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Int J Comput Assist Radiol Surg ; 15(8): 1379-1387, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-32445126


PURPOSE: Biomechanical simulation of anatomical deformations caused by ultrasound probe pressure is of outstanding importance for several applications, from the testing of robotic acquisition systems to multi-modal image fusion and development of ultrasound training platforms. Different approaches can be exploited for modelling the probe-tissue interaction, each achieving different trade-offs among accuracy, computation time and stability. METHODS: We assess the performances of different strategies based on the finite element method for modelling the interaction between the rigid probe and soft tissues. Probe-tissue contact is modelled using (i) penalty forces, (ii) constraint forces, and (iii) by prescribing the displacement of the mesh surface nodes. These methods are tested in the challenging context of ultrasound scanning of the breast, an organ undergoing large nonlinear deformations during the procedure. RESULTS: The obtained results are evaluated against those of a non-physically based method. While all methods achieve similar accuracy, performance in terms of stability and speed shows high variability, especially for those methods modelling the contacts explicitly. Overall, prescribing surface displacements is the approach with best performances, but it requires prior knowledge of the contact area and probe trajectory. CONCLUSIONS: In this work, we present different strategies for modelling probe-tissue interaction, each able to achieve different compromises among accuracy, speed and stability. The choice of the preferred approach highly depends on the requirements of the specific clinical application. Since the presented methodologies can be applied to describe general tool-tissue interactions, this work can be seen as a reference for researchers seeking the most appropriate strategy to model anatomical deformation induced by the interaction with medical tools.

Modelos Anatômicos , Ultrassonografia/métodos , Fenômenos Biomecânicos , Simulação por Computador , Humanos
Int J Comput Assist Radiol Surg ; 14(11): 2043, 2019 11.
Artigo em Inglês | MEDLINE | ID: mdl-31250254


The original version of this article unfortunately contained a mistake.

Int J Comput Assist Radiol Surg ; 14(8): 1329-1339, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31161556


PURPOSE: Although ultrasound (US) images represent the most popular modality for guiding breast biopsy, malignant regions are often missed by sonography, thus preventing accurate lesion localization which is essential for a successful procedure. Biomechanical models can support the localization of suspicious areas identified on a preoperative 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. METHODS: The PBD implementation available in NVIDIA FleX is exploited to create an anatomical model capable of deforming online. Simulation parameters are initialized on a calibration phantom under different levels of probe-induced deformations; then, they are fine-tuned by minimizing the localization error of a US-visible landmark of a realistic breast phantom. The updated model is used to estimate the displacement of other internal lesions due to probe-tissue interaction. RESULTS: The 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. This 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. CONCLUSION: 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.

Neoplasias da Mama/diagnóstico por imagem , Mama/diagnóstico por imagem , Biópsia Guiada por Imagem , Imageamento Tridimensional , Ultrassonografia Mamária , Algoritmos , Biópsia , Calibragem , Simulação por Computador , Humanos , Modelos Anatômicos , Posicionamento do Paciente , Imagens de Fantasmas , Robótica , Software