Epilepsy, a common neurological disorder causing recurring seizures. Magnetic Resonance-guided Laser Interstitial Thermal Therapy (MRgLITT) is a promising minimally-invasive technique to ablate the target especially for drug resistance epilepsy. MRgLITT employs a laser fiber to ablate brain tissue through heat deposition, offering real-time monitoring through Magnetic Resonance (MR) thermometry images and precise treatment planning using MRI planning images. In this study, we developed an AI-based approach utilizing a U-Net model, a convolutional neural network architecture widely used for image to image translation, to predict MR thermometry images from anatomical MRI planning images from a dataset of 81 patients with mesial temporal lobe epilepsy. The model’s performance was evaluated on a test dataset using the structural similarity index (SSIM) and root mean squared error (RMSE).
MRI-guided focused-ultrasound is a non-invasive technique that can enhance the delivery of therapeutic agents. The
objective of this work was to develop a focused-ultrasound system for preclinical research in small animals that is
capable of sonicating with high spatial precision within a closed-bore MRI. The system features a computer-controlled,
non-magnetic, three-axis positioning system that uses piezoelectric actuators and linear optical encoders to position a
focused-ultrasound transducer to targeted tissues under MRI guidance. The actuator and encoder signals are transmitted
through low-pass-filtered connectors on a grounded RF-penetration panel to prevent artifacts during image acquisition.
The transducer is attached to the positioning system by a rigid arm and is submerged within a closed water tank. The arm
passes into the tank through flexible bellows to ensure that the system remains sealed. An RF coil acquires high-resolution
images in the vicinity of the target tissue. An aperture on the water tank, centered about the RF coil, provides
an access point for target sonication. Registration between ultrasound and MRI coordinates involves sonicating a
temperature-sensitive phantom and measuring the centroid of the thermal focal zone in 3D with MR thermometry. Linear
distances of 5 cm with a positioning resolution of 0.05 mm can be achieved for each axis. The system was operated
successfully on MRI scanners from different vendors at both 1.5 and 3.0 T, and simultaneous motion and imaging was
possible without any mutual interference or imaging artifacts. This system is used for high-throughput small-animal experiments to study the efficacy of ultrasound-enhanced drug delivery.
Preclinical research often requires the delivery of biological substances to specific locations in small animals.
Guiding a needle to targets in small animals with an error < 200 μm requires accurate registration. We are
developing techniques to register a needle-positioning robot to high-resolution three-dimensional ultrasound
and computed tomography small animal imaging systems. Both techniques involve moving the needle to predetermined
robot coordinates and determining corresponding needle locations in image coordinates. Registration
accuracy will therefore be affected by the robot positioning error and is assessed by measuring the target registration
error (TRE). A point-based registration between robot and micro-ultrasound coordinates was accomplished
by attaching a fiducial phantom onto the needle. A TRE of 145 μm was achieved when moving the needle to a set
of robot coordinates and registering the coordinates to needle tip locations determined from ultrasound fiducial
measurements. Registration between robot and micro-CT coordinates was accomplished by injecting barium sulfate
into tracks created when the robot withdraws the needle from a phantom. Points along cross-sectional slices
of the segmented needle tracks were determined using an intensity-weighted centroiding algorithm. A minimum
distance TRE of 194 ± 18 μm was achieved by registering centroid points to robot trajectories using the iterative
closest point (ICP) algorithm. Simulations, incorporating both robot and ultrasound fiducial localization errors,
verify that robot error is a significant component of the experimental registration. Simulations of micro-CT to
robot ICP registration similarly agree with the experimental results. Both registration techniques produce a
TRE < 200 μm, meeting design specification.
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