Motion‐corrected and high‐resolution anatomically assisted (MOCHA) reconstruction of arterial spin labeling MRI
Autor: | Colm J. McGinnity, Claudia Prieto, Enrico De Vita, Alexander Hammers, Abolfazl Mehranian, Andrew J. Reader, Radhouene Neji |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
Point spread function
reconstruction Computer science Image quality Full Papers—Imaging Methodology Partial volume High resolution 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Arterial Spin Labeling MRI Imaging Three-Dimensional Humans Radiology Nuclear Medicine and imaging partial‐volume correction Full Paper business.industry Brain Pattern recognition arterial spin labeling Magnetic Resonance Imaging Cerebral blood flow anatomical priors Undersampling Cerebrovascular Circulation Arterial spin labeling Spin Labels Artificial intelligence perfusion MRI business 030217 neurology & neurosurgery |
Zdroj: | Magnetic Resonance in Medicine |
ISSN: | 1522-2594 0740-3194 |
Popis: | Purpose A 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. Methods Six 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. Results The 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. Conclusion The 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. |
Databáze: | OpenAIRE |
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