Search results for: breast cancer classification

Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

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Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

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Authors: Ana L. M. Pavan, Guilherme Giacomini, Allan F. F. Alves, Marcela De Oliveira, Fernando A. B. Neto, Maria E. D. Rosa, Andre P. Trindade, Diana R. De Pina

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Mammography is a worldwide image modality used to diagnose breast cancer, even in asymptomatic women. Due to its large availability, mammograms can be used to measure breast density and to predict cancer development. Women with increased mammographic density have a four- to sixfold increase in their risk of developing breast cancer. Therefore, studies have been made to accurately quantify mammographic breast density. In clinical routine, radiologists perform image evaluations through BIRADS (Breast Imaging Reporting and Data System) assessment. However, this method has inter and intraindividual variability. An automatic objective method to measure breast density could relieve radiologist’s workload by providing a first aid opinion. However, pectoral muscle is a high density tissue, with similar characteristics of fibroglandular tissues. It is consequently hard to automatically quantify mammographic breast density. Therefore, a pre-processing is needed to segment the pectoral muscle which may erroneously be quantified as fibroglandular tissue. The aim of this work was to develop an automatic algorithm to segment and extract pectoral muscle in digital mammograms. The database consisted of thirty medio-lateral oblique incidence digital mammography from São Paulo Medical School. This study was developed with ethical approval from the authors’ institutions and national review panels under protocol number 3720-2010. An algorithm was developed, in Matlab® platform, for the pre-processing of images. The algorithm uses image processing tools to automatically segment and extract the pectoral muscle of mammograms. Firstly, it was applied thresholding technique to remove non-biological information from image. Then, the Hough transform is applied, to find the limit of the pectoral muscle, followed by active contour method. Seed of active contour is applied in the limit of pectoral muscle found by Hough transform. An experienced radiologist also manually performed the pectoral muscle segmentation. Both methods, manual and automatic, were compared using the Jaccard index and Bland-Altman statistics. The comparison between manual and the developed automatic method presented a Jaccard similarity coefficient greater than 90% for all analyzed images, showing the efficiency and accuracy of segmentation of the proposed method. The Bland-Altman statistics compared both methods in relation to area (mm²) of segmented pectoral muscle. The statistic showed data within the 95% confidence interval, enhancing the accuracy of segmentation compared to the manual method. Thus, the method proved to be accurate and robust, segmenting rapidly and freely from intra and inter-observer variability. It is concluded that the proposed method may be used reliably to segment pectoral muscle in digital mammography in clinical routine. The segmentation of the pectoral muscle is very important for further quantifications of fibroglandular tissue volume present in the breast.

Keywords: active contour, fibroglandular tissue, hough transform, pectoral muscle

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Authors: Sadeem Aljamaan, Reem Hariri, Rahaf Alghamdi, Batool Alotaibi, Batool Alsenan, Lama Althunayyan, Areej Alnemer

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The aim of this study is to correlate between radiological findings and histopathological results in regard to the breast imaging-reporting and data system scores, size of breast masses, molecular subtypes and suspicious radiological features, as well as to assess the concordance rate in histological grade between core biopsy and surgical excision among breast cancer patients, followed by analyzing the change of concordance rate in relation to neoadjuvant chemotherapy in a Saudi population. A retrospective review was conducted over 6-year period (2017-2022) on all breast core biopsies of women preceded by radiological investigation. Chi-squared test (χ2) was performed on qualitative data, the Mann-Whitney test for quantitative non-parametric variables, and the Kappa test for grade agreement. A total of 641 cases were included. Ultrasound, mammography, and magnetic resonance imaging demonstrated diagnostic accuracies of 85%, 77.9% and 86.9%; respectively. magnetic resonance imaging manifested the highest sensitivity (72.2%), and the lowest was for ultrasound (61%). Concordance in tumor size with final excisions was best in magnetic resonance imaging, while mammography demonstrated a higher tendency of overestimation (41.9%), and ultrasound showed the highest underestimation (67.7%). The association between basal-like molecular subtypes and the breast imaging-reporting and data system score 5 classifications was statistically significant only for magnetic resonance imaging (p=0.04). Luminal subtypes demonstrated a significantly higher percentage of speculation in mammography. Breast imaging-reporting and data system score 4 manifested a substantial number of benign pathologies in all the 3 modalities. A fair concordance rate (k= 0.212 & 0.379) was demonstrated between excision and the preceding core biopsy grading with and without neoadjuvant therapy, respectively. The results demonstrated a down-grading in cases post-neoadjuvant therapy. In cases who did not receive neoadjuvant therapy, underestimation of tumor grade in biopsy was evident. In summary, magnetic resonance imaging had the highest sensitivity, specificity, positive predictive value and accuracy of both diagnosis and estimation of tumor size. Mammography demonstrated better sensitivity than ultrasound and had the highest negative predictive value, but ultrasound had better specificity, positive predictive value and accuracy. Therefore, the combination of different modalities is advantageous. The concordance rate of core biopsy grading with excision was not impacted by neoadjuvant therapy.

Keywords: breast cancer, mammography, MRI, neoadjuvant, pathology, US

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Authors: Julianne Macmullen

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Due to advances in technology and early detection and treatment of cancer, many cancer patients are surviving longer than five years post-diagnosis. Most cancer patients suffer from depression, anxiety, and post-traumatic stress disorder (PTSD) at some point during diagnosis, treatment, and survivorship. A subgroup of patients will continue to suffer from depression and PTSD and require early intervention. Support groups provide patients with the emotional and informational support they require while also giving survivors a sense of community, friendship, and purpose. This type of support is recognized by researchers to improve the quality of life while also decreasing depression and PTSD symptoms. The gaps in the literature include cultural diversity, minorities, and support groups involving cancer types other than breast cancer. Another gap in the literature includes the perceptions of cancer patients as well as longitudinal studies to determine the relationships between support groups and decreased depression and PTSD rates over time. Future research is required to fill the gaps in the literature mentioned previously. Future research is also needed to analyze the difference in age groups and different types of support groups such as professionally-led, peer-led, and online. Implications for practice involve providers assessing for the symptoms of depression and PTSD in order to offer prompt treatment and support services to those patients. In conclusion, social support by way of support groups improves the quality of life, gives survivors a sense of purpose to help others while also gaining the support they need, and reduces the rate of depressive episodes related to PTSD.

Keywords: cancer survivor, survivorship, post-traumatic stress disorder (PTSD), depression, support groups

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Authors: Kunal Shah, Swati Patel

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Many real world problems involve data which can be considered as multi-label data streams. Efficient methods exist for multi-label classification in non streaming scenarios. However, learning in evolving streaming scenarios is more challenging, as the learners must be able to adapt to change using limited time and memory. Classification is used to predict class of unseen instance as accurate as possible. Multi label classification is a variant of single label classification where set of labels associated with single instance. Multi label classification is used by modern applications, such as text classification, functional genomics, image classification, music categorization etc. This paper introduces the task of multi-label classification, methods for multi-label classification and evolution measure for multi-label classification. Also, comparative analysis of multi label classification methods on the basis of theoretical study, and then on the basis of simulation was done on various data sets.

Keywords: binary relevance, concept drift, data stream mining, MLSC, multiple window with buffer

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Authors: Sonia Mahajan Dinesh, Anant Dinesh, Madhavi Tripathi, Vinod Kumar Ramteke, Rajnish Sharma, Anupam Mondal

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Background: Neo-adjuvant chemotherapy plays an important role in treatment of breast cancer by decreasing the tumour load and it offers an opportunity to evaluate response of primary tumour to chemotherapy. Standard anatomical imaging modalities are unable to accurately reflect the response to chemotherapy until several cycles of drug treatment have been completed. Metabolic imaging using tracers like 18F-fluorodeoxyglucose (FDG) as a marker of glucose metabolism or amino acid tracers like L-methyl-11C methionine (MET) have potential role for the measurement of treatment response. In this study, our objective was to compare these two PET tracers for assessment of response to neoadjuvant chemotherapy, in locally advanced breast carcinoma. Methods: In our prospective study, 20 female patients with histology proven locally advanced breast carcinoma underwent PET-CT imaging using FDG and MET before and after three cycles of neoadjuvant chemotherapy (CAF regimen). Thereafter, all patients were taken for MRM and the resected specimen was sent for histo-pathological analysis. Tumour response to the neoadjuvant chemotherapy was evaluated by PET-CT imaging using PERCIST criteria and correlated with histological results. Responses calculated were compared for statistical significance using paired t- test. Results: Mean SUVmax for primary lesion in FDG PET and MET PET was 15.88±11.12 and 5.01±2.14 respectively (p<0.001) and for axillary lymph nodes was 7.61±7.31 and 2.75±2.27 respectively (p=0.001). Statistically significant response in primary tumour and axilla was noted on both FDG and MET PET after three cycles of NAC. Complete response in primary tumour was seen in only 1 patient in FDG and 7 patients in MET PET (p=0.001) whereas there was no histological complete resolution of tumor in any patient. Response to therapy in axillary nodes noted on both PET scans were similar (p=0.45) and correlated well with histological findings. Conclusions: For the primary breast tumour, FDG PET has a higher sensitivity and accuracy than MET PET and for axilla both have comparable sensitivity and specificity. FDG PET shows higher target to background ratios so response is better predicted for primary breast tumour and axilla. Also, FDG-PET is widely available and has the advantage of a whole body evaluation in one study.

Keywords: 11C-methionine, 18F-FDG, breast carcinoma, neoadjuvant chemotherapy

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Authors: Eashwar V. Somasundaram, Raoul R. Wadhwa, Jacob G. Scott

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The use of radiomics in measuring geometric properties of tumor images such as size, surface area, and volume has been invaluable in assessing cancer diagnosis, treatment, and prognosis. In addition to analyzing geometric properties, radiomics would benefit from measuring topological properties using persistent homology. Intuitively, features uncovered by persistent homology may correlate to tumor structural features. One example is necrotic cavities (corresponding to 2D topological features), which are markers of very aggressive tumors. We develop a data pipeline in R that clusters tumors images based on persistent homology is used to identify meaningful clinical distinctions between tumors and possibly new relationships not captured by established clinical categorizations. A preliminary analysis was performed on 16 Magnetic Resonance Imaging (MRI) breast tissue segments downloaded from the 'Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis' (I-SPY TRIAL or ISPY1) collection in The Cancer Imaging Archive. Each segment represents a patient’s breast tumor prior to treatment. The ISPY1 dataset also provided the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status data. A persistent homology matrix up to 2-dimensional features was calculated for each of the MRI segmentation. Wasserstein distances were then calculated between all pairwise tumor image persistent homology matrices to create a distance matrix for each feature dimension. Since Wasserstein distances were calculated for 0, 1, and 2-dimensional features, three hierarchal clusters were constructed. The adjusted Rand Index was used to see how well the clusters corresponded to the ER/PR/HER2 status of the tumors. Triple-negative cancers (negative status for all three receptors) significantly clustered together in the 2-dimensional features dendrogram (Adjusted Rand Index of .35, p = .031). It is known that having a triple-negative breast tumor is associated with aggressive tumor growth and poor prognosis when compared to non-triple negative breast tumors. The aggressive tumor growth associated with triple-negative tumors may have a unique structure in an MRI segmentation, which persistent homology is able to identify. This preliminary analysis shows promising results in the use of persistent homology on tumor imaging to assess the severity of breast tumors. The next step is to apply this pipeline to other tumor segment images from The Cancer Imaging Archive at different sites such as the lung, kidney, and brain. In addition, whether other clinical parameters, such as overall survival, tumor stage, and tumor genotype data are captured well in persistent homology clusters will be assessed. If analyzing tumor MRI segments using persistent homology consistently identifies clinical relationships, this could enable clinicians to use persistent homology data as a noninvasive way to inform clinical decision making in oncology.

Keywords: cancer biology, oncology, persistent homology, radiomics, topological data analysis, tumor imaging

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Authors: Gholamreza Hashemitabr, Reza Valadan, Alireza Rafiei, Mohammad Reza Bassami

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Breast cancer is the most common malignancy among women worldwide. Cancer cells use a complex multilayer network of epidermal growth factor receptors (EGFRs) signaling pathways to support their survival and growth. The overlapping networks of EGFRs signaling pathways account for the failure of most ErbB-targeted therapies. The aim of this study was to enrich a pool of recombinant antibody fragments against common epitopes of ErbB1 and ErbB2 in order to simultaneous blockade of ErbBs signaling pathways. ErbB1 and ErbB2 were expressed stably in VERO cells. Selection of recombinant antibodies was performed on live cells expressing either of ErbB1 and ErbB2 receptors using subtractive phage display approach. The results of PCR and DNA fingerprinting in the last round of panning showed that most clones contained insert (80% and 85% for ErbB1 and ErbB2 respectively) with an identical restriction pattern. The selected clones showed positive reaction to both ErbB1 and ErbB2 receptors in phage-ELISA test. Furthermore, the resulting soluble antibody fragments recognized common epitopes of both immunoprecipitated ErbB1 and ErbB2 in western blot. Additionally, the antibodies directed against the dimerization domain of ErbB1 demonstrated a significant absorbance in EGF-stimulated VERO/ErbB1 cells than non-stimulated cells (1.91 and 1.09 respectively). Moreover, the results of dimerization inhibition test showed that these antibodies blocked ErbB1 and ErbB2 dimerization on the surface of ErbB1 and ErbB2 expressing VERO cells. Regarding the importance of pan-ErbB approach to cancer therapy, the antibodies developed here might provide novel therapeutics for simultaneous blockade of ErbBs signaling pathways.

Keywords: breast cancer, single-chain antibody, ErbB1, ErbB2, epitope

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Authors: M. Pourshirazi, M. Esmaelifar, A. Aliahmadi, F. Yazdian, A. S. Hatamian Zarami, S. J. Ashrafi

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Medicinal fungi are the new potential source of drugs to improve the treatment of diseases with association to oxidative agents such as cancers. Monascus purpureus contains functional components potentially effective in improving human health. In the present work, ethanolic extract of Monascus purpureus (EEM) was evaluated for health improving potential mainly focusing on antioxidant and anticancer activities. Ferric ion reducing power (FRAP), scavenging of DPPH radicals and determining viability of breast carcinoma MCF-7 and cervical carcinoma HeLa cells with MTT assay were evaluated. Our data showed a significant antioxidant activity of EEM with 142.45 µg/ml inhibition concentration of 50% DPPH radicals and 2112.33 µg eq.Fe2+/mg extract of FRAP assay. These results might be caused by antioxidant components such as pigments and phenolic compounds. Further, the results demonstrated that EEM caused significant reduction in the viability of MCF-7 with IC50 of 7 µg/ml but not have good effect against viability of HeLa cells. Accordingly, Monascus purpureus is presented as a strong potential of breast cancer treatment. In further study, the mechanistic studies are needed to determine the mechanisms of anticancer activity of EEM.

Keywords: Monascus purpureus, antioxidant, cancer, ethanolic extract

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Authors: Behnaz Sohani, Sahand Shahalinezhad, Amir Rahmani, Aliyu Aliyu

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Recently, medical imaging and specifically medical image processing is becoming one of the most dynamically developing areas of medical science. It has led to the emergence of new approaches in terms of the prevention, diagnosis, and treatment of various diseases. In the process of diagnosis of lung cancer, medical professionals rely on computed tomography (CT) scans, in which failure to correctly identify masses can lead to incorrect diagnosis or sampling of lung tissue. Identification and demarcation of masses in terms of detecting cancer within lung tissue are critical challenges in diagnosis. In this work, a segmentation system in image processing techniques has been applied for detection purposes. Particularly, the use and validation of a novel lung cancer detection algorithm have been presented through simulation. This has been performed employing CT images based on multilevel thresholding. The proposed technique consists of segmentation, feature extraction, and feature selection and classification. More in detail, the features with useful information are selected after featuring extraction. Eventually, the output image of lung cancer is obtained with 96.3% accuracy and 87.25%. The purpose of feature extraction applying the proposed approach is to transform the raw data into a more usable form for subsequent statistical processing. Future steps will involve employing the current feature extraction method to achieve more accurate resulting images, including further details available to machine vision systems to recognise objects in lung CT scan images.

Keywords: lung cancer detection, image segmentation, lung computed tomography (CT) images, medical image processing

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Authors: Roohallah Fallah-Moshkani, Mohammad Ali Mohsenpour, Reza Ghiasvand, Hossein Khosravi-Boroujeni, Seyed Mehdi Ahmadi, Paula Brauer, Amin Salehi-Abargouei

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Purpose: Several investigations have proposed the protective association between dietary approaches to stop hypertension (DASH) style diet and risk of cancers; however, they have led to inconsistent results. The present study aimed to systematically review the prospective cohort studies conducted in this regard and, if possible, to quantify the overall effect of using meta-analysis. Methods: PubMed, EMBASE, Scopus, and Google Scholar were searched for cohort studies published up to December 2017. Relative risks (RRs) which were reported for fully adjusted models and their confidence intervals were extracted for meta-analysis. Random effects model was incorporated to combine the RRs. Results: Sixteen studies were eligible to be included in the systematic review from which 8 reports were conducted on the effect of DASH on the risk of mortality from all cancer types, four on the risk of colorectal cancer, and three on the risk of colon and rectal cancer. Four studies examined the association with other cancers (breast, hepatic, endometrial, and lung cancer). Meta-analysis showed that high concordance with DASH significantly decreases the risk of all cancer types (RR=0.83, 95% confidence interval (95%CI):0.80-0.85); furthermore participants who highly adhered to the DASH had lower risk of developing colorectal (RR=0.79, 95%CI: 0.75-0.83), colon (RR=0.81, 95%CI: 0.74-0.87) and rectal (RR=0.79, 95%CI: 0.63-0.98) cancer compared to those with the lowest adherence. Conclusions: DASH-style diet should be suggested as a healthy approach to protect from cancer in the community. Prospective studies exploring the effect on other cancer types and from regions other than the United States are highly recommended.

Keywords: cancer, DASH-style diet, dietary patterns, meta-analysis, systematic review

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Authors: Sourour Khouaja, Hejer Jlassi, Nadia Feddaoui, Kamel Hamrouni

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Most medical images, and especially mammographies, are now stored in large databases. Retrieving a desired image is considered of great importance in order to find previous similar cases diagnosis. Our method is implemented to assist radiologists in retrieving mammographic images containing breast with similar density aspect as seen on the mammogram. This is becoming a challenge seeing the importance of density criteria in cancer provision and its effect on segmentation issues. We used the BEMD (Bidimensional Empirical Mode Decomposition) to characterize the content of images and Euclidean distance measure similarity between images. Through the experiments on the MIAS mammography image database, we confirm that the results are promising. The performance was evaluated using precision and recall curves comparing query and retrieved images. Computing recall-precision proved the effectiveness of applying the CBIR in the large mammographic image databases. We found a precision of 91.2% for mammography with a recall of 86.8%.

Keywords: BEMD, breast density, contend-based, image retrieval, mammography

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Authors: Ali A. A. Alqarni, Gamal A. Mohamed, Hossam M. Abdallah, Sabrin R. M. Ibrahim

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Phytochemical investigation of the methanolic extract of aerial parts of Tagetes minuta L. (Family: Asteraceae) using different chromatographic techniques led to the isolation of five compounds; ecliptal (1), scopoletin (2), P-hydroxy benzoic acid (3), patuletin (4), and patuletin-7-O-β-D-glucopyranoside (5) (Figure 1). Their structures were established based on physical, chemical, and spectral data [Ultraviolet (UV), Proton ¹H, Carbon thirteen ¹³C, and Heteronuclear Multiple Bond Correlation (HMBC) NMR], as well as Electrospray Ionization Mass Spectroscopy (ESIMS) and comparison with literature data. Their cytotoxic activity was assessed towards human liver hepatocellular carcinoma (HepG2), human breast cancer (MCF-7), and human colon cancer (HCT116) cancer cell lines using sulphorhodamine B (SRB) assay. It is noteworthy that compound 1 demonstrated a significant cytotoxic potential towards HepG2, MCF7, and HCT116 cells with IC₅₀s ranging from 2.74 to 7.01 μM, compared to doxorubicin (IC₅₀ 0.18, 0.60, and 0.20 μM, respectively), whereas compounds 2, 4, and 5 showed moderate cytotoxic potential with IC50s ranging from 11.71 to 35.64 μM. However, 3 was inactive up to a concentration of 100 μM towards the three tested cancer cell lines.

Keywords: Asteraceae, cytotoxicity, metabolites, Tagetes minuta

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Authors: Fadzil Ahmad, Noor Ashidi Mat Isa

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This study introduces an improved genetic algorithm procedure that focuses search around near optimal solution corresponded to a group of elite chromosome. This is achieved through a novel crossover technique known as Segmented Multi Chromosome Crossover. It preserves the highly important information contained in a gene segment of elite chromosome and allows an offspring to carry information from gene segment of multiple chromosomes. In this way the algorithm has better possibility to effectively explore the solution space. The improved GA is applied for the automatic and simultaneous parameter optimization and feature selection of artificial neural network in pattern recognition of medical problem, the cancer and diabetes disease. The experimental result shows that the average classification accuracy of the cancer and diabetes dataset has improved by 0.1% and 0.3% respectively using the new algorithm.

Keywords: genetic algorithm, artificial neural network, pattern clasification, classification accuracy

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Authors: Mohammad Kazem Mohammadi

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The use of anticancer agents forms an important part of the treatment of cancer of various types. Uranyl Complexes with DPHMP ligand have been used for the prevention and treatment of cancers. U(IV) metal complexes prepared by reaction of uranyl salt UO2 (NO3)2.6H2O with DPHMP in dry acetonitrile. Characterization of the ligand and its complexes was made by microanalyses, FT-IR, 1H NMR, 13C NMR and UV–Visible spectroscopy. These new complex showed excellent antitumor activity against two kinds of cancer cells that that are HT29:Haman colon adenocarcinoma cell line and T47D:human breast adenocarcinoma cell line.

Keywords: uranyl complexes, DPHMP ligand, antitumor activity, HT29, T47D

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Authors: Maryam Tajadod

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The treatment of cancer is one of the main challenges of nuclear medicine; while cancer begins in an organ, such as the breast or prostate, it spreads to the bone, resulting in metastatic bone. In the treatment of cancer with radiotherapy, the determination of the involved tissues’ dose is one of the important steps in the treatment protocol. Comparing absorbed doses for Lu-177 and Ra-223 and Ac-225 in the bone marrow and soft tissue of bone phantom with evaluating energetic emitted particles of these radionuclides is the important aim of this research. By the use of MCNPX computer code, a model for bone phantom was designed and the values of absorbed dose for Ra-223 and Ac-225, which are Alpha emitters & Lu-177, which is a beta emitter, were calculated. As a result of research, in comparing gamma radiation for three radionuclides, Lu-177 released the highest dose in the bone marrow and Ra-223 achieved the lowest level. On the other hand, the result showed that although the figures of absorbed dose for Ra and Ac in the bone marrow are near to each other, Ra spread more energy in cortical bone. Moreover, The alpha component of the Ra-223 and Ac-225 have very little effect on bone marrow and soft tissue than a beta component of the lu-177 and it leaves the highest absorbed dose in the bone where the source is located.

Keywords: bone metastases, lutetium-177, radium-223, actinium-225, absorbed dose

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Authors: Nebi Gedik

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One of the significant and continual public health problems in the world is breast cancer. Early detection is very important to fight the disease, and mammography has been one of the most common and reliable methods to detect the disease in the early stages. However, it is a difficult task, and computer-aided diagnosis (CAD) systems are needed to assist radiologists in providing both accurate and uniform evaluation for mass in mammograms. In this study, a multiresolution statistical method to classify mammograms as normal and abnormal in digitized mammograms is used to construct a CAD system. The mammogram images are represented by wave atom transform, and this representation is made by certain groups of coefficients, independently. The CAD system is designed by calculating some statistical features using each group of coefficients. The classification is performed by using support vector machine (SVM).

Keywords: wave atom transform, statistical features, multi-resolution representation, mammogram

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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: 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: P. Narrima, C. Y. Looi, M. A. Mohd, H. M. Ali

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Persea declinata (Bl.) Kosterm is a member of the Lauraceae family, widely distributed in Southeast Asia. It is from the same genus with avocado (Persea americana Mill), which is widely consumed as food and for medicinal purposes. In the present study, we examined the anticancer properties of Persea declinata (Bl.) Kosterm bark methanolic crude extract (PDM). PDM exhibited a potent antiproliferative effect in MCF-7 human breast cancer cells, with an IC50 value of 16.68 µg/mL after 48h of treatment. We observed that PDM caused cell cycle arrest and subsequent apoptosis in MCF-7 cells, as exhibited by increased population at G0/G1 phase, higher lactate dehydrogenase (LDH) release, and DNA fragmentation. Mechanistic studies showed that PDM caused significant elevation in ROS production, leading to perturbation of mitochondrial membrane potential, cell permeability, and activation of caspases-3/7. On the other hand, real-time PCR and Western blot analysis showed that PDM treatment increased the expression of the proapoptotic molecule, Bax, but decreased the expression of prosurvival proteins, Bcl-2 and Bcl-xL, in a dose-dependent manner. These findings imply that PDM could inhibit proliferation in MCF-7 cells via cell cycle arrest and apoptosis induction, indicating its potential as a therapeutic agent worthy of further development.

Keywords: antiproliferative, apoptosis, MCF-7 human breast cancer, Persea declinata

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Authors: Monika Kallubai, Shreya Dubey, Rajagopal Subramanyam

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Our study is all about the biological interactions of synthesized 5β-dihydrocortisol (Dhc) and 5β-dihydrocortisol acetate (DhcA) molecules with carrier protein Human Serum Albumin (HSA). The cytotoxic study was performed on breast cancer cell line (MCF-7) normal human embryonic kidney cell line (HEK293), the IC50 values for MCF-7 cells were 28 and 25 µM, respectively, whereas no toxicity in terms of cell viability was observed with HEK293 cell line. The further experiment proved that Dhc and DhcA induced 35.6% and 37.7% early apoptotic cells and 2.5%, 2.9% late apoptotic cells respectively. Morphological observation of cell death through TUNEL assay revealed that Dhc and DhcA induced apoptosis in MCF-7 cells. The complexes of HSA–Dhc and HSA–DhcA were observed as static quenching, and the binding constants (K) was 4.7±0.03×104 M-1 and 3.9±0.05×104 M-1, and their binding free energies were found to be -6.4 and -6.16 kcal/mol, respectively. The displacement studies confirmed that lidocaine 1.4±0.05×104 M-1 replaced Dhc, and phenylbutazone 1.5±0.05×104 M-1 replaced by DhcA, which explains domain I and domain II are the binding sites for Dhc and DhcA. Further, CD results revealed that the secondary structure of HSA was altered in the presence of Dhc and DhcA. Furthermore, the atomic force microscopy and transmission electron microscopy showed that the dimensions like height and molecular sizes of the HSA–Dhc and HSA–DhcA complex were larger compared to HSA alone. Detailed analysis through molecular dynamics simulations also supported the greater stability of HSA–Dhc and HSA–DhcA complexes, and root-mean-square-fluctuation interpreted the binding site of Dhc as domain IB and domain IIA for DhcA. This information is valuable for the further development of steroid derivatives with improved pharmacological significance as novel anti-cancer drugs.

Keywords: apoptosis, dihydrocortisol, fluorescence quenching, protein conformations

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Authors: Nkechi V. Enwuru, Bullum Nkeki, Elizabeth A. Adekoya, Olumide A. Adebesin, Rebecca F. Peters, Victoria A. Aikhomu, Mendie E. U.

Abstract:

Background: Probiotics are live microbial feed supplement beneficial for host. Probiotics and their postbiotic products have been used to prevent or treat various health conditions. However, the products cell viability is often low due to harsh conditions subjected during processing, handling, storage, and gastrointestinal transit. These strongly influence probiotics’ benefits; thus, viability is essential for probiotics to produce health benefits for the host. Microencapsulation is a promising technique with considerable effects on probiotic survival. The study is aimed to formulate a microencapsulated probiotic and evaluate its viability, antimicrobial efficacy, and cytotoxic activity of its postbiotic on the MCF-7 breast cancer cell line. Method: Human and animal raw milk were sampled for lactic acid bacteria. The isolated bacteria were identified using conventional and VITEK 2 systems. The identified lactic acid bacterium was encapsulated using spray-dried and extrusion methods. The free, encapsulated, and chitosan-coated encapsulated probiotics were tested for viability in simulated-gastric intestinal (SGI) fluid and different storage conditions at refrigerated (4oC) and room (25oC) temperatures. The disintegration time and weight uniformity of the spray-dried hard gelatin capsules were tested. The antimicrobial property of free and encapsulated probiotics was tested against enteric pathogenic isolates from antiretroviral therapy (ART) treated HIV-positive patients. The postbiotic of the free cells was extracted, and its cytotoxic effect on the MCF-7 breast cancer cell line was tested through an MTT assay. Result: The Lactobacillus plantarum was isolated from animal raw milk. Zero-size hard gelatin L. plantarum capsules with granules within a size range of 0.71–1.00 mm diameter was formulated. The disintegration time ranges from 2.14±0.045 to 2.91±0.293 minutes, while the average weight is 502.1mg. Simulated gastric solution significantly affected viability of both free and microcapsules. However, the encapsulated cells were more protected and viable due to impermeability in the microcapsules. Furthermore, the viability of free cells stored at 4oC and 25oC were less than 4 log CFU/g and 6 log CFU/g respectively after 12 weeks. However, the microcapsules stored at 4oC achieved the highest viability among the free and microcapsules stored at 25oC and the free cells stored at 4oC. Encapsulated cells were released in the simulated gastric fluid, viable and effective against the enteric pathogens tested. However, chitosan-coated calcium alginate encapsulated probiotics significantly inhibited Shigella flexneri, Candida albicans, and Escherichia coli. The Postbiotic Metabolites (PM) of L. plantarum produced a cytotoxic effect on the MCF-7 breast cancer cell line. The postbiotic showed significant cytotoxic activity similar to 5FU, a standard antineoplastic agent. The inhibition concentration of 50% growth (IC50) of postbiotic metabolite K3 is low and consistent with the IC50 of the positive control (Cisplatin). Conclusions: Lactobacillus plantarum postbiotic exhibited a cytotoxic effect on the MCF-7 breast cancer cell line and could be used as combined adjuvant therapy in breast cancer management. The microencapsulation technique protects the probiotics, improving their viability and delivery to the gastrointestinal tract. Chitosan enhances antibacterial efficacy; thus, chitosan-coated microencapsulated L. plantarum probiotics could be more effective and used as a combined therapy in HIV management of opportunistic enteric infection.

Keywords: probiotics, encapsulation, gastrointestinal conditions, antimicrobial effect, postbiotic, cytotoxicity effect

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Authors: Swati Srivastava, Mattia Lauriola, Yuval Gilad, Adi Kimchi, Yosef Yarden

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The glucocorticoid receptor (GR) has been proposed to play important, but incompletely understood roles in cancer. Glucocorticoids (GCs) are widely used as co-medication of various carcinomas, due to their ability to reduce the toxicity of chemotherapy. Furthermore, GR antagonism has proven to be a strategy to treat triple negative breast cancer and castration-resistant prostate cancer. These observations suggest differential GR involvement in cancer subtypes. The goal of our study has been to elaborate the current understanding of GR signaling in tumor progression and metastasis. Our study involves two cellular models, non-tumorigenic breast epithelial cells (MCF10A) and Ewing sarcoma cells (CHLA9). In our breast cell model, the results indicated that the GR agonist dexamethasone inhibits EGF-induced mammary cell migration, and this effect was blocked when cells were stimulated with a GR antagonist, namely RU486. Microarray analysis for gene expression revealed that the mechanism underlying inhibition involves dexamenthasone-mediated repression of well-known activators of EGFR signaling, alongside with enhancement of several EGFR’s negative feedback loops. Because GR mainly acts primarily through composite response elements (GREs), or via a tethering mechanism, our next aim has been to find the transcription factors (TFs) which can interact with GR in MCF10A cells.The TF-binding motif overrepresented at the promoter of dexamethasone-regulated genes was predicted by using bioinformatics. To validate the prediction, we performed high-throughput Protein Complementation Assays (PCA). For this, we utilized the Gaussia Luciferase PCA strategy, which enabled analysis of protein-protein interactions between GR and predicted TFs of mammary cells. A library comprising both nuclear receptors (estrogen receptor, mineralocorticoid receptor, GR) and TFs was fused to fragments of GLuc, namely GLuc(1)-X, X-GLuc(1), and X-GLuc(2), where GLuc(1) and GLuc(2) correspond to the N-terminal and C-terminal fragments of the luciferase gene.The resulting library was screened, in human embryonic kidney 293T (HEK293T) cells, for all possible interactions between nuclear receptors and TFs. By screening all of the combinations between TFs and nuclear receptors, we identified several positive interactions, which were strengthened in response to dexamethasone and abolished in response to RU486. Furthermore, the interactions between GR and the candidate TFs were validated by co-immunoprecipitation in MCF10A and in CHLA9 cells. Currently, the roles played by the uncovered interactions are being evaluated in various cellular processes, such as cellular proliferation, migration, and invasion. In conclusion, our assay provides an unbiased network analysis between nuclear receptors and other TFs, which can lead to important insights into transcriptional regulation by nuclear receptors in various diseases, in this case of cancer.

Keywords: epidermal growth factor, glucocorticoid receptor, protein complementation assay, transcription factor

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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: Abiola Falilat Ibraheem, Akinyimika Sowunmi, Valerie Otti

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Background: Introduction of innovative cancer clinical trials to Nigeria is a critical step in addressing global inequities of cancer burden. Low health and clinical trial literacy among Nigerian patients have been sighted as a significant barrier to ensuring that patients enrolled in clinical trials are truly informed. Video intervention has been shown to be the most proactive method to improving patient’s clinical trial knowledge. In the US, video interventions have been successful at improving education about cancer clinical trials among minority patients. Thus, this study aimed to apply and adapt video interventions addressing attitudinal barriers peculiar to Nigerian patients. Methods: A hospital-based representative mixed-method study was conducted at the Lagos State University Teaching Hospital (LASUTH) from July to December 2020, comprising of cancer patients aged 18 and above. Patients were randomly selected during every clinic day, of which 63 patients volunteered to participate in this study. We first administered a cancer literacy survey to determine patients’ knowledge about clinical trials. For patients who had prior knowledge, a pre-intervention test was administered, after which a 15-minute video (attitudes and intention to enroll in therapeutic clinical trials (AIET)) to improve patients’ knowledge, perception, and attitudes towards clinical trials was played, and then ended by administering a post-intervention test to the patients. For patients who had no prior knowledge, the AIET video was played for them, followed by the post-intervention test. Results: Out of 63 patients sampled, 43 (68.3%) had breast cancer. On average, patients agreed to understand their cancer diagnosis and treatment very well. 84.1% of patients had never heard about cancer clinical trials, and 85.7% did not know what cancer clinical trials were. There was a strong positive relationship (r=0.916) between the pretest and posttest, which means that the intervention improved patients’ knowledge, perception, and attitudes about cancer clinical trials. In the focus groups, patients recommended adapting the video in Nigerian settings and representing all religions in order to address trust in local clinical trialists. Conclusion: Due to the small size of patients, change in clinical trial knowledge was not statistically significant. However, there is a trend suggesting that culturally adapted video interventions can be used to improve knowledge and perception about cancer clinical trials.

Keywords: clinical trials, culturally targeted intervention, patient education, video intervention

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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: Seyda Can, Meryem Unulu

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

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

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Authors: Shoukat Ali, Amjad Hussain, Latif-ur-Rehman, Sehrish Inam

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Radiotherapy plays an important role in the management of cancer patients. Approximately 50% of the cancer patients receive radiotherapy at one point or another during the course of treatment. The entire radiotherapy treatment of curative intent is divided into different phases, depending on the histology of the tumor. The established protocols are useful in deciding the total dose, fraction size, and numbers of phases. The objective of this study was to evaluate the dosimetric differences between the conventional treatment protocols and the three-dimensional conformal simultaneously integrated boost (SIB) plans for three different tumors sites (i.e. bladder, breast, and brain). A total of 30 patients with brain, breast and bladder cancers were selected in this retrospective study. All the patients were CT simulated initially. The primary physician contoured PTV1 and PTV2 in the axial slices. The conventional doses prescribed for brain and breast is 60Gy/30 fractions, and 64.8Gy/36 fractions for bladder treatment. For the SIB plans biological effective doses (BED) were calculated for 25 fractions. The two conventional (Phase I and Phase II) and a single SIB plan for each patient were generated on Eclipse™ treatment planning system. Treatment plans were compared and analyzed for coverage index, conformity index, homogeneity index, dose gradient and organs at risk doses.In both plans 95% of PTV volume received a minimum of 95% of the prescribe dose. Dose deviation in the optic chiasm was found to be less than 0.5%. There is no significant difference in lung V20 and heart V30 in the breast plans. In the rectum plans V75%, V50% and V25% were found to be less than 1.2% different. Deviation in the tumor coverage, conformity and homogeneity indices were found to be less than 1%. SIB plans with three dimensional conformal radiotherapy technique reduce the overall treatment time without compromising the target coverage and without increasing dose to the organs at risk. The higher dose per fraction may increase the late effects to some extent. Further studies are required to evaluate the late effects with the intention of standardizing the SIB technique for practical implementation.

Keywords: coverage index, conformity index, dose gradient, homogeneity index, simultaneously integrated boost

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Authors: Nadia el Atlas, Mohammed el Aroussi, Mohammed Wahbi

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In this paper a novel technique of mass characterization based on robust features-fusion is presented. The proposed method consists of mainly four stages: (a) the first phase involves segmenting the masses using edge information’s. (b) The second phase is to calculate and fuse the most relevant morphological features. (c) The last phase is the classification step which allows us to classify the images into benign and malignant masses. In this step we have implemented Support Vectors Machines (SVM) and Artificial Neural Networks (ANN), which were evaluated with the following performance criteria: confusion matrix, accuracy, sensitivity, specificity, receiver operating characteristic ROC, and error histogram. The effectiveness of this new approach was evaluated by a recently developed database: INBREAST database. The fusion of the most appropriate morphological features provided very good results. The SVM gives accuracy to within 64.3%. Whereas the ANN classifier gives better results with an accuracy of 97.5%.

Keywords: breast cancer, mammography, CAD system, features, fusion

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Authors: Amir Seyfoori, Ehsan Samiei, Mohsen Akbari

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The use of microtechnology for detection and high yield isolation of circulating tumor cells (CTCs) has shown enormous promise as an indication of clinical metastasis prognosis and cancer treatment monitoring. The Immunomagnetic assay has been also coupled to microtechnology to improve the selectivity and efficiency of the current methods of cancer biomarker isolation. In this way, generation and configuration of the local high gradient magnetic field play essential roles in such assay. Additionally, considering the intrinsic heterogeneity of cancer cells, real-time analysis of isolated cells is necessary to characterize their responses to therapy. Totally, on-chip isolation and monitoring of the specific tumor cells is considered as a pressing need in the way of modified cancer therapy. To address these challenges, we have developed a bi-layer magnetic-based microfluidic chip for enhanced CTC detection and capturing. Micromagnet arrays at the bottom layer of the chip were fabricated using a new method of magnetic nanoparticle paste deposition so that they were arranged at the center of the chain microchannel with the lowest fluid velocity zone. Breast cancer cells labelled with EPCAM-conjugated smart microgels were immobilized on the tip of the micromagnets with greater localized magnetic field and stronger cell-micromagnet interaction. Considering different magnetic nano-powder usage (MnFe2O4 & gamma-Fe2O3) and micromagnet shapes (ellipsoidal & arrow), the capture efficiency of the systems was adjusted while the higher CTC capture efficiency was acquired for MnFe2O4 arrow micromagnet as around 95.5%. As a proof of concept of on-chip tumor cell monitoring, magnetic smart microgels made of thermo-responsive poly N-isopropylacrylamide-co-acrylic acid (PNIPAM-AA) composition were used for both purposes of targeted cell capturing as well as cell monitoring using antibody conjugation and fluorescent dye loading at the same time. In this regard, magnetic microgels were successfully used as cell tracker after isolation process so that by raising the temperature up to 37⁰ C, they released the contained dye and stained the targeted cell just after capturing. This microfluidic device was able to provide a platform for detection, isolation and efficient real-time analysis of specific CTCs in the liquid biopsy of breast cancer patients.

Keywords: circulating tumor cells, microfluidic, immunomagnetic, cell isolation

Procedia PDF Downloads 118