Quantitative Time-of-Flight Head Magnetic Resonance Angiography of Cerebrovascular Disease.

BACKGROUND: Standard Cartesian time-of-flight (TOF) head magnetic resonance angiography (MRA) is routinely used to evaluate the intracranial arteries, but does not provide quantitative hemodynamic information that is useful for patient risk stratification as well as for monitoring treatment and tracking changes in blood flow over time. Quantitative TOF (qTOF) MRA represents a new and efficient method for simultaneous evaluating the intracranial arteries and quantifying blood flow velocity, but it has not yet been evaluated in patients with cerebrovascular disease. PURPOSE: To evaluate qTOF for simultaneously evaluating the intracranial arteries and quantifying intracranial blood flow velocity in patients with cerebrovascular disease, without the need for a phase contrast (PC) scan. STUDY TYPE: Prospective. SUBJECTS: Twenty-four patients (18 female, 6 male) with cerebrovascular disease. FIELD STRENGTH/SEQUENCES: Head MRA at 3 T using gradient-echo 3D qTOF, standard Cartesian TOF, and PC protocols. ASSESSMENT: Three independent readers assessed arterial image quality using a 4-point scale (1: non-diagnostic, 4: excellent) and artifact presence. Total and component flow velocities obtained with qTOF and PC were measured. STATISTICAL TESTS: Wilcoxon signed-rank tests, Gwet's AC2, intraclass correlation coefficients (ICC) for absolute agreement, Bland-Altman analyses, tests of equal proportions. P values <0.05 were considered statistically significant. RESULTS: Averaged across readers and compared to standard Cartesian TOF, qTOF significantly improved overall arterial image quality (3.8 ± 0.2 vs. 3.6 ± 0.5), image quality at locations of pathology (3.7 ± 0.5 vs. 3.4 ± 0.7), and increased the proportion of evaluations rated without artifacts (63.9% [46/72] vs. 37.5% [27/72]). qTOF significantly agreed with PC for total flow velocity (ICC = 0.71) and component flow velocity (ICC = 0.89). DATA CONCLUSION: qTOF angiography of the head matched or improved upon the image quality of standard Cartesian TOF, reduced image artifacts, and provided quantitative hemodynamic data, without the need for a PC scan. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

High spatial resolution whole-neck MR angiography using thin-slab stack-of-stars quiescent interval slice-selective acquisition.

PURPOSE: To report a 3D multi-echo thin-slab stack-of-stars (tsSOS) quiescent-interval slice-selective (QISS) strategy for high-resolution magnetic resonance angiography (MRA) of the entire neck in under seven minutes. METHODS: The neck arteries of eight subjects were imaged at 3 Tesla. Multi-echo 3D tsSOS QISS using a FLASH readout was compared with 3D tsSOS FLASH, 2D QISS, 2D TOF, and 3D TOF. A root-mean-square (RMS) combination of echo time images was tested. Evaluation metrics included arterial signal-to-noise ratio (SNR), arterial-to-muscle contrast-to-noise ratio (CNR), and image quality. RESULTS: 3D multi-echo tsSOS QISS using a RMS combination of echo time images increased SNR and CNR by 60% and 63% with respect to the reconstruction obtained with the shortest echo time. 3D tsSOS QISS showed superior CNR with respect to 3D tsSOS FLASH imaging, and more than 3-fold higher SNR and CNR with respect to 2D radial QISS when normalized for voxel size. 3D tsSOS QISS provided good to excellent image quality that exceeded the image quality of 2D QISS, 2D TOF, and 3D TOF (P < .05). CONCLUSION: Whole-neck high-resolution nonenhanced MRA is feasible using 3D tsSOS QISS, and produced image quality that exceeded those of competing nonenhanced MRA protocols at 3 Tesla.

Feasibility of a sub-3-minute imaging strategy for ungated quiescent interval slice-selective MRA of the extracranial carotid arteries using radial k-space sampling and deep learning-based image processing.

PURPOSE: To develop and test the feasibility of a sub-3-minute imaging strategy for non-contrast evaluation of the extracranial carotid arteries using ungated quiescent interval slice-selective (QISS) MRA, combining single-shot radial sampling with deep neural network-based image processing to optimize image quality. METHODS: The extracranial carotid arteries of 12 human subjects were imaged at 3 T using ungated QISS MRA. In 7 healthy volunteers, the effects of radial and Cartesian k-space sampling, single-shot and multishot image acquisition (1.1-3.3 seconds/slice, 141-423 seconds/volume), and deep learning-based image processing were evaluated using segmental image quality scoring, arterial temporal SNR, arterial-to-background contrast and apparent contrast-to-noise ratio, and structural similarity index. Comparison of deep learning-based image processing was made with block matching and 3D filtering denoising. RESULTS: Compared with Cartesian sampling, radial k-space sampling increased arterial temporal SNR 107% (P < .001) and improved image quality during 1-shot imaging (P < .05). The carotid arteries were depicted with similar image quality on the rapid 1-shot and much lengthier 3-shot radial QISS protocols (P = not significant), which was corroborated in patient studies. Deep learning-based image processing outperformed block matching and 3D filtering denoising in terms of structural similarity index (P < .001). Compared with original QISS source images, deep learning image processing provided 24% and 195% increases in arterial-to-background contrast (P < .001) and apparent contrast-to-noise ratio (P < .001), and provided source images that were preferred by radiologists (P < .001). CONCLUSION: Rapid, sub-3-minute evaluation of the extracranial carotid arteries is feasible with ungated single-shot radial QISS, and benefits from the use of deep learning-based image processing to enhance source image quality.