جستجوی مقالات مرتبط با کلیدواژه « ماموگرافی » در نشریات گروه « پزشکی »

Mammography has diagnostic value as a tool for the early detection of intangible breast cancers, both in screening and in the detection of disease. The present study was performed with aim to evaluate the findings related to focal asymmetry density of breast and their relationship with malignancy rate.

This descriptive analytical study was performed in 2019 on 150 patients with focal asymmetric density mammography referred to Khatam Al-Anbia Clinic of Jahrom city. Variables such as the appearance of the lesion on ultrasound, the presence or absence of a mass, the type of mass and the location of the lesion on ultrasound were examined and then hormonal and pathological evaluation was performed if necessary. Data analysis was done using SPSS software (version 19) and Chi-square and t-test. P<0.05 was considered statistically significant.

Out of 150 patients, 134 cases of focal asymmetry density (FAD) were observed on mammography. The age distribution of people whose mammographic findings showed the presence of FAD did not show a significant difference compared to patients without FAD (P=0.728). The outer upper quadrant or UOQ with 84 cases (56%) is the most common site of FAD involvement. Mammographic findings including normal, benign, suspected, borderline and malignant were significantly associated with the presence or absence of FAD (P=0.001). BI-RADS score was also significantly associated with the presence or absence of FAD in mammography (P=0.0001). The pathology was performed only for 21 cases. Based on this test, the sensitivity and specificity of focal asymmetry density for malignancy were determined as 63.64% and 20.00%.

Considering to the sensitivity and specificity of positive focal asymmetric density in mammography, for additional studies and to increase the diagnostic value, it is necessary to use other screening methods along with mammography for patients prone to focal asymmetric density.

One of the most important factors in determining prognosis and therapeutic plan in patients with breast cancer is tumor size. Our aim in this study was to compare the estimated tumor size in two common imaging modalities, ultrasound and mammography with pathologic assessment.

In this cross sectional study, we analyzed 287 patients with breast cancer diagnosis whose pathologic specimen was reported in pathology department of Omid hospital (Isfahan, Iran) from March 2015 to March 2020. The difference in tumor size were evaluated based on imaging and pathological reports. Then, we classified them in three groups as concordant, underestimated, and overestimated for which the effect of various factors such as age, tumor type, T stage and molecular subtype on accuracy of each modality was assessed.

Concordance rate was 58.3% in ultrasonography and 51.7% in mammography. Ultrasonography and mammography respectively underestimated the tumor size in 30.6% and 31%, and overestimated in 11.1% and 17.2% of cases indicating no statistically significant difference between the two modalities. Ultrasonography and mammography underestimate large tumors more commonly than small tumors. For tumors smaller than 20 mm and HER2- tumors, ultrasonography is more accurate than mammography. Also, mammography estimates the size of Luminal A tumors compared to ultrasound.

There was no significant difference between the accuracy of ultrasonography and mammography measurement of tumor size, but inherent factors such as T stage, her2 expression and molecular subtype influence this issue.

Mammography screening as the most sensitive diagnostic test, while reducing mortality, will improve the quality of life. Training that has the ability to change perceptions and acceptance can be used in designing effective interventions to perform and perpetuate this behavior. The present study aimed to investigate the effect of targeted education based on the transtheoretical Model on the acceptance and perception of mammography in women over 40.

In this experimental study, 128 eligible women over 40 years of age referring to comprehensive health centers in Amol were randomly assigned to two groups of intervention and control (n=62 in each group). For the intervention group, four online training sessions were held using WhatsApp over a period of four weeks. Leaflets and instructional videos were provided to participants, and their questions were answered online. The control group received the same educational content after sampling. The Rakowski Stages of Change Questionnaire and the Decision Balance Questionnaire for both groups were completed before, immediately, and one month after training. Data analysis was performed in SPSS software using paired t-test, chi-square, repeated measures RM, and independent t-test.

The frequency percentage of the stages of change model before the intervention was not significantly different between the control and intervention groups immediately after the intervention (P=0.022) and one month later (P=0.008). In the intervention group, the frequency of pre-thinking stages decreased, while the stages of thinking and acting increased. The mean score of negative perception based on the decision balance questionnaire was significantly different between the two groups of control and intervention before training, immediately after training, and one month after training (P<0.001). The mean score of positive perception based on the decision balance questionnaire demonstrated a significant difference between the control and intervention groups immediately after training and one month after training (P<0.001).

Based on the results of this study, the use of the transtheoretical model, while increasing positive perception, improves people's performance and can be used to improve screening programs.

Background &

Mammography is one of the reliable methods for early detection of breast cancer. However, it is difficult for the radiologist to provide an accurate and uniform assessment of the massive mammograms produced in the extensive screening. Therefore, the presence of an intelligent system that is highly accurate in detecting the location of a cancerous mass will be very necessary and necessary. In this regard, this research, by using mammography images and image processing techniques, has been tried to get an accurate diagnosis of the location of breast cancer. For this purpose, first by using some digital image enhancement techniques, an attempt is made to increase the recognition of cancerous tissues, and then by using classification techniques, the precise separation of cancerous parts from healthy parts of the breast is done. In research, various techniques have been proposed to improve the detection of tumors in mammograms and the accuracy of breast cancer classification. The basic problems in breast mammography in identifying and classifying masses and microcalcifications are caused by various factors. One of these complications is due to the awkward and illogical shape of some clusters of calcifications. The boundaries of each of the microcalcifications in the cluster cannot be well defined, and the radiologist may not be able to make an accurate diagnostic decision about the clinical nature of the microcalcifications in an area, but he can usually identify suspicious areas. In the paper, they presented a CAD system for processing mammographic images. They used the compressed breast thickness parameter for feature selection showed the importance of breast compression and changes in breast composition and then applied it to a variety of mammography image processing tasks. Considering that breast thickness is a key parameter in calculations and is not usually recorded; they showed that breast thickness can be estimated from an image and examined its sensitivity on the estimates. Then they discussed how to simulate X-rays in each examination and also simulate the appearance of anatomical structures inside the breast. In the research, tissue characteristics were used to automatically evaluate breast tissue density in digital mammograms. In this approach, the target area is limited to breast tissue only; so that artifacts, background, and head muscles are removed.Breast cancer is the most common cancer among women and the second cause of cancer-related death in women. Mammography is a simple type of imaging and a tool for early detection of non-palpable breast cancers; however, examining and interpreting a large number of mammogram images is a challenging and time-consuming task, and the possibility of human errors is high. One of the most important deep learning methods is convolutional neural networks. In the article, the digital database for screening mammography from the CBIS version was used to improve data validation.

In this research, three types of architecture were designed in the two-class mode and one type of architecture was designed in the three-class mode. To design the network, the layers were arranged according to Figure 5, which uses an input layer of size 159 x 145 a two-dimensional convolution layer of size 20 x 8, and a maximum integration layer of size 5 x 2, and two fully connected layers. (The maximum integration layer was used because it uses the maximum amount of neuron clusters of the previous layer and also causes faster convergence, and improves generalization and selection of invariant features). The third designed network architecture is shown in such a way that one input layer three 2D convolutional layers three maximum integration layers and two fully connected layers are used, the size of each layer is shown in Table (3). Layering is equal to one. The training time is 6:37 and the accuracy obtained for the validation data is 92.58% and the test data is 86.5%.

The simulation results for 310 data for the second type of two-class architecture, the training time is 6:06, and the accuracy obtained for the validation data is 84.40% and 72.82% for the test data. Also, the simulation results for 1240 The data for the first type of two-class architecture, the training time is 3:44:54, and the accuracy obtained for the validation data is 51.72% and the test data is 51.69%.

After a series of pre-processing, the number of used images was selected as 310. Then two other types of architecture were designed, and by applying the processed data, the accuracy of the architectures for 310 data was 42.39%, 7and 2.82%, respectively. 79.34% was obtained. The accuracy of the architectures for 1240 data was 51.69%, 65.45%, 72.46%. In the three-class mode, 1318 images in the database were used, and due to the lack of the same size, the images were resized. Then the image mask was applied to the images and given to the designed convolutional neural network, and the data was classified into three classes. According to the pre-processing and operations that have been done, the accuracy of the network has increased (72.39%) and the result has improved. The advantage of the method is the increased accuracy of validation and test data.

This study was conducted with the aim of comparision study of the effect of educational intervention based on health belief model using two methods of web-based multimedia education and booklet on adherence to mammography in women 40 years and older in Bushehr.

This study is a quasi-experimental study that was performed on 126 women 40 years and older (three groups, each consisting of 42 people). Educational content was designed based on the Health Belief Model. Data gathered by questionnaire before and two months after the educational intervention and, were analyzed using chi-square test and repeated measures analysis of variance in SPSS v.22.

after Intervention, comparison of the three groups showed that the mean score of knowledge in both Web-Based and booklet groups increased compared to the control group. Perceived benefit, susceptibility, perceived severity and health motivation also increased significantly after intervention in the web-based intervention group, but no significant change was observed in control groups. Perceived barriers also decreased in the web-based group after intervention. Adhering to mammography in the web-based intervention after training was significantly higher than the booklet and control group.

The results of this study showed that educational intervention based on psychological structures and web-based can be useful in improving women's beliefs about mammography behavior and promoting their behavior. It seems that the use of web-based teaching methods is more acceptable and effective than previous methods such as booklets. Therefore, designing studies using modern web-based educational methods is suggested.

Breast cancer is one of the most common cancers and a leading cause of death worldwide and in Iran. Mammography is commonly used in breast cancer screening and diagnosis. This study was performed with aim to evaluate the efficacy and cost-effectiveness of mammography, especially the mobile type, in breast cancer screening in Iran.

This study is an overview of reviews. After a systematic search in the databases of Cochrane Library, Trip, Pubmed, CRD and magiran, the appropriate, relevant and up-to-date reports including systematic review, health technology assessment, economic assessment and clinical guidance were found and used.

Mammography sensitivity for breast cancer screening in fixed type was reported between 84% and 96% and in mobile type between 77% and 98%. Its specificity has been reported between 50% and 100% in fixed type and between 92% and 95% in mobile type. In Iran, the use of mammography in the screening program increases the cost by about $ 37,000 per QALY (quality adjusted life years).

Due to the incidence of the disease, mammography is not cost effective in breast cancer screening, although in certain communities, for example, with a relatively high incidence may be cost effective. Mobile mammography is usually more expensive than fixed mammography and its technical performance is not much different, so it may be less cost effective than fixed mammography.

Breast cancer is the most common female cancer in the world and Iran and the leading cause of cancer death among Iranian women. One way to control this cancer is to get screened and diagnosed early. Given that screening in the general population is not possible, early detection of this cancer in high-risk women is one way to control it. Mammography is one way to diagnose breast cancer, but unfortunately, most people do not want to have a mammogram. This is an important issue for women with a family history of breast cancer, which constitutes one of the most high-risk groups for the disease. Therefore, the present study aimed to identify the views of relatives of patients with breast cancer about the reasons for unwillingness to perform mammography.

The present study was a qualitative study performed on 160 first-degree relatives and 118 second-degree relatives of breast cancer patients who were selected by purposive sampling to discover the reasons for not performing mammography. In-depth semi-structured interviews were used to collect data. All data were recorded and handwritten and analyzed using structural methods.

In the content analysis of the interviews, 5 themes, 14 main categories, and 73 subcategories were extracted. Preoccupation with daily life matters and lack of knowledge were the most common barriers to participation in screening among 1st-degree relatives, while wrong beliefs and attitudes constituted the most common barriers contributing to the unwillingness to getting mammography screening among 2nd-degree relatives.

Relatives of women with breast cancer are neglected despite facing a high probability of developing this cancer. It is suggested that the country’s health system provide comprehensive and effective education for relatives of women with breast cancer to raise awareness and eliminate misconceptions.

Breast cancer is one of the most common types of cancer in women. Screening mammography is a low‑dose X‑ray examination of breasts, which is conducted to detect breast cancer at early stages when the cancerous tumor is too small to be felt as a lump. Screening mammography is conducted for women with no symptoms of breast cancer, for early detection of cancer when the cancer is most treatable and consequently greatly reduce the death rate from the breast cancer. Screening mammography should be performed every year for women age 45-54, and every two years for women age 55 and older who are in good health. A mammogram is read by a radiologist to diagnose cancer. To assist radiologists in reading mammograms, computer-aided detection (CAD) systems have been developed which can identify suspicious lesions on mammograms. CADs can improve the accuracy and confidence level of radiologists in decision making and have been approved by FDA for clinical use. Traditional CAD systems work based on conventional machine learning (ML) and image processing algorithms. With recent advances in software and hardware resources, a great breakthrough in deep learning (DL) algorithms was followed, which revolutionized various engineering areas including medical technologies. Recently, DL models have been applied in CAD systems in mammograms and achieved outstanding performance. In contrast to conventional ML, DL algorithms eliminate the need for the tedious task of human-designed feature engineering, as they are capable of learning useful features automatically from the raw data (mammogram). One of the most common DL frameworks is the convolutional neural network (CNN). To localize lesions in a mammogram, a CNN should be applied in region‑based algorithms such as R‑CNN, Fast R‑CNN, Faster R‑CNN, and YOLO. Proper training of a DL‑based CAD requires a large amount of annotated mammogram data, where cancerous lesions have been marked by an experienced radiologist. This highlights the importance of establishing a large, annotated mammogram dataset for the development of a reliable CAD system. This article provides a brief review of the state‑of‑the‑art techniques for DL‑based CAD in mammography.

Mammography is the gold standard for diagnosis of breast cancer. But in recent years, other methods such as the Breast Light and thermography have been raised in cancer screening. There are conflicting results about the accuracy of these methods. This review study was performed with aim to determine the diagnostic accuracy of the diagnosis of two methods of breast light and thermography in breast cancer screening.

To achieve the studies, the search was conducted between 1900-2019 on the electronic databases of SID, Google scholar, Pubmed, Cochran, Scopus, Web Of Sciences using the keywords of Mammography, Ultrasound, Breast light, Thermography, Breast Cancer. Participants in the study were all women referred to medical centers who were evaluated by thermography and Brest Light method. The main inclusion criteria included the published articles on sensitivity, specificity, positive predictive value and negative predictive value of thermography and Brest Light methods. Insufficient data of articles and inappropriate and out-of-study content were considered as exclusion criteria. The STARD checklists were used to assess the full-text of the articles, and finally 9 articles which met the inclusion criteria were selected.

In the assessment of various studies comparing sensitivity, specificity, positive and negative predictive value of two methods of Breast light and thermography with other methods (mammography, ultrasound and clinical examination of the breast) showed that Bright light method had the sensitivity of 85.56% -93%, specificity of 53.4%-73.3%, the positive predictive value of 91.4%-93.5% and negative predictive value of 29.7%-77.8%. Thermography method had the sensitivity of 100%, specificity of 68.68%-95.3%, positive predictive value of 15.8% - 41.1% and negative predictive value of 99.1%-100%.

Bright light method has low specificity and although thermography method has high sensitivity, but the specificity and positive predictive value of the method is low, therefore these two methods can be used as an auxiliary method beside mammography or ultrasound.

Delay in diagnosis of PABC (pregnancy associated breast cancer) is common and the lack of awareness of PABC may preclude timely imaging investigation or biopsy. This study was performed with aim to evaluate the mammographic and sonographic findings in women with PABC.

This retrospective cross-sectional study was conducted on 24 women with PABC during pregnancy and lactation in radiology ward of Imam Reza hospital, Mashhad university of Medical sciences in 2006-2018. The mammographic and sonographic features were assessed in 24 women with PABC. The diagnosis of PABC was performed after histological examination in all patients. Data were analyzed by SPSS software (version 22). p < 0.05 was considered statistically significant.

PABC was diagnosed in six patients (25%) during pregnancy and in 18 patients (75%) after delivery. The most common cause of admission was breast mass (83%). The most common finding in mammography examination was breast mass with microcalcification (40%). The most common finding in sonography was breast mass (83.3%). The most common manifestation in sonography was hypoechoic mass with non-uniform echogenesity with irregular margin and vertical orientation. Pathology finding showed ductal invasive carcinoma in 22 patients (91.66%), non-invasive carcinoma in one patient (4.16%) and inflammatory carcinoma in one patient (4.16%)

Ultrasound appearance of PABC may be different from that of breast cancer in non-pregnant women and ultrasound findings such as prominent cystic component, posterior enhancement, and parallel orientation are not uncommon findings in PABC. So, ultrasound findings may mimic benign breast lesion during pregnancy and lactation. Mammography and ultrasound are two complementary imaging methods in women with palpable mass during pregnancy and lactation.

Breast cancer is the most common cancer among women and the earlier it is diagnosed, the easier it is to treat. The most common way to diagnose breast cancer is mammography. Mammography is a simple chest x-ray and a tool for early detection of non-palpable breast cancers and tumors. However, due to some limitations of this method such as low sensitivity especially in dense breasts, other methods such as 3d mammography, ultrasound and magnetic resonance imaging are often suggested to obtain additional useful information. Recently, computer-aided diagnostic or intelligent diagnostic have been developed to assist radiologists to improve diagnostic accuracy. In general, a computer system consists of four steps: pre-processing, dividing areas of interest, extracting and selecting features, and finally classification. Nowadays, the use of imaging techniques in the identification of patterns for diagnosis and automatic determination of breast cancer by mammography and even digital pathology (which is one of the emerging trends in modern medicine) reduces human errors and speeds up the diagnosis. In this article, We reviewed recent findings and their disadvantages and benefits in the diagnosis of breast cancer by neural networks, especially the artificial neural network, which is widely used in the diagnosis of cancers and intelligent breast cancers. This literature review shows that hybrid algorithms have been better at improving classification and detection accuracy. Providing a convenient way to diagnose tumors in the breast by computer-assisted diagnosis systems will be of great help to the physicians. Much work has been done in recent years to diagnose breast cancer, and many advances have been made in improving and diagnosing breast cancer by computer. All methods have a significant error percentage and are different depending on the type of breast, but compared to other types of neural networks, convolution and combining methods with convo have better results. Another advantage of the convoluted network is the automatic extraction of desirable features. Today, the best percentages of accuracy in detecting benign or malignant cancerous mass are achieved by convolution.

Due to the fact that breast cancer has a high prevalence in the society and in a significant number of patients, its initial manifestation is only in the form of microcalcification on mammography, this study was performed with aim to  evaluate the pathologic results of stereotactic core needle  biopsy to determine the prevalence of malignant and benign lesion and subtype in each group in patients with  suspicious microcalcifications on mammography based on BIRADS classification.

In this descriptive study, 59 patients referred to mammographic clinic in Mashhad city between April2017-September2019, and underwent sterotactic core biopsy because of the presence of suspicious microcalcifications (including morphology and distribution) without mass or focal asymmetry on mammography. In all patients, calcification was identified in at least one core needle specimen after performing specimen mammography. The specimens were submitted and referred to pathologic laboratory and analyzed by two pathologists. The total prevalence of benign and malignant lesions and also the prevalence of subtype lesions in each group were evaluated. The results of different mammographic appearance of suspicious microcalcifications were also compared with pathologic diagnosis. Data were analyzed using SPSS statistical software (version 16) and descriptive statistics methods and frequency distribution of variables in the form of tables. P<0.05 was considered statistically significant.

Benign lesions were seen in 42 patients (71%) and malignant lesions in 17 patients (29%) in histopathologic examination. Total prevalence of benign lesions was more than malignant lesions and the prevalence of non-proliferative lesions more than proliferative lesions. Fibrocystic change was the most common lesion in non-proliferative group (54%). In malignant group, prevalence of Dcis Carcinoma and invasive ductal carcinoma was 74% and 26%, respectively. Prevalence of malignancy was more in pleomorphic type of microcalcifications than amorphous and coarse heterogeneous types.

According to the significant prevalence of malignancy especially the prevalence of DCIS, sterotactic biopsy can be used as a noninvasive biopsy method for Microcalcifications which have a suspicious morphology and distribution to detect early breast cancer.

Breast cancer is the most common cancer in women around the world. Early detection of this cancer plays an important role in its treatment. Therefore, the aim of this study was to determine the effect of educational intervention based on health belief model in adopting breast cancer prevention behaviors in female health workers in Torbat Heydariyeh.

This study was a quasi-experimental intervention with a control group, which was conducted in 1398 on 70 female health workers working in health centers. Data were collected from both intervention and control groups by a valid and reliable questionnaire before and after the intervention and analyzed by Chi-square, Mann-Whitney and Wilcoxon statistical interventions version 16. SPSS in software.

The mean age of the participants in the experimental group was 77.42±8.43 years and the control group 40.09±8.21 years (P=0.178). According to the results obtained after interventional education, the mean score of Health Belief Model constructs (perceived susceptibility, perceived severity, perceived benefits of breast self-test, perceived barriers of breast self-test, perceived self-efficacy of breast self-test, perceived benefits of mammography and perceived barriers of mammography) showed a significant increase in the experimental group in comparison to the control group (P<0.001). It should be noted that the mean score for perceived self-efficacy of mammography was not significant.

Health belief model training improved participantschr('39') perceptions. Therefore, the use of this educational model in other educational and prevention programs is recommended.

Breast cancer is considered as a serious health concern worldwide. The early diagnosis of this disease plays an important role in reducing mortality and morbidity rates. Therefore, the present study was conducted to investigate the role of motivational interviewing on changing women's mammography behavior in 2017.

The study population was selected using simple random sampling and then the subjects were assigned into two groups of intervention and control. The motivational interview was conducted in 5 sessions (one hour in each session) once a week for the intervention group. The control group received no intervention. Both groups filled out the demographic and the stages of change questionnaire before and two months after the intervention.

In the interview group, no significant differences were observed in the pre-contemplation and action stage prior and two months after intervention (p= 0.333, and 0.219, respectively). However, after two months, significant differences were observed in contemplation and maintenance stage in intervention group (p= 0.006, and 0.035, respectively). In the control group, most of the women were in contemplation (24%) and maintenance (32%) stages prior to the intervention. Nevertheless, there were no statically significant differences in any stages before and two months after intervention in the control group (p>0.05).

It seems that motivational interview based on the stages of change model was effective in promoting mammography behavior of women. Moreover, counseling based on this model could lead to the promotion of screening behaviors in women.

Cancer, such chronic and non - contagious diseases, is known to its importance, due to the changes in the incidence of diseases in the world and the profound psychological impact of the disease on the foundation of family, and community. Breast cancer is the most common type of cancer and is the second reason for deaths in women. Mammography is the most accurate method of distinction and diagnosis of breast cancer at the early stages in many countries and can identify non-touch waste and help to detect tangible masses.
  The present study is of a cross-sectional base manner that has been carried out on 160 healthy volunteers from the healthcare unit of the city of Isfahan. Sampling was carried out in accessible manner. The data collection tool was a multi-part questionnaire including awareness questions, demographic characteristics, behavior, and behavioral intention and standardized questionnaire (Champion’s Health Belief Model). The collected data were analyzed with SPSS Version 16 software. Participation in this study was informed consent.
  Also, in this study, the highest percentage of research units (53 percent) in the age group were under 45. The median age of the participants was 46.52 with a standard deviation of 7.06. 145(90.6%) of the participants so far were informed about breast cancer, a source of information (62.5%) 100 of the physicians and health centers employees. Regarding the evaluation of model constructs in the field of breast cancer and breast self-examination, 98 (61.2%) persons with moderate knowledge, 122(76.2%) persons with low perceived susceptibility, 105 (65.6%) Of the subjects with moderate perceived severity,93 (58.1%) persons had moderate perceived benefits and 110(68.8%) persons had moderate perceived benefits.
The results of the study showed that the level of behavior and behavioral intentions of mammography in healthy volunteers is low. The results of this study also reveal the need for more attention of health planners in the country to educate and promote screening methods and remove barriers.