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Abstract Background Mammography plays a great role in reducing breast cancer mortality as it is the standard method of breast imaging and screening. But the accuracy of mammography performance reduces in cancer detection in women with dense breast due to the summation of images and overlapping of breast tissue. ABUS and tomosynthesis both recently help to detect breast cancer in dense breasted women. This prospective study was done in the female imaging unit and approved by its research and ethical committee; all the patients did an informed consent during the period from October 2018 to March 2019. The study was conducted on 38 patients with 38 lesions subjected to digital mammography, tomosynthesis and automated breast ultrasound (ABUS), who all had dense breast in mammography. Results Automated breast ultrasound (ABUS) showed 100% in all sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV) as well as accuracy, while the digital mammography tomosynthesis showed 100% in specificity, 87.5% in sensitivity, 100% in PPV, 82.4% in NPV and 92.1% accuracy. Conclusion Automated breast ultrasound (ABUS) together with tomosynthesis makes a revolution in breast screening and detecting cancer in women with dense breasts.

Background: Mammography plays a great role in reducing breast cancer mortality as it is the standard method of breast imaging and screening. But the accuracy of mammography performance reduces in cancer detection in women with dense breast due to the summation of images and overlapping of breast tissue. ABUS and tomosynthesis both recently help to detect breast cancer in dense breasted women. This prospective study was done in the female imaging unit and approved by its research and ethical committee; all the patients did an informed consent during the period from October 2018 to March 2019. The study was conducted on 38 patients with 38 lesions subjected to digital mammography, tomosynthesis and automated breast ultrasound (ABUS), who all had dense breast in mammography. Results: Automated breast ultrasound (ABUS) showed 100% in all sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV) as well as accuracy, while the digital mammography tomosynthesis showed 100% in specificity, 87.5% in sensitivity, 100% in PPV, 82.4% in NPV and 92.1% accuracy. Conclusion: Automated breast ultrasound (ABUS) together with tomosynthesis makes a revolution in breast screening and detecting cancer in women with dense breasts. [ABSTRACT FROM AUTHOR]

The number one cause of cancer in women worldwide is breast cancer. Over the last three decades, the use of traditional screen-film mammography has increased, but in recent years, digital mammography and 3D tomosynthesis have become standard procedures for breast cancer screening. With the advancement of technology, the interpretation of images using automated algorithms has become a subject of interest. Initially, computer-aided detection (CAD) was introduced; however, it did not show any long-term benefit in clinical practice. With recent advances in artificial intelligence (AI) methods, these technologies are showing promising potential for more accurate and efficient automated breast cancer detection and treatment. While AI promises widespread integration in breast cancer detection and treatment, challenges such as data quality, regulatory, ethical implications, and algorithm validation are crucial. Addressing these is essential for fully realizing AI's potential in enhancing early diagnosis and improving patient outcomes in breast cancer management. In this review article, we aim to provide an overview of the latest developments and applications of AI in breast cancer screening and treatment. While the existing literature primarily consists of retrospective studies, ongoing and future prospective research is poised to offer deeper insights. Artificial intelligence is on the verge of widespread integration into breast cancer detection and treatment, holding the potential to enhance early diagnosis and improve patient outcomes., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2024, Rentiya et al.)

Mammography is an essential tool for early detection of breast cancer. Breast imaging based on three-dimensional digital breast tomosynthesis (DBT) is a new method for breast cancer screening and diagnosis that uses three-dimensional digital images to allow separation of overlapping breast structures, which may allow for improved visualization of potentially significant findings. This article will highlight the utility of DBT as a tool for the detection of breast pathology; it will demonstrate normal findings as well as breast pathology on DBT and two-dimensional conventional mammography. DBT is a very promising modality, which may decrease the false-positive rate of mammography and find additional abnormalities not seen on two-dimensional mammography. [ABSTRACT FROM AUTHOR]

Objective: We aimed to compare radiation dose received during contrast-enhanced spectral mammography (CESM) using high- and low-energy projections with radiation dose received during 2D full field digital mammography (FFDM) and 3D tomosynthesis on phantoms and patients with varying breast thickness and density., Materials and Methods: A single left craniocaudal projection was chosen to determine the doses for 6214 patients who underwent 2D FFDM, 3662 patients who underwent 3D tomosynthesis, and 173 patients who underwent CESM in this retrospective study. Dose measurements were also collected in phantoms with composition mimicking nondense and dense breast tissue., Results: Average glandular dose (AGD) ± SD was 3.0 ± 1.1 mGy for CESM exposures at a mean breast thickness of 63 mm. At this thickness, the dose was 2.1 mGy from 2D FFDM and 2.5 mGy from 3D tomosynthesis. The nondense phantom had a mean AGD of 1.0 mGy with 2D FFDM, 1.3 mGy with 3D tomosynthesis, and 1.6 mGy with CESM. The dense breast phantom had a mean AGD of 1.3 mGy with 2D FFDM, 1.4 mGy with 3D tomosynthesis, and 2.1 mGy with CESM. At a compressed thickness of 4.5 cm, radiation exposure from CESM was approximately 25% higher in dense breast phantoms than in nondense breast phantoms. The dose in the dense phantom at a compressed thickness of 6 cm was approximately 42% higher than the dose in the nondense phantom at a compressed thickness of 4.5 cm., Conclusion: CESM was found to increase AGD at a mean breast thickness of 63 mm by approximately 0.9 mGy and 0.5 mGy compared with 2D FFDM and 3D tomosynthesis, respectively. Of note, CESM provides a standard image (similar to 2D FFDM) that is obtained using the low-energy projection. Overall, the AGD from CESM falls below the dose limit of 3 mGy set by Mammography Quality Standards Act regulations.