CT‐guided biopsy of breast lesions: When should it be considered?

Graziano, Luciana; Barbosa, Paula Nicole Vieira Pinto; Travesso, Demian Junklaus; Tourinho, Thais de Lima; Tyng, Chiang Jeng; Bitencourt, Almir Galvão Vieira

doi:10.1111/tbj.13407

Cited by 3 publications

(2 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ultrasonography has the characteristics of a real-time observation, low cost and high diagnostic level, and it has become the most important method of breast examination [9][10][11][12][13]. Hospitals generate many ultrasound images of the breast every day, which requires experienced ultrasound doctors to analyze the ultrasound images.…”

Section: Introductionmentioning

confidence: 99%

An Intelligent Breast Ultrasound System for Diagnosis and 3D Visualization

Chen

et al. 2022

Electronics

View full text Add to dashboard Cite

Background: Ultrasonography is the main examination method for breast diseases. Ultrasound imaging is currently relied upon by doctors to form statements of characteristics and locations of lesions, which severely limits the completeness and effectiveness of ultrasound image information. Moreover, analyzing ultrasonography requires experienced ultrasound doctors, which are not common in hospitals. Thus, this work proposes a 3D-based breast ultrasound system, which can automatically diagnose ultrasound images of the breasts and generate a representative 3D breast lesion model through typical ultrasonography. Methods: In this system, we use a weighted ensemble method to combine three different neural networks and explore different combinations of the neural networks. On this basis, a breast locator was designed to measure and transform the spatial position of lesions. The breast ultrasound software generates a 3D visualization report through the selection and geometric transformation of the nodular model. Results: The ensemble neural network improved in all metrics compared with the classical neural network (DenseNet, AlexNet, GoogLeNet, etc.). It proved that the ensemble neural network proposed in this work can be used for intelligent diagnosis of breast ultrasound images. For 3D visualization, magnetic resonance imaging (MRI) scans were performed to achieve their 3D reconstructions. By comparing two types of visualized results (MRI and our 3D model), we determined that models generated by the 3D-based breast ultrasound system have similar nodule characteristics and spatial relationships with the MRI. Conclusions: In summary, this system implements automatic diagnosis of ultrasound images and presents lesions through 3D models, which can obtain complete and accurate ultrasound image information. Thus, it has clinical potential.

show abstract

Section: Introductionmentioning

confidence: 99%

An Intelligent Breast Ultrasound System for Diagnosis and 3D Visualization

Chen

et al. 2022

Electronics

View full text Add to dashboard Cite

show abstract

“…Although few reports in the literature address the use of this technique for performing breast lesion biopsies, CT guidance is possible as long as the lesion is well characterized by this method. Despite the additional radiation dose, this procedure is faster and less expensive than MRI-guided biopsy (4,5) .…”

Section: Introductionmentioning

confidence: 99%