scholarly journals Discrimination of Malignant and Benign Breast Masses Using Computer-Aided Diagnosis from Dynamic Contrast-Enhanced Magnetic Resonance

2021 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
Turkan Ikizceli ◽  
Seyhan Karacavus ◽  
Hasan Erbay ◽  
Ahmet Yurttakal
Keyword(s):  
Magnetic Resonance ◽  
Computer Aided Diagnosis ◽  
Breast Masses ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced ◽  
Computer Aided ◽  
Aided Diagnosis

scholarly journals Classification of Breast Masses Using a Computer-Aided Diagnosis Scheme of Contrast Enhanced Digital Mammograms

2018 ◽  
Vol 46 (9) ◽  
pp. 1419-1431 ◽  
Author(s):  
Gopichandh Danala ◽  
Bhavika Patel ◽  
Faranak Aghaei ◽  
Morteza Heidari ◽  
Jing Li ◽  
...  
Keyword(s):  
Computer Aided Diagnosis ◽  
Breast Masses ◽  
Contrast Enhanced ◽  
Computer Aided ◽  
Aided Diagnosis

Reproducibility of Dynamic Contrast-enhanced MR Imaging. Part I. Perfusion Characteristics in the Female Pelvis by Using Multiple Computer-aided Diagnosis Perfusion Analysis Solutions

Radiology ◽  
2013 ◽  
Vol 266 (3) ◽  
pp. 801-811 ◽  
Author(s):  
Tobias Heye ◽  
Matthew S. Davenport ◽  
Jeffrey J. Horvath ◽  
Sebastian Feuerlein ◽  
Steven R. Breault ◽  
...  
Keyword(s):  
Mr Imaging ◽  
Computer Aided Diagnosis ◽  
Female Pelvis ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced ◽  
Computer Aided ◽  
Aided Diagnosis

Clinical Application of Computer-Aided Diagnosis According to S-Detect in Category 4 Breast Lesions: Prospective Single-Center Study (Preprint)

2020 ◽  
Author(s):  
Pengfei Sun ◽  
Chen Chen ◽  
Weiqi Wang ◽  
Lei Liang ◽  
Dan Luo ◽  
...  
Keyword(s):  
Clinical Management ◽  
Diagnostic Performance ◽  
Breast Biopsy ◽  
Computer Aided Diagnosis ◽  
Breast Lesions ◽  
Breast Masses ◽  
Computer Aided ◽  
Conventional Ultrasound ◽  
Us Findings ◽  
Aided Diagnosis

BACKGROUND Computer-aided diagnosis (CAD) is a useful tool that can provide a reference for the differential diagnosis of benign and malignant breast lesion. Previous studies have demonstrated that CAD can improve the diagnostic performance. However, conventional ultrasound (US) combined with CAD were used to adjust the classification of category 4 lesions has been few assessed. OBJECTIVE The objective of our study was to evaluate the diagnosis performance of conventional ultrasound combined with a CAD system S-Detect in the category of BI-RADS 4 breast lesions. METHODS Between December 2018 and May 2020, we enrolled patients in this study who received conventional ultrasound and S-Detect before US-guided biopsy or surgical excision. The diagnostic performance was compared between US findings only and the combined use of US findings with S-Detect, which were correlated with pathology results. RESULTS A total of 98 patients (mean age 51.06 ±16.25 years, range 22-81) with 110 breast masses (mean size1.97±1.38cm, range0.6-8.5) were included in this study. Of the 110 breast masses, 64/110 (58.18%) were benign, 46/110 (41.82%) were malignant. Compared with conventional ultrasound, a significant increase in specificity (0% to 53.12%, P<.001), accuracy (41.81% to70.19%, P<.001) were noted, with no statistically significant decrease on sensitivity(100% to 95.65% ,P=.48). According to S-Detect-guided US BI-RADS re-classification, 30 out of 110 (27.27%) breast lesions underwent a correct change in clinical management, 74of 110 (67.27%) breast lesions underwent no change and 6 of 110 (5.45%) breast lesions underwent an incorrect change in clinical management. The biopsy rate decreased from 100% to 67.27 % (P<.001).Benign masses among subcategory 4a had higher rates of possibly benign assessment on S-Detect for the US only (60% to 0%, P<.001). CONCLUSIONS S-Detect can be used as an additional diagnostic tool to improve the specificity and accuracy in clinical practice. S-Detect have the potential to be used in downgrading benign masses misclassified as BI-RADS category 4 on US by radiologist, and may reduce unnecessary breast biopsy. CLINICALTRIAL none

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