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.

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.

scholarly journals Pros and cons for breast cancer screening with tomosynthesis – a review of the

2020 ◽  
Author(s):  
Julian Hans Kleinknecht ◽  
Anca Ileana Ciurea ◽  
Cristiana Augusta Ciortea
Keyword(s):  
Breast Cancer ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Breast Imaging ◽  
Digital Breast Tomosynthesis ◽  
Detection Rates ◽  
Breast Tomosynthesis ◽  
Screening Programs ◽  
Long Term Follow Up ◽  
Imaging Research

Breast cancer screening programs using mammography proved their value in detecting breast cancer at early stages and, consequently, reducing the mortality from this disease. Due to the technological progress, the screening programs have shifted from screen-film mammography to digital mammography and nowadays digital breast tomosynthesis became the focus of breast imaging research. Using tomosynthesis in screening increases cancer detection rates and decreases recall and false-positive rates, thus improving the effectiveness of breast cancer screening programs, with positive consequences on health care costs and on patient psychology. More long-term follow-up data must be collected for assessing absolute sensitivity and specificity of digital breast tomosynthesis, together with efforts for addressing the limitations of the method.

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