Needle insertion into soft tissue is one of the common minimally invasive surgical procedures. Many diagnostic and therapeutic clinical procedures require insertion of a needle to a specific location in soft-tissue, including biopsy or radioactive seed implantation for cancer treatment (brachytherapy). In this thesis, we start with modeling the effect of skin thickness on target motion during insertion. A closed-loop control algorithm is then developed for flexible needle steering using camera and ultrasound images for feedback. An ultrasound-based 3D needle tracking algorithm is then combined with real-time path planning for needle steering. The needle is steered during insertion in gelatin-based and biological soft-tissue phantoms. A non-imaging approach (fiber Bragg grating (FBG) sensors) is also used for real-time needle shape reconstruction and tip tracking. FBG sensors are used as feedback to the control algorithm to steer the needle towards a target in 3D space. We then focus on physical target localization and 3D shape reconstruction for needle steering in phantoms with curved surfaces. A clinical application (needle insertion in the prostate) is also investigated where the needle is steered in a multi-layer phantom with different tissue elasticities. In order to bring the proposed algorithms to clinical environments, we consider practical issues such as including the clinician in the control loop to merge robot accuracy with clinical expertise. The proposed system is adapted to enable clinicians to directly control the insertion procedure while receiving navigation cues from the control algorithm. Navigation cues are provided through a combination of haptic (vibratory) and visual feedback to the operator who controls the needle for steering. The proposed system is further adapted by using a clinically-approved Automated Breast Volume Scanner (ABVS) which is experimentally evaluated to be used for needle insertion procedures. The ultrasound-based ABVS system is used for pre-operative scanning of soft-tissue for target localization, shape reconstruction, and also intra-operatively for needle tip tracking during the steering process. The achieved targeting errors suggest that our approach is convenient for targeting lesions that can be detected using clinical ultrasound imaging systems. These promising results allow us to proceed further in bringing our system towards clinical practice.
|Award date||26 Aug 2015|
|Place of Publication||Enschede|
|Publication status||Published - 26 Aug 2015|