Characterization of breast masses: a comparative study between automated breast ultrasound (ABUS) and digital breast tomosynthesis (DBT)

Hashem, Lamiaa Mohamed Bassam; Ali, Reham Hussein Mohamed; Helal, M. A.; Gemeae, Emad ELdin E. L.; Moustafa, Azza A.

doi:10.1186/s43055-020-00161-x

Cited by 4 publications

(3 citation statements)

References 14 publications

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“…Lamiaa Mohamed Bassam Hashem., et al concluded in their study that 78.6% of the benign lesions had well-circumscribed regular margins on DBT [16]. The lesion having an indistinct margin indicates a lack of demarcation with the surrounding tissue which raises the suspicion of the malignant nature of the lesion with infiltration into the adjacent tissues.…”

Section: Marginsmentioning

confidence: 96%

Diagnostic Accuracy of Full-Field Digital Mammography and Digital Breast Tomosynthesis in the Evaluation of Breast Lesions

Basaboina,

Avansta

2023

Act Sci wom hea

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Aim/Objectives: This study aimed to evaluate the diagnostic accuracy of full-field digital mammography (FFDM) and digital breast tomosynthesis (DBT) in detecting and characterizing the lesions. Also, we compared both modalities in detecting breast lesions.Methods: A prospective study was conducted from January 2021 to June 2022 on 76 patients. All of them underwent FFDM, DBT, and ultrasonography (USG), and the features of breast lesions were characterized based on the BIRADS followed by histopathological confirmation.Results: This study found that DBT (97.3%) was more accurate than FFDM (88.4%) in detecting breast lesions and is superior to FFDM when used alone or as an adjunctive tool for FFDM. The sensitivity of DBT vs FFDM (100% vs 92%) and DBT +FFDM vs FFDM (100% vs 92%) was relatively higher. Also, the specificity of DBT vs FFDM was 91.4% vs 76.7% and FFDM+DBT vs FFDM was 89.8% vs 76.7%.The individual characteristics of breast lesions with the highest sensitivity were spiculations, lobulations, and architectural distortion being 100% for all on DBT and 90.9%, 88%, and 80.8% on FFDM respectively. They also showed high specificity of 96% for spiculations and architectural distortion, 90% for lobulations on DBT and 90% for spiculations, 50% for lobulations, and 84.3% for architectural distortion on FFDM. Calcifications showed high sensitivity of 95.2% on DBT. The features favoring malignancy on DBT and FFDM were spiculated margins, architectural distortion, microlobulations, microcalcifications, irregularly shaped lesions with irregular margins, and also, >2cm size of the lesion. With the addition of DBT to FFDM, 14 out of 76 lesions had shown up gradation on BIRADS. Conclusion:The performance of DBT was significantly higher for the detection and characterization of breast lesions. Evaluation of the features of breast lesions on DBT can help to identify the malignant and benign potential of the lesions. The addition of DBT as a screening tool can decrease false positives and recall rates as well.

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Section: Marginsmentioning

confidence: 96%

Diagnostic Accuracy of Full-Field Digital Mammography and Digital Breast Tomosynthesis in the Evaluation of Breast Lesions

Basaboina,

Avansta

2023

Act Sci wom hea

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“…Research by Hashem et al was conducted on 32 female patients with the aim of comparing the DBT and the ABUS [21]. Patients underwent both examinations and the images were analyzed by two experienced radiologists.…”

Section: Comparison Of Dbt and Abusmentioning

confidence: 99%

“…In breast cancer screening, both mentioned methods showed very good results. However, the ABUS method of screening can be regarded as more effective given that it functions better on women with dense breasts and it exposes patients to less radiation compared to the DBT [21].…”

Section: Comparison Of Dbt and Abusmentioning

confidence: 99%

Automated Breast Ultrasound

Žaja

Matijaš

2022

Radiol. vjesn. (Online)

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Due to the growing number of breast cancer patients, an early diagnosis is important in order to reduce the mortality rate of those affected. Methods such as mammography, DBT, MRI, HHUS or ABUS are used in the detection of breast cancer. The aim of this article is to review the literature showing the basic principle of ABUS and to point out its advantages and disadvantages in relation to conventional methods of breast imaging. ABUS is a relatively new ultrasound method that performs well on patients with dense breast tissue. It reduces operator dependence and provides valuable diagnostic information with multiplanar reconstructions. Using evidence from reliable researches, studies have demonstrated that ABUS has a higher diagnostic accuracy compared to mammography, which remains the primary modality for early diagnosis of breast cancer. Applying ABUS as an adjunct to mammography during the screening test has proven effective and further confirmed the importance of their application in clinical practice. The disadvantage of the combination of ABUS and mammography was that in a large number of studies the specificity was lower compared to mammography itself. Compared to DBT, ABUS has demonstrated to have a higher diagnostic performance, with the exception that it lacks the ability to effectively detect calcifications. Although MRI seem to outperform ABUS, ABUS devices offer a cost-effective and easy to use imaging system, making it the best alternative. The HHUS technique, on the other hand, was perceived by many studies as less painful, with a shorter operative time compared to ABUS. However, the sensitivity and specificity of this screening method continues to remain inferior to ABUS. The use of artificial intelligence is becoming widely used today. As a result, the CAD software has been developed to be applied in conjunction with ABUS in order to improve the detection rate of breast cancer as well as its accuracy. The use of CAD significantly reduced image reading time and improved the overall diagnostic accuracy of ABUS. According to all the presented data, the use of ABUS medical devices in clinical practice continues to grow in importance and with the further development of technology and medicine, its full integration into healthcare systems around the world is expected.

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Advancements in Breast Cancer Detection: A Comprehensive Review of Deep Learning Techniques for Mammogram Analysis

Saini,

Khurana,

Challa

2023

2023 1st International Conference on Circuits, Power and Intelligent Systems (CCPIS)

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Characterization of breast masses: a comparative study between automated breast ultrasound (ABUS) and digital breast tomosynthesis (DBT)

Cited by 4 publications

References 14 publications

Diagnostic Accuracy of Full-Field Digital Mammography and Digital Breast Tomosynthesis in the Evaluation of Breast Lesions

Diagnostic Accuracy of Full-Field Digital Mammography and Digital Breast Tomosynthesis in the Evaluation of Breast Lesions

Automated Breast Ultrasound

Advancements in Breast Cancer Detection: A Comprehensive Review of Deep Learning Techniques for Mammogram Analysis

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