM. The diffuse interface model, which incorporates the haptotaxis mechanism and interface energies, is employed. The semi-implicit Fourier spectral scheme is adopted for efficient evaluation of the simulation. The simulation results thoroughly reveal the dynamics of cancer-cell migration.

Keywords: Haptotaxis, Cancer Cells, Cell Migration, Interface Energy, Diffuse Interface Model

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Authors: A. Taqaddas

Abstract:

The following case study presents the management of stage III Differentiated Thyroid Cancer (DTC) patient in an NHS hospital in London, UK during period of 2004-2005.

Keywords: Differentiated Thyroid Cancer, Oncological Management, Papillary, Thyroid Cancer, Stage III.

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Authors: Devasis Ghosh

Abstract:

The main hindrance to total cure of cancer is a) the failure to control continued production of cancer cells, b) its sustenance and c) its metastasis. This review study has tried to address this issue of total cancer cure in a more innovative way. A 10-pronged “CRAB METHOD”, a novel holistic scientific approach of Cancer treatment has been hypothesized in this paper. Apart from available Chemotherapy, Radiotherapy and Oncosurgery, (which shall not be discussed here), seven other points of interference and treatment has been suggested, i.e. 1. Efficient stress management. 2. Dampening of ATF3 expression. 3. Selective inhibition of Platelet Activity. 4. Modulation of serotonin production, metabolism and 5HT receptor antagonism. 5. Auxin, its anti-proliferative potential and its modulation. 6. Melatonin supplementation because of its oncostatic properties. 7. HDAC Inhibitors especially valproic acid use due to its apoptotic role in many cancers. If all the above stated seven steps are thoroughly taken care of at the time of initial diagnosis of cancer along with the available treatment modalities of Chemotherapy, Radiotherapy and Oncosurgery, then perhaps, the morbidity and mortality rate of cancer may be greatly reduced.

Keywords: ATF3 dampening, auxin modulation, cancer, platelet activation, serotonin, stress, valproic acid.

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Authors: Valentina L. Kouznetsova, Jonathan W. Wang, Igor F. Tsigelny

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Metabolomics has become a rising field of research for various diseases, particularly cancer. Increases or decreases in metabolite concentrations in the human body are indicative of various cancers. Further elucidation of metabolic pathways and their significance in cancer research may greatly spur medicinal discovery. We analyzed the metabolomics profiles of lung cancer. Thirty-three metabolites were selected as significant. These metabolites are involved in 37 metabolic pathways delivered by MetaboAnalyst software. The top pathways are glyoxylate and dicarboxylate pathway (its hubs are formic acid and glyoxylic acid) along with Citrate cycle pathway followed by Taurine and hypotaurine pathway (the hubs in the latter are taurine and sulfoacetaldehyde) and Glycine, serine, and threonine pathway (the hubs are glycine and L-serine). We studied interactions of the metabolites with the proteins involved in cancer-related signaling networks, and developed an approach to metabolomics biomarker use in cancer diagnostics. Our analysis showed that a significant part of lung-cancer-related metabolites interacts with main cancer-related signaling pathways present in this network: PI3K–mTOR–AKT pathway, RAS–RAF–ERK1/2 pathway, and NFKB pathway. These results can be employed for use of metabolomics profiles in elucidation of the related cancer proteins signaling networks.

Keywords: Cancer, metabolites, metabolic pathway, signaling pathway.

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Authors: Mashayekh Amir Shahriar, Akhlaghi Morteza, Rajaee Hajar, Khani Mohammad Reza, Shokri Babak

Abstract:

A new and novel approach in medicine is the use of cold plasma for various applications such as sterilization blood coagulation and cancer cell treatment. In this paper a pin-to-hole plasma jet suitable for biological applications is investigated and characterized and the possibility and feasibility of cancer cell treatment is evaluated. The characterization includes power consumption via Lissajous method, thermal behavior of plasma using Infra-red camera as a novel method, Optical Emission Spectroscopy (OES) to determine the species that are generated. Treatment of leukemia cancer cells is also implemented and MTT assay is used to evaluate viability.

Keywords: Atmospheric Pressure Plasma Jet (APPJ), Plasma Medicine, Cancer cell treatment, leukemia.

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Authors: G. Tamilpavai, C. Vishnuppriya

Abstract:

Studying DNA (deoxyribonucleic acid) sequence is useful in biological processes and it is applied in the fields such as diagnostic and forensic research. DNA is the hereditary information in human and almost all other organisms. It is passed to their generations. Earlier stage detection of defective DNA sequence may lead to many developments in the field of Bioinformatics. Nowadays various tedious techniques are used to identify defective DNA. The proposed work is to analyze and identify the cancer-causing DNA motif in a given sequence. Initially the human DNA sequence is separated as k-mers using k-mer separation rule. The separated k-mers are clustered using Self Organizing Map (SOM). Using Levenshtein distance measure, cancer associated DNA motif is identified from the k-mer clusters. Experimental results of this work indicate the presence or absence of cancer causing DNA motif. If the cancer associated DNA motif is found in DNA, it is declared as the cancer disease causing DNA sequence. Otherwise the input human DNA is declared as normal sequence. Finally, elapsed time is calculated for finding the presence of cancer causing DNA motif using clustering formation. It is compared with normal process of finding cancer causing DNA motif. Locating cancer associated motif is easier in cluster formation process than the other one. The proposed work will be an initiative aid for finding genetic disease related research.

Keywords: Bioinformatics, cancer motif, DNA, k-mers, Levenshtein distance, SOM.

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Authors: A. Taqaddas

Abstract:

Chemotherapy and radiotherapy are one of the major treatment modalities that play important role in the management of a number of different cancers. This study for the first time evaluates the toxicity of these treatment modalities and its impact on quality of life of cancer patients in Pakistan. The study also for the first time determines what cancer patients of different ages and cancer stages believe would be an effective intervention to manage their psychosocial needs and treatment induced toxicity. The article also provides evidence based approach for the use of variety of interventions to mange cancer treatment induced morbidity and toxicity. In light of the present study and reviewed research data, evidence based recommendations are also made for selection of appropriate interventions to manage Pain, Nausea and Vomiting, Anxiety and Depression, Fatigue and Overall QOL of cancer survivors.

Keywords: Chemotherapy Toxicity, Psycho-Social Interventions, Quality of Life, Radiotherapy Toxicity.

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Authors: B. Salmasian, A. Rabiee, T. Yousefzadeh

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In this research, the risk assessment of radiation hazard for the Research Nuclear Reactor has been studied. In the current study, the MCNPx computational code has been used and coupled with a developed program using MATLAB software to evaluate Total Effective Dose Equivalent (TEDE) and cancer risk according to the BEIR equations for various human organs. In this study, the risk assessment of cancer has been calculated for ten years after exposure, in each of body organs of different ages and sexes. Also, the risk assessment of cancer has been calculated in each of body organs of different ages and sexes due to exposure after the retirement of the reactor staff. According to obtained results, a conservative whole-body dose rate, during a year, is 0.261 Sv and the probability the cancer risk for women is more than men and for children is more than adults. It has been shown that thyroid cancer was more possible than others.

Keywords: MCNPx code, BEIR equation, equivalent dose, risk analysis.

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Authors: Ş. Çiftcioğlu, E. Efe

Abstract:

In recent years, cancer has been at the top of diseases that cause death in children. Adequate and balanced nutrition plays an important role in the treatment of cancer. Cancer and cancer treatment is affecting food intake, absorption and metabolism, causing nutritional disorders. Appropriate nutrition is very important for the cancerous child to feel well before, during and after the treatment. There are various difficulties in feeding children with cancer. These are the cancer-related factors. Other factors are environmental and behavioral. As health professionals who spend more time with children in the hospital, nurses should be able to support the children on nutrition and help them to have balanced nutrition. This study aimed to evaluate the importance of nursing approaches in the nutrition of children with cancer. This article is planned as a review article by searching the literature on this field. Anorexia may develop due to psychogenic causes or chemotherapeutic agents or accompanying infections and nutrient uptake may be reduced.  In addition, stomatitis, mucositis, taste and odor changes in the mouth, the feeling of nausea, vomiting and diarrhea can also reduce oral intake and result in significant losses in the energy deficit. In assessing the nutritional status of children with cancer, determining weight loss and good nutrition is essential anamnesis of a child.  Some anthropometric measurements and biochemical tests should be used to evaluate the nutrition of the child. The nutritional status of pediatric cancer patients has been studied for a long time and malnutrition, in particular under nutrition, in this population has long been recognized. Yet, its management remains variable with many malnourished children going unrecognized and consequently untreated. Nutritional support is important to pediatric cancer patients and should be integrated into the overall treatment of these children.

Keywords: Cancer treatment, children, complication, nutrition, nursing approaches.

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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.

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Authors: E. B. Jo, J. H. Lee, J. Y. Park, S. M. Kim

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In this study, we present an advanced detection technique for mass type breast cancer based on texture information of organs. The proposed method detects the cancer areas in three stages. In the first stage, the midpoints of mass area are determined based on AHE (Adaptive Histogram Equalization). In the second stage, we set the threshold coefficient of homogeneity by using MLE (Maximum Likelihood Estimation) to compute the uniformity of texture. Finally, mass type cancer tissues are extracted from the original image. As a result, it was observed that the proposed method shows an improved detection performance on dense breast tissues of Korean women compared with the existing methods. It is expected that the proposed method may provide additional diagnostic information for detection of mass-type breast cancer.

Keywords: Mass Type Breast Cancer, Mammography, Maximum Likelihood Estimation (MLE), Ranklets, SVM

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Authors: Souâd Demigha

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Early detection of breast cancer is considered as a major public health issue. Breast cancer screening is not generalized to the entire population due to a lack of resources, staff and appropriate tools. Systematic screening can result in a volume of data which can not be managed by present computer architecture, either in terms of storage capabilities or in terms of exploitation tools. We propose in this paper to design and develop a data warehouse system in radiology-senology (DWRS). The aim of such a system is on one hand, to support this important volume of information providing from multiple sources of data and images and for the other hand, to help assist breast cancer screening in diagnosis, education and research.

Keywords: Breast cancer screening, data warehouse, diagnosis, education, research.

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