Biomechanical modelling of probe to tissue interaction during ultrasound scanning

Tagliabue, Eleonora; Dall’Alba, Diego; Magnabosco, Enrico; Fiorini, Paolo

doi:10.1007/s11548-020-02183-2

Cited by 8 publications

(8 citation statements)

References 23 publications

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“…The localization error obtained with the proposed robotic system improves the one obtained by [22] on a similar experimental setup, but on freehand scanning. Improvement in the results can be explained by the presence of the robotic manipulator, which enhances the precision in tracking and positioning of the US probe, and measuring the applied force.…”

Section: Discussionmentioning

confidence: 51%

“…Finally, the median MSE obtained at a preloading of 2 N when considering the same 10 internal lesions as [22] is 3.34 mm.…”

Section: Resultsmentioning

confidence: 92%

“…Moreover, this approach does not require prior definition of the contact surface, allowing to deal with any probe position in input. Although this approach can be computationally demanding due to the complexity of the equation system, previous work demonstrated that a good trade-off between accuracy, computation time and numerical stability can be achieved, provided that the number of elements used for spatial discretization is kept below a few thousands [22].…”

Section: Deformation Compensationmentioning

confidence: 99%

“…As a final evaluation, we assess the contribution brought by the presence of the robotic manipulator with respect to manual US-guided examination. To do so, we compared our experimental results with those described in [22], where authors report a median MSE of 4.2 mm when using the same formulation described in Section III-D to model probe-induced deformations and comparable 3D mesh resolution (i.e., 7,369 elements), on freehand US scanning of the same breast phantom considered in our work. For consistent comparison, we compute the median MSE obtained when considering the same 10 lesions as in [22].…”

Section: B Experimentsmentioning

confidence: 99%

“…This approach does not allow to track out-of-plane lesion movements, and it has been tested on a simplistic phantom which only allows very small deformation. Some works have proposed to track the displacement of internal breast targets due to US probe compression during freehand US using patient-specific deformation models [21], [22]. Groenhuis et al have incorporated a biomechanical model within a robotic setup for breast biopsy to compensate for probe-induced deformations [23].…”

Section: Introductionmentioning

confidence: 99%

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Autonomous Robotic System for Breast Biopsy With Deformation Compensation

Ferrari

Tagliabue

Maris

et al. 2023

IEEE Robot. Autom. Lett.

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Image-guided biopsy is the most common technique for breast cancer diagnosis. Although magnetic resonance imaging (MRI) has the highest sensitivity in breast lesion detection, ultrasound (US) biopsy guidance is generally preferred due to its non-invasiveness and real-time image feedback during the insertion. In this work, we propose an autonomous robotic system for US-guided biopsy of breast lesions identified on pre-operative MRI. After initial MRI to breast registration, the US probe attached to the robotic manipulator compresses the breast tissues until a pre-determined force level is reached. This technique, known as preloading, will allow to minimize lesion displacement during the needle insertion. Our workflow integrates a deformation compensation strategy based on patient-specific biomechanical model to update the US probe orientation keeping the target lesion on the US image plane during compression. By relying on a deformation model, the proposed system does not require lesion visibility on US. Experimental evaluation is performed to assess the performance of the system on a realistic breast phantom with 15 internal lesions, considering different preloading forces. The deformation compensation strategy allows to improve localization accuracy, and as a consequence final probe positioning, for all considered lesions. Median lesion localization error is 3.3 mm, which is lower than the median lesion radius, when applying a preloading of 2 N, which guarantees both minimal needle insertion error and tissue stress.

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Section: Discussionmentioning

confidence: 51%

“…Finally, the median MSE obtained at a preloading of 2 N when considering the same 10 internal lesions as [22] is 3.34 mm.…”

Section: Resultsmentioning

confidence: 92%

Section: Deformation Compensationmentioning

confidence: 99%

Section: B Experimentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%