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High-resolution post-contrast T1-weighted imaging is a workhorse sequence in the evaluation of neurological disorders. The T1-MPRAGE sequence has been widely adopted for the visualization of enhancing pathology in the brain. However, this three-dimensional (3D) acquisition is lengthy and prone to motion artifact, which often compromises diagnostic quality. The goal of this study was to compare a highly accelerated wave-controlled aliasing in parallel imaging (CAIPI) post-contrast 3D T1-MPRAGE sequence (Wave-T1-MPRAGE) with the standard 3D T1-MPRAGE sequence for visualizing enhancing lesions in brain imaging at 3 T.This study included 80 patients undergoing contrast-enhanced brain MRI. The participants were scanned with a standard post-contrast T1-MPRAGE sequence (acceleration factor [R] = 2 using GRAPPA parallel imaging technique, acquisition time [TA] = 5 min 18 s) and a prototype post-contrast Wave-T1-MPRAGE sequence (R = 4, TA = 2 min 32 s). Two neuroradiologists performed a head-to-head evaluation of both sequences and rated the visualization of enhancement, sharpness, noise, motion artifacts, and overall diagnostic quality. A 15% noninferiority margin was used to test whether post-contrast Wave-T1-MPRAGE was noninferior to standard T1-MPRAGE. Inter-rater and intra-rater agreement were calculated. Quantitative assessment of CNR/SNR was performed.Wave-T1-MPRAGE was noninferior to standard T1-MPRAGE for delineating enhancing lesions with unanimous agreement in all cases between raters. Wave-T1-MPRAGE was noninferior in the perception of noise (p0.001), motion artifact (p0.001), and overall diagnostic quality (p0.001).High-accelerated post-contrast Wave-T1-MPRAGE enabled a two-fold reduction in acquisition time compared to the standard sequence with comparable performance for visualization of enhancing pathology and equivalent perception of noise, motion artifacts and overall diagnostic quality without loss of clinically important information.• Post-contrast wave-controlled aliasing in parallel imaging (CAIPI) T1-MPRAGE accelerated the acquisition of three-dimensional (3D) high-resolution post-contrast images by more than two-fold. • Post-contrast Wave-T1-MPRAGE was noninferior to standard T1-MPRAGE with unanimous agreement between reviewers (100% in 80 cases) for the visualization of intracranial enhancing lesions. • Wave-T1-MPRAGE was equivalent to the standard sequence in the perception of noise in 94% (75 of 80) of cases and was preferred in 16% (13 of 80) of cases for decreased motion artifact.

To evaluate the impact of magnetization transfer (MT) on brain tissue contrast in turbo-spin-echo (TSE) and EPI fluid-attenuated inversion recovery (FLAIR) images, and to optimize an MT-prepared EPI FLAIR pulse sequence to match the tissue contrast of a clinical reference TSE FLAIR protocol.Five healthy volunteers underwent 3T brain MRI, including single slice TSE FLAIR, multi-slice TSE FLAIR, EPI FLAIR without MT-preparation, and MT-prepared EPI FLAIR with variations of the MT-preparation parameters, including number of preparation pulses, pulse amplitude, and resonance offset. Automated co-registration and gray matter (GM) versus white matter (WM) segmentation was performed using a T1-MPRAGE acquisition, and the GM versus WM signal intensity ratio (contrast ratio) was calculated for each FLAIR acquisition.Without MT preparation, EPI FLAIR showed poor tissue contrast (contrast ratio = 0.98), as did single slice TSE FLAIR. Multi-slice TSE FLAIR provided high tissue contrast (contrast ratio = 1.14). MT-prepared EPI FLAIR closely approximated the contrast of the multi-slice TSE FLAIR images for two combinations of the MT-preparation parameters (contrast ratio = 1.14). Optimized MT-prepared EPI FLAIR provided a 50% reduction in scan time compared to the reference TSE FLAIR acquisition.Optimized MT-prepared EPI FLAIR provides comparable brain tissue contrast to the multi-slice TSE FLAIR images used in clinical practice.

Acute ischemic stroke can be subtle to detect on non-contrast computed tomography imaging. We show that a novel artificial intelligence model significantly improves the performance of physicians, including ED physicians, neurologists and radiologists, in identifying and quantifying the volume of acute ischemic stroke lesions. This model may lead to improved clinical decision-making for stroke patients.

We introduce and validate an artificial intelligence (AI)-accelerated multi-shot echo-planar imaging (msEPI)-based method that provides T1w, T2w,The rapid imaging technique combines a novel machine learning (ML) scheme to limit g-factor noise amplification and improve SNR, a magnetization transfer preparation module to provide clinically desirable contrast, and high per-shot EPI undersampling factors to reduce distortion. The ML training and image reconstruction incorporates a tunable parameter for controlling the level of denoising/smoothness. The performance of the reconstruction method is evaluated across various acceleration factors, contrasts, and SNR conditions. The 2-minute protocol is directly compared to a 10-minute clinical reference protocol through deployment in a clinical setting, where five representative cases with pathology are examined.Optimization of custom msEPI sequences and protocols was performed to balance acquisition efficiency and image quality compared to the five-fold longer clinical reference. Training data from 16 healthy subjects across multiple contrasts and orientations were used to produce ML networks at various acceleration levels. The flexibility of the ML reconstruction was demonstrated across SNR levels, and an optimized regularization was determined through radiological review. Network generalization toward novel pathology, unobserved during training, was illustrated in five clinical case studies with clinical reference images provided for comparison.The rapid 2-minute msEPI-based protocol with tunable ML reconstruction allows for advantageous trade-offs between acquisition speed, SNR, and tissue contrast when compared to the five-fold slower standard clinical reference exam.

Fast magnetic resonance imaging (MRI) sequences are advantageous in pediatric imaging as they can lessen child discomfort, decrease motion artifact and improve scanner availability. To evaluate the feasibility of an ultrafast wave-CAIPI (controlled aliasing in parallel imaging) MP-RAGE (magnetization-prepared rapid gradient echo) sequence for brain imaging of awake pediatric patients. Each MRI included a standard MP-RAGE sequence and an ultrafast wave-MP-RAGE sequence. Two neuroradiologists evaluated both sequences in terms of artifacts, noise, anatomical contrast and pathological contrast. A predefined 5-point scale was used by two independent pediatric neuroradiologists. A Wilcoxon signed-rank test was used to evaluate the difference between sequences for each variable. Twenty-four patients (14 males; mean age: 11.5±4.5 years, range: 1 month to 17.8 years) were included. Wave-CAIPI MP-RAGE provided a 77% reduction in scan time using a 32-channel coil and a 70% reduction using a 20-channel coil. Visualization of the pathology, artifacts and pathological enhancement (including parenchymal, leptomeningeal and dural enhancement) was not significantly different between standard MP-RAGE and wave-CAIPI MP-RAGE (all P>0.05). For central (P

BACKGROUND. Anesthetic exposure in children may impact long-term neurocognitive outcomes. Therefore, minimizing pediatric MRI scan time in children under anesthesia and the associated anesthetic exposure is necessary. OBJECTIVE. The purpose of this study was to evaluate pediatric MRI scan time as a predictor of total propofol dose, considering imaging and clinical characteristics as covariates. METHODS. Electronic health records were retrospectively searched to identify MRI examinations performed from 2016 to 2019 in patients 0-18 years old who received propofol anesthetic. Brain; brain and spine; brain and abdomen; and brain, head, and neck MRI examinations were included. Demographic, clinical, and imaging data were extracted for each examination, including anesthesia maintenance phase time, MRI scan time, and normalized propofol dose. MRI scan time and propofol dose were compared between groups using a t test. A multiple linear regression with backward selection (threshold, p < .05) was used to evaluate MRI scan time as a predictor of total propofol dose, adjusting for sex, age, time between scan and study end, body part, American Society of Anesthesiologists (ASA) classification, diagnosis, magnet strength, and IV contrast medium administration as covariates. RESULTS. A total of 501 examinations performed in 426 patients (172 girls, 254 boys; mean age, 6.55 ± 4.59 [SD] years) were included. Single body part examinations were shorter than multiple body part examinations (mean, 52.7 ± 18.4 vs 89.3 ± 26.4 minutes) and required less propofol (mean, 17.7 ± 5.7 vs 26.1 ± 7.7 mg/kg; all p < .001). Among single body part examinations, a higher ASA classification, oncologic diagnosis, 1.5-T magnet, and IV contrast medium administration were associated with longer MRI scan times (all p ≤ .009) and higher propofol exposure (all p ≤ .005). In multivariable analysis, greater propofol exposure was predicted by MRI scan time (mean dose per minute of examination, 0.178 mg/kg; 95% CI, 0.155-0.200; p < .001), multiple body part examination (p = .04), and IV contrast medium administration (p = .048); lower exposure was predicted by 3-T magnet (p = .04). CONCLUSION. Anesthetic exposure during pediatric MRI can be quantified and predicted based on imaging and clinical variables. CLINICAL IMPACT. This study serves as a valuable baseline for future efforts to reduce anesthetic doses and scan times in pediatric MRI.

Background Prediction of early progression in glioblastoma may provide an opportunity to personalize treatment. Simplified intravoxel incoherent motion (IVIM) MRI offers quantitative estimates of diffusion and perfusion metrics. We investigated whether these metrics, during chemoradiation, could predict treatment outcome. Methods 38 patients with newly diagnosed IDH-wildtype glioblastoma undergoing 6-week/30-fraction chemoradiation had standardized post-operative MRIs at baseline (radiation planning), and at the 10th and 20th fractions. Non-overlapping T1-enhancing (T1C) and non-enhancing T2-FLAIR hyperintense regions were independently segmented. Apparent diffusion coefficient (ADCT1C, ADCT2-FLAIR) and perfusion fraction (fT1C, fT2-FLAIR) maps were generated with simplified IVIM modelling. Parameters associated with progression before or after 6.9 months (early vs late progression, respectively), overall survival (OS) and progression-free survival (PFS) were investigated. Results Higher ADCT2-FLAIR at baseline [Odds Ratio (OR) = 1.06, 95% CI 1.01–1.15, p = 0.025], lower fT2-FLAIR at fraction 10 (OR = 2.11, 95% CI 1.04–4.27, p = 0.018), and lack of increase in ADCT2-FLAIR at fraction 20 compared to baseline (OR = 1.12, 95% CI 1.02–1.22, p = 0.02) were associated with early progression. Combining ADCT2-FLAIR at baseline, fT2-FLAIR at fraction 10, ECOG and MGMT promoter methylation status significantly improved AUC to 90.3% compared to a model with only ECOG and MGMT promoter methylation status (p = 0.001). Using multivariable analysis, neither IVIM metrics were associated with OS but higher fT2-FLAIR at fraction 10 (HR = 0.72, 95% CI 0.56–0.95, p = 0.018) was associated with longer PFS. Conclusion ADCT2-FLAIR at baseline, its lack of increase from baseline to fraction 20, or fT2-FLAIR at fraction 10 significantly predicted early progression. fT2-FLAIR at fraction 10 was associated with PFS.

Clinical risk prediction requires comprehensive integration of clinical information and concurrent radiological findings. We present an upgraded chest radiograph (CXR) explainable artificial intelligence (xAI) model, which was trained on 241,723 well-annotated CXRs obtained prior to the onset of the COVID-19 pandemic. Mean area under the receiver operating characteristic curve (AUROC) for detection of 20 radiographic features was 0.955 (95% CI 0.938-0.955) on PA view and 0.909 (95% CI 0.890-0.925) on AP view. Coexistent and correlated radiographic findings are displayed in an interpretation table, and calibrated classifier confidence is displayed on an AI scoreboard. Retrieval of similar feature patches and comparable CXRs from a Model-Derived Atlas provides justification for model predictions. To demonstrate the feasibility of a fine-tuning approach for efficient and scalable development of xAI risk prediction models, we applied our CXR xAI model, in combination with clinical information, to predict oxygen requirement in COVID-19 patients. Prediction accuracy for high flow oxygen (HFO) and mechanical ventilation (MV) was 0.953 and 0.934 at 24 hours and 0.932 and 0.836 at 72 hours from the time of emergency department (ED) admission, respectively. Our CXR xAI model is auditable and captures key pathophysiological manifestations of cardiorespiratory diseases and cardiothoracic comorbidities. This model can be efficiently and broadly applied via a fine-tuning approach to provide fully automated risk and outcome predictions in various clinical scenarios in real-world practice.

The goal of this study is to leverage an advanced fast imaging technique, wave-controlled aliasing in parallel imaging (Wave-CAIPI), and a generative adversarial network (GAN) for denoising to achieve accelerated high-quality high-signal-to-noise-ratio (SNR) volumetric magnetic resonance imaging (MRI).Three-dimensional (3D) THDnGAN effectively denoised low-SNR Wave-CAIPI images with sharpness and rich textural details, which could be adjusted by controlling the contribution of the adversarial loss to the total loss when training the generator. Quantitatively, HDnGAN (λ = 10HDnGAN provides robust and feasible denoising while preserving rich textural detail in empirical volumetric MRI data. Our study using empirical patient data and systematic evaluation supports the use of HDnGAN in combination with modern fast imaging techniques such as Wave-CAIPI to achieve high-fidelity fast volumetric MRI and represents an important step to the clinical translation of GANs.

Satellite constellations are growing in size and in utility for applications as diverse as providing reliable, low-latency internet service to rural areas and Earth science missions. This expansion of satellite constellations brings attention to the need for responsive and reliable satellite communication. Current research focuses on using pulsed laser communications as the method of relaying time signals instead of the radio frequency (RF). The upcoming CLICK (CubeSat Laser Infrared CrosslinK) missions (Massachusetts Institute of Technology, University of Florida, NASA Ames Research Center) [1] will demonstrate a space-craft-to-spacecraft laser communication link and time-transfer. For pre-flight technology assessment of missions such as CLICK, a simulation of a spacecraft constellation in Earth orbit has been created to estimate clock synchronization and precision orbit determination based on measured instrumentation performance. We have developed a novel MATLAB-based numerical simulator to model spacecraft-to-spacecraft laser time-transfer and estimate the offset between the spacecraft clocks over time. This simulation includes timing errors associated with laser pulse generation and detection, as well as non-Gaussian clock drift models. The two on-board clocks modeled are a cesium-based Chip-Scale Atomic Clock (CSAC) and a rubidium-based Miniature Atomic Clock (MAC), both produced by Microchip [2][3]. An example case of two spacecraft in a circular, low-Earth orbit receiving GPS position, GPS timing, and laser pulse timeof-flight measurements is simulated. The positions and velocities of the two spacecraft at a reference epoch and the constant clock model coefficients are estimated. Polynomial models of different orders were used as clock models. The effect of clock model order on the root-mean-square (RMS) of the clock error is apparent in the case using GPS and lasing measurements, showing that the clock model improves with increasing clock model order. Results compare the estimated clock model of a mission operation that only uses GPS measurements and a mission operation that uses both GPS and laser pulse time-of-flight measurements between spacecraft referenced to their on-board CSACs. Including lasing measurements reduces the RMS clock model error to approximately half the RMS of the cases with only GPS measurements. This simulation tool can be used to optimize the lasing operations schedule based on mission timing performance objectives.

BACKGROUND AND PURPOSE: Our aim was to evaluate an ultrafast 3D-FLAIR sequence using Wave–controlled aliasing in parallel imaging encoding (Wave-FLAIR) compared with standard 3D-FLAIR in the visualization and volumetric estimation of cerebral white matter lesions in a clinical setting. MATERIALS AND METHODS: Forty-two consecutive patients underwent 3T brain MR imaging, including standard 3D-FLAIR (acceleration factor = 2, scan time = 7 minutes 50 seconds) and resolution-matched ultrafast Wave-FLAIR sequences (acceleration factor = 6, scan time = 2 minutes 45 seconds for the 20-channel coil; acceleration factor = 9, scan time = 1 minute 50 seconds for the 32-channel coil) as part of clinical evaluation for demyelinating disease. Automated segmentation of cerebral white matter lesions was performed using the Lesion Segmentation Tool in SPM. Student t tests, intraclass correlation coefficients, relative lesion volume difference, and Dice similarity coefficients were used to compare volumetric measurements among sequences. Two blinded neuroradiologists evaluated the visualization of white matter lesions, artifacts, and overall diagnostic quality using a predefined 5-point scale. RESULTS: Standard and Wave-FLAIR sequences showed excellent agreement of lesion volumes with an intraclass correlation coefficient of 0.99 and mean Dice similarity coefficient of 0.97 (SD, 0.05) (range, 0.84–0.99). Wave-FLAIR was noninferior to standard FLAIR for visualization of lesions and motion. The diagnostic quality for Wave-FLAIR was slightly greater than for standard FLAIR for infratentorial lesions (P

PURPOSE To demonstrate a navigator/tracking-free retrospective motion estimation technique that facilitates clinically acceptable reconstruction time. METHODS Scout accelerated motion estimation and reduction (SAMER) uses a single 3-5 s, low-resolution scout scan and a novel sequence reordering to independently determine motion states by minimizing the data-consistency error in a SENSE plus motion forward model. This eliminates time-consuming alternating optimization as no updates to the imaging volume are required during the motion estimation. The SAMER approach was assessed quantitatively through extensive simulation and was evaluated in vivo across multiple motion scenarios and clinical imaging contrasts. Finally, SAMER was synergistically combined with advanced encoding (Wave-CAIPI) to facilitate rapid motion-free imaging. RESULTS The highly accelerated scout provided sufficient information to achieve accurate motion trajectory estimation (accuracy ~0.2 mm or degrees). The novel sequence reordering improved the stability of the motion parameter estimation and image reconstruction while preserving the clinical imaging contrast. Clinically acceptable computation times for the motion estimation (~4 s/shot) are demonstrated through a fully separable (non-alternating) motion search across the shots. Substantial artifact reduction was demonstrated in vivo as well as corresponding improvement in the quantitative error metric. Finally, the extension of SAMER to Wave-encoding enabled rapid high-quality imaging at up to R = 9-fold acceleration. CONCLUSION SAMER significantly improved the computational scalability for retrospective motion estimation and correction.

Wave-CAIPI (Controlled Aliasing in Parallel Imaging) enables dramatic reduction in acquisition time of 3D MRI sequences such as 3D susceptibility-weighted imaging (SWI) but has not been clinically evaluated at 1.5 T. We sought to compare highly accelerated Wave-CAIPI SWI (Wave-SWI) with two alternative standard sequences, conventional three-dimensional SWI and two-dimensional T2*-weighted Gradient-Echo (T2*w-GRE), in patients undergoing routine brain MRI at 1.5 T.In this study, 172 patients undergoing 1.5 T brain MRI were scanned with a more commonly used susceptibility sequence (standard SWI or T2*w-GRE) and a highly accelerated Wave-SWI sequence. Two radiologists blinded to the acquisition technique scored each sequence for visualization of pathology, motion and signal dropout artifacts, image noise, visualization of normal anatomy (vessels and basal ganglia mineralization), and overall diagnostic quality. Superiority testing was performed to compare Wave-SWI to T2*w-GRE, and non-inferiority testing with 15% margin was performed to compare Wave-SWI to standard SWI.Wave-SWI performed superior in terms of visualization of pathology, signal dropout artifacts, visualization of normal anatomy, and overall image quality when compared to T2*w-GRE (all p0.001). Wave-SWI was non-inferior to standard SWI for visualization of normal anatomy and pathology, signal dropout artifacts, and overall image quality (all p0.001). Wave-SWI was superior to standard SWI for motion artifact (p0.001), while both conventional susceptibility sequences were superior to Wave-SWI for image noise (p0.001).Wave-SWI can be performed in a 1.5 T clinical setting with robust performance and preservation of diagnostic quality.• Wave-SWI accelerated the acquisition of 3D high-resolution susceptibility images in 70% of the acquisition time of the conventional T2*GRE. • Wave-SWI performed superior to T2*w-GRE for visualization of pathology, signal dropout artifacts, and overall diagnostic image quality. • Wave-SWI was noninferior to standard SWI for visualization of normal anatomy and pathology, signal dropout artifacts, and overall diagnostic image quality.

Constellations of CubeSats will benefit from high data rate communications links and precision time transfer and ranging. The CubeSat Laser Infrared CrosslinK (CLICK) mission intends to demonstrate low size, weight, and power (SWaP) laser communication terminals, capable of conducting full-duplex high data rate downlinks and crosslinks, as well as high precision ranging and time transfer. A joint project between the Massachusetts Institute of Technology (MIT), the University of Florida (UF), and NASA Ames Research Center, CLICK consists of two separate demonstration flights: the initial CLICK-A, which will demonstrate a space-to-ground downlink and serve as a risk-reduction mission, and CLICK-B/C, a crosslink demonstration mission. The CLICK payloads each consist of laser transceivers and pointing, acquisition, and tracking (PAT) systems, and will fly on 3U CubeSat buses from Blue Canyon Technologies to perform their optical downlink and crosslink experiments in low Earth orbit (LEO). We present an update on the status of both the CLICK-A and CLICK-B/C payloads. At the time of writing, the final assembly and testing of the CLICK-A payload has been completed and the payload has been delivered for integration with the spacecraft bus. The final testing included the validation of the transmitter and the PAT system, the performance of both of which was characterized under various environmental test conditions and shown to meet their requirements for operation on orbit. On CLICK-B/C, the payload electronics have been designed and are under test. The optical bench of the payload has been assembled, the characterization of which is ongoing.

BACKGROUND AND PURPOSE: High-resolution three-dimensional (3D) post-contrast imaging of the brain is essential for comprehensive evaluation of inflammatory, neoplastic, and neurovascular diseases of the brain. 3D T1-weighted spin-echo-based sequences offer increased sensitivity for the detection of enhancing lesions but are relatively prolonged examinations. We evaluated whether a highly accelerated Wave-controlled aliasing in parallel imaging (Wave-CAIPI) post-contrast 3D T1-sampling perfection with application-optimized contrasts using different flip angle evolutions (T1-SPACE) sequence (Wave-T1-SPACE) was noninferior to the standard high-resolution 3D T1-SPACE sequence for visualizing enhancing lesions with comparable diagnostic quality. METHODS: One hundred and three consecutive patients were prospectively evaluated with a standard post-contrast 3D T1-SPACE sequence (acquisition time [TA] = 4 min 19 s) and an optimized Wave-CAIPI 3D T1-SPACE sequence (TA = 1 min 40 s) that was nearly three times faster than the standard sequence. Two blinded neuroradiologists performed a head-to-head comparison to evaluate the visualization of enhancing pathology, perception of artifacts, and overall diagnostic quality. A 15% margin was used to test whether post-contrast Wave-T1-SPACE was noninferior to standard T1-SPACE. RESULTS: Wave-T1-SPACE was noninferior to standard T1-SPACE for delineating parenchymal and meningeal enhancing pathology (p

Introduction Clinical validation studies have demonstrated the ability of accelerated MRI sequences to decrease acquisition time and motion artifact while preserving image quality. The operational benefits, however, have been less explored. Here, we report our initial clinical experience in implementing fast MRI techniques for outpatient brain imaging during the COVID-19 pandemic. Methods Aggregate acquisition times were extracted from the medical record on consecutive imaging examinations performed during matched pre-implementation (7/1/2019-12/31/2019) and post-implementation periods (7/1/2020-12/31/2020). Expected acquisition time reduction for each MRI protocol was calculated through manual collection of acquisition times for the conventional and accelerated sequences performed during the pre- and post-implementation periods. Aggregate and expected acquisition times were compared for the five most frequently performed brain MRI protocols: brain without contrast (BR-), brain with and without contrast (BR+), multiple sclerosis (MS), memory loss (MML), and epilepsy (EPL). Results The expected time reductions for BR-, BR+, MS, MML, and EPL protocols were 6.6 min, 11.9 min, 14 min, 10.8 min, and 14.1 min, respectively. The overall median aggregate acquisition time was 31 [25, 36] min for the pre-implementation period and 18 [15, 22] min for the post-implementation period, with a difference of 13 min (42%). The median acquisition time was reduced by 4 min (25%) for BR-, 14.0 min (44%) for BR+, 14 min (38%) for MS, 11 min (52%) for MML, and 16 min (35%) for EPL. Conclusion The implementation of fast brain MRI sequences significantly reduced the acquisition times for the most commonly performed outpatient brain MRI protocols.

Susceptibility-weighted imaging (SWI) is highly sensitive for intracranial hemorrhagic and mineralized lesions but is associated with long scan times. Wave controlled aliasing in parallel imaging (Wave-CAIPI) enables greater acceleration factors and might facilitate broader application of SWI, especially in motion-prone populations.To compare highly accelerated Wave-CAIPI SWI to standard SWI in the non-sedated pediatric outpatient setting, with respect to the following variables: estimated scan time, image noise, artifacts, visualization of normal anatomy and visualization of pathology.Twenty-eight children (11 girls, 17 boys; mean age ± standard deviation [SD] = 128.3±62 months) underwent 3-tesla (T) brain MRI, including standard three-dimensional (3-D) SWI sequence followed by a highly accelerated Wave-CAIPI SWI sequence for each subject. We rated all studies using a predefined 5-point scale and used the Wilcoxon signed rank test to assess the difference for each variable between sequences.Wave-CAIPI SWI provided a 78% and 67% reduction in estimated scan time using the 32- and 20-channel coils, respectively, corresponding to estimated scan time reductions of 3.5 min and 3 min, respectively. All 28 children were imaged without anesthesia. Inter-reader agreement ranged from fair to substantial (k=0.67 for evaluation of pathology, 0.55 for anatomical contrast, 0.3 for central noise, and 0.71 for artifacts). Image noise was rated higher in the central brain with wave SWI (P0.01), but not in the peripheral brain. There was no significant difference in the visualization of normal anatomical structures and visualization of pathology between the standard and wave SWI sequences (P=0.77 and P=0.79, respectively).Highly accelerated Wave-CAIPI SWI of the brain can provide similar image quality to standard SWI, with estimated scan time reduction of 3-3.5 min depending on the radiofrequency coil used, with fewer motion artifacts, at a cost of mild but perceptibly increased noise in the central brain.