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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.

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.

BACKGROUND Rapid volumetric imaging protocols could better utilize limited scanner resources. PURPOSE To develop and validate an optimized 6-minute high-resolution volumetric brain MRI examination using Wave-CAIPI encoding. STUDY TYPE Prospective. POPULATION/SUBJECTS Ten healthy subjects and 20 patients with a variety of intracranial pathologies. FIELD STRENGTH/SEQUENCE At 3 T, MPRAGE, T2 -weighted SPACE, SPACE FLAIR, and SWI were acquired at 9-fold acceleration using Wave-CAIPI and for comparison at 2-4-fold acceleration using conventional GRAPPA. ASSESSMENT Extensive simulations were performed to optimize the Wave-CAIPI protocol and minimize both g-factor noise amplification and potential T1 /T2 blurring artifacts. Moreover, refinements in the autocalibrated reconstruction of Wave-CAIPI were developed to ensure high-quality reconstructions in the presence of gradient imperfections. In a randomized and blinded fashion, three neuroradiologists assessed the diagnostic quality of the optimized 6-minute Wave-CAIPI exam and compared it to the roughly 3× slower GRAPPA accelerated protocol using both an individual and head-to-head analysis. STATISTICAL TEST A noninferiority test was used to test whether the diagnostic quality of Wave-CAIPI was noninferior to the GRAPPA acquisition, with a 15% noninferiority margin. RESULTS Among all sequences, Wave-CAIPI achieved negligible g-factor noise amplification (gavg ≤ 1.04) and burring artifacts from T1 /T2 relaxation. Improvements of our autocalibration approach for gradient imperfections enabled increased robustness to gradient mixing imperfections in tilted-field of view (FOV) prescriptions as well as variations in gradient and analog-to-digital converter (ADC) sampling rates. In the clinical evaluation, Wave-CAIPI achieved similar mean scores when compared with GRAPPA (MPRAGE: OW = 4.03, OG = 3.97; T2 w SPACE: OW = 4.00, OG = 4.00; SPACE FLAIR: OW = 3.97, OG = 3.97; SWI: OW = 3.93, OG = 3.83) and was statistically noninferior (N = 30, P

Objective: White matter hyperintensities (WMH) observed on neuroimaging of elderly individuals are associated with cognitive decline and disability. However, the pathogenesis of WMH remains poorly understood. We observed that regions of reduced cerebrovascular reactivity (CVR) in the white matter of young individuals correspond to the regions most susceptible to WMH in the elderly. This finding prompted us to consider that reduced CVR may play a role in the pathogenesis of WMH. We hypothesized that reduced CVR precedes development of WMH. Methods: We examined 45 subjects (age range: 50-91; 25 males) with moderate-severe WMH, and measured their baseline CVR using the blood-oxygen-level-dependent MRI signal response to a standardized step change in the end-tidal partial pressure of carbon dioxide. Diffusion-tensor imaging and transverse relaxation time (T2) relaxometry were performed at baseline and one-year follow-up, with automated co-registration between time points. Baseline fractional anisotropy (FA), mean diffusivity (MD), T2, and CVR were measured in areas that progressed from normal-appearing white matter (NAWM) to WMH over the one-year period. Results: CVR and FA values in baseline NAWM that progressed to WMH were lower by mean (standard deviation) = 26.5% (23.2%) and 11.0% (7.2%), respectively, compared to the contralateral homologous NAWM that did not progress (P

Neuroimaging of older adults commonly reveals abnormality (leukoaraiosis) in the cerebral white matter. Studies have established that extensive leukoaraiosis predicts dementia and disability, but the pathogenesis of leukoaraiosis remains unclear. We recruited 5 patients with leukoaraiosis and performed magnetic resonance mapping of the brain for 16 consecutive weeks. We observed tiny lesions arising de novo in the cerebral white matter. These lesions were clinically silent. They had the signature features of acute ischemic stroke. With time, the characteristics of these lesions approached those of pre-existing leukoaraiosis. Together, these findings suggest that tiny silent acute infarcts are a cause of leukoaraiosis.