Purpose of the review: Robotics is a rapidly advancing field, and its introduction in healthcare can have a multitude of benefits for clinical practice. Especially, applications depending on the radiologist’s accuracy and precision, such as percutaneous interventions, may profit. This paper provides an overview of recent robot-assisted percutaneous solutions. Recent findings: Percutaneous interventions are relatively simple and the quality of the procedure increases a lot by introducing robotics due to the improved accuracy and precision. The success of the procedure is heavily dependent on the ability to merge pre- and intraoperative images, as an accurate estimation of the current target location allows to exploit the robot’s capabilities. Summary: Despite much research, the application of robotics in some branches of healthcare is not commonplace yet. Recent advances in percutaneous robotic solutions and imaging are highlighted, as they will pave the way to more widespread implementation of robotics in clinical practice.

Breast cancer is one of the most diagnosed types of cancer worldwide. Volumetric ultrasound breast imaging, combined with MRI can improve lesion detection rate, reduce examination time, and improve lesion diagnosis. However, to our knowledge, there are no 3D US breast imaging systems available that facilitate 3D US - MRI image fusion. In this paper, a novel Automated Cone-based Breast Ultrasound System (ACBUS) is introduced. The system facilitates volumetric ultrasound acquisition of the breast in a prone position without deforming it by the US transducer. Quality of ACBUS images for reconstructions at different voxel sizes (0.25 and 0.50 mm isotropic) was compared to quality of the Automated Breast Volumetric Scanner (ABVS) (Siemens Ultrasound, Issaquah, WA, USA) in terms of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and resolution using a custom made phantom. The ACBUS image data were registered to MRI image data utilizing surface matching and the registration accuracy was quantified using an internal marker. The technology was also evaluated in vivo. The phantom-based quantitative analysis demonstrated that ACBUS can deliver volumetric breast images with an image quality similar to the images delivered by a currently commercially available Siemens ABVS. We demonstrate on the phantom and in vivo that ACBUS enables adequate MRI-3D US fusion. To our conclusion, ACBUS might be a suitable candidate for a second-look breast US exam, patient follow-up, and US guided biopsy planning.

Pneumatic stepper motors can be used to actuate MR safe robotics and other devices. Due to tight space requirements inside the MRI scanner it is useful to combine several individual stepper motors into a single device with an efficient shared actuator mechanism, called the multiple concentric shaft pneumatic stepper motor. The demonstrated "multi-motor" prototype has six geared shafts driven by four pneumatic cylinders and is controlled by five pneumatic lines. The dimensions are 58 x 25 mm (excluding shafts) and the maximum torque at 1.5 bar system pressure is in the range 56 N mm to 114 N mm. The maximum unloaded stepping frequency is 50 Hz when using 0.3 m tubes and drops to 12 Hz when using 5.1 m tubes and 15 N mm load on each shaft. The positioning accuracy is two steps and the most efficient path planning algorithm needs 1.7 times as many steps as six separate single-axis motors. An examplatory 6-DOF manipulator design concept driven by the proposed motor requires an order of magnitude fewer components than state-of-art robotic systems with comparable kinematics. While the multi-motor concept offers significant advantages in motor dimensions and pneumatic tube count, the dynamic performance is fundamentally poor, accuracy is compromised and the coaxial output shafts requires thoughtful kinematic design of robotic systems to make effective use of the motor.

Biopsy of breast lesions only visible on MRI may benefit from patient-specific finite-element modeling of the breast. This requires acquisition of the heterogeneous elasticity distribution. An acoustically transparent pad has been developed which enables strain elastography imaging using ultrasound without need for additional force or pressure sensors. The elasticity of the pad is known a priori while the change in thickness is detectable on ultrasound by edge detection. Based on the calculated pressure distribution across the pad, the pressure in inner tissue can be approximated. The strain is measured using a cross-correlation block matching algorithm and from these measurements the heterogeneous elasticity distribution can be estimated. The ultrasound probe with pad is moved over the breast surface by a robot arm. At sixteen sites on the surface of one phantom the probe with pad performed an inward push movement perpendicular to the breast surface. The ultrasound scans were post-processed to reconstruct a heterogeneous elasticity map in the local imaging plane. While it is challenging to accurately estimate the stress and strain in deeper tissue, certain features such as the skin can be effectively distinguished from the underlying soft tissue which demonstrates the potential of the system.

Purpose: Abnormalities in the bladder wall require careful investigation regarding type, spatial position and invasiveness. Construction of a 3-D model of the bladder is helpful to ensure adequate coverage of the scanning procedure, quantitative comparison of bladder wall textures between successive sessions and finding back previously discovered abnormalities. Methods: Videos of both an in vivo bladder and a textured bladder phantom were acquired. Structure-from-motion and bundle adjustment algorithms were used to construct a 3-D point cloud, approximate it by a surface mesh, texture it with the back-projected camera frames and draw the corresponding 2-D atlas. Reconstructions of successive sessions were compared; those of the bladder phantom were co-registered, transformed using 3-D thin plate splines and post-processed to highlight significant changes in texture. Results: The reconstruction algorithms of the presented workflow were able to construct 3-D models and corresponding 2-D atlas of both the in vivo bladder and the bladder phantom. For the in vivo bladder the portion of the reconstructed surface area was 58% and 79% for the pre- and post-operative scan, respectively. For the bladder phantom the full surface was reconstructed and the mean reprojection error was 0.081 mm (range 0–0.79 mm). In inter-session comparison the changes in texture were correctly indicated for all six locations. Conclusion: The proposed proof of concept was able to perform 3-D and 2-D reconstruction of an in vivo bladder wall based on a set of monocular images. In a phantom study the computer vision algorithms were also effective in co-registering reconstructions of successive sessions and highlighting texture changes between sessions. These techniques may be useful for detecting, monitoring and revisiting suspicious lesions.