Overview of Digital Breast Tomosynthesis

2018 ◽  
Author(s):  
Emily F. Conant
Keyword(s):  
Cancer Detection ◽  
Three Dimensional ◽  
Digital Breast Tomosynthesis ◽  
Early Screening ◽  
Breast Tomosynthesis ◽  
X Ray ◽  
Effectiveness Studies ◽  
Work Up ◽  
Diagnostic Setting ◽  
Efficient Work

Digital breast tomosynthesis (DBT) is a relatively new X-ray technique that allows quasi–three-dimensional imaging of the breast to overcome limitations of conventional 2-D digital mammography (DM). Several early screening studies have shown that DBT reduces the number of false-positive recalls while simultaneously improving the cancer detection rate. Cost-effectiveness studies have shown that incorporating DBT in screening has the potential to save health care dollars due to lower recall rates as well as reduced treatment costs resulting from the earlier detection of breast cancer. In the diagnostic setting, DBT imaging may allow a more efficient work-up of breast lesions due to improved lesion conspicuity and the ability to better localize lesions within the breast.

Fusion Techniques for the Breast Cancer Detection

2020 ◽  
Vol 17 (9) ◽  
pp. 4036-4040
Author(s):  
M. Veena ◽  
M. C. Padma
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
Computer Technology ◽  
Medical Science ◽  
Three Dimensional ◽  
Digital Breast Tomosynthesis ◽  
Breast Tomosynthesis ◽  
Breast Image ◽  
Cancerous Cells

Breast cancer is a considerable prime cause which affects the lives of women’s and leads to death all around the world. A tumor is said to be malignancy if a number of cancerous cells can spread to other organs. There has been great impact on the field of medical imaging by the advancement of the computer technology as new and improved techniques of data acquisition, analysis, processing and visualization has evolved. A Digital Breast Tomosynthesis is used for the detection of breast cancer. This is also called as three-dimensional mammography, which eliminates the overlapping tissue problem. Digital Breast Tomosynthesis (DBT) provides information about potential abnormal tissues necessary for medical follow up and diagnosis. DBT gets additional importance in medical science as it is the only preliminary method of diagnosing a breast cancer with the dense breast. Early and accurate diagnosis can be sufficient in resolving various complications and guiding the patient with timely and proper treatment. By considering the above factors there is a great requirement to explore for DBT. The proposed work develops a computer aided methodology for automatic tumor detection and diagnosing in tomosynthesis Patient’s image. This method is incredibly helpful for doctors or the radiologist automatically locates the tumor space within the breast image for further surgery.

scholarly journals Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case study

2021 ◽  
Author(s):  
Suzanne L. van Winkel ◽  
Alejandro Rodríguez-Ruiz ◽  
Linda Appelman ◽  
Albert Gubern-Mérida ◽  
Nico Karssemeijer ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Artificial Intelligence ◽  
Cancer Detection ◽  
Support System ◽  
Reading Time ◽  
Digital Breast Tomosynthesis ◽  
Breast Tomosynthesis ◽  
Screening Programs ◽  
The Impact

Abstract Objectives Digital breast tomosynthesis (DBT) increases sensitivity of mammography and is increasingly implemented in breast cancer screening. However, the large volume of images increases the risk of reading errors and reading time. This study aims to investigate whether the accuracy of breast radiologists reading wide-angle DBT increases with the aid of an artificial intelligence (AI) support system. Also, the impact on reading time was assessed and the stand-alone performance of the AI system in the detection of malignancies was compared to the average radiologist. Methods A multi-reader multi-case study was performed with 240 bilateral DBT exams (71 breasts with cancer lesions, 70 breasts with benign findings, 339 normal breasts). Exams were interpreted by 18 radiologists, with and without AI support, providing cancer suspicion scores per breast. Using AI support, radiologists were shown examination-based and region-based cancer likelihood scores. Area under the receiver operating characteristic curve (AUC) and reading time per exam were compared between reading conditions using mixed-models analysis of variance. Results On average, the AUC was higher using AI support (0.863 vs 0.833; p = 0.0025). Using AI support, reading time per DBT exam was reduced (p < 0.001) from 41 (95% CI = 39–42 s) to 36 s (95% CI = 35– 37 s). The AUC of the stand-alone AI system was non-inferior to the AUC of the average radiologist (+0.007, p = 0.8115). Conclusions Radiologists improved their cancer detection and reduced reading time when evaluating DBT examinations using an AI reading support system. Key Points • Radiologists improved their cancer detection accuracy in digital breast tomosynthesis (DBT) when using an AI system for support, while simultaneously reducing reading time. • The stand-alone breast cancer detection performance of an AI system is non-inferior to the average performance of radiologists for reading digital breast tomosynthesis exams. • The use of an AI support system could make advanced and more reliable imaging techniques more accessible and could allow for more cost-effective breast screening programs with DBT.

scholarly journals Tecnica di Imaging tridimensionale (Digital Breast Tomosynthesis) per la diagnosi del tumore alla mammella

2019 ◽  
Author(s):  
Di Guida Lisa ◽  
De Rosa Salvatore
Keyword(s):  
Breast Cancer ◽  
Early Diagnosis ◽  
Imaging Techniques ◽  
Three Dimensional ◽  
Digital Breast Tomosynthesis ◽  
Recurrence Time ◽  
Digital Tomosynthesis ◽  
Breast Tomosynthesis ◽  
X Ray Imaging ◽  
Projective Image

Breast cancer affects one in eight women over a lifetime. It is the most common cancer in women and represents 29% of all cancers affecting women, with a mortality rate of 17% of all deaths due to cancer on women. Sooner the cancer is identified with an early diagnosis, higher are the possibilities to treat it completely and longer is the recurrence time. Mammography is the most common method for early diagnosis. is a two-dimensional X-ray imaging technique and this involves the overlapping of the tissues in the projective image inability to visualize cancer in the first stage. In recent years, three-dimensional imaging techniques have been introduced, including digital tomosynthesis for the diagnosis of breast cancer, this technique has the advantages to perform dozens of projections, and not just one, from various angular views around the compressed breast. The major benefits of tomosynthesis are a lower stratification of breast tissues, better visibility of tumor masses especially for small tumors, breast tomosynthesis provides the ability to visualize 3D images to obtain a more accurated evaluation of lesions allowing better differentiation between overlapping fabrics.

Computer-Aided Detection and Diagnosis for 3D X-Ray Based Breast Imaging

2012 ◽  
pp. 66-85
Author(s):  
Gautam S. Muralidhar ◽  
Alan C. Bovik ◽  
Mia K. Markey
Keyword(s):  
Breast Imaging ◽  
Digital Breast Tomosynthesis ◽  
Future Research ◽  
Computer Aided Detection ◽  
Breast Tomosynthesis ◽  
X Ray ◽  
Computer Aided ◽  
Recent Developments ◽  
Initial Work ◽  
Detection And Diagnosis

The last 15 years has seen the advent of a variety of powerful 3D x-ray based breast imaging modalities such as digital breast tomosynthesis, digital breast computed tomography, and stereo mammography. These modalities promise to herald a new and exciting future for early detection and diagnosis of breast cancer. In this chapter, the authors review some of the recent developments in 3D x-ray based breast imaging. They also review some of the initial work in the area of computer-aided detection and diagnosis for 3D x-ray based breast imaging. The chapter concludes by discussing future research directions in 3D computer-aided detection.

Digital Breast Tomosynthesis: Clinical Operations

2019 ◽  
Vol 1 (2) ◽  
pp. 122-126
Author(s):  
Sarah M Friedewald ◽  
Sonya Bhole ◽  
Lilian Wang ◽  
Dipti Gupta
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
Digital Mammography ◽  
Digital Breast Tomosynthesis ◽  
Standard Of Care ◽  
Breast Tomosynthesis ◽  
Mandated Training ◽  
Process Understanding ◽  
Quality Imaging

Abstract Digital breast tomosynthesis (DBT) is rapidly becoming the standard of care for breast cancer screening. Implementing DBT into practice is relatively straightforward. However, there are important elements of the transition that one must consider to facilitate this process. Understanding the Digital Imaging and Communications in Medicine (DICOM) standard for DBT, as well as how images are displayed, is critical to a successful transition. Standardization of these processes will allow easier transmission of images from facility to facility, and limit the potential for errors in interpretation. Additionally, recent changes in federal regulations will require compliance with mandated training for the radiologist, technologist, and physicist, as well as accreditation for each DBT unit. These regulations aim to ensure high-quality imaging across the country as has been previously seen with standard digital mammography. Synthesized imaging is the most recent improvement for DBT, potentially obviating the need for a simultaneous traditional digital mammogram exposure. Studies have demonstrated near equivalent performance when comparing the combination imaging of DBT and digital mammography versus DBT combined with synthetic imaging. As the quality of the synthetic images continues to improve, it is increasingly likely that it will replace the traditional mammogram. Adherence to DBT-specific parameters will enhance the physician experience and ultimately translate to increased cancer detection and fewer false positive examinations, benefiting all women who are screened for breast cancer.

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