Diagnosis Of Breast Disease Research Articles

Benign and malignant breast lesions in children and adolescents - diagnostic and therapeutic approach.

Benign and malignant breast lesions in children and adolescents are rare compared to adults. Most tumors are benign. Malignant breast lesions are extremely rare. Fibroadenomas are the most common, accounting for 95% of all lesions. Diagnosis is based on history and physical examination of the breast and armpit. Imaging studies include ultrasound, mammography, and magnetic resonance imaging. Ultrasound is the most commonly used imaging test. Other tests are used in cases of diagnostic doubt. Core needle biopsy should be considered for appropriate diagnostic management. Excisional biopsy should be considered for complex clinical conditions and imaging studies. Except in doubtful situations in children and adolescent girls, a conservative approach and observation of the lesions along with periodic ultrasound examination initially every 6-12 months is advisable. Management of malignant breast lesions in children typically involves a multidisciplinary team consisting of pediatric oncologists, surgeons, radiation oncologists, pathologists, and other specialists and depends on the clinical condition of the patient. An important aspect is the experience of the clinician and radiologist in the treatment of breast lesions, as well as increasing patient and family awareness of possible breast lesions and self-examination. This review aims to provide a scoping overview of the available literature on benign and malignant lesions of the breast in pediatric and adolescent populations to assist physicians and surgeons in making decisions regarding the appropriate diagnosis and management of pediatric breast disease.

Artificial intelligence in action: Improving breast disease management through surgical robotics and remote monitoring

ObjectivesThis article aims to discuss the transformative impact of artificial intelligence (AI) on the identification and management of breast diseases, with a specific focus on breast cancer. Materials and methodsHealthcare providers have integrated AI technologies such as surgical robots and remote monitoring systems to improve the accuracy and efficiency of breast disease diagnosis and treatment. ResultsSurgical robots equipped with AI algorithms provide real-time guidance to surgeons, analyze imaging data, and ensure precise procedures for better outcomes in breast cancer surgeries. AI-driven remote monitoring systems allow for close monitoring of patient health data, disease progression prediction, and personalized treatment recommendations. ConclusionsThe incorporation of AI technology into healthcare practices for breast diseases has revolutionized patient care delivery, enhancing outcomes, promoting patient engagement, and improving overall quality of care. These advancements offer personalized and tailored healthcare strategies that meet the unique needs of each patient, reshaping the healthcare industry.

Diagnosis and features of the treatment algorithm of non-lactational chronic mastitis on the example of a clinical case

Inflammatory processes in the mammary gland (MG) do not lose their relevance, the frequency of occurrence reaches 16% among all diseases of the MG. Non-lactational mastitis (NM) – inflammation in the MG outside the period of pregnancy and lactation – stands out among them [1]. With untimely and non-radical treatment of acute forms, there is a transition to chronic, with the formation of bacterial biofilm in the focus of inflammation and thick scar capsule after repeated surgical interventions, which is due to a vicious circle. The clinical picture of non-lactational chronic mastitis in most cases resembles a diffuse (mastitis-like, edematous-infiltrative) form of breast cancer (BC), which determines the differential-diagnostic difficulties in referring to a doctor both at initial treatment and at recurrence. This problem is faced by doctors of different specialties: oncologists, surgeons, gynecologists, therapists, specialists in radiation and radiological diagnostics [2, 3]. Radiation diagnostics is always the «gold standard» in the diagnosis of breast diseases, but has a number of disadvantages in the inflammatory process in the breast, and, in some cases, it is worth prioritizing the ultrasound method of investigation [4]. Through the combined interpretation of clinical data and ultrasound (USG) findings, the following parameters should be evaluated: skin thickness, pre-mammary fatty tissue, structure of glandular parenchyma of the MJ, presence and boundaries of inflammatory infiltrate/infiltrates in the MJ tissue; formation of «rarefaction» zones, microabscesses and/or already formed «draining» abscess cavities, assess the content of fluid cavities (homogeneity/homogeneity), the presence of pyogenic capsule, as well as the boundaries of inflammation/abscessing with unchanged breast tissue, taking into account possible «microfoci» outside the main mass of changes (like «satellites», «fluid spurs»). It is important to analyze the state of the ductal system of the breast (ductal diameter dilation, intraluminal content) and possible connection of ducts with abscessed areas, which may be a predictor of further spread of the process, recurrence or chronicization of the disease. Inflammation on the background of subacute and chronic process can lead to the development of fistulas [5]. However, there is not always the classic ultrasound picture of a purulent focus in the breast [6–9].

Effect of music therapy combined with aerobic exercise on sleep quality among breast cancer patients undergoing chemotherapy after a radical mastectomy: a randomized controlled trial

PurposeWe aimed to study the effect of music therapy combined with aerobic exercise on the sleep quality of patients undergoing chemotherapy after a radical mastectomy.MethodsA randomized controlled trial was conducted at the Breast Disease Diagnosis and Treatment Center, Shaanxi Province Tumor Hospital, from July 2017 to June 2019. 110 female breast cancer patients who underwent a radical mastectomy were recruited and randomly allocated into an intervention group or a control group. The intervention group completed music therapy combined with aerobic exercise from the first to the sixth admission to the hospital for chemotherapy, while the control group received only routine nursing care. The sleep quality of these patients was measured using the Pittsburgh Sleep Quality Index (PSQI). A linear mixed model was used to adjust the PSQI of patients after controlling for other confounding factors.ResultsThe mean sleep quality score of the breast cancer patients who received chemotherapy after a radical mastectomy (baseline) was 8.86 ± 2.34. The intervention group had a significantly lower mean global PSQI score than the control group from the first test to the third test, with an adjusted mean difference of -1.05 (95%CI: -1.86, -0.24; P = 0.01), -2.89 (95%CI: -3.70, -2.08; P < 0.001) and − 4.84 (95%CI: -5.65, -4.03; P < 0.001), respectively. A change in the global PSQI score from baseline for the intervention group was from 0.55 (95%CI: -0.24, 1.34; P = 0.171) at the first test to 2.75 (95%CI: 1.96, 3.53; P < 0.001) at the last test, and for the control group was from − 0.51 (95%CI: -1.31, 0.29; P = 0.213 at the first test to -2.10 (95%CI: -2.91, -1.30; P < 0.001) at the last test.ConclusionsAn intervention of music therapy combined with aerobic exercise can significantly improve the sleep quality of female breast cancer patients undergoing chemotherapy after a radical mastectomy, and this intervention continuously improves many aspects of sleep reactivity.Clinical trial registrationThis study was registered in the Chinese Clinical Trial Registry (ChiCTR2100042975, 02/02/2021).

Detection and diagnosis of automated breast ultrasound in patients with BI-RADS category 4 microcalcifications: a retrospective study

BackgroundAutomated Breast Ultrasound (AB US) has shown good application value and prospects in breast disease screening and diagnosis. The aim of the study was to explore the ability of AB US to detect and diagnose mammographically Breast Imaging Reporting and Data System (BI-RADS) category 4 microcalcifications.Methods575 pathologically confirmed mammographically BI-RADS category 4 microcalcifications from January 2017 to June 2021 were included. All patients also completed AB US examinations. Based on the final pathological results, analyzed and summarized the AB US image features, and compared the evaluation results with mammography, to explore the detection and diagnostic ability of AB US for these suspicious microcalcifications.Results250 were finally confirmed as malignant and 325 were benign. Mammographic findings including microcalcifications morphology (61/80 with amorphous, coarse heterogeneous and fine pleomorphic, 13/14 with fine-linear or branching), calcification distribution (189/346 with grouped, 40/67 with linear and segmental), associated features (70/96 with asymmetric shadow), higher BI-RADS category with 4B (88/120) and 4 C (73/38) showed higher incidence in malignant lesions, and were the independent factors associated with malignant microcalcifications. 477 (477/575, 83.0%) microcalcifications were detected by AB US, including 223 malignant and 254 benign, with a significantly higher detection rate for malignant lesions (x2 = 12.20, P < 0.001). Logistic regression analysis showed microcalcifications with architectural distortion (odds ratio [OR] = 0.30, P = 0.014), with amorphous, coarse heterogeneous and fine pleomorphic morphology (OR = 3.15, P = 0.037), grouped (OR = 1.90, P = 0.017), liner and segmental distribution (OR = 8.93, P = 0.004) were the independent factors which could affect the detectability of AB US for microcalcifications. In AB US, malignant calcification was more frequent in a mass (104/154) or intraductal (20/32), and with ductal changes (30/41) or architectural distortion (58/68), especially with the both (12/12). BI-RADS category results also showed that AB US had higher sensitivity to malignant calcification than mammography (64.8% vs. 46.8%).ConclusionsAB US has good detectability for mammographically BI-RADS category 4 microcalcifications, especially for malignant lesions. Malignant calcification is more common in a mass and intraductal in AB US, and tend to associated with architectural distortion or duct changes. Also, AB US has higher sensitivity than mammography to malignant microcalcification, which is expected to become an effective supplementary examination method for breast microcalcifications, especially in dense breasts.

Role of Ultrasound in Diagnosis of Fibrocystic Breast Disease

Background: Fibrocystic breast disease is the most typical benign breast disease, which is seen in women worldwide with features of pain and feeling of nodules. Its diagnosis is based on clinical symptoms, ultrasound, mammography, and in doubt cases, biopsy is indicated. For assessment of the breast, we clinically examined the breast, axilla, and both supra and infraclavicular regions for lymph node assessment, followed by ultrasound examination. Detection of lesions in any breast quadrant assessed by BIRADs, Breast Imaging Reporting, and Data System grouped in five brackets. Scanning by sonography using B-mode and Doppler study was improved for detecting and characterizing benign and malignant lesions. Objective: To assess a breast lesion by ultrasound with features suggestive of a benign or malignant nature. Method: This study included 210 women aged 20 - 45 who visited a clinic from October 2020 to April 2022 and were examined by ultrasound machine Samsung HS50 (KOREA) with an LA3-14AD probe. B-mode images obtained detection of the lesion, and we also used Doppler ultrasound for assessment of the vascularity of the lesion. The BI-RADS system was used for the categorization of all findings. Result: In 210 women, complaints of lumps were involved in our study. Imaging by B-mode ultrasound using the Doppler study assesses the vascularity of the lesion and provides more characterization of benign and malignant lesions. By B–mode imaging, 99 patients had regular ultrasound study, and 79 patients had simple cysts that appeared well defined, had familiar outlines, and had an anechoic rounded or oval shape with posterior enhancement. Twenty-eight patients with fibroadenoma visualized as round or oval-shaped hypoechoic lesions horizontally oriented to the planes of the breast with lateral shadowing. 2 patients had complex cysts that appear as well-defined, irregular outlines, rounded shape, a thick wall with internal echoes with posterior enhancement. 2 patients have a malignant lesion that appears ill-defined rough outline vertically oriented with breast planes and show posterior shadowing. Conclusion: Ultrasound was established as the most suitable imaging modality for the categorization of breast lesions and exclusion of malignancy, which is helpful for evading unnecessary biopsies.

The diagnostic value of multimodal imaging based on MR combined with ultrasound in benign and malignant breast diseases

We aimed to construct and validate a multimodality MRI combined with ultrasound based on radiomics for the evaluation of benign and malignant breast diseases. The preoperative enhanced MRI and ultrasound images of 131 patients with breast diseases confirmed by pathology in Aerospace Center Hospital from January 2021 to August 2023 were retrospectively analyzed, including 73 benign diseases and 58 malignant diseases. Ultrasound and 3.0 T multiparameter MRI scans were performed in all patients. Then, all the data were divided into training set and validation set in a 7:3 ratio. Regions of interest were drawn layer by layer based on ultrasound and MR enhanced sequences to extract radiomics features. The optimal radiomic features were selected by the best feature screening method. Logistic Regression classifier was used to establish models according to the best features, including ultrasound model, MRI model, ultrasound combined with MRI model. The model efficacy was evaluated by the area under the curve (AUC) of the receiver operating characteristic, sensitivity, specificity, and accuracy. The F-test based on ANOVA was used to screen out 20 best ultrasonic features, 11 best MR Features, and 14 best features from the combined model. Among them, texture features accounted for the largest proportion, accounting for 79%.The ultrasound combined with MR Image fusion model based on logistic regression classifier had the best diagnostic performance. The AUC of the training group and the validation group were 0.92 and 091, the sensitivity was 0.80 and 0.67, the specificity was 0.90 and 0.94, and the accuracy was 0.84 and 0.79, respectively. It was better than the simple ultrasound model (AUC of validation set was 0.82) or the simple MR model (AUC of validation set was 0.85). Compared with the traditional ultrasound or magnetic resonance diagnosis of breast diseases, the multimodal model of MRI combined with ultrasound based on radiomics can more accurately predict the benign and malignant breast diseases, thus providing a better basis for clinical diagnosis and treatment.

The application of mammography imaging in the diagnosis and prediction of breast diseases

Breast diseases pose a significant threat to women’s health, so early detection and treatment are extremely important. In this context, early disease identification has become crucial in the diagnosis and treatment of breast diseases. This paper begins by outlining the pivotal role of mammography in the early diagnosis of breast cancer, comparing the structural similarities and differences between normal and diseased breast tissues. This comparison underscores the primary role of mammography in the diagnosis and treatment of breast diseases. Additionally, our paper provides an overview of fundamental concepts related to breast cancer detection, diagnosis, and prediction systems. It delves into the latest research developments in auxiliary diagnostic detection, examination, and risk prediction systems associated with breast cancer. Our objective is to offer a comprehensive understanding of the role of computer-aided detection, diagnosis, and prediction systems in breast diseases, fostering further development and application. This work aims to explore and drive innovation in the field, enhance early detection rates of breast diseases, and guide readers towards novel directions, thus contributing to female healthcare management.

The Canadian Breast Cancer Symposium 2023 Meeting Report.

On 15-16 June 2023, healthcare professionals and breast cancer patients and advocates from across Canada met in Toronto, Ontario, for the 2023 Canadian Breast Cancer Symposium (CBSC.). The CBSC. is a national, multidisciplinary event that occurs every 2 years with the goal of developing a personalized approach to the management of breast cancer in Canada. Experts provided state-of-the-art information to help optimally manage breast cancer patients, including etiology, prevention, diagnosis, experimental biology, and therapy of breast cancer and premalignant breast disease. The symposium also had the objectives of increasing communication and collaboration among breast cancer healthcare providers nationwide and providing a comprehensive and real-life review of the many facets of breast cancer. The sessions covered the patient voice, the top breast cancer papers from different disciplines in 2022, artificial intelligence in breast cancer, systemic therapy updates, the management of central nervous system metastases, multidisciplinary management of ductal carcinoma in situ, special populations, optimization-based individual prognostic factors, toxicity management of novel therapeutics, survivorship, and updates in surgical oncology. The key takeaways of these sessions have been summarized in this conference report.

Specific characteristics and challenges associated with breast cancer diagnostics in women after breast augmentation and reconstructive surgeries with implants

Background. The number of plastic surgeries is constantly growing worldwide. Breast augmentation remains the most common surgical procedure in women, which demonstrated a 0.5 % increase over the past 4 years. As the number of women with breast implants increases, specialists and patients themselves face difficulties related to screening, diagnosis, and treatment of tumors, including breast cancer.Aim. To analyze specific characteristics of breast examination in patients after breast augmentation who were examined and treated in the mammological clinic of Russian Research Center of Radiology, Ministry of Health of the Russian Federation.Materials and methods. This study included 273 patients aged between 21 and 63 years (mean age 49.0 ± 7.6 years) after breast augmentation and after reconstructive surgery for breast cancer and symmetrizing surgery on the contralateral side. All women underwent clinical examination plus breast ultrasound (for patients under 40 years of age) or mammography followed by ultrasound (patients over 40 years of age). Patients who were found to have BI-RADS 3–4 tumors underwent ultrasound-guided or stereotactic breast biopsy. In case of suspicious intraductal formations according to breast nipple smears the patients were referred to breast ductography. Patients with suspected implant rupture or capsular contracture, as well as patients requiring the assessment of the disease stage underwent contrast-enhanced magnetic resonance imaging.Results. After comprehensive examination, 12 patients (5.4 %) were diagnosed with breast cancer; 38 patients (13.9 %), with implant rupture; 3 patients (1 %), with intraductal formations.Conclusion. Breast augmentation is not a contraindication to mammography in women aged over 40 years with glandular tissue. Additional examination methods include breast ultrasound, contrast-enhanced mammography, and breast magnetic resonance imaging. In case of no glandular tissue, contrast-enhanced breast magnetic resonance imaging and breast ultrasound are the methods of choice. It is important to develop new standards of screening and diagnosis of breast diseases in women after aesthetic surgery, since breast cancer incidence is likely to increase among women after breast augmentation over the next decades, considering the fact that breast cancer is the most common malignancy in women and its incidence is constantly growing.

Analysis of mathematical methods for diagnosis of breast diseases

This paper analyzes the diagnosis of breast diseases is a critical aspect of modern healthcare, as early detection can greatly improve patient outcomes. Mathematical methods have increasingly been utilized in recent years as a means of aiding in the diagnosis of breast diseases. This abstract provides an analysis of the various mathematical methods that have been developed and applied to this important area of medical research. The methods include but are not limited to artificial intelligence (AI), machine learning, and statistical modeling. The strengths and limitations of these approaches are examined, as well as their potential impact on clinical practice. Furthermore, the abstract will discuss the current state of research in this field and offer insights into future directions for the development and application of mathematical methods in the diagnosis of breast diseases. Keywords: mathematical methods, breast diseases (BD), mastopathy, fibroadenoma, risk factors, X-ray devices, ultrasound examination (USE).

Лучевые методы диагностики заболеваний молочной железы

Abstract. Breast cancer is one of the most common and urgent healthcare issues. For primary diagnosis and clarification of the diagnosis of breast cancer specialists use most often such methods of breast examination as examination and palpation, computed tomography, magnetic resonance imaging, ultrasound, radionuclide examination of the mammary glands. Radiologists and mammalogists-oncologists face an important task of early detection of various forms of breast cancer, which enables to improve significantly the disease prognosis, as this is a priority. To solve the issue the world community is developing and putting into practice new methods of mammary gland research, the X-ray method of investigation has a leading position. In addition to breast cancer, the attention of the diagnostician should also be directed to benign breast dysplasia due to its correlation with the risk of developing breast cancer. The severity of dysplasia determines the risk of developing cancer. The practical application of methods of early diagnosis of benign and malignant breast diseases, increased funding of medical institutions to raise the technical level, and retraining of personnel can significantly reduce the incidence and increase the frequency of breast cancer detection in the early stages of its development.

Expression analysis of lymphocyte subsets and lymphocyte-to-monocyte ratio: reveling immunosuppression and chronic inflammation in breast cancer

ObjectiveTo explore the immune status and chronic inflammation of breast cancer patients, this study aims to analyze the diagnostic value of peripheral blood lymphocyte subsets (CD3+T, CD4+T, CD8+T, CD3+CD4−CD8−T, CD19+B, and NK cells) and lymphocyte-to-monocyte ratio (LMR) for breast cancer. Furthermore, it seeks to examine the correlation between these subsets and LMR with clinicopathological features.MethodsA total of 100 breast cancer patients were selected as the experimental group, while 55 patients with benign breast diseases were included in the control group. Statistical analysis, including the Wilcoxon test, Kruskal–Wallis test and the receiver operating characteristic curve, was employed to investigate the association between these serum indexes and the clinicopathological characteristics of the patients.ResultsThe levels of CD3+T cells, CD4+T cells, CD8+T cells, CD4+/CD8+ ratio, NK cells, CD3+CD4−CD8−T cells, and LMR were found to be related to the occurrence of breast cancer when analyzing data from patients with benign and malignant breast diseases. Among these biomarkers, CD3+T cells, CD4+T cells, CD4+/CD8+ ratio, CD3+CD4−CD8−T cells, and LMR were identified as independent risk factors for breast cancer development, and the AUCs were 0.760, 0.750, 0.598, 0.697, and 0.761 (P < 0.05), respectively. Furthermore, we observed varying degrees of differences in the expression of CD3+T cells, CD4+T cells, CD8+T cells, CD4+/CD8+ ratio, and LMR in lymph node metastasis, clinical staging, molecular typing, Ki-67 level (P < 0.05). However, statistical differences in histologic grade and pathology type were not found (P ≥ 0.05).ConclusionLymphocyte subsets and LMR reflect the immune status and chronic inflammation of the body, respectively. They have certain value in the diagnosis of benign and malignant breast diseases, and correlate with lymph node metastasis, clinical staging, molecular typing and other clinicopathological features of breast cancer. Therefore, monitoring the expression of lymphocyte subsets and LMR in the body may help the auxiliary diagnosis and condition analysis of breast cancer in the clinic.

Histomorphological study of breast lesion in a tertiary care centre in Kathmandu

Various types of lesion from inflammation to carcinoma can affect the breast. Some lesions are common in young age group while others are more common in elderly age group. Accurate diagnosis is essential to relieve anxiety of patients. In case of carcinoma, early and accurate diagnosis can save the patient from metastases thus reducing mortality and morbidity. Histopathology plays a major role in distinguishing benign lesions from malignant lesions. Hospital based descriptive study was carried out in the Department of Pathology of a tertiary care centre in Kathmandu over a period of eleven months (1st September 2022 to 30th July 2023). A total of 52 cases of breast lesions were included in the study. Among 52 cases, 17 (33%) were non-neoplastic and 35 (67.0%) were neoplastic. Among neoplastic, 21 (40.3%) were benign and 14 (26.9%) were malignant. Among non neoplastic lesions, inflammatory lesion (17.3%) was the most common diagnosis. Among neoplastic lesion, fibroadenoma (34.6%) was the most common diagnosis. All cases of malignant breast lesions (26.9%) were diagnosed as invasive breast carcinoma, no special type. This study helped us to analyze the histopathological spectrum and prevalence of breast lesions in this part of our country. It is well known fact that the histomorphological study of the breast lesions is an important aspect for the diagnosis, management and prognosis of breast diseases.

Contribution of mammography in the diagnosis of breast tumours at the senology unit of the chu aristid le dantec hospital

Introduction: In Senegal, breast cancer is the second most common cancer in women after cervical cancer.1 It is responsible for a high mortality rate of around 70% after five years,2 as in many other developing countries. Mammography plays an important role in the screening and diagnosis of breast diseases. The unfavourable conditions in our regions are at the origin of the inaccessibility and unavailability of this diagnostic tool. Objectives: The objective of our study was to evaluate the availability, accessibility and use of mammography in the diagnosis of breast diseases in the Senology Unit of the University Hospital Aristide Le Dantec in Dakar. Materials and methods: This was a descriptive and analytical cross-sectional study of 120 patients followed at the Senology Unit of the Aristide Le Dantec University Hospital in Dakar, during the period from 1 January 2010 to 31 December 2014. The parameters studied were: the socio-economic profile of women, the geographical distribution of functional mammography centres, the time taken to perform mammography, its cost, its quality and its contribution to diagnosis. Results: In our study, the majority of patientes lived in the suburbs of Dakar (67.5%). The average age was 44.2 years. More than half (54.2%) had no regular source of income. The rate of use of mammography was 8.9%. The average cost was 48,944 FCFA. The average time taken to carry out a mammogram after it was prescribed was 28.8 days. In 76.6% of cases, mammography was performed for diagnostic purposes. In no case was an additional examination performed. As regards the quality of the mammographic examination, in 17.5% of cases the usual marking was not respected and the transparency of the images was not optimal in 26.6% of cases. The validity criteria were not met in 18.3% of the results and the American College of Radiology (ACR) BIRADS classification was used in 95 patients (79.2%). Payment before the examination was carried out was in cash in the majority of cases (70.8%). However, the difference in cost was significant according to the type of imaging centre (p = 0.015). Conclusion: Mammography was characterised by the unavailability of centres, a fairly long time to carry out the examination and a lower quality of the examinations.

Progress in the Application of Artificial Intelligence in Ultrasound Diagnosis of Breast Cancer

The mammary gland is an important human organ that secretes milk and feeds offspring, while breast tumors are benign or malignant tumors that occur in the breast tissue. There are many causes of breast cancer, and the incidence continues to rise, which is an important killer that threatens women's health. In recent years, a large number of researchers have been interested in the study of AI diagnosis of breast cancer. Artificial intelligence uses a specific algorithm to intelligently process ultrasound images, and develops a high-precision and high-efficiency breast cancer recognition model through training and optimization of the algorithm. At present, the application of computer-aided detection methods in breast cancer ultrasound has been gradually promoted, and the combined application of artificial intelligence has played an advantageous role in the field of breast disease ultrasound diagnosis, such as shortening the examination time, effectively improving the detection rate and diagnostic accuracy rate. The main reasons are: the accuracy of traditional AI diagnosis model of breast cancer based on machine learning is not high; The aim of this paper is to improve the accuracy of early diagnosis of breast diseases effectively and reduce the misdiagnosis rate caused by overwork of doctors on the basis of clear medical images and computer-aided diagnosis technology.

Comparative Evaluation of Contrast-Enhanced Spectral Mammography and Digital Breast Tomosynthesis for Diagnosing and Treating Breast Cancer.

BACKGROUND The aim of this study was to evaluate the efficacy of contrast-enhanced spectral mammography (CESM) and digital breast tomosynthesis (DBT) in the diagnosis and chemotherapy of breast cancer. MATERIAL AND METHODS We retrospectively analyzed data on 125 lesions of 115 patients with breast diseases in Lanzhou First People's Hospital from January 2020 to June 2022. Patients were examined by digital breast tomographic fusion and contrast-enhanced spectral mammography after chemotherapy. We compared the diagnostic accuracy of the 2 imaging techniques, and the diagnostic efficacy was evaluated with ROC curves. RESULTS There were significant differences in the type and degree of CESM enhancement between benign and malignant lesions. Malignant lesions mostly showed moderate to severe enhancement, while benign lesions mostly showed mild to moderate enhancement. There was no significant difference in DBT manifestations between benign and malignant lesions. After neoadjuvant chemotherapy, 88 patients had pathological remission, and the remission rate was 70.40%. Thirty-seven patients did not respond (nonresponse rate: 29.60%). The accuracy of CESM lesion size assessment was 84.00% (105/125), with high consistency. The accuracy of DBT lesion size assessment was 68.00% (85/125), and the consistency was poor. BI-RADS 4B was the truncation point. CESM had significantly higher sensitivity, specificity, accuracy, positive predictive value, and negative predictive value than DBT. In premenopausal patients and patients aged less than 50 years, the diagnostic efficacy of DBT and CESM was significantly different. CONCLUSIONS The diagnostic efficacy of CESM was significantly better than DBT in premenopausal women and patients under age 50. Diagnosis and treatment of breast diseases may be enhanced by the use of CESM.

Association of breast arterial calcification and carotid atherosclerosis as a marker of cardiovascular risk

Aim. To study the relationship between breast arterial calcification (BAC) and the presence and severity of carotid atherosclerosis.Material and methods. We analyzed 4274 digital mammograms of women who underwent diagnostic mammography. In addition to the standard diagnosis of breast diseases, BAC was assessed in all mammograms. The study included 198 women aged 40-74 years, who made up 2 groups with and without BAC, each consisting of 99 people, formed on a case-control basis. The severity of BAC was assessed by a 12-point score. Duplex ultrasound of extracranial arteries determined plaque presence, the severity of CA stenosis (in percent) and intima-media thickness (IMT). All women underwent physical and laboratory examinations, electrocardiography, and were interviewed using a questionnaire assessing socio-demographic data, menopausal status, risk factors, and diseases.Results. The groups did not differ in lipid levels, blood glucose, body mass index, incidence of hypertension, diabetes, or smoking. Women with BAC had a higher incidence of menopause (94,9% vs 84,8%, p=0,033), coronary artery disease (13,1% vs 4,2%, p=0,039) and osteoporosis (18,2% vs 6,1%, p=0,016) in history. In women with BAC, at least one carotid plaque was observed significantly more often than in those without BAC — in 79,8% and 60,6% of cases, respectively (p=0,005). Women with BAC compared with women without BAC had a greater plaque number (1,0 [1,0; 3,0] vs, 1,0 [1,0; 2,0], p&lt;0,001) and a more severe carotid stenosis, assessed by maximum (25,0 [17,5; 35,0] vs 20,0 [0,0; 27,5], p=0,001), total (30,0 [20,0; 92,5] vs 25,0 [0,0; 50,0], p&lt;0,001) and mean arterial stenosis (25,0 [17,5; 30,0] vs 20,0 [0,0; 25,0], p=0,001). For the first time, a positive relationship was revealed between the severity of carotid atherosclerosis and BAC as follows: women with greater severity of maximum and total carotid stenosis had more severe BAC (p=0,018 and p=0,003, respectively). There was no association between BAC and IMT (p=0,115).Conclusion. BAC is associated with a higher incidence and severity of carotid atheromatosis. A positive relationship was found between the severity of BAC and carotid stenosis. The data obtained confirm the prospects of mammography as a screening technique for identifying individuals with an increased cardiovascular risk.

A multispectral transmission image cluster analysis method based on “Terrace compression Method” and window function

Multispectral transmission imaging has a great potential for the early screening of breast cancer due to the low cost, safety and ease in operation. Accurate detection of heterogeneity is important for the diagnosis of breast disease. The low contrast and unclear heterogeneity boundaries of transmission images can lead to difficulties in recognition and segmentation. Therefore, we propose a clustering segmentation method of multispectral transmission images based on “terrace compression method” and window transformation. The images are preprocessed by the frame accumulation to improve the signal-to-noise ratio. After that, the “terrace compression method” is used to compress the images nonlinearly, to reduce data redundancy and then to improve the edge information of heterogeneities. Afterwards, the window function is used to eliminate the redundant information of the background and to reduce the influence of background noise on clustering. Finally, the processed images at each wavelength are transformed into multidimensional data for cluster analysis. The multispectral transmission images of breast phantom are acquired for experimental validation. Then, compared the method with common clustering segmentation methods (including K-means, K-means++, Mean-shift, Gaussian Mixture). The results showed that this processing method can effectively segment and classify the three heterogeneities in the breast phantom. Among these methods, the method proposed in the paper has the best segmentation and classification results for the three types of heterogeneities in the breast phantom. The Dice coefficients of all the heterogeneities segmentation reached more than 0.84 and increased by a maximum of 1.08 times as compared to the common clustering methods. The applications of the terrace compression method and the grayscale window transformation improved the effect of image clustering segmentation.

Breast cancer prediction using K Nearest Neighbors, Support Vector Machine Techniques

Breast cancer is the trickiest and sneakiest diseases that modern science is aware of. It is one of the most important causes of death for women worldwide. We introduce the SVM (Support Vector Machine) and KNN (K Nearest Neighbors), which are the machine learning algorithms for breast disease diagnosis by training its attributes, and we present an original prediction of breast cancer. The suggested system employs 10-fold cross validation to produce accurate results. The UCI machine learning warehouse was used to obtain the Wisconsin breast melanoma diagnosis data set. The accurateness, sensitiveness, specificity, false detection rate, false exclusion rate, and Matthews' correlation coefficient are used to evaluate the presentation of the suggested system.