Project in Progress

I initiated a project to leverage my expertise in image-guided therapy and AI to focus on transcranial focused ultrasound (TFUS) therapy in ongoing research. TFUS offers a non-invasive, image-guided approach for treating brain disorders, significantly reducing surgical risks and collateral damage often associated with radiation therapy. However, the application of high-intensity focused ultrasound (HIFU) for brain treatments encounters significant challenges due to the skull's interaction with ultrasound waves, which shifts the ultrasound focal spot, deviating from the target location. Currently, TFUS is suitable for treating small, centrally located targets such as the thalamus in conditions like essential tremor. Treating deeper and off-center targets, including brain tumors, remains a challenge. To facilitate the use of TFUS for tumor treatment, new image-guided technologies are needed that:

1. Allow greater degrees of freedom in transmitting ultrasound waves through the skull to the brain.
2. Enable real-time treatment planning and guidance capable of managing advanced treatments.

I am passionate about defining research projects to address these challenges through interdisciplinary research that integrates TFUS principles with AI, robotics, and advanced computational modeling.

Enhancing TFUS Treatment Planning with Computational Intelligence

I aim to apply my expertise in multimodal imaging and computational intelligence to develop more sophisticated image-guided methods and models for treatment planning and guidance of TFUS brain treatment. Currently, MRI thermometry provides a solution for monitoring treatment. However, treatment planning for TFUS guidance is performed preoperatively using a comprehensive computational simulation model in conjunction with 3D CT scans of a patient's skull. My short-term goal involves pursuing the following research objectives:

1. Integrate TFUS theories for modeling ultrasound propagation through the skull with AI algorithms to develop a fast model for simulating TFUS. This modeling will be expanded with AI-powered inverse analysis for TFUS treatment planning, accounting for skull aberration effects and adjusting treatment parameters.
2. Develop a novel multimodal imaging method that combines real-time MRI imaging with preoperative CT brain images. This method will provide a highly detailed image-guided approach for TFUS treatment and can be integrated with the AI-driven treatment planning model for real-time TFUS guidance.

Achieving these objectives will significantly advance the goal of using TFUS for brain tumor treatment.

 Advancing Innovative Systems for TFUS Brain Tumor Treatment

I aim to spearhead research projects that design innovative technologies and systems for TFUS, facilitating its application in brain tumor treatment. This involves designing new systems that offer increased freedom in ultrasound wave propagation, thereby diminishing the impact of the skull during wave transmission. A potential avenue is the development of robotic-assisted TFUS technology, which allows control over the angle of each ultrasound beam element relative to the skull surface, beyond phase and amplitude. Theoretically, maximum ultrasound levels can be transmitted through the skull by maintaining a 90-degree angle between the skull and the ultrasound beam. Furthermore, I aim to develop an AI-driven control system, utilizing computational intelligence, to enhance the precision of TFUS in treating brain tumors. The main objectives for my long-term research plan include:

1. Engineer a robotic-assisted TFUS platform to enable precise manipulation of the beam angle in relation to the skull surface.
2. Combine the AI-driven treatment planning algorithms with the platform for intelligent control of TFUS guidance.
3. Establish a robust experimental framework for TFUS to test and validate the developed algorithms and systems for this application.