Hybrid Spectroscopy Imaging for Epileptic Cortex Detection
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Solution Overview
Problem
Current methods for identifying epileptogenic brain areas during epilepsy surgery lack precision, particularly in differentiating between epileptogenic and eloquent cortices, leading to incomplete resections and postoperative morbidity, and require invasive techniques or high-infrastructure imaging modalities.
Innovation Solution
A method and system that detect and differentiate epileptogenic cortices by analyzing cerebral blood volume and blood oxygenation low-frequency oscillations using non-invasive imaging, specifically capturing images within certain wavelength ranges and employing dichroic mirrors or bandpass filters to separate relevant wavelengths, and applying Granger causality analysis to identify cause areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If non-invasive imaging modalities (fMRI, PET, SPECT) are used to identify epileptogenic areas, then the general location can be determined, but the exact boundaries cannot be precisely identified and the information accuracy degrades during surgery due to brain shifting
Solution Approach 1:
The patent performs functional mapping and identifies epileptogenic boundaries during the preoperative phase using non-invasive imaging, then uses this pre-acquired functional information to guide intraoperative resection. This preliminary functional characterization allows the surgical team to target specific boundaries identified before surgery, compensating for the loss of real-time functional imaging capability during surgery.
Solution Approach 2:
The patent creates a preoperative functional map that serves as a reference or copy of the brain's functional organization. This pre-acquired functional information is then used to guide resection boundaries during surgery, effectively copying the preoperative functional boundaries onto the intraoperative resection plan despite brain shifting and deformation.
2Measurement precision
If invasive techniques like ECoG with implanted electrodes are used to precisely delineate boundaries, then accurate identification is achieved, but the risks of hemorrhage, infection and cerebral edema increase
Solution Approach 1:
The patent employs non-invasive or minimally invasive imaging techniques that avoid the need for long-term electrode implantation. By using techniques such as fMRI, PET, or SPECT for functional mapping, the method eliminates the need for permanent foreign bodies in the brain, thereby avoiding the serious complications associated with electrode implantation while still achieving the goal of precise functional boundary identification.
3Reliability
If intraoperative MRI or fMRI is used to enable maximum extent of resection, then favorable seizure-reduction outcomes are achieved, but the infrastructure requirements and costs are extremely high
Solution Approach 1:
The patent performs comprehensive functional mapping and epileptogenic area identification using preoperative non-invasive imaging modalities (fMRI, PET, SPECT) before the patient enters the operating room. This pre-acquired functional information is then integrated with intraoperative findings to guide resection, eliminating the need for expensive intraoperative MRI or fMRI equipment while achieving comparable surgical outcomes.
Solution Approach 2:
The patent creates a preoperative functional map that serves as a reference for intraoperative resection planning. By copying the functional boundaries identified in preoperative imaging onto the surgical resection plan, the method achieves accurate resection guidance without requiring the presence of expensive intraoperative imaging equipment in the operating room.
4Adaptability or versatility
If ifMRI functional mapping is used to locate eloquent cortex, then resection near eloquent areas can be performed, but the accuracy is compromised by reliance on hemodynamic response functions
Solution Approach 1:
The patent employs multiple different imaging modalities (fMRI, PET, SPECT) with different physiological parameters and mechanisms to map functional areas. By comparing results across modalities that measure different aspects of brain function (hemodynamic response, metabolic activity, blood flow), the method cross-validates functional boundaries and reduces reliance on any single parameter or assumption, thereby improving the accuracy of eloquent cortex localization.
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 improves the accuracy of identifying epileptogenic cortex intraoperatively, enhancing surgical planning and outcomes by providing a non-invasive, cost-effective means to differentiate epileptogenic from eloquent areas without the need for high-infrastructure imaging, thus improving seizure reduction outcomes and reducing neurological deficits.
Implementation Method 1
capturing images of a surface of the brain within a wavelength range of 300 nm to 800 nm
Implementation Method 2
analyzing images within a wavelength range of about 400 nm to about 595 nm for cerebral blood volume and about 640 to 750 nm for blood oxygenation
Implementation Method 3
employing dichroic mirrors or bandpass filters to separate relevant wavelengths
Data Source
AI summary
Methods and systems that detect and differentiate epileptogenic from eloquent and normal cortices are provided. A method for identifying epileptogenic cortices in a brain may include detecting areas in the brain that are undergoing cerebral blood volume low frequency oscillations, detecting areas in the brain that are undergoing blood oxygenation low frequency oscillations; mapping clusters of the brain in which the cerebral blood volume low frequency oscillations are negatively correlated with the blood oxygenation low frequency oscillations, and analyzing the time based relationship between the clusters of the brain that are undergoing negatively correlated low frequency oscillations to determine cause areas, which are areas of the brain that are causing negatively correlated low frequency oscillations to occur elsewhere.