Dataset Information

A general framework for optimizing arterial spin labeling MRI experiments.

ABSTRACT:

Purpose

Arterial spin labeling (ASL) MRI is a non-invasive perfusion imaging technique that is inherently SNR limited, so scan protocols ideally need to be rigorously optimized to provide the most accurate measurements. A general framework is presented for optimizing ASL experiments to achieve optimal accuracy for perfusion estimates and, if required, other hemodynamic parameters, within a fixed scan time. The effectiveness of this framework is then demonstrated by optimizing the post-labeling delays (PLDs) of a multi-PLD pseudo-continuous ASL experiment and validating the improvement using simulations and in vivo data.

Theory and methods

A simple framework is proposed based on the use of the Cramér-Rao lower bound to find the protocol design which minimizes the predicted parameter estimation errors. Protocols were optimized for cerebral blood flow (CBF) accuracy or both CBF and arterial transit time (ATT) accuracy and compared to a conventional multi-PLD protocol, with evenly spaced PLDs, and a single-PLD protocol, using simulations and in vivo experiments in healthy volunteers.

Results

Simulations and in vivo data agreed extremely well with the predicted performance of all protocols. For the in vivo experiments, optimizing for just CBF resulted in a 48% and 15% decrease in CBF errors, relative to the reference multi-PLD and single-PLD protocols, respectively. Optimizing for both CBF and ATT reduced CBF errors by 37%, without a reduction in ATT accuracy, relative to the reference multi-PLD protocol.

Conclusion

The presented framework can effectively design ASL experiments to minimize measurement errors based on the requirements of the scan.

SUBMITTER: Woods JG

PROVIDER: S-EPMC6492260 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Publications

A general framework for optimizing arterial spin labeling MRI experiments.

Woods Joseph G JG Chappell Michael A MA Okell Thomas W TW

Magnetic resonance in medicine 20181226 4

<h4>Purpose</h4>Arterial spin labeling (ASL) MRI is a non-invasive perfusion imaging technique that is inherently SNR limited, so scan protocols ideally need to be rigorously optimized to provide the most accurate measurements. A general framework is presented for optimizing ASL experiments to achieve optimal accuracy for perfusion estimates and, if required, other hemodynamic parameters, within a fixed scan time. The effectiveness of this framework is then demonstrated by optimizing the post-la ...[more]

PMID: 30588656

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Project description:BackgroundNoninvasive measurement of placental blood flow is the major technical challenge for predicting ischemic placenta (IPD). Pseudocontinuous arterial spin labeling (pCASL) MRI was recently shown to be promising, but the potential value in predicting the subsequence development of IPD is not known.PurposeTo derive global and regional placental blood flow parameters from longitudinal measurements of pCASL MRI and to assess the associations between perfusion-related parameters and IPD.Study typeProspective.PopulationEighty-four women completed two pCASL MRI scans (first; 14-18 weeks and second; 19-24 weeks) from prospectively recruited 118 subjects. A total of 69 subjects were included for the analysis, of which 15 subjects developed IPD.Field strength/sequence3T/T2 -weighted half-Fourier single-shot turbo spin-echo (HASTE) and pCASL.AssessmentFour perfusion-related parameters in the placenta were derived: placenta volume, placental blood flow (PBF), high PBF (hPBF), and relative hPBF. The longitudinal changes of the parameters and their association with IPD were tested after being normalizing to the 16th and 20th weeks of gestation.Statistical testsComparisons between two gestational ages within subjects were performed using the paired Wilcoxon tests, and comparisons between normal and IPD groups were performed using the unpaired Wilcoxon tests.ResultsThe difference between the first and second MRI scans was statistically significant for volume (156.6 cm3 vs. 269.7 cm3 , P < 0.001) and PBF (104.9 ml/100g/min vs. 111.3 ml/100g/min, P = 0.02) for normal subjects, indicating an increase in pregnancy with advancing gestation. Of the parameters tested, the difference between the normal and IPD subjects was most pronounced in hPBF (278.1 ml/100g/min vs. 180.7 ml/100g/min, P < 0.001) and relative hPBF (259.1% vs. 183.2%, P < 0.001) at 16 weeks.Data conclusionThe high perfusion-related image parameters for IPD were significantly decreased from normal pregnancy at 14-18 weeks of gestation.Level of evidence2 TECHNICAL EFFICACY STAGE: 1 J. Magn. Reson. Imaging 2020;51:1247-1257.

Project description:PurposeA model-based reconstruction framework is proposed for motion-corrected and high-resolution anatomically assisted (MOCHA) reconstruction of arterial spin labeling (ASL) data. In this framework, all low-resolution ASL control-label pairs are used to reconstruct a single high-resolution cerebral blood flow (CBF) map, corrected for rigid-motion, point-spread-function blurring and partial volume effect.MethodsSix volunteers were recruited for CBF imaging using pseudo-continuous ASL labeling, two-shot 3D gradient and spin-echo sequences and high-resolution T1 -weighted MRI. For 2 volunteers, high-resolution scans with double and triple resolution in the partition direction were additionally collected. Simulations were designed for evaluations against a high-resolution ground-truth CBF map, including a simulated hyperperfused lesion and hyperperfusion/hypoperfusion abnormalities. The MOCHA technique was compared with standard reconstruction and a 3D linear regression partial-volume effect correction method and was further evaluated for acquisitions with reduced control-label pairs and k-space undersampling.ResultsThe MOCHA reconstructions of low-resolution ASL data showed enhanced image quality, particularly in the partition direction. In simulations, both MOCHA and 3D linear regression provided more accurate CBF maps than the standard reconstruction; however, MOCHA resulted in the lowest errors and well delineated the abnormalities. The MOCHA reconstruction of standard-resolution in vivo data showed good agreement with higher-resolution scans requiring 4-times and 9-times longer acquisitions. The MOCHA reconstruction was found to be robust for 4-times-accelerated ASL acquisitions, achieved by reduced control-label pairs or k-space undersampling.ConclusionThe MOCHA reconstruction reduces partial-volume effect by direct reconstruction of CBF maps in the high-resolution space of the corresponding anatomical image, incorporating motion correction and point spread function modeling. Following further evaluation, MOCHA should promote the clinical application of ASL.

Dataset Information

A general framework for optimizing arterial spin labeling MRI experiments.

Purpose

Theory and methods

Results

Conclusion

Publications

A general framework for optimizing arterial spin labeling MRI experiments.

Similar Datasets

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