Brain Infusion Planning via Diffusion Tensor Imaging
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Solution Overview
Problem
Current methods for treating Parkinson's disease do not effectively utilize planned targeted delivery of therapeutic substances within the brain to address the dopamine deficiency associated with the condition.
Innovation Solution
A system and method for delivering therapeutic agents, such as GDNF, to specific regions of the brain using magnetic resonance diffusion tensor imaging (MR-DTI) scans to calculate diffusion tensors and simulate electrical fields, allowing for precise placement of delivery instruments to achieve desired agent concentrations and distributions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional drug delivery methods are used to treat Parkinson's disease, then the treatment can be administered, but the delivery precision and targeting accuracy to specific brain regions is insufficient
Solution Approach 1:
The system performs preliminary planning of the catheter insertion path and drug delivery strategy before the actual procedure. MR-DTI scans are acquired and diffusion tensors are calculated in advance to simulate and optimize the delivery plan, ensuring precise targeting before the invasive procedure begins.
Solution Approach 2:
The system uses MR-DTI imaging to provide real-time feedback on the distribution of therapeutic agents in the brain. This feedback mechanism allows for verification of delivery precision and enables adjustments to ensure the drug reaches the intended target regions with the desired concentration.
2Measurement precision
If MR-DTI scanning and diffusion tensor calculation are performed to achieve precise agent distribution, then the targeting accuracy improves, but the time required for treatment planning increases
Solution Approach 1:
All necessary imaging, calculations, and simulations are performed in advance before the actual drug delivery procedure. The system pre-calculates diffusion tensors from MR-DTI scans and pre-plans the optimal catheter path and delivery parameters, so that when the procedure begins, execution can proceed efficiently without time-consuming calculations during the actual treatment.
Solution Approach 2:
The system creates a virtual model or simulation of the patient's brain anatomy and drug distribution based on MR-DTI data. This digital copy allows for repeated testing and optimization of delivery plans without affecting the actual patient, enabling high precision planning to be completed efficiently before the real procedure.
3Reliability
If high concentration of therapeutic agent is delivered to target region, then treatment effectiveness improves, but the risk of off-target effects and toxicity increases
Solution Approach 1:
The system delivers the therapeutic agent with highly localized concentration gradients, achieving high concentration at the target region while maintaining low concentration in surrounding tissues. The diffusion tensor-based planning allows for precise control of the delivery parameters to create a concentration profile that is high where needed and low where not needed, minimizing off-target effects.
Solution Approach 2:
The system replaces conventional mechanical injection methods with a computer-guided, simulation-based delivery approach. By using diffusion tensor calculations and electrical field simulations, the system can predict and control agent distribution patterns, allowing high concentrations to be achieved at targets while avoiding harmful concentrations in adjacent regions through intelligent parameter optimization.
Data Source
AI summary
A system and method for treating Parkinson's disease by delivery of an agent within the brain. At least one image of a target region is acquired, and at least one magnetic resonance diffusion tensor imaging (MR-DTI) scan of the target region is acquired. A diffusion tensor is calculated from the at least one MR-DTI scan, and at least one of an agent distribution and an agent concentration from the images and the calculated diffusion tensor is calculated. Using at least one of the calculated diffusion tensor, the images, the calculated agent distribution, and the calculated agent concentration, the placement of a delivery instrument is planned to deliver the agent to the target region to achieve a desired agent concentration and/or agent distribution within the target region. Delivery of the agent can be coordinated with an applied electrical stimulation.