Quantitative MRI Brain Volume Estimation

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Solution Overview

Problem

Current methods for obtaining clinical brain measures such as brain parenchymal volume, intracranial volume, and brain parenchymal fraction from MRI images are time-consuming, imprecise, and require frequent re-optimization due to variations in MR scanner settings and image imperfections.

Innovation Solution

An automated method using quantitative MRI to estimate these measures by measuring and selecting tissues based on absolute physical properties like R1, R2 relaxation rates, and proton density, employing region growing algorithms and thresholding to generate accurate and objective volume calculations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual methods are used to obtain brain volume measures, then measurement precision can be improved, but time consumption increases significantly

Engineering Contradiction:

Improvemeasurement precisionVSAvoidtime consumption

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs automated segmentation and volume calculation without requiring manual intervention. The algorithm automatically identifies brain tissue, excludes non-brain tissues, and calculates volumes based on quantitative MRI parameters, making the system self-sufficient and eliminating time-consuming manual procedures while maintaining precision.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical measurement methods with automated computer-based quantitative MRI analysis. By using algorithmic processing of quantitative MRI data (R1, R2, PD values) rather than manual visual assessment, the system achieves both high precision and automation, resolving the time-precision tradeoff.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Extent of automation

If ad-hoc filtering and empirical image intensity thresholding are used, then object recognition can be generated directly from MR images, but reliability decreases due to scanner setting variations

Engineering Contradiction:

ImproveautomationVSAvoidreliability

Core Design Contradiction:

Extent of automationVSReliability

Solution Approach 1:

The system transitions from using image intensity parameters (which are scanner-dependent) to using quantitative MRI parameters (R1, R2, PD) that represent absolute tissue properties. This parameter transformation makes the segmentation reliable across different scanner settings and acquisition protocols, as these physical parameters are intrinsic to the tissue regardless of imaging conditions.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent introduces quantitative MRI parameters as an intermediary between the raw MR images and the tissue segmentation. Instead of directly thresholding image intensities (which are unreliable), the system uses quantitative parameters as an intermediate representation that captures true tissue properties, thereby improving reliability while maintaining automation.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Productivity

If image intensity thresholding is used for tissue segmentation, then processing speed increases, but measurement precision decreases due to sensitivity to scanner settings

Engineering Contradiction:

Improveprocessing speedVSAvoidmeasurement precision

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system changes from using image intensity parameters to quantitative MRI parameters (R1, R2, PD) for tissue segmentation. This parameter transformation maintains the speed of automated processing while significantly improving precision, as quantitative parameters are intrinsic tissue properties that do not vary with scanner settings or acquisition protocols.

Inventive Principle:

Principle #35Parameter changes

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

Provides objective and user-independent measurements of brain volumes, reducing the need for manual adjustments and improving precision by utilizing absolute tissue properties, independent of scanner settings.

Implementation Method 1

The realignment of proton spins with the magnetic field is termed longitudinal relaxation and the time (typically about 1 sec) required for a certain percentage of the tissue nuclei to realign is termed 'Time 1' or T1

Methodology Applied

Scientific EffectLongitudinal relaxation:

Implementation Method 2

T2-weighted imaging relies upon local dephasing of spins following the application of the transverse energy pulse; the transverse relaxation time (typically about 0.1 sec) is termed 'Time 2' or T2

Methodology Applied

Scientific EffectTransverse relaxation:

Data Source

PatentUS8873822B2Methods and apparatus for estimating clinical measures

Publication Date: 2014.10.28 SYNTHETICMR AB PUBL

AI summary

In a magnetic resonance imaging display system, the brain parenchymal fraction, a clinical measure for brain atrophy, is found by selection of white matter, grey matter, and/or cerebrospinal fluid based on quantitative magnetic resonance properties.