Magnetic resonance imaging (MRI) provides both anatomical imaging with excellent soft tissue contrast and functional MRI imaging (fMRI) of physiological parameters. The last two decades have witnessed the manifestation of increased interest in MRI-guided minimally invasive intervention procedures and fMRI for rehabilitation and neuroscience research. Accompanying the aspiration to utilize MRI to provide imaging feedback during interventions and brain activity for neuroscience study, there is an accumulated effort to utilize force sensors compatible with the MRI environment to meet the growing demand of these procedures, with the goal of enhanced interventional safety and accuracy, improved efficacy and rehabilitation outcome. This paper summarizes the fundamental principles, the state of the art development, and challenges of fiber-optic force sensors for MRI-guided interventions and rehabilitation. It provides an overview of MRI-compatible fiber-optic force sensors based on different sensing principles, including light intensity modulation, wavelength modulation, and phase modulation. Extensive design prototypes are reviewed to illustrate the detailed implementation of these principles. Advantages and disadvantages of the sensor designs are compared and analyzed. A perspective on the future development of fiber-optic sensors is also presented, which may have additional broad clinical applications. Future surgical interventions or rehabilitation will rely on intelligent force sensors to provide situational awareness to augment or complement human perception in these procedures.

MRI-conditional robotic platforms have proved to be an effective approach for image-guided interventions. In this study, a computer-assisted, pneumatically actuated robot is designed, built, and tested for MRI-guided prostate cancer focal laser ablation (FLA). The robotic manipulator provides two active planar degrees of freedom (DoFs) by using a customized CoreXY frame and one passive rotational DoF. A remote insertion mechanism improves the surgical workflow by keeping the patients inside the scanner during needle insertion. The robotic manipulator is tested in a 3T MR scanner to evaluate its MR compliance, and the results demonstrated that the signal-to-noise ratio (SNR) variation is less than 8%. The in-scanner template positioning accuracy test demonstrates that the manipulator achieves high targeting accuracy with a mean error of 0.46 mm and a standard deviation of 0.25 mm. Phantom studies have shown that the needle insertion accuracy of the manipulator is within 2 mm (mean = 1.7 mm, standard deviation = 0.2 mm).

Objective: a magnetic resonance imaging (MRI)-conditional needle guidance robot is developed to enhance MRI-guided focal laser ablation (FLA) therapy in patients with focal prostate cancer. Methods: inspired by the workflow of the manual FLA therapy, we developed an MRI-conditional robot with two degrees of freedom to provide the guidance for laser ablation catheter. This robot is powered by pneumatic turbine motors and encoded with the custom-designed optical encoder. The needle could be inserted manually through the designed robotic system, which keeps the patients inside MRI bore throughout the procedure. The robot hardware is integrated with the custom ablation planning and monitoring software (OncoNav) to provide an iterative treatment plan to cover the whole ablation zone. Virtual tumors were selected in three canine cadavers as targets to validate the performance of the proposed hardware and software system. Results: phantom studies show that the average targeting error is less than 2 mm and the workflow of the entire procedure lasts for 100 minutes. Canine cadaver experiment results show that all the targets were successfully ablated in no more than three administrations. Significance: MRI-guided prostate FLA is feasible using the proposed hardware and software system, indicating potential utility in future human trials.

Purpose: A novel grid-template-mimicking MR-compatible robot was developed for in-gantry MRI-guided focal laser ablation of prostate cancer. Method: A substantially compact robot was designed and prototyped to meet in-gantry lithotomy ergonomics and allow for accommodation in the perineum. The controller software was reconfigured and integrated with the custom-designed navigation and multi-focal ablation software. Three experiments were conducted: (1) free space accuracy test; (2) phantom study under computed tomography (CT) guidance for image-guided accuracy test and overall workflow; and (3) magnetic resonance imaging (MRI)-guided focal laser ablation of an ex vivo prostate. The free space accuracy study included five targets that were selected across the workspace. The robot was then commanded five times to each target. The phantom study used a gel phantom made with color changing thermos-chromic ink, and four spherical metal fiducials were deployed with the robot. Then, laser ablation was applied, and the phantom was sliced for gross observation. For an MR-guided ex vivo test, a prostate from a donor who died of prostate cancer was obtained and multi-focally ablated using the system within the MRI gantry. The tissue was sliced after ablation for validation. Results: free-space accuracy was 0.38 ± 0.27 mm. The overall system targeting accuracy under CT guidance (including robot, registration, and insertion error) was 2.17 ± 0.47 mm. The planned ablation zone was successfully covered in both acrylamide gel phantom and in human prostate tissue. Conclusions: The new robot can accurately facilitate fiber targeting for MR-guided focal laser ablation of targetable prostate cancer.

Purpose: This study aims to investigate the accuracy of a cross platform augmented reality (AR) system for percutaneous needle interventions irrespective of operator error. In particular, we study the effect of the relative position and orientation of the AR device and the marker, the location of the target, and the angle of needle on the overlay accuracy. Method: A needle guidance AR platform developed using Unity and Vuforia SDK platforms was used to display a planned needle trajectory for targets via mobile and wearable devices. To evaluate the system accuracy, a custom phantom embedded with metal fiducial markers and an adjustable needle guide was designed to mimic different relative position and orientation scenarios of the smart device and the marker. After segmenting images of CT-visible fiducial markers as well as different needle trajectories, error was defined by comparing them to the corresponding augmented target/needle trajectory projected by smartphone and smartglasses devices. Results: The augmentation error for targets and needle trajectories were reported as a function of marker position and orientation, as well as the location of the targets. Overall, the image overlay error for needle trajectory was 0.28±0.32° (Max = 0.856°) and 0.41±0.23° (Max = 0.805°) using the iPhone and HoloLens glasses, respectively. The overall image overlay error for targets was 1.75±0.59 mm for iPhone, and 1.74±0.86 mm for HoloLens. Conclusions: The image overlay error caused by different sources can be quantified for different AR devices.