Cerebral oxygen extraction fraction (OEF)： Comparison of challenge-free gradient echo QSM+qBOLD (QQ) with 15O PET in healthy 思维导图

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2023-09-23

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$Cerebral oxygen extraction fraction (OEF)： Comparison of challenge-free gradient echo QSM+qBOLD (QQ) with 15O PET in healthy$

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Abstract

目的

We aimed to validate oxygen extraction fraction (OEF) estimations by quantitative susceptibility mapping plus quantitative blood oxygen-level dependence (QSM+qBOLD, or QQ) using 15O-PET

PET was acquired using C[15O], O[15O], and H2[15O]

MRI included T1-weighted imaging, time-of-flight angiography, and multi-echo gradient-echo imaging that was processed for QQ

结论

Our validation study suggests that respiratory challenge-free QQ-OEF mapping may be useful for non-invasive clinical assessment of regional OEF impairment

Introduction

Regional oxygen extraction fraction (OEF) is an essential biomarker for investigating tissue vulnerability and function in various diseases such as stroke, cerebral tumors, and Alzheimer’s Disease

Positron emission tomography (PET) with 15O tracers is the reference standard for quantitative mapping of OEF

tracer kinetic modeling of 15O tracers

An image-derived arterial input function method was further introduced for 15O PET imaging using PET/MR

However, PET with 15O has not been widely used in clinical settings because 15O tracers with 122-second half-lives must be produced by a cyclotron within the PET facility. This has substantially limited 15O PET availability

In contrast, with widely available MR scanners, tissue cerebral oxygen consumption can be estimated by modeling conversion of diamagnetic oxyheme into paramagnetic deoxyheme in the vasculature.

OEF can be estimated from MRI signal magnitudes by methods such as T2-Relaxation-Under-Spin-Tagging (TRUST), quantitative BOLD (qBOLD), quantitative imaging of extraction of oxygen and tissue consumption (QUIXOTIC)

QQ estimates OEF maps from multi-echo gradient (mGRE) data alone. It does so without burdensome gas inhalation or respiratory-control procedures

The robustness of QQ OEF has been significantly improved by introduction of an unsupervised machine learning method, cluster analysis of time evolution, which may enable clinically practical use of the QQ OEF mapping method

the purpose of this study is to validate QQ OEF measurements as compared to reference standard 15O PET OEF measurements in healthy adults

Materials and methods

Data acquisition

Ten healthy subjects (8 females, age 43± 20 years) underwent MRI and PET

PET/MR system

Anatomical MRI images were first acquired

PET data was acquired with sequential administrations of C[15O], O[15O], H2[15O], C[15O], O[15O], and H2[15O]

During PET, MRI was acquired simultaneously

Data processing

QQ-OEF mapping from mGRE data

The QQ model estimates oxygen extraction fraction based on the venous deoxyheme-dependent signal in mGRE signal phase using QSM and signal magnitude using qBOLD

The QSM modeling considers that voxelwise susceptibility is the sum of three components: non-blood tissue susceptibility (χnb), the plasma susceptibility, and the hemoglobin susceptibility

The hemoglobin susceptibility is mainly determined by venous blood volume (v) and venous oxygenation (Y). For instance, the hemoglobin susceptibility increases as v increases and Y decreases

The qBOLD modeling distinguishes the mGRE magnitude signal decay into three contributions

The two inputs for QQ are voxel-wise susceptibility and mGRE magnitude signal

Based on the obtained susceptibility and mGRE magnitude, OEF was estimated using QQ

15O PET-OEF mapping

Using the tracer kinetic modeling with these TACs, CBF and CBV were estimated from the 15O-water scansand 15O-carbon monoxide scans, respectively. OEF was finally estimated from the 15O-oxygen scans in conjunction with calculated CBF and CBV images

ROI analysis

To compare QQ and PET, QQ- and PET-OEF maps were averaged over the two scans (scan-rescan)

Comparisons of OEF measures between QQ-OEF and PET-OEF were performed in the whole brain and regional ROIs: cortical gray matter (CGM), frontal, temporal, parietal, and occipital lobe of CGM, white matter (WM), and deep gray matter (DGM) regions (Thalamus, Caudate, Putamen, and Pallidum)

Results

Both PET and QQ show uniform OEF maps and good agreement between scans and methods

Bland-Altman plots comparing OEF values in whole brain between PET and QQ scans

OEF comparison in cortical gray matters (a–e), white matter (f), and deep gray matters (g–j) among PET and QQ average → PET and QQ provided similar regional OEF values

Bland-Altman plots comparing OEF values in regional ROIs between PET and QQ scans

Discussion

the QQ method provides similar OEF values both globally and regionally when compared to 15O PET

QQ-OEF mapping may be particularly valuable for more widespread and repeated evaluation of cerebral oxygen deficiency causing brain tissue vulnerability or injury in various brain disorders, such as ischemic stroke, Alzheimer’s disease (AD), and multiple sclerosis

子主题 3

Region of interest (ROI) analyses compared PET OEF and QQ OEF. In ROI analyses, the averaged OEF differences between PET and QQ were generally small and statistically insignificant思维导图模板大纲

OEF can be estimated by the combined model of QSM + qBOLD (QQ)思维导图模板大纲

Paired t-tests estimated significant differences between QQ-OEF and PET-OEF思维导图模板大纲

QQ音乐功能结构图思维导图