MB EPI Slice Ordering for ASL Perfusion Imaging

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Solution Overview

Problem

In multi-band echo planar imaging (MB EPI) with pseudo-continuous arterial spin labeling (PCASL), sequential ascending slice acquisition order leads to significant relative static tissue signal differences between neighboring slices, causing severe subtraction errors and artifacts, especially with background suppression and subject motion, which are difficult to correct.

Innovation Solution

Implementing alternative slice acquisition orders such as peripheral-to-central or central-to-peripheral ordering during MB EPI acquisition, where odd or even numbered slices are acquired first, followed by ascending or descending order, to minimize static tissue signal differences and reduce motion-associated errors.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If sequential ascending slice acquisition order is used in MB EPI PCASL imaging with background suppression, then the acquisition process is simple and systematic, but relative static tissue signal differences between neighboring slices become dramatically larger, causing severe subtraction errors and artifacts

Engineering Contradiction:
Improveslice acquisition process simplicityVSAvoidsubtraction error magnitude
Core Design Contradiction:
Ease of operationVSManufacturing precision

Solution Approach 1:

The patent applies inversion by reversing the conventional sequential ascending slice acquisition order. Instead of acquiring slices from inferior to superior in sequence, the method uses alternative ordering patterns such as alternating odd-even slice acquisition or interleaved slice bands. This inversion of the acquisition sequence equalizes the timing differences between neighboring slices, thereby minimizing static tissue signal differences and reducing subtraction errors in the final perfusion images.

Inventive Principle:
Principle #13The other way round (Inversion)

2Ease of manufacture

If sequential ascending slice acquisition order is used, then the acquisition protocol is straightforward to implement, but motion-associated subtraction errors cannot be corrected through motion correction

Engineering Contradiction:
Improveacquisition protocol implementationVSAvoidmotion correction effectiveness
Core Design Contradiction:
Ease of manufactureVSReliability

Solution Approach 1:

The patent applies preliminary action by pre-planning and implementing alternative slice acquisition ordering before the actual imaging process. The alternating odd-even or interleaved slice band patterns are predetermined and executed during data acquisition. This preliminary structuring of the acquisition sequence ensures that static tissue signals remain consistent across slices despite subject motion, making the imaging inherently more robust to motion artifacts before any post-processing correction is attempted.

Inventive Principle:
Principle #10Preliminary action

3Stability of the object's composition

If background suppression is applied to improve high-resolution MB EPI PCASL imaging, then temporal stability of perfusion signal is improved, but relative static tissue signal differences between neighboring slices increase dramatically

Engineering Contradiction:
Improveperfusion signal temporal stabilityVSAvoidstatic tissue signal difference magnitude
Core Design Contradiction:
Stability of the object's compositionVSManufacturing precision

Solution Approach 1:

The patent applies local quality by implementing slice-specific acquisition timing patterns. Instead of treating all slices uniformly, the alternating odd-even or interleaved slice band methods assign different acquisition sequences to different slice groups. This localized differentiation in acquisition timing ensures that each slice is acquired at optimally spaced intervals, maintaining consistent static tissue signals locally across neighboring slices while preserving the global background suppression benefits for temporal stability.

Inventive Principle:
Principle #3Local quality

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 significantly reduces motion-associated subtraction errors and artifacts, enhancing the robustness of MB EPI PCASL imaging with background suppression by minimizing relative static tissue signal differences between neighboring slices, resulting in more accurate cerebral blood flow measurements.

Implementation Method 1

Arterial spin labeling (ASL) is a non-contrast enhanced perfusion imaging method performed with magnetic resonance imaging (MRI) scanners

Methodology Applied
Scientific EffectArterial spin labeling: Magnetic Field

Implementation Method 2

background suppression (BS) of the static tissue using combined pre-saturation and inversion RF pulses

Methodology Applied
Scientific EffectBackground suppression: Magnetic Field

Data Source

PatentUS11965950B2Slice ordering for MB-EPI ASL imaging
Publication Date: 2024.04.23 SIEMENS HEALTHINEERS AG
  • US11965950B2 patent drawing
  • US11965950B2 patent drawing
  • US11965950B2 patent drawing

AI summary

A method for generating a perfusion weighted image using arterial spin labeling (ASL) with segmented acquisitions includes dividing an anatomical area of interest into a plurality of slices and performing a multi-band (MB) echo planar imaging (EPI) acquisition process using a magnetic resonance imaging (MRI) system to acquire a control image dataset representative of the plurality of slices using a central-to-peripheral or peripheral-to-central slice acquisition order. An ASL preparation process is performed using the MRI system to magnetically label protons in arterial blood water in an area upstream from the anatomical area of interest. Following a post-labeling delay time period, the MB EPI acquisition process is performed to a labeled image dataset corresponding to the slices using the central-to-peripheral or peripheral-to-central slice acquisition order. A perfusion weighted image of the anatomical area is generated by subtracting the labeled image dataset from the control image dataset.