Application of Computer‐Aided Diagnosis on Breast Ultrasonography: Evaluation of Diagnostic Performances and Agreement of Radiologists According to Different Levels of Experience. (1st August 2017)
- Record Type:
- Journal Article
- Title:
- Application of Computer‐Aided Diagnosis on Breast Ultrasonography: Evaluation of Diagnostic Performances and Agreement of Radiologists According to Different Levels of Experience. (1st August 2017)
- Main Title:
- Application of Computer‐Aided Diagnosis on Breast Ultrasonography: Evaluation of Diagnostic Performances and Agreement of Radiologists According to Different Levels of Experience
- Authors:
- Cho, Eun
Kim, Eun‐Kyung
Song, Mi Kyung
Yoon, Jung Hyun - Abstract:
- Abstract : Objectives: To investigate the feasibility of a computer‐aided diagnosis (CAD) system (S‐Detect; Samsung Medison, Co, Ltd, Seoul, Korea) for breast ultrasonography (US), according to radiologists with various degrees of experience in breast imaging. Methods: From December 2015 to March 2016, 119 breast masses in 116 women were included. Ultrasonographic images of the breast masses were retrospectively reviewed and analyzed by 2 radiologists specializing in breast imaging (7 and 1 years of experience, respectively) and S‐Detect, according to the individual ultrasonographic descriptors from the fifth edition of the American College of Radiology Breast Imaging Reporting and Data System and final assessment categories. Diagnostic performance and the interobserver agreement among the radiologists and S‐Detect was calculated and compared. Results: Among the 119 breast masses, 54 (45.4%) were malignant, and 65 (54.6%) were benign. Compared to the radiologists, S‐Detect had higher specificity (90.8% compared to 49.2% and 55.4%) and positive predictive value (PPV; 86.7% compared to 60.7% and 63.8%) (all P < .001). Both radiologists had significantly improved specificity, PPV, and accuracy when using S‐Detect compared to US alone (all P < .001). The area under the receiving operating characteristic curves of the both radiologists did not show a significant improvement when applying S‐Detect compared to US alone (all P > .05). Moderate agreement was seen in finalAbstract : Objectives: To investigate the feasibility of a computer‐aided diagnosis (CAD) system (S‐Detect; Samsung Medison, Co, Ltd, Seoul, Korea) for breast ultrasonography (US), according to radiologists with various degrees of experience in breast imaging. Methods: From December 2015 to March 2016, 119 breast masses in 116 women were included. Ultrasonographic images of the breast masses were retrospectively reviewed and analyzed by 2 radiologists specializing in breast imaging (7 and 1 years of experience, respectively) and S‐Detect, according to the individual ultrasonographic descriptors from the fifth edition of the American College of Radiology Breast Imaging Reporting and Data System and final assessment categories. Diagnostic performance and the interobserver agreement among the radiologists and S‐Detect was calculated and compared. Results: Among the 119 breast masses, 54 (45.4%) were malignant, and 65 (54.6%) were benign. Compared to the radiologists, S‐Detect had higher specificity (90.8% compared to 49.2% and 55.4%) and positive predictive value (PPV; 86.7% compared to 60.7% and 63.8%) (all P < .001). Both radiologists had significantly improved specificity, PPV, and accuracy when using S‐Detect compared to US alone (all P < .001). The area under the receiving operating characteristic curves of the both radiologists did not show a significant improvement when applying S‐Detect compared to US alone (all P > .05). Moderate agreement was seen in final assessments made by each radiologist and S‐Detect (κ = 0.40 and 0.45, respectively). Conclusions: S‐Detect is a clinically feasible diagnostic tool that can be used to improve the specificity, PPV, and accuracy of breast US, with a moderate degree of agreement in final assessments, regardless of the experience of the radiologist. … (more)
- Is Part Of:
- Journal of ultrasound in medicine. Volume 37:Number 1(2018)
- Journal:
- Journal of ultrasound in medicine
- Issue:
- Volume 37:Number 1(2018)
- Issue Display:
- Volume 37, Issue 1 (2018)
- Year:
- 2018
- Volume:
- 37
- Issue:
- 1
- Issue Sort Value:
- 2018-0037-0001-0000
- Page Start:
- 209
- Page End:
- 216
- Publication Date:
- 2017-08-01
- Subjects:
- breast -- Breast Imaging Reporting and Data System -- computer‐aided diagnosis -- neoplasm -- ultrasonography -- ultrasound equipment and products
Ultrasonics in medicine -- Periodicals
Ultrasonics
Ultrasonography
Ultrasonics in medicine
Electronic journals
Periodicals
Periodicals
616.07543 - Journal URLs:
- http://www.jultrasoundmed.org/ ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/jum.14332 ↗
- Languages:
- English
- ISSNs:
- 0278-4297
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5071.455000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 5599.xml