Autonomous Robotic System for Breast Biopsy With Deformation Compensation

Abstract

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.

Review of robotic systems for thoracoabdominal puncture interventional surgery

“… 87 Similarly, an autonomous robotic system for US-guided biopsy of breast lesions was proposed, in which the applied force was measured by a force sensor located in the flange of the robot. 88 There are some research with the robot's built-in force and torque sensors, further allowing ultrasound acquisitions with optimal skin force and providing repeatable 3D ultrasound volumetric datasets. 89–92 Although the reported systems generated a contact force by pushing the ultrasound probe onto the body surface directly with actuators and sensors, it is of concern that an excessive contact force can be accidentally applied through control error or because of the failure of actuators and sensors.…”

IVNet: Transfer Learning Based Diagnosis of Breast Cancer Grading Using Histopathological Images of Infected Cells

“…The breast biopsy samples are examined under a microscope during classical diagnosis to detect potential abnormalities [4]. Breast biopsies serve to identify both cancerous and non-cancerous conditions.…”