MRI-compatible electromagnetic servomotor for image-guided medical robotics

MatchMorph: A real-time pre- and intra-operative deformable image registration framework for MRI-guided surgery

PURPOSE

The technological advancements in surgical robots compatible with magnetic resonance imaging (MRI) have created an indispensable demand for real-time deformable image registration (DIR) of pre- and intra-operative MRI, but there is a lack of relevant methods. Challenges arise from dimensionality mismatch, resolution discrepancy, non-rigid deformation and requirement for real-time registration.

METHODS

In this paper, we propose a real-time DIR framework called MatchMorph, specifically designed for the registration of low-resolution local intraoperative MRI and high-resolution global preoperative MRI. Firstly, a super-resolution network based on global inference is developed to enhance the resolution of intraoperative MRI to the same as preoperative MRI, thus resolving the resolution discrepancy. Secondly, a fast-matching algorithm is designed to identify the optimal position of the intraoperative MRI within the corresponding preoperative MRI to address the dimensionality mismatch. Further, a cross-attention-based dual-stream DIR network is constructed to manipulate the deformation between pre- and intra-operative MRI, real-timely.

RESULTS

We conducted comprehensive experiments on publicly available datasets IXI and OASIS to evaluate the performance of the proposed MatchMorph framework. Compared to the state-of-the-art (SOTA) network TransMorph, the designed dual-stream DIR network of MatchMorph achieved superior performance with a 1.306 mm smaller HD and a 0.07 mm smaller ASD score on the IXI dataset. Furthermore, the MatchMorph framework demonstrates an inference speed of approximately 280 ms.

CONCLUSIONS

The qualitative and quantitative registration results obtained from high-resolution global preoperative MRI and simulated low-resolution local intraoperative MRI validated the effectiveness and efficiency of the proposed MatchMorph framework.

Validation of single reference variable flip angle (SR-VFA) dynamic T1 mapping with T2 * correction using a novel rotating phantom

PURPOSE

To validate single reference variable flip angle (SR-VFA) dynamic T1 mapping with and without T2 * correction against inversion recovery (IR) T1 measurements.

METHODS

A custom cylindrical phantom with three concentric compartments was filled with variably doped agar to produce a smooth spatial gradient of the T1 relaxation rate as a function of angle across each compartment. IR T1 , VFA T1 , and B1 + measurements were made on the phantom before rotation, and multi-echo stack-of-radial dynamic images were acquired during rotation via an MRI-compatible motor. B1 + -corrected SR-VFA and SR-VFA-T2 * T1 maps were computed from the sliding window reconstructed images and compared against rotationally registered IR and VFA T1 maps to determine the percentage error.

RESULTS

Both VFA and SR-VFA-T2 * T1 maps fell within 10% of IR T1 measurements for a low rotational speed, with a mean accuracy of 2.3% ± 2.6% and 2.8% ± 2.6%, respectively. Increasing rotational speed was found to decrease the accuracy due to increasing temporal smoothing over ranges where the T1 change had a nonconstant slope. SR-VFA T1 mapping was found to have similar accuracy as the SR-VFA-T2 * and VFA methods at low TEs (˜<2 ms), whereas accuracy degraded strongly with later TEs. T2 * correction of the SR-VFA T1 maps was found to consistently improve accuracy and precision, especially at later TEs.

CONCLUSION

SR-VFA-T2 * dynamic T1 mapping was found to be accurate against reference IR T1 measurements within 10% in an agar phantom. Further validation is needed in mixed fat-water phantoms and in vivo.

Challenges regarding MR compatibility of an MRgFUS robotic system

Numerous challenges are faced when employing Magnetic Resonance guided Focused Ultrasound (MRgFUS) hardware in the Magnetic Resonance Imaging (MRI) setting. The current study aimed to provide insights on this topic through a series of experiments performed in the framework of evaluating the MRI compatibility of an MRgFUS robotic device. All experiments were performed in a 1.5 T MRI scanner. The main metric for MRI compatibility assessment was the signal to noise ratio (SNR). Measurements were carried out in a tissue mimicking phantom and freshly excised pork tissue under various activation states of the system. In the effort to minimize magnetic interference and image distortion, various set-up parameters were examined. Significant SNR degradation and image distortion occurred when the FUS transducer was activated mainly owing to FUS-induced target and coil vibrations and was getting worse as the output power was increased. Proper design and stable positioning of the imaged phantom play a critical role in reducing these vibrations. Moreover, isolation of the phantom from the imaging coil was proven essential for avoiding FUS-induced vibrations from being transferred to the coil during sonication and resulted in a more than 3-fold increase in SNR. The use of a multi-channel coil increased the SNR by up to 50 % compared to a single-channel coil. Placement of the electronics outside the coil detection area increased the SNR by about 65 %. A similar SNR improvement was observed when the encoders' counting pulses were deactivated. Overall, this study raises awareness about major challenges regarding operation of an MRgFUS system in the MRI environment and proposes simple measures that could mitigate the impact of noise sources so that the monitoring value of MR imaging in FUS applications is not compromised.