Comparison of 3D-Automated Breast Ultrasound With Handheld Breast Ultrasound Regarding Detection and BI-RADS Characterization of Lesions in Dense Breasts: A Study of 592 Cases

Güldoğan, Nilgün; Yılmaz, Ebru; Arslan, Aydan; Küçükkaya, Fikret; Atila, Naz; Arıbal, Erkin

doi:10.1016/j.acra.2021.11.022

Cited by 8 publications

(4 citation statements)

References 22 publications

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“…Figure 3B shows that the detection of benign lesions was lower than that of malignant lesions while Table 4 shows that the false negative malignant lesions were fewer than the benign lesions using both the coronal and transverse views, consistent with the findings of Güldogan et al (11) showing that ABUS detected fewer benign lesions than HHUS while having a similar performance to HHUS for cancer detection. This indicates that ABUS has the potential to decrease the incidence of false positives while maintaining the detection of malignant lesions.…”

Section: Discussionsupporting

confidence: 85%

“…The ABUS was developed to overcome the limitations of operator dependency, poor standardization, and reproducibility of handheld ultrasound (HHUS), with identical diagnostic accuracy to that of HHUS (8)(9)(10). Furthermore, ABUS showed similar efficacy for cancer detection with less benign findings compared with HHUS, suggesting that ABUS can potentially decrease the incidence of false positives (11). Use of an ABUS allows for the uncoupling of acquisition and interpretation, with the advantage of double-reading, objective comparison with previous examinations, and re-evaluation of stored images, even after the acquisition.…”

Section: Introductionmentioning

confidence: 99%

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Potential Usefulness a Coronal View using an Automated Breast Ultrasound System in Detecting Breast Lesions

Suzuki,

Nakayama,

Namba

et al. 2024

EJBH

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The coronal view obtained from an automated breast ultrasound system was useful for results interpretation. •This coronal view in the automated breast ultrasound system was associated with significantly shorter reading times compared with the conventional transverse view while maintaining breast lesion detection accuracy.• Interpretation accuracy may be increased by interpreting a mass with retraction in the coronal view and focusing on hypoechoic non-mass lesions and lesions located behind the nipples in the transverse view.

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Section: Discussionsupporting

confidence: 85%

Section: Introductionmentioning

confidence: 99%

Potential Usefulness a Coronal View using an Automated Breast Ultrasound System in Detecting Breast Lesions

Suzuki,

Nakayama,

Namba

et al. 2024

EJBH

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“…Studies in clinical practice have shown that in female patients with dense breast tissue, the use of ABUS leads to increased speci city in the diagnosis of breast cancer 11 . Its detection rate for breast lesions is comparable to that of handheld ultrasound 12 . The use of automated breast ultrasound can also facilitate preoperative planning and save physicians signi cant time relative to the use of handheld ultrasound in symptomatic outpatients and the feasibility evaluation of response control for neoadjuvant treatment of breast cancer 13,14 .…”

Section: Introductionmentioning

confidence: 80%

A Nomogram for Diagnosis of BI-RADS 4 Breast Nodules Based on Three-dimensional Volume Ultrasound

Jiang

Chen

Yao

et al. 2023

Preprint

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Objective To investigate whether the use of a nomogram prediction model with automated breast ultrasound (ABUS) can help improve accuracy in the differentiation of benign and malignant Breast Imaging Reporting and Data System (BI-RADS) 4 breast nodules. Methods Data were collected for a total of 257 nodules with breast nodules corresponding to BI-RADS 4 who underwent ABUS examination and for whom pathology results were obtained from January 2019 to August 2022. The patients were divided into a benign group (188 cases) and a malignant group (69 cases) using a retrospective study method. Ultrasound imaging features were recorded. Logistic regression analysis was used to screen the clinical and ultrasound characteristics. Using the results of these analyses, a nomogram prediction model was established accordingly. Results Age, distance between nodule and nipple, calcification and C-plane convergence sign were independent risk factors that enabled differentiation between benign and malignant breast nodules (all P < 0.05). A nomogram model was established based on these variables. The AUC values for the nomogram model, age, distance between nodule and nipple, calcification, and C-plane convergence sign were 0.86, 0.735, 0.645, 0.697, and 0.685, respectively. Thus, the AUC value for the model was significantly higher than a single variable. Conclusions A nomogram based on the clinical and ultrasound imaging features of ABUS can be used to improve the accuracy of the diagnosis of benign and malignant BI-RADS 4 nodules. It can function as a relatively accurate predictive tool for sonographers and clinicians and is therefore clinically useful. Advances in knowledge statement: we retrospectively analyzed the clinical and ultrasound characteristics of ABUS BI-RADS 4 nodules and established a nomogram model to improve the efficiency of the majority of ABUS readers in the diagnosis of BI-RADS 4 nodules.

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“…However, US encounters significant limitations, including its real-time nature and user-dependent operation, leading to archiving and retrospective analysis challenges. Automated breast ultrasound system (ABUS) can be used for screening and diagnostically, providing a 3-dimensional volume view (18). Undoubtedly, AI algorithms to be developed in the future will enable better visualization of this 3D data, facilitate lesion detection with CAD solutions, and allow faster evaluation with decision support algorithms.…”

Section: From Volume Screening To Personalized Screeningmentioning

confidence: 99%

Future of Breast Radiology

Arıbal

2023

EJBH

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Following the inception of mammography (MG) for screening purposes in the early 1960s, the field of breast imaging has undergone a transformative progression. This evolution gathered significant momentum by incorporating ultrasound (US) and advanced imageguided biopsies into routine clinical practice during the 1990s. Subsequently, in the early 2000s, magnetic resonance imaging (MRI) emerged as a discriminating option for advanced imaging modalities. Furthermore, the shift from conventional to digital radiology occurred between the late twentieth and early twenty-first centuries. Concerns mainly revolved around the reduced resolution of digital images compared to conventional MG, which raised worries about potentially missing lesions like microcalcifications and the challenge of detailed breast tissue visualization. Nevertheless, due to the broader dynamic range of digital MG compared to screen-film MG, it displayed greater tolerance to exposure errors. Additionally, the digital format of images offered a significant advantage, allowing for the integration of advanced techniques. This, in turn, facilitated the incorporation of digital breast tomosynthesis imaging, contrast-enhanced MG, and artificial intelligence (AI) applications. Subsequently, in the early 2000s, MRI emerged as a discerning option for advanced imaging modalities. Through the assessment of multimodality and multiparametric imaging, breast radiology has indisputably established itself as an indispensable and irreplaceable component in the management of breast disorders. Key Points •Advancing integration of artificial intelligence (AI): AI is becoming integral to breast radiology, streamlining workflows, smart dataprocessing, aiding detection and diagnosis, and optimizing decision-making processes.• Personalized screening and diagnosis: Evolving from mammography, automated breast ultrasound, magnetic resonance imaging (MRI), and contrastenhanced mammography offer personalized screening options with AI-driven enhancements for accuracy.• Innovative imaging and therapies: Multiparametric MRI, virtual biopsy, and photoacoustic imaging provide advanced diagnostic insights. Imagingguided therapies and theranostics promise targeted precision treatment, transforming breast radiology's future.

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Comparison of 3D-Automated Breast Ultrasound With Handheld Breast Ultrasound Regarding Detection and BI-RADS Characterization of Lesions in Dense Breasts: A Study of 592 Cases

Cited by 8 publications

References 22 publications

Potential Usefulness a Coronal View using an Automated Breast Ultrasound System in Detecting Breast Lesions

Potential Usefulness a Coronal View using an Automated Breast Ultrasound System in Detecting Breast Lesions

A Nomogram for Diagnosis of BI-RADS 4 Breast Nodules Based on Three-dimensional Volume Ultrasound

Future of Breast Radiology

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