scholarly journals The value of computer aided detection system for mammography in the fatty breast: the results of the single-centered, prospective, randomized clinical trial

2021 ◽  
Vol 25 (4) ◽  
pp. 93-105
Author(s):  
D. V. Pasynkov ◽  
M. G. Tukhbatullin ◽  
R. Sh. Khasanov
Keyword(s):  
Detection System ◽  
Low Density ◽  
Breast Cancers ◽  
Computer Aided Detection ◽  
Initial Screening ◽  
Prospective Randomized Clinical Trial ◽  
Primary Screening ◽  
Targeted Ultrasound ◽  
Computer Aided

Aim. To assess the reasonability to use CAD added to mammography with subsequent targeted ultrasound (US) of CAD markings in patients with low-density (ACR A-В) breasts.Materials and methods. In the prospective study we included 2326 women with low breast density. They were randomized for CAD (MammCheck II of our own design) checking with subsequent targeted US (MMG + CAD group) or without CAD (MMG only group). After the initial screening we performed the 3-year follow-up phase.Results. Totally, during the primary screening in the MMG only group we found 77 breast cancers (BCs) (28,57% of them sized less than 1 cm), in the MMG + CAD group – 69 BCs (36,23% of them sized less than 1 cm), р > 0.05. The suspicious lesion was identified only during the targeted US of the CAD marking in 4 of 25 women in the MMG + CAD group, and all these BCs were below 1 cm in size. During the subsequent follow-up in the MMG only group we found 5 additional BCs, with no such cases in the MMG + CAD group (p < 0.05). Three of these five BCs were retrospectively marked by CAD. The only visible BC that was not marked by CAD was 3 mm in size.Discussion. The overall false positive marking rate was 0.31 и 0.28 per film-screen and digital image, respectively (р > 0.05).Conclusion. The CAD usage added to mammography with subsequent targeted US of markings in patients with low-density (ACR A-В) breast is reasonable due to the significant decrease of the BC rate diagnosed during the 3-year follow-up. This combination detected 77 of the 77 (100.00%) BCs compared to 69 of 74 (93.24%) BCs when only mammography used.

Does computer‐aided detection assist in the early detection of breast cancer?

2005 ◽  
Vol 46 (2) ◽  
pp. 135-139 ◽  
Author(s):  
K. Hukkinen ◽  
M. Pamilo
Keyword(s):  
Small Mass ◽  
Breast Cancers ◽  
Computer Aided Detection ◽  
Initial Screening ◽  
Cad System ◽  
Computer Aided ◽  
Group A ◽  
Size And Morphology ◽  
Group B ◽  
Mass Lesions

Purpose: To evaluate whether breast cancers detected at screening are visible in previous mammograms, and to assess the performance of a computer‐aided detection (CAD) system in detecting lesions in preoperative and previous mammograms. Material and Methods: Initial screening detected 67 women with 69 surgically verified breast cancers (Group A). An experienced screening radiologist retrospectively analyzed previous mammograms for visible lesions (Group B), noting in particular their size and morphology. Preoperative and previous mammograms were analyzed with CAD; a relatively inexperienced resident also analyzed previous mammograms. The performances of CAD and resident were then compared. Results: Of the 69 lesions identified, 36 were visible in previous mammograms. Of these 36 “missed” lesions, 14 were under 10 mm in diameter and 29 were mass lesions. The sensitivity of CAD was 81% in Group A and 64% in Group B. Small mass lesions were harder for CAD to detect. The specificity of CAD was 3% in Group A and 9% in Group B. Together, CAD and the resident found more “missed” lesions than separately. Conclusion: Of the 69 breast cancers, 36 were visible in previous mammograms. CAD's sensitivity in detecting cancer lesions ranged from 64% to 81%, while specificity ranged from 9% to as low as 3%. CAD may be helpful if the radiologist is less subspecialized in mammography.

Accuracy of Segmentation of a Commercial Computer-aided Detection System for Mammography

Radiology ◽  
2005 ◽  
Vol 235 (2) ◽  
pp. 385-390 ◽  
Author(s):  
Jay A. Baker ◽  
Eric L. Rosen ◽  
Michele M. Crockett ◽  
Joseph Y. Lo
Keyword(s):  
Detection System ◽  
Computer Aided Detection ◽  
Computer Aided

scholarly journals Computer-Aided System Application Value for Assessing Hip Development

2020 ◽  
Vol 11 ◽  
Author(s):  
Yaoxian Jiang ◽  
Guangyao Yang ◽  
Yuan Liang ◽  
Qin Shi ◽  
Boqi Cui ◽  
...  
Keyword(s):  
Hip Joint ◽  
Detection System ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Diagnostic Efficiency ◽  
X Rays ◽  
Computer Aided Detection ◽  
Sharp Angle ◽  
Center Edge ◽  
Computer Aided

PurposeA computer-aided system was used to semiautomatically measure Tönnis angle, Sharp angle, and center-edge (CE) angle using contours of the hip bones to establish an auxiliary measurement model for developmental screening or diagnosis of hip joint disorders.MethodsWe retrospectively analyzed bilateral hip x-rays for 124 patients (41 men and 83 women aged 20–70 years) who presented at the Affiliated Zhongshan Hospital of Dalian University in 2017 and 2018. All images were imported into a computer-aided detection system. After manually outlining hip bone contours, Tönnis angle, Sharp angle, and CE angle marker lines were automatically extracted, and the angles were measured and recorded. An imaging physician also manually measured all angles and recorded hip development, and Pearson correlation coefficients were used to compare computer-aided system measurements with imaging physician measurements. Accuracy for different angles was calculated, and the area under the receiver operating characteristic (AUROC) curve was used to represent the diagnostic efficiency of the computer-aided system.ResultsFor Tönnis angle, Sharp angle, and CE angle, correlation coefficients were 0.902, 0.887, and 0.902, respectively; the accuracies of the computer-aided detection system were 89.1, 93.1, and 82.3%; and the AUROC curve values were 0.940, 0.956, and 0.948.ConclusionThe measurements of Tönnis angle, Sharp angle, and CE angle using the semiautomatic system were highly correlated with the measurements of the imaging physician and can be used to assess hip joint development with high accuracy and diagnostic efficiency.

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