Validation of artificial intelligence contrast mammography in diagnosis of breast cancer: Relationship to histopathological results.

Introduction: Contrast-enhanced mammography (CEM) is used for characterization of breast lesions with increased diagnostic accuracy compared to digital mammography (DM). Artificial intelligence (AI) approaches are emerging with accuracies equal to an average radiologist. However, most studies trained deep learning (DL) models on DM images and there is a paucity in literature for discovering the application of AI using CEM.

Biological and molecular studies on specific immune cells treated with checkpoint inhibitors for the thera-personal approach of breast cancer patients ( study).

Unlabelled: Immunotherapy becomes a promising line of treatment for breast cancer (BC) however, its success rate is still limited.

Methods: The study was designed to optimize the condition for producing an effective dendritic cell (DCs) based immunotherapy by using DCs and T lymphocytes together with tumor-infiltrating lymphocytes (TILs) and tumor-infiltrating DCs (TIDCs), treated with anti-PD1 and anti-CTLA4 monoclonal antibodies. This mixture of immune cells was co-cultured with autologous breast cancer cells (BCCs) isolated from 26 BC females.

Imaging Modalities in Inflammatory Breast Cancer (IBC) Diagnosis: A Computer-Aided Diagnosis System Using Bilateral Mammography Images.

Inflammatory breast cancer (IBC) is an aggressive type of breast cancer. It leads to a significantly shorter survival than other types of breast cancer in the U.S.

Categorized contrast enhanced mammography dataset for diagnostic and artificial intelligence research.

Contrast-enhanced spectral mammography (CESM) is a relatively recent imaging modality with increased diagnostic accuracy compared to digital mammography (DM). New deep learning (DL) models were developed that have accuracies equal to that of an average radiologist. However, most studies trained the DL models on DM images as no datasets exist for CESM images.

The role of automated breast ultrasound in the assessment of the local extent of breast cancer.

Automated breast ultrasound (ABUS) is a non-invasive advanced ultrasound modality. The degree of extension of the cancer within the breast is very important to choose the appropriate kind of surgery/therapy. In the current work, the aim was to evaluate the role of the ABUS in the assessment of the local extent of the breast cancer before management.

The impact of contrast-enhanced spectral mammogram (CESM) and three-dimensional breast ultrasound (3DUS) on the characterization of the disease extend in cancer patients.

Objective: The main importance of imaging breast cancer is to guide conservative surgeries. In this study, we evaluated the role of contrast-enhanced spectral mammogram (CESM) in correlation with three-dimensional (3D) breast ultrasound in characterizing the extension of the intramammary cancer in view of the: (i) the size of the main tumor, (ii) the multiplicity of the breast cancer, and (iii) the peri-tumoral stromal involvement (i.e.

Staging of breast cancer and the advanced applications of digital mammogram: what the physician needs to know?

Objective: To study the role of advanced applications of digital mammogram, whether contrast-enhanced spectral mammography (CESM) or digital breast tomosynthesis (DBT), in the "T" staging of histologically proven breast cancer before planning for treatment management.

Methods: In this prospective analysis, we evaluated 98 proved malignant breast masses regarding their size, multiplicity and the presence of associated clusters of microcalcifications. Evaluation methods included digital mammography (DM), 3D tomosynthesis and CESM.

Can we apply the MRI BI-RADS lexicon morphology descriptors on contrast-enhanced spectral mammography?

Objective:: To assess the feasibility of using the MRI breast imaging reporting and data system (BI-RADS) lexicon morphology descriptors to characterize enhancing breast lesions identified on contrast-enhanced spectral mammography (CESM).

Methods:: The study is a retrospective analysis of the morphology descriptors of 261 enhancing breast lesions identified on CESM in 239 patients. We presented the morphological categorization of the included lesions into focus, mass and non-mass.

Evaluation of BreastLight as a tool for early detection of breast lesions among females attending National Cancer Institute, Cairo University.

Background: Breast illumination was suggested as a simple method for breast cancer screening. BreastLight is a simple apparatus for this purpose.

Objective: To evaluate the diagnostic performance of BreastLight as a screening tool of breast cancer in comparison to mammography and histopathology.

Role of Sonoelastography in the Differentiation between Benign and Malignant Breast Lesions.

Purpose: To prospectively evaluate the accuracy of real time elastography (ultrasound strain imaging) for distinguishing between benign and malignant solid breast lesions with the pathologic results as the reference standard. We also evaluated if the fat÷lesion ratio could semiquantitatively evaluate the stiffness of breast lesions.

Patients And Methods: Conventional ultrasonography (US) and real time elastography were performed in 100 women with breast masses with the mean age is 50 years.

Women Health Outreach Program; a New Experience for all Egyptian Women.

Unlabelled: The global health community faces a challenge with breast cancer being the most common cause of cancer related death among women around the globe. Since breast cancer's pathogenesis is poorly understood, primary prevention is still a distant goal. Thus secondary prevention through early detection is the only feasible approach at present.