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Advanced Ultrasound in Diagnosis and Therapy ›› 2022, Vol. 6 ›› Issue (4): 180-187.doi: 10.37015/AUDT.2022.220007

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  • 收稿日期:2022-02-23 修回日期:2022-03-16 接受日期:2022-04-09 出版日期:2022-12-30 发布日期:2022-10-25

Using S-Detect to Improve Breast Ultrasound: The Different Combined Strategies Based on Radiologist Experience

Ying Zhu, MDa,1, Xiaohong Jia, MDa,1, Yijie Dong, MDa, Juan Liu, MDa, Yilai Chen, MDa, Congcong Yuan, MDa, Weiwei Zhan, MDa, Jianqiao Zhou, MDa,*()   

  1. a Department of Ultrasound, Shanghai Ruijin Hospital affiliated to Medical School of Shanghai Jiaotong University, Shanghai, China
  • Received:2022-02-23 Revised:2022-03-16 Accepted:2022-04-09 Online:2022-12-30 Published:2022-10-25
  • Contact: Jianqiao Zhou, MD E-mail:zhousu30@126.com
  • About author:First author contact:1 Ying Zhu and Xiaohong Jia contributed equally to this study.

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Abstract:

Objective: To investigate the best combined method of S-Detect, a computer-aided diagnosis (CAD) system, with breast ultrasound (US) according to radiologists’ experience.

Methods: From March 2019 to June 2019, 259 breast masses in 255 women were included in this study. Ultrasonographic images of the target masses were prospectively analyzed by radiologists and CAD. Three combined methods, including method 1 [selective downgrading combination for Breast Imaging Reporting and Data System (BI-RADS) 4a lesions], method 2 (selective upgrading combination for BI-RADS 3 lesions) and method 3 (selective upgrading or downgrading combination for BI-RADS 3 or 4a lesions), were applied to interpret the CAD results. The sensitivity, specificity, the area under the receiver operating characteristic curve (AUC) of experienced or inexperienced radiologists before and after adding CAD results were compared using the histopathological results as a reference standard.

Results: In identifying breast malignancy, the AUC for CAD was similar to that of experienced radiologists (P= 0.410), but higher than that of inexperienced radiologists (P= 0.003). When combining CAD with experienced radiologists based on method 1 and combining CAD results with inexperienced radiologists based on method 3, the AUCs were significantly improved (P= 0.024 and 0.003, respectively) compared to US alone, with significantly increased specificity (P< 0.001 for both) and no significantly decreased sensitivity (P> 0.05 for both).

Conclusion: The combination of CAD system and conventional ultrasound can improve ultrasound diagnostic performance in determining breast malignancy. The method 1 and method 3 combinations are respectively recommended for experienced and inexperienced radiologists when CAD is combined with conventional breast ultrasound.

Key words: Ultrasound, Breast, Computer-assisted diagnosis, Neoplasms, BI-RAD classification

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Initial BI-RADS category BI-RADS 3 BI-RADS 4a
CAD (-) CAD (+) CAD (-) CAD (+)
Reevaluation on Method 1 BI-RADS 3 BI-RADS 3 BI-RADS 3 BI-RADS 4a
Reevaluation on Method 2 BI-RADS 3 BI-RADS 4a BI-RADS 4a BI-RADS 4a
Reevaluation on Method 3 BI-RADS 3 BI-RADS 4a BI-RADS 3 BI-RADS 4a

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Pathological results No. (%)
Benign
Fibroadenoma 96 (37.1%)
Papilloma 32 (12.4%)
ANDI 31 (1,2%)
Granulomatous lobular mastitis 4 (1.5%)
Nodular fasciitis 1 (0.4%)
Lobular CIS 1 (0.4%)
Benign phyllodes tumors 1 (0.4%)
Fat necrosis 1 (0.4%)
Hamartoma 1 (0.4%)
Malignant
Invasive ductal carcinoma 64 (24.7%)
Ductal carcinoma in situ 13 (5.0%)
Invasive lobular carcinoma 6 (2.3%)
Mucinous carcinoma 2 (0.8%)
Intracystic papillary carcinoma 2 (0.8%)
Solid papillary carcinoma 2 (0.8%)
Primary angiosarcoma 1 (0.4%)
AAC 1 (0.4%)

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Items Sensitivity Specificity PPV NPV Accuracy AUC (95 % CI)
CAD 82.4 % 74.4 % 64.6 % 88.7 % 77.2 % 0.784(0.729-0.833)
Experienced radiologist
US alone 97.8 %# 63.7 %# 59.3 % 98.1 % 75.7 % 0.813(0.760-0.859)
CAD + US: Method 1 93.4 % 80.9 %* 72.7 %* 95.8 % 85.3 %* 0.872(0.825-0.910)*
CAD + US: Method 2 97.8 % 53.6 %* 53.3 % 97.8 % 69.1 % 0.759(0.693-0.818) *
CAD + US: Method 3 93.4 % 70.8 % 63.4 % 95.2 % 78.8 % 0.832(0.772-0.881)
Inexperienced reader
US alone 90.1 % 42.9 %# 46.1 %# 88.9 % 59.5 %# 0.665(0.604-0.722) #
CAD + US: Method 1 86.8 % 71.4 %† 62.2 %† 90.9 % 76.8 %† 0.791(0.737-0.839) †
CAD + US: Method 2 95.6 % 37.5 %† 45.3 % 94.0 % 57.9 % 0.666(0.604-0.723)
CAD + US: Method 3 92.3 % 66.1 %† 59.6 % 94.1 %† 75.3 %† 0.792(0.737-0.840) †

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BI-RADS category Before adding CAD results After adding CAD results
CAD Benign Malignant M% CAD Benign Malignant M%
3 (-) 91 1 1.8 (-) 120 5 4.2
(+) 16 1 (+) 16 1
4a (-) 29 4# 17.5 (-) 0 0 25.0
(+) 18 6 (+) 18 6

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BI-RADS category Before adding CAD results After adding CAD results
CAD Benign Malignant M% CAD Benign Malignant M%
3 (-) 63 4 11.1 (-) 111 7 6.3
(+) 9 5* (+) 0 0
4a (-) 48 3# 15.4 (-) 27 14 34.1
(+) 18 9 (+) 0 0
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