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Int J Comput Assist Radiol Surg ; 16(8): 1393-1401, 2021 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-34224068


PURPOSE: We present the validation of PROST, a robotic device for prostate biopsy. PROST is designed to minimize human error by introducing some autonomy in the execution of the key steps of the procedure, i.e., target selection, image fusion and needle positioning. The robot allows executing a targeted biopsy through ultrasound (US) guidance and fusion with magnetic resonance (MR) images, where the target was defined. METHODS: PROST is a parallel robot with 4 degrees of freedom (DOF) to orient the needle and 1 DOF to rotate the US probe. We reached a calibration error of less than 2 mm, computed as the difference between the needle positioning in robot coordinates and in the US image. The autonomy of the robot is given by the image analysis software, which employs deep learning techniques, the integrated image fusion algorithms and automatic computation of the needle trajectory. For safety reasons, the insertion of the needle is assigned to the doctor. RESULTS: System performance was evaluated in terms of positioning accuracy. Tests were performed on a 3D printed object with nine 2-mm spherical targets and on an anatomical commercial phantom that simulates human prostate with three lesions and the surrounding structures. The average accuracy reached in the laboratory experiments was [Formula: see text] in the first test and [Formula: see text] in the second test. CONCLUSIONS: We introduced a first prototype of a prostate biopsy robot that has the potential to increase the detection of clinically significant prostate cancer and, by including some level of autonomy, to simplify the procedure, to reduce human errors and shorten training time. The use of a robot for the biopsy of the prostate will create the possibility to include also a treatment, such as focal ablation, to be delivered through the same system.

Processamento de Imagem Assistida por Computador/métodos , Biópsia Guiada por Imagem/métodos , Neoplasias da Próstata/diagnóstico , Robótica/métodos , Software , Biópsia por Agulha/métodos , Humanos , Imageamento por Ressonância Magnética/métodos , Masculino , Imagens de Fantasmas , Projetos Piloto , Ultrassonografia
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
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.