Connectivity-Image Guided TMS Targeting via Robotic Delivery
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Solution Overview
Problem
Current transcranial magnetic stimulation (TMS) treatments for major depressive disorder (MDD) and post-traumatic stress disorder (PTSD) lack sophistication in targeting brain regions, relying on gross anatomical references rather than individual anatomy or connectivity, leading to suboptimal neuromodulatory effects.
Innovation Solution
The use of connectivity-image guidance (CIG) and cortical column cosine (C3) principles for precise TMS targeting, combining meta-analytic connectivity-based parcellation with resting-state BOLD fMRI to identify optimal stimulation locations based on network properties, enabling personalized treatment planning and robotic delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If connectivity-image guidance and robotic delivery are implemented, then treatment precision and effectiveness improve, but device complexity and operational complexity increase
Solution Approach 1:
A robotic arm serves as an intermediary device between the operator and the TMS coil, enabling precise positioning and delivery while reducing direct manual manipulation. The robotic system integrates imaging data and treatment protocols to automatically position the coil with high precision, resolving the contradiction between improved targeting and increased system complexity by automating the coordination function.
Solution Approach 2:
Manual mechanical positioning of the TMS coil is replaced with an automated robotic system that uses computer-controlled mechanisms. This substitution enables more precise and repeatable positioning while reducing human error and variability, addressing the contradiction by replacing simple manual mechanics with sophisticated but automated robotic mechanics.
2Reliability
If connectivity-based parcellation and per-subject anatomy are used, then treatment effectiveness improves, but treatment planning time and complexity increase
Solution Approach 1:
Connectivity-based parcellation and anatomical mapping are performed in advance during treatment planning, creating pre-computed maps of functional connectivity and anatomical landmarks. These preliminary actions allow the robotic system to quickly reference pre-analyzed data during actual treatment delivery, reducing real-time planning time while maintaining high treatment effectiveness based on personalized anatomy.
Solution Approach 2:
The system creates digital copies or models of the patient's specific anatomy and functional connectivity patterns from imaging data. These virtual models allow for detailed analysis and treatment planning without requiring physical manipulation or extended procedures on the patient, reducing planning time while preserving the benefits of personalized treatment based on individual anatomy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for more precise and effective modulation of brain regions, as demonstrated by significant changes in functional connectivity and symptom improvement in clinical trials, confirming the efficacy of connectivity-based parcellation for TMS treatment planning.
Implementation Method 1
Rapidly changing magnetic fields induce electrical currents that, in turn, depolarize neurons
Data Source
AI summary
Transcranial magnetic stimulation may be delivered to a subject based on a treatment plan. This treatment plan is generated using connectivity-image guidance to identify one or more optimal locations to stimulate based on network properties. In turn, a cortical column cosine principle may be applied to identify one or more particular subject locations at which to deliver TMS to the subject to the optimal locations.