Although ultrasound (US) images represent the most popular modality for guiding breast biopsy, they are sometimes unable to render malignant regions, thus preventing accurate lesion localization which is essential for a successful procedure. Biomechanical models can support the localization of suspicious areas identified on a pre-operative image during US scanning since they are able to account for anatomical deformations resulting from US probe pressure. We propose a deformation model which relies on position-based dynamics (PBD) approach to predict the displacement of internal targets induced by probe interaction during US acquisition. The PBD implementation available in NVIDIA FleX is exploited to create an anatomical model capable of deforming in real-time. In order to account for each patient’s specificities, model parameters are selected as those minimizing the localization error of a US-visible landmark of the anatomy of interest (in our case, a realistic breast phantom). The updated model is used to estimate the displacement of other internal lesions due to probe-tissue interaction. The proposed approach is compared to a finite element model (FEM), generally used in breast biomechanics, and a rigid one. Localization error obtained when applying the PBD model remains below 11 mm for all the tumors even for input displacements in the order of 30 mm. The proposed method obtains results aligned with FE models with faster computational performance, suitable for real-time applications. In addition, it outperforms rigid model used to track lesion position in US-guided breast biopsies, at least halving the localization error for all the displacement ranges considered. Position-based dynamics approach has proved to be successful in modeling breast tissue deformations during US acquisition. Its stability, accuracy and real-time performance make such model suitable for tracking lesions displacement during US-guided breast biopsy.


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    Titel :

    Real-time prediction of breast lesions displacement during Ultrasound scanning using a position-based dynamics approach.



    Erscheinungsdatum :

    2019-01-01


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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