Periodic Deoxyhemoglobin MRI for Voxel-Wise Perfusion Mapping
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Solution Overview
Problem
Existing perfusion MRI methods using the default mode network (DMN) for identifying vascular pathologies are limited by the complexity of DMN patterns and lack of understanding of vasculature in non-DMN voxels, leading to uncertain analysis and limited knowledge of brain function.
Innovation Solution
Implementing a periodic deoxyhemoglobin (dOHb) signal using a sequential gas delivery device to target arterial oxygen partial pressures (PaO2) in a sinusoidal pattern, combined with magnetic resonance imaging (MRI) to measure BOLD signals and compute perfusion metrics, allowing for voxel-wise characterization of vascular tissues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex DMN pattern analysis is used to identify vascular pathologies, then vascular pathology identification is possible, but measurement precision and analysis reliability are limited due to complexity and lack of understanding of vasculature in non-DMN voxels
Solution Approach 1:
The patent applies periodic action by using respiratory-induced periodic variations in deoxyhemoglobin concentration as the basis for perfusion measurement. Instead of analyzing complex spontaneous DMN patterns, the method uses the periodic breathing cycle to create predictable signal variations that can be systematically measured and quantified, thereby simplifying the analysis while improving measurement precision.
Solution Approach 2:
The patent utilizes parameter changes by monitoring the periodic variations in deoxyhemoglobin concentration that occur with the respiratory cycle. By tracking these parameter changes (signal intensity variations) rather than analyzing complex spatial patterns, the method achieves more reliable and precise perfusion measurements without requiring complex computational analysis.
2Measurement precision
If periodic PaO2 targeting is implemented using sequential gas delivery, then signal-to-noise ratio is optimized and vascular traits are precisely identified, but device complexity and operational complexity increase
Solution Approach 1:
The patent implements feedback by continuously monitoring the BOLD signal response to periodic PaO2 changes and using this information to verify that the expected vascular response is occurring. The feedback loop ensures that the periodic gas delivery is producing the anticipated signal variations, allowing for precise control and optimization of the measurement process while maintaining operational simplicity through automated closed-loop control.
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
Enhances the accuracy of vascular health assessment by optimizing signal-to-noise ratio and enabling precise identification of vascular traits through phase and period changes, improving the detection of conditions like arterial stenosis and neurodegenerative diseases.
Implementation Method 1
targeting a sequence of partial pressures of oxygen in arterial blood (PaO2) values in a subject using a sequential gas delivery device in a periodic input pattern
Implementation Method 2
measuring a blood-oxygen level dependent (BOLD) signal in a voxel of the subject's brain using a magnetic resonance imaging device
Implementation Method 3
When blood flow in a tissue increases beyond its metabolic requirements, the [dOHb] is reduced by virtue of being diluted by the 'excess' oxyhemoglobin. Thus, the changes in BOLD signal are surrogate markers of the degree of blood flow.
Implementation Method 4
convolving the periodic input pattern with a plurality of candidate slopes to generate a plurality of candidate output functions, each of the plurality of candidate slopes representing a proposed cerebral blood flow value derived from a hypothetical step change
Implementation Method 5
comparing the candidate output functions to the measured signal and, based on the comparison, selecting one of the candidate slopes
Data Source
AI summary
When a periodic deoxyhemoglobin signal is implemented in a subject, the blood flow in a selected voxel can be measured and compared to the input signal. Differences in phase lag reflect the degree of dispersion in the tissue. In conjunction with amplitude, phase lag can be used to distinguish veins from arteries, identify vessel orientation and identify changes in voxel cerebral blood flow or cerebral blood volume.