Search results for: cancer tissue classification

Authors: Fakhrosadat Sajjadian, Ramin Ghasemi Shayan

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The tumor microenvironment plays an fundamental part in tumor start, movement, metastasis, and treatment resistance. It varies from ordinary tissue in terms of its extracellular network, vascular and lymphatic arrange, as well as physiological conditions. The clinical application of atomic cancer imaging is regularly prevented by the tall commercialization costs of focused on imaging operators as well as the constrained clinical applications and little showcase measure of a few operators. . Since numerous cancer types share comparable characteristics of the tumor microenvironment, the capacity to target these biomarkers has the potential to supply clinically translatable atomic imaging advances for numerous types encompassing cancer and broad clinical applications. Noteworthy advance has been made in focusing on the tumor microenvironment for atomic cancer imaging. In this survey, we summarize the standards and methodologies of later progresses in atomic imaging of the tumor microenvironment, utilizing distinctive imaging modalities for early discovery and conclusion of cancer. To conclude, The tumor microenvironment (TME) encompassing tumor cells could be a profoundly energetic and heterogeneous composition of safe cells, fibroblasts, forerunner cells, endothelial cells, flagging atoms and extracellular network (ECM) components.

Keywords: molecular, imaging, TME, medicine

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Authors: Ilma Robo, Saimir Heta, Vera Ostreni, Elsaida Agrushi, Eduart Kapaj

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Introduction: Cyclic hormonal fluctuations are known from literature to have a clinically visible effects on gingival tissue reactions, to the diagnosed processes of gingival inflammation. Materials and methods: At a total of 47 female patients, ad-hock presented at the University Clinic, were recorded data on effect of hormonal oscillations at periodontal treatment protocol. Oral examination was performed on soft tissue of gingiva and the oral mucous membrane, always respecting the air-drying procedure and then checking with free eye differences in oral mucosal relief. After the patients were informed about the study protocol, the purpose of the study and the ongoing procedure, verbal consensus was required. Results: The study was conducted in a total of 47 patients, out of which 13 patients were under the gingivitis classification, and 24 patients under the periodontal classification. Patients included in the study are divided by age, cycle week respectively 1,2,3 and 4.The younger age of female patients is more prone to the appearance of gingivitis, which is further aggravated by the effects of sexual hormones and the effect of the controlled or non-regulated fluctuations of the latter. Conclusions: The healing process is more fuel-intensive in the absence of high hormone levels, as they are these pro-inflammatory hormones, both in or near the ho Younger women are more open to volunteering in studies that record individual and study data that may last in time.

Keywords: gingiva, hormonal oscillations, female patients, mucosa, periodontal non-surgical treatment

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Authors: A. Dashti, M. Eskandari, L. Farahmand, P. Parvin, A. Jafargholi

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Breast Cancer is one of the most considerable diseases in the United States and other countries and is the second leading cause of death in women. Common breast cancer treatments would lead to adverse side effects such as loss of hair, nausea, and weakness. These complications arise because these cancer treatments damage some healthy cells while eliminating the cancer cells. In an effort to address these complications, laser radiation was utilized and tested as a targeted cancer treatment for breast cancer. In this regard, tissue engineering approaches are being employed by using an electrospun scaffold in order to facilitate the growth of breast cancer cells. Polycaprolacton (PCL) was used as a material for scaffold fabricating because of its biocompatibility, biodegradability, and supporting cell growth. The specific breast cancer cells have the ability to create a three-dimensional cell cluster due to the spontaneous accumulation of cells in the porosity of the scaffold under some specific conditions. Therefore, we are looking for a higher density of porosity and larger pore size. Fibers showed uniform diameter distribution and final scaffold had optimum characteristics with approximately 40% porosity. The images were taken by SEM and the density and the size of the porosity were determined with the Image. After scaffold preparation, it has cross-linked by glutaraldehyde. Then, it has been washed with glycine and phosphate buffer saline (PBS), in order to neutralize the residual glutaraldehyde. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromidefor (MTT) results have represented approximately 91.13% viability of the scaffolds for cancer cells. In order to create a cluster, Michigan Cancer Foundation-7 (MCF-7, breast cancer cell line) and Michigan Cancer Foundation-10A (MCF-10A, human mammary epithelial cell line) cells were cultured on the scaffold in 24 well plate for five days. Then, we have exposed the cluster to the laser diode 808 nm radiation to investigate the effect of laser on the tumor with different power and time. Under the same conditions, cancer cells lost their viability more than the healthy ones. In conclusion, laser therapy is a viable method to destroy the target cells and has a minimum effect on the healthy tissues and cells and it can improve the other method of cancer treatments limitations.

Keywords: breast cancer, electrospun scaffold, polycaprolacton, laser diode, cancer treatment

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Authors: Jacklynn Walters, Amanda A. Alblas, Linda M. Greyling

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Cervical carcinoma is the second most common cancer found in women. Diagnosis of skeletal metastases is uncommon in cervical cancer patients. The aim of this study was to determine the prevalence of skeletal metastases in in a Western Cape skeletal population. Skeletal samples (n=14) from the Kirsten Skeletal Collection at Stellenbosch University, diagnosed pre-mortem with cervical cancer, were examined. Macroscopic analysis was done using low magnification to examine each skeletal element for signs of disease. Skeletons were also x-rayed using the Lodox® Statscan® Imaging system and the scans evaluated by a musculoskeletal radiologist. Three (21%) of the skeletons showed metastases, with the os coxae and lower vertebral column affected in all three cases. Furthermore, metastases occurred in the scapulae and ribs in two of the cases and in one case the skull, mandible, and long bones were affected. Additionally, three skeletons without evidence of skeletal metastases presented with a periosteal reaction on the os coxae in response to the diseased adjacent soft tissue. Previous studies observed that skeletal metastases are more common than what is diagnosed pre-mortem with the vertebral spine most commonly affected. The findings of this study agree with previous reports and illustrate the effectiveness of the Lodox® scanner in diagnoses of metastases in skeletal material.

Keywords: cancer, cervix, radiology, skeletal metastases

Procedia PDF Downloads 335

Authors: Maria Karnachoriti, Ellas Spyratou, Dimitrios Lykidis, Maria Lambropoulou, Yiannis S. Raptis, Ioannis Seimenis, Efstathios P. Efstathopoulos, Athanassios G. Kontos

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Colorectal cancer is the third most common cancer diagnosed in Europe, according to the latest incidence data provided by the World Health Organization (WHO), and early diagnosis has proved to be the key in reducing cancer-related mortality. In cases where surgical interventions are required for cancer treatment, the accurate discrimination between healthy and cancerous tissues is critical for the postoperative care of the patient. The current study focuses on the ex vivo handling of surgically excised colorectal specimens and the acquisition of their spectral fingerprints using Raman spectroscopy. Acquired data were analyzed in an effort to discriminate, in microscopic scale, between healthy and malignant margins. Raman spectroscopy is a spectroscopic technique with high detection sensitivity and spatial resolution of few micrometers. The spectral fingerprint which is produced during laser-tissue interaction is unique and characterizes the biostructure and its inflammatory or cancer state. Numerous published studies have demonstrated the potential of the technique as a tool for the discrimination between healthy and malignant tissues/cells either ex vivo or in vivo. However, the handling of the excised human specimens and the Raman measurement conditions remain challenging, unavoidably affecting measurement reliability and repeatability, as well as the technique’s overall accuracy and sensitivity. Therefore, tissue handling has to be optimized and standardized to ensure preservation of cell integrity and hydration level. Various strategies have been implemented in the past, including the use of balanced salt solutions, small humidifiers or pump-reservoir-pipette systems. In the current study, human colorectal specimens of 10X5 mm were collected from 5 patients up to now who underwent open surgery for colorectal cancer. A novel, non-toxic zinc-based fixative (Z7) was used for tissue preservation. Z7 demonstrates excellent protein preservation and protection against tissue autolysis. Micro-Raman spectra were recorded with a Renishaw Invia spectrometer from successive random 2 micrometers spots upon excitation at 785 nm to decrease fluorescent background and secure avoidance of tissue photodegradation. A temperature-controlled approach was adopted to stabilize the tissue at 2 °C, thus minimizing dehydration effects and consequent focus drift during measurement. A broad spectral range, 500-3200 cm-1,was covered with five consecutive full scans that lasted for 20 minutes in total. The average spectra were used for least square fitting analysis of the Raman modes.Subtle Raman differences were observed between normal and cancerous colorectal tissues mainly in the intensities of the 1556 cm-1 and 1628 cm-1 Raman modes which correspond to v(C=C) vibrations in porphyrins, as well as in the range of 2800-3000 cm-1 due to CH2 stretching of lipids and CH3 stretching of proteins. Raman spectra evaluation was supported by histological findings from twin specimens. This study demonstrates that Raman spectroscopy may constitute a promising tool for real-time verification of clear margins in colorectal cancer open surgery.

Keywords: colorectal cancer, Raman spectroscopy, malignant margins, spectral fingerprints

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Authors: Karim Abouelmehdi, Loubna Dali, Elmoutaoukkil Abdelmajid, Hoda Elsayed, Eladnani Fatiha, Benihssane Abderahim

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The security of cloud services is the concern of cloud service providers. In this paper, we will mention different classifications of cloud attacks referred by specialized organizations. Each agency has its classification of well-defined properties. The purpose is to present a high-level classification of current research in cloud computing security. This classification is organized around attack strategies and corresponding defenses.

Keywords: cloud computing, classification, risk, security

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Authors: Ipsita Biswas, Arnab Sarkar, Ashikur Rahaman, Gopeswar Mukherjee, Subhrangsu Chatterjee, Shamee Bhattacharjee, Deba Prasad Mandal

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One of the major reasons for the high mortality rate of lung cancer is the substantial delays in disease detection at late metastatic stages. It is of utmost importance to understand the detailed molecular signaling and detect the molecular markers that can be used for the early diagnosis of cancer. Several studies explored the emerging roles of long noncoding RNAs (lncRNAs) in various cancers as well as lung cancer. A long non-coding RNA LINC00273 was recently discovered to promote cancer cell migration and invasion, and its positive correlation with the pathological stages of metastasis may prove it to be a potential target for inhibiting cancer cell metastasis. Comparing real-time expression of LINC00273 in various human clinical cancer tissue samples with normal tissue samples revealed significantly higher expression in cancer tissues. This long intergenic noncoding RNA was found to be highly expressed in human liver tumor-initiating cells, human gastric adenocarcinoma AGS cell line, as well as human non-small cell lung cancer A549 cell line. SiRNA and shRNA-induced knockdown of LINC00273 in both in vitro and in vivo nude mice significantly subsided AGS and A549 cancer cell migration and invasion. LINC00273 knockdown also reduced TGF-β induced SNAIL, SLUG, VIMENTIN, ZEB1 expression, and metastasis in A549 cells. Plenty of reports have suggested the role of microRNAs of the miR200 family in reversing epithelial to mesenchymal transition (EMT) by inhibiting ZEB transcription factors. In this study, hsa-miR-200a-3p was predicted via IntaRNA-Freiburg RNA tools to be a potential target of LINC00273 with a negative free binding energy of −8.793 kcal/mol, and this interaction was verified as a confirmed target of LINC00273 by RNA pulldown, real-time PCR and luciferase assay. Mechanistically, LINC00273 accelerated TGF-β induced EMT by sponging hsa-miR-200a-3p which in turn liberated ZEB1 and promoted prometastatic functions in A549 cells in vitro as verified by real-time PCR and western blotting. The similar expression patterns of these EMT regulatory pathway molecules, viz. LINC00273, hsa-miR-200a-3p, ZEB1 and TGF-β, were also detected in various clinical samples like breast cancer tissues, oral cancer tissues, lung cancer tissues, etc. Overall, this LINC00273 mediated EMT regulatory signaling can serve as a potential therapeutic target for the prevention of lung cancer metastasis.

Keywords: epithelial to mesenchymal transition, long noncoding RNA, microRNA, non-small-cell lung carcinoma

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Authors: Shu-Ching Chen, Li-Yun Lee

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The purpose of the study was to identify the factors associated with head and neck cancer-related lymphoedema (HNCRL)-related symptoms, body image, and HNCRL-related functional outcomes among patients with resected advanced head and neck cancer. A cross-sectional correlational design was conducted to examine the predictors of HNCRL-related functional outcomes in patients with resected advanced head and neck cancer. Eligible patients were recruited from a single medical center in northern Taiwan. Consecutive patients were approached and recruited from the Radiation Head and Neck Outpatient Department of this medical center. Eligible subjects were assessed for the Symptom Distress Scale–Modified for Head and Neck Cancer (SDS-mhnc), Brief International Classification of Functioning, Disability and Health (ICF) Core Set for Head and Neck Cancer (BCSQ-H&N), Body Image Scale–Modified (BIS-m), The MD Anderson Head and Neck Lymphedema Rating Scale (MDAHNLRS), The Foldi’s Stages of Lymphedema (Foldi’s Scale), Patterson’s Scale, UCLA Shoulder Rating Scale (UCLA SRS), and Karnofsky’s Performance Status Index (KPS). The results showed that the worst problems with body HNCRL functional outcomes. Patients’ HNCRL symptom distress and performance status are robust predictors across over for overall HNCRL functional outcomes, problems with body HNCRL functional outcomes, and activity and social functioning HNCRL functional outcomes. Based on the results of this period research program, we will develop a Cancer Rehabilitation and Lymphedema Care Program (CRLCP) to use in the care of patients with resected advanced head and neck cancer.

Keywords: head and neck cancer, resected, lymphedema, symptom, body image, functional outcome

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Authors: Siva Chander Chabattula, Piyush Kumar Gupta, Debashis Chakraborty, Rama Shanker Verma

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Green nanoparticles have gotten a lot of attention because of their potential applications in tissue regeneration, bioimaging, wound healing, and cancer therapy. The physical and chemical methods to synthesize metal oxide nanoparticles have an environmental impact, necessitating the development of an environmentally friendly green strategy for nanoparticle synthesis. In this study, we used Annona muricata plant leaf extract to synthesize Zinc Oxide nanoparticles (Am-ZnO NPs), which were evaluated using UV/Visible spectroscopy, FTIR spectroscopy, X-Ray Diffraction, DLS, and Zeta potential. Nanoparticles had an optical absorbance of 355 nm and a net negative surface charge of ~ - 2.59 mV. Transmission Electron Microscope characterizes the Shape and size of the nanoparticles. The obtained Am-ZnO NPs are biocompatible and hemocompatible in nature. These nanoparticles caused an anti-cancer therapeutic effect in MIA PaCa2 and MOLT4 cancer cells by inducing oxidative stress, and a change in mitochondrial membrane potential leads to programmed cell death. Further, we observed a reduction in the size of lung cancer spheroids (act as tumor micro-environment) with doxorubicin as a positive control.

Keywords: Biomaterials, nanoparticle, anticancer activity, ZnO nanoparticles

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Authors: Lucian Mocan

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We present method of Nanoparticle enhanced laser thermal ablation of HepG2 cells (Human hepatocellular liver carcinomacell line), using gold nanoparticles combuned with a specific growth factor and demonstrate its selective therapeutic efficacy usig ex vivo specimens. Ex vivo-perfused liver specimens were obtained from hepatocellular carcinoma patients similarly to the surgical technique of transplantation. Ab bound to GNPs was inoculated intra-arterially onto the resulting specimen and determined the specific delivery of the nano-bioconjugate into the malignant tissue by means of the capillary bed. The extent of necrosis was considerable following laser therapy and at the same time surrounding parenchyma was not seriously affected. The selective photothermal ablation of the malignant liver tissue was obtained after the selective accumulation of Ab bound to GNPs into tumor cells following ex-vivo intravascular perfusion. These unique results may represent a major step in liver cancer treatment using nanolocalized thermal ablation by laser heating.

Keywords: HepG2 cells, gold nanoparticles, nanoparticle functionalization, laser irradiation

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Authors: S. Oudjemia, F. Alim, S. Seddiki

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This paper shows the application of multifractal analysis for additional help in cancer diagnosis. The medical image processing is a very important discipline in which many existing methods are in search of solutions to real problems of medicine. In this work, we present results of multifractal analysis of brain MRI images. The purpose of this analysis was to separate between healthy and cancerous tissue of the brain. A nonlinear method based on multifractal detrending moving average (MFDMA) which is a generalization of the detrending fluctuations analysis (DFA) is used for the detection of abnormalities in these images. The proposed method could make separation of the two types of brain tissue with success. It is very important to note that the choice of this non-linear method is due to the complexity and irregularity of tumor tissue that linear and classical nonlinear methods seem difficult to characterize completely. In order to show the performance of this method, we compared its results with those of the conventional method box-counting.

Keywords: irregularity, nonlinearity, MRI brain images, multifractal analysis, brain tumor

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Authors: Hyekyung Woo, Gwihyun Kim

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mHealth, which encompasses mobile health technologies and interventions, is rapidly evolving in various medical specialties, and its impact is evident in oncology. This review describes current trends in research addressing the integration of mHealth into the management of breast cancer by examining evaluations of mHealth and its contributions across the cancer care continuum. Mobile technologies are perceived as effective in prevention and as feasible for managing breast cancer, but the diagnostic accuracy of these tools remains in doubt. Not all phases of breast cancer treatment involve mHealth, and not all have been addressed by research. These drawbacks in the application of mHealth to breast cancer management call for intensified research to strengthen its role in breast cancer care.

Keywords: mobile application, breast cancer, content analysis, mHealth

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Authors: Mohammad Hassan Heidari, Amir Hossein Goodarzi, Majid Azarniush

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Radiation doses to tissues and organs were measured using the anthropomorphic phantom as an equivalent to the human body. When high-energy X-rays are externally applied to treat laryngeal cancer, the absorbed dose at the laryngeal lumen is lower than given dose because of air space which it should pass through before reaching the lesion. Specially in case of high-energy X-rays, the loss of dose is considerable. Three-dimensional absorbed dose distributions have been computed for high-energy photon radiation therapy of laryngeal and hypo pharyngeal cancers, using a coaxial pair of opposing lateral beams in fixed positions. Treatment plans obtained under various conditions of irradiation.

Keywords: 3D treatment planning, anthropomorphic phantom, larynx cancer, radiotherapy

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Authors: Fakhrosadat Sajjadian

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The majority of deaths in cancer patients are caused by distant metastasis. Breast cancer shows a unique spread pattern, often affecting bone, liver, lung, and brain. Breast cancer can be categorized into various subtypes according to gene expression patterns, and these subtypes exhibit specific preferences for organs where metastasis occurs. Breast tumors with luminal characteristics have a preference for spreading to the bone, whereas basal-like breast cancer (BLBC) shows a tendency to metastasize to the lungs. Still, the mechanisms behind this particular pattern of metastasis in organs have yet to be fully understood. In this evaluation, we will outline the latest progress in molecular signaling pathways and treatment methods for breast cancer lung metastasis.

Keywords: lung cancer, liver cancer, diagnosis, BLBC, metastasis

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Authors: Chi-Chang Lin, Jiun-Yan Chiu

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Periodontal disease, oral cancer relating trauma is the prominent factor devastating bone tissue that is crucial to reestablishing in clinical. As we know, common symptom, osteoporosis, and infection limiting the ability of the bone tissue to recover cause difficulty before implantation therapy. Regeneration of bone tissue is the fundamental therapy before surgical processes. To promote the growth of bone tissue, many commercial products still have sophisticated problems that need to overcome. Regrettably, there is no available material which is apparently preferable for releasing and controlling of loading dosage, or mitigating inflammation. In our study, a hydrogel-based composite membrane has been prepared by using Gellan gum (GG), gamma-polyglutamic acid (γ-PGA) and glycerol with simple sol-gel method. GG is a natural material that is massively adopted in cartilage. Unfortunately, the strength of pure GG film is a manifest weakness especially under simulating body fluidic conditions. We utilize another biocompatible material, γ-PGA as cross-linker which can form tri-dimension structure that enhancing the strength. Our result indicated the strength of pure GG membrane can be obviously improved by cross-linked with γ-PGA (0.5, 0.6, 0.7, 0.8, 0.9, 1.0 w/v%). Besides, blending with glycerol (0, 1.0, 2.0, 3.0 w/v%) can significantly improve membrane toughness that corresponds to practical use. The innovative composited hydrogel made of GG, γ-PGA, and glycerol is attested with neat results including elongation and biocompatibility that take the advantage of extension covering major trauma. Recommendations are made for treatment to build up the foundation of bone tissue that would help patients to escape from the suffering and shorten the amount of time in recovery.

Keywords: bone tissue, gellan gum, regeneration, toughness

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Authors: Sachinkumar Patil, Sonali Patil, Shitalkumar Patil

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Nanoparticles played important role in the biomedicine. New advanced methods having great potential apllication in the diagnosis and therapy of cancer. Now a day’s magnetic nanoparticles used in cancer therapy. Cancer is the major disease causes death. Magnetic nanoparticles show response to the magnetic field on the basis of this property they are used in cancer therapy. Cancer treated with hyperthermia by using magnetic nanoparticles it is unconventional but more safe and effective method. Magnetic nanoparticles prepared by using different innovative techniques that makes particles in uniform size and desired effect. Magnetic nanoparticles already used as contrast media in magnetic resonance imaging. A magnetic nanoparticle has been great potential application in cancer diagnosis and treatment as well as in gene therapy. In this review we will discuss the progress in cancer therapy based on magnetic nanoparticles, mainly including magnetic hyperthermia, synthesis and characterization of magnetic nanoparticles, mechanism of magnetic nanoparticles and application of magnetic nanoparticles.

Keywords: magnetic nanoparticles, synthesis, characterization, cancer therapy, hyperthermia, application

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Authors: Ramandeep Kaur, Gurjit Singh Bhathal

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Cancer diagnosis is very difficult task. Magnetic resonance imaging (MRI) scan is used to produce image of any part of the body and provides an efficient way for diagnosis of cancer or tumor. In existing method, fuzzy clustering mean (FCM) is used for the diagnosis of the tumor. In the proposed method FCM is used to diagnose the cancer of the foot. FCM finds the centroids of the clusters of the foot cancer obtained from MRI images. FCM thresholding result shows the extract region of the cancer. Morphological operations are applied to get extracted region of cancer.

Keywords: magnetic resonance imaging (MRI), fuzzy C mean clustering, segmentation, morphological operations

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Authors: Gökçe Erdemir, İlhan Yaylım, Serap Erdem-Kuruca, Musa Mutlu Can

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It has been determined that the main reason for the death of cancer disease is caused by metastases rather than the primary tumor. The cells that leave the primary tumor and enter the circulation and cause metastasis in the secondary organs are called "circulating tumor cells" (CTCs). The presence and number of circulating tumor cells has been associated with poor prognosis in many major types of cancer, including breast, prostate, and colorectal cancer. It is thought that knowledge of circulating tumor cells, which are seen as the main cause of cancer-related deaths due to metastasis, plays a key role in the diagnosis and treatment of cancer. The fact that tissue biopsies used in cancer diagnosis and follow-up are an invasive method and are insufficient in understanding the risk of metastasis and the progression of the disease have led to new searches. Liquid biopsy tests performed with a small amount of blood sample taken from the patient for the detection of CTCs are easy and reliable, as well as allowing more than one sample to be taken over time to follow the prognosis. However, since these cells are found in very small amounts in the blood, it is very difficult to capture them and specially designed analytical techniques and devices are required. Methods based on the biological and physical properties of the cells are used to capture these cells in the blood. Early diagnosis is very important in following the prognosis of tumors of epithelial origin such as breast, lung, colon and prostate. Molecules such as EpCAM, vimentin, and cytokeratins are expressed on the surface of cells that pass into the circulation from very few primary tumors and reach secondary organs from the circulation, and are used in the diagnosis of cancer in the early stage. For example, increased EpCAM expression in breast and prostate cancer has been associated with prognosis. These molecules can be determined in some blood or body fluids to be taken from patients. However, more sensitive methods are required to be able to determine when they are at a low level according to the course of the disease. The aim is to detect these molecules found in very few cancer cells with the help of sensitive, fast-sensing biosensors, first in breast cancer cells reproduced in vitro and then in blood samples taken from breast cancer patients. In this way, cancer cells can be diagnosed early and easily and effectively treated.

Keywords: electrochemical biosensors, breast cancer, circulating tumor cells, EpCAM, Vimentin, Cytokeratins

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

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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: Hussein Alahmer, Amr Ahmed

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Liver cancer is one of the common diseases that cause the death. Early detection is important to diagnose and reduce the incidence of death. Improvements in medical imaging and image processing techniques have significantly enhanced interpretation of medical images. Computer-Aided Diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver disease and hence reduce liver cancer death rate.  This paper presents an automated CAD system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features. Finally, classifying liver lesions into benign and malignant by using the novel contrasting feature-difference approach. Several types of intensity, texture features are extracted from both; the lesion area and its surrounding normal liver tissue. The difference between the features of both areas is then used as the new lesion descriptors. Machine learning classifiers are then trained on the new descriptors to automatically classify liver lesions into benign or malignant. The experimental results show promising improvements. Moreover, the proposed approach can overcome the problems of varying ranges of intensity and textures between patients, demographics, and imaging devices and settings.

Keywords: CAD system, difference of feature, fuzzy c means, lesion detection, liver segmentation

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Authors: Nesreen M. Alqaissi

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Little is known about the lived experiences of breast cancer among Arab Muslim women. The researcher used a qualitative interpretive phenomenological research design to explore the lived experiences of breast cancer as described by Jordanian Muslim women. A purposive sample of 20 women with breast cancer was recruited. Data were collected utilizing individual semi-structured interviews, and analyzed using Heideggerian Hermeneutical methodology. Results: Five related themes and one constitutive pattern: (a) breast cancer means death; (b) matriarchal family members as important source of support; (c) spirituality as a way to live and survive breast cancer; (d) concealing cancer experiences to protect self and families; (e) physicians as protectors and treatment decision makers; (f) the constitutive pattern: culture influencing Jordanian women experiences with breast cancer. In conclusion, researchers and healthcare providers should consider the influence of culture, spirituality, and families, when caring for women with breast cancer from Jordan.

Keywords: breast cancer, Arab Muslim, Jordan, lived experiences, spirituality, culture

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Authors: Sahar Heidary

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Breast cancer is a main public common obstacle global. Additionally, it is the second top reason for tumor death across women. Considering breast cancer cure choices can aid private doctors in precaution for their patients through future cancer treatment. This article reviews usual management centered on stage, histology, and biomarkers. The growth of breast cancer is a multi-stage procedure including numerous cell kinds and its inhibition residues stimulating in the universe. Timely identification of breast cancer is one of the finest methods to stop this illness. Entirely chief therapeutic administrations mention screening mammography for women aged 40 years and older. Breast cancer metastasis interpretations for the mainstream of deaths from breast cancer. The discovery of breast cancer metastasis at the initial step is essential for managing and estimate of breast cancer development. Developing methods consuming the exploration of flowing cancer cells illustrate talented outcomes in forecasting and classifying the initial steps of breast cancer metastasis in patients. In public, mammography residues are the key screening implement though the efficiency of medical breast checks and self-checkup is less. Innovative screening methods are doubtful to exchange mammography in the close upcoming for screening the overall people.

Keywords: breast cancer, screening, metastasis, methods

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Authors: H. Feza Carlak, N. G. Gencer

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To increase the temperature contrast in thermal images, the characteristics of the electrical conductivity and thermal imaging modalities can be combined. In this experimental study, it is objected to observe whether the temperature contrast created by the tumor tissue can be improved just due to the current application within medical safety limits. Various thermal breast phantoms are developed to simulate the female breast tissue. In vitro experiments are implemented using a thermal infrared camera in a controlled manner. Since experiments are implemented in vitro, there is no metabolic heat generation and blood perfusion. Only the effects and results of the electrical stimulation are investigated. Experimental study is implemented with two-dimensional models. Temperature contrasts due to the tumor tissues are obtained. Cancerous tissue is determined using the difference and ratio of healthy and tumor images. 1 cm diameter single tumor tissue causes almost 40 °mC temperature contrast on the thermal-breast phantom. Electrode artifacts are reduced by taking the difference and ratio of background (healthy) and tumor images. Ratio of healthy and tumor images show that temperature contrast is increased by the current application.

Keywords: medical diagnostic imaging, breast phantom, active thermography, breast cancer detection

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Authors: Mubita Namuyamba

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Despite an increase in the number of cancer programs and partnerships in cancer care provision, the burden of cancer in Zambia is increasingly having a significant impact on morbidity and mortality rates. The increase in cancer morbidity and mortality rates has given rise to psychological and psycho social implications (PPsI) in cancer care. Cancer patients, care givers and health care providers are faced with a multitude of PPsIs in cancer care that mainly impact negatively on the management of cancer patients. The study adopted a case study design and was purposively conducted at the Cancer Diseases Hospital in Lusaka (Zambia) after obtaining ethical clearance from the Ethics committee. The sample for this study included 70 cancer patients, 20 care givers and 5 hospital staff (4 nurses and 1 doctor). Data was collected using interviews guides, focus group discussion guides and questionnaires respectively. The qualitative data was analysed thematically. The various psychological and psychosocial challenges that conspire to deter the provision of effective cancer care nursing and improved methods of minimizing the psychological and psychosocial implications in cancer care are the products of this study.

Keywords: case study, enquiry, psychological and psycho social aspects, Zambia

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

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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

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Authors: Imran Ali

Abstract:

General chemotherapy for cancer treatment has many side and toxic effects. A new approach of targeting nano anti-cancer drug is under development stage and only few drugs are available in the market today. The unique features of these drugs are targeted action on cancer cells only without any side effect. Sometimes, these are called magic drugs. The important molecules used for nano anti-cancer drugs are cisplatin, carboplatin, bleomycin, 5-fluorouracil, doxorubicin, dactinomycin, 6-mercaptopurine, paclitaxel, topotecan, vinblastin and etoposide etc. The most commonly used materials for preparing nano particles carriers are dendrimers, polymeric, liposomal, micelles inorganic, organic etc. The proposed lecture will comprise the-of-art of nano drugs in cancer chemo-therapy including preparation, types of drugs, mechanism, future perspectives etc.

Keywords: cancer, nano-anti-cancer drugs, chemo-therapy, mechanism of action, future perspectives

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Authors: Suzan Wedyan

Abstract:

Data mining is one of the main phases in the Knowledge Discovery Database (KDD) which is responsible of finding hidden and useful knowledge from databases. There are many different tasks for data mining including regression, pattern recognition, clustering, classification, and association rule. In recent years a promising data mining approach called associative classification (AC) has been proposed, AC integrates classification and association rule discovery to build classification models (classifiers). This paper surveys and critically compares several AC algorithms with reference of the different procedures are used in each algorithm, such as rule learning, rule sorting, rule pruning, classifier building, and class allocation for test cases.

Keywords: associative classification, classification, data mining, learning, rule ranking, rule pruning, prediction

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Authors: Fabio Fabris, Alex A. Freitas

Abstract:

Hierarchical classification is a special type of classification task where the class labels are organised into a hierarchy, with more generic class labels being ancestors of more specific ones. Meta-learning for classification-algorithm recommendation consists of recommending to the user a classification algorithm, from a pool of candidate algorithms, for a dataset, based on the past performance of the candidate algorithms in other datasets. Meta-learning is normally used in conventional, non-hierarchical classification. By contrast, this paper proposes a meta-learning approach for more challenging task of hierarchical classification, and evaluates it in a large number of bioinformatics datasets. Hierarchical classification is especially relevant for bioinformatics problems, as protein and gene functions tend to be organised into a hierarchy of class labels. This work proposes meta-learning approach for recommending the best hierarchical classification algorithm to a hierarchical classification dataset. This work’s contributions are: 1) proposing an algorithm for splitting hierarchical datasets into new datasets to increase the number of meta-instances, 2) proposing meta-features for hierarchical classification, and 3) interpreting decision-tree meta-models for hierarchical classification algorithm recommendation.

Keywords: algorithm recommendation, meta-learning, bioinformatics, hierarchical classification

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Authors: Kazeem Adesina Dauda, Waheed Babatunde Yahya

Abstract:

To design a tree that maximizes within-node homogeneity, there is a need for a homogeneity measure that is appropriate for event history data with multiple risks. We consider the use of Deviance and Modified Cox-Snell residuals as a measure of impurity in Classification Regression Tree (CART) and compare our results with the results of Fiona (2008) in which homogeneity measures were based on Martingale Residual. Data structure approach was used to validate the performance of our proposed techniques via simulation and real life data. The results of univariate competing risk revealed that: using Deviance and Cox-Snell residuals as a response in within node homogeneity classification tree perform better than using other residuals irrespective of performance techniques. Bone marrow transplant data and double-blinded randomized clinical trial, conducted in other to compare two treatments for patients with prostate cancer were used to demonstrate the efficiency of our proposed method vis-à-vis the existing ones. Results from empirical studies of the bone marrow transplant data showed that the proposed model with Cox-Snell residual (Deviance=16.6498) performs better than both the Martingale residual (deviance=160.3592) and Deviance residual (Deviance=556.8822) in both event of interest and competing risks. Additionally, results from prostate cancer also reveal the performance of proposed model over the existing one in both causes, interestingly, Cox-Snell residual (MSE=0.01783563) outfit both the Martingale residual (MSE=0.1853148) and Deviance residual (MSE=0.8043366). Moreover, these results validate those obtained from the Monte-Carlo studies.

Keywords: within-node homogeneity, Martingale residual, modified Cox-Snell residual, classification and regression tree

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Authors: Mehwish Asghar

Abstract:

Breast Cancer (BC) is a common type of cancer among women. Its screening is usually performed using different imaging modalities such as magnetic resonance imaging, mammogram, X-ray, CT, etc. Among these modalities’ mammogram is considered a powerful tool for diagnosis and screening of breast cancer. Sophisticated machine learning approaches have shown promising results in complementing human diagnosis. Generally, machine learning methods can be divided into two major classes: one is Radiomics analysis (RA), where image features are extracted manually; and the other one is the concept of convolutional neural networks (CNN), in which the computer learns to recognize image features on its own. This research aims to improve the incidence of early detection, thus reducing the mortality rate caused by breast cancer through the latest advancements in computer science, in general, and machine learning, in particular. It has also been aimed to ease the burden of doctors by improving and automating the process of breast cancer detection. This research is related to a relative analysis of different techniques for the implementation of different models for detecting and classifying breast cancer. The main goal of this research is to provide a detailed view of results and performances between different techniques. The purpose of this paper is to explore the potential of a convolutional neural network (CNN) w.r.t feature extractor and as a classifier. Also, in this research, it has been aimed to add the module of Radiomics for comparison of its results with deep learning techniques.

Keywords: breast cancer (BC), machine learning (ML), convolutional neural network (CNN), radionics, magnetic resonance imaging, artificial intelligence

Procedia PDF Downloads 193