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Head motion systematically distorts clinical and research MRI data. Motion artifacts have biased findings from many structural and functional brain MRI studies. An effective way to remove motion artifacts is to exclude MRI data frames affected by head motion. However, such post-hoc frame censoring can lead to data loss rates of 50% or more in our pediatric patient cohorts. Hence, many scanner operators collect additional ‘buffer data’, an expensive practice that, by itself, does not guarantee sufficient high-quality MRI data for a given participant. Therefore, we developed an easy-to-setup, easy-to-use Framewise Integrated Real-time MRI Monitoring (FIRMM) software suite that provides scanner operators with head motion analytics in real-time, allowing them to scan each subject until the desired amount of low-movement data has been collected. Our analyses show that using FIRMM to identify the ideal scan time for each person can reduce total brain MRI scan times and associated costs by 50% or more. [Display omitted]

Biophysical modeling of macroscopic diffusion-weighted MRI signal in terms of microscopic cellular parameters holds the promise of quantifying the integrity of white matter. Unfortunately, even fairly simple multi-compartment models of proton diffusion in the white matter do not provide a unique, biophysically plausible solution. Here we report a nontrivial diffusion MRI signal dependence on echo time (TE) in human white matter in vivo. We demonstrate that such TE dependence originates from compartment-specific T2 values and that it is a promising “orthogonal measure” able to break the degeneracy in parameter estimation, and to yield important relaxation metrics robustly. We thereby enable the precise estimation of the intra- and extra-axonal water T2 relaxation times, which is precluded by a limited signal-to-noise ratio when using multi-echo relaxometry alone. •Empirical evidence for different compartmental T2 values.•TE dependency of diffusion MRI signals biases the interpretation of diffusion parameters.•Including compartmental diffusivities in the biophysical models improves T2 relaxometry.•Including compartmental T2's in the biophysical models improve diffusion modeling.•Compartmental T2's may become valuable parameters for WM microstructure.

Visual snow syndrome (VSS) is a neurological disorder characterized by a range of continuous visual disturbances. Little is known about the functional pathological mechanisms underlying VSS and their effect on brain network topology, studied using high‐resolution resting‐state (RS) 7 T MRI. Forty VSS patients and 60 healthy controls underwent RS MRI. Functional connectivity matrices were calculated, and global efficiency (network integration), modularity (network segregation), local efficiency (LE, connectedness neighbors) and eigenvector centrality (significance node in network) were derived using a dynamic approach (temporal fluctuations during acquisition). Network measures were compared between groups, with regions of significant difference correlated with known aberrant ocular motor VSS metrics (shortened latencies and higher number of inhibitory errors) in VSS patients. Lastly, nodal co‐modularity, a binary measure of node pairs belonging to the same module, was studied. VSS patients had lower modularity, supramarginal centrality and LE dynamics of multiple (sub)cortical regions, centered around occipital and parietal lobules. In VSS patients, lateral occipital cortex LE dynamics correlated positively with shortened prosaccade latencies (p = .041, r = .353). In VSS patients, occipital, parietal, and motor nodes belonged more often to the same module and demonstrated lower nodal co‐modularity with temporal and frontal regions. This study revealed reduced dynamic variation in modularity and local efficiency strength in the VSS brain, suggesting that brain network dynamics are less variable in terms of segregation and local clustering. Further investigation of these changes could inform our understanding of the pathogenesis of the disorder and potentially lead to treatment strategies. Visual snow syndrome (VSS) is a neurological disorder characterized by a range of continuous visual disturbances. Little is known about the functional pathological mechanisms underlying VSS and their effect on brain network topology, which was studied using high‐resolution resting‐state 7 T MRI. VSS patients demonstrated reduced dynamic variation in modularity and local efficiency strength, suggesting that brain network dynamics are less variable in terms of segregation and local clustering. Network dynamic alterations were centered around occipital cortices and related to ocular motor processing changes.

•Spinal cord morphology estimated based on synthetic T1-weighted MRI shows high repeatability.•Spinal cord atrophy following spinal cord injury can reliably be measured on synthetic MR images.•Synthetic MRI allows to reduce acquisition time in long imaging protocols and application in clinical studies. Short MRI acquisition time, high signal-to-noise ratio, and high reliability are crucial for image quality when scanning healthy volunteers and patients. Cross-sectional cervical cord area (CSA) has been suggested as a marker of neurodegeneration and potential outcome measure in clinical trials and is conventionally measured on T1-weigthed 3D Magnetization Prepared Rapid Acquisition Gradient-Echo (MPRAGE) images. This study aims to reduce the acquisition time for the comprehensive assessment of the spinal cord, which is typically based on MPRAGE for morphometry and multi-parameter mapping (MPM) for microstructure. The MPRAGE is replaced by a synthetic T1-w MRI (synT1-w) estimated from the MPM, in order to measure CSA. SynT1-w images were reconstructed using the MPRAGE signal equation based on quantitative maps of proton density (PD), longitudinal (R1) and effective transverse (R2*) relaxation rates. The reliability of CSA measurements from synT1-w images was determined within a multi-center test-retest study format and validated against acquired MPRAGE scans by assessing the agreement between both methods. The response to pathological changes was tested by longitudinally measuring spinal cord atrophy following spinal cord injury (SCI) for synT1-w and MPRAGE using linear mixed effect models. CSA measurements based on the synT1-w MRI showed high intra-site (Coefficient of variation [CoV]: 1.43% to 2.71%) and inter-site repeatability (CoV: 2.90% to 5.76%), and only a minor deviation of -1.65 mm2 compared to MPRAGE. Crucially, by assessing atrophy rates and by comparing SCI patients with healthy controls longitudinally, differences between synT1-w and MPRAGE were negligible. These results demonstrate that reliable estimates of CSA can be obtained from synT1-w images, thereby reducing scan time significantly.

Background Fiducial markers in image‐guided prostate cancer radiotherapy reduce geometric uncertainty during daily patient setup and enable assessment of target position changes. Diffusion‐weighted magnetic resonance imaging (MRI) for target delineation improves prostate cancer localization, beneficial for intraprostatic focal boost. Artifacts from fiducial markers on prostate diffusion‐weighted MRI (DWI) need to be investigated, as they could be detrimental for target delineation. This study aims to determine the distances of artifact extensions caused by fiducial markers in DWI and in the apparent diffusion coefficient (ADC) maps and to assess how motion and signal‐to‐noise ratio (SNR) influence the artifact size in ADC maps. Materials and methods Three phantoms were used: two homogeneous gel phantoms—one containing three cylindrical gold fiducial markers (GFM) and the other containing three spherical gold anchor (GA) markers—and a third heterogeneous phantom consisting of a piece of sirloin embedded with three GFM and three GA. Diffusion‐weighted images were acquired on a 3T MRI system. The artifacts were analyzed along the phase‐encoding (PE) and frequency‐encoding (FE) directions. Motion was induced and simulated during acquisition, and SNR was varied. The impact of motion and SNR on the artifact extension was evaluated, and the artifact extensions in diffusion images from eight patients were also analyzed. Results The artifacts were smaller in the ADC maps compared to DWI. The largest artifact extension occurred along the PE‐direction. Larger artifact extensions were observed in homogeneous phantom images compared to patient images. In homogeneous phantom images: 13.8  ±  0.4 mm / 9.1  ±  0.4 mm (PE/FE) in DWI with b = 0 s/mm2 and 11.6  ±  0.9 mm / 8.1  ±  0.4 mm (PE/FE) in the ADC map. In patient images: 10.7  ±  1.2 mm / 8.2  ±  1.3 mm (PE/FE) in DWI with b = 0 s/mm2 and 7.3  ±  1.6 mm / 6.8  ±  1.1 mm (PE/FE) in the ADC map. Motion caused larger artifact extensions compared to no motion. A motion of 2 mm increased the artifact from 11.6 ± 0.9 mm / 8.1 ± 0.4 mm (PE/FE) to 14.1 ± 0.8 mm / 9.7 ± 0.4 mm (PE/FE) in homogeneous phantom images and from 10.3 ± 0.8 mm / 8.1 ± 0.4 mm (PE/FE) to 13.1 ± 0.8 mm / 8.4 ± 0.8 mm (PE/FE) in heterogeneous phantom images. Lower SNR resulted in smaller visible artifact extensions. Conclusion This study assessed the distances of artifact extensions in homogeneous phantoms, heterogeneous phantoms, and patient images caused by fiducial markers in DWI and ADC maps. ADC maps had smaller artifact extensions compared to DWI. The artifact extensions were largest in the homogeneous phantom, smaller in the heterogeneous phantom, and the smallest in the patient images. In patient images, the extensions were approximately 7–11 mm (PE) and 7‐8 mm (FE). However, extensions reached up to ∼14 mm (PE) and ∼9 mm (FE) in homogeneous phantom images, suggesting that the true artifact extension may be partially obscured in patient images. Further, motion in images caused larger artifact extensions, and lower SNR caused smaller artifact extensions. The study underlines the need for precise marker placement to avoid obscuring critical anatomical structures, especially for delineation of small boost volumes, and distorting ADC values in quantitative analyses of tumors.

•This article covers multiple aspects of imaging perivascular spaces (PVS) in humans with brain MRI, including acquisition protocols, processing methods, and the advantages and pitfalls of these strategies.•This article summarizes techniques to quantify morphological and functional characteristics of PVS using brain structural and diffusion MRI.•This article reviews the results from human neuroimaging studies pertaining PVS both across the normative lifespan and in neurological conditions. In this article, we provide an overview of current neuroimaging methods for studying perivascular spaces (PVS) in humans using brain MRI. In recent years, an increasing number of studies highlighted the role of PVS in cerebrospinal/interstial fluid circulation and clearance of cerebral waste products and their association with neurological diseases. Novel strategies and techniques have been introduced to improve the quantification of PVS and to investigate their function and morphological features in physiological and pathological conditions. After a brief introduction on the anatomy and physiology of PVS, we examine the latest technological developments to quantitatively analyze the structure and function of PVS in humans with MRI. We describe the applications, advantages, and limitations of these methods, providing guidance and suggestions on the acquisition protocols and analysis techniques that can be applied to study PVS in vivo. Finally, we review the human neuroimaging studies on PVS across the normative lifespan and in the context of neurological disorders.

•FC predicts behavior better than anatomical and diffusion features.•Cognition is predicted better than other behavioral components regardless of modality.•Combining resting & task FC improves prediction as much as combining all modalities.•Findings were replicated over 3 regression models and 2 datasets. A fundamental goal across the neurosciences is the characterization of relationships linking brain anatomy, functioning, and behavior. Although various MRI modalities have been developed to probe these relationships, direct comparisons of their ability to predict behavior have been lacking. Here, we compared the ability of anatomical T1, diffusion and functional MRI (fMRI) to predict behavior at an individual level. Cortical thickness, area and volume were extracted from anatomical T1 images. Diffusion Tensor Imaging (DTI) and approximate Neurite Orientation Dispersion and Density Imaging (NODDI) models were fitted to the diffusion images. The resulting metrics were projected to the Tract-Based Spatial Statistics (TBSS) skeleton. We also ran probabilistic tractography for the diffusion images, from which we extracted the stream count, average stream length, and the average of each DTI and NODDI metric across tracts connecting each pair of brain regions. Functional connectivity (FC) was extracted from both task and resting-state fMRI. Individualized prediction of a wide range of behavioral measures were performed using kernel ridge regression, linear ridge regression and elastic net regression. Consistency of the results were investigated with the Human Connectome Project (HCP) and Adolescent Brain Cognitive Development (ABCD) datasets. In both datasets, FC-based models gave the best prediction performance, regardless of regression model or behavioral measure. This was especially true for the cognitive component. Furthermore, all modalities were able to predict cognition better than other behavioral components. Combining all modalities improved prediction of cognition, but not other behavioral components. Finally, across all behaviors, combining resting and task FC yielded prediction performance similar to combining all modalities. Overall, our study suggests that in the case of healthy children and young adults, behaviorally-relevant information in T1 and diffusion features might reflect a subset of the variance captured by FC.

MRI is undoubtedly the cornerstone of brain tumor imaging, playing a key role in all phases of patient management, starting from diagnosis, through therapy planning, to treatment response and/or recurrence assessment. Currently, neuroimaging can describe morphologic and non-morphologic (functional, hemodynamic, metabolic, cellular, microstructural, and sometimes even genetic) characteristics of brain tumors, greatly contributing to diagnosis and follow-up. Knowing the technical aspects, strength and limits of each MR technique is crucial to correctly interpret MR brain studies and to address clinicians to the best treatment strategy. This article aimed to provide an overview of neuroimaging in the assessment of adult primary brain tumors. We started from the basilar role of conventional/morphological MR sequences, then analyzed, one by one, the non-morphological techniques, and finally highlighted future perspectives, such as radiomics and artificial intelligence.

Purpose To compare a faster, new, high-resolution accelerated 3D-fast-spin-echo (3D-FSE) acquisition sequence (CS-SPACE) to traditional 2D and high-resolution 3D sequences for knee 3-T magnetic resonance imaging (MRI). Materials and methods Twenty patients received knee MRIs that included routine 2D (T1, PD ± FS, T2-FS; 0.5 × 0.5 × 3 mm 3 ; ∼10 min), traditional 3D FSE (SPACE-PD-FS; 0.5 × 0.5 × 0.5 mm 3 ; ∼7.5 min), and accelerated 3D-FSE prototype (CS-SPACE-PD-FS; 0.5 × 0.5 × 0.5 mm 3 ; ∼5 min) acquisitions on a 3-T MRI system (Siemens MAGNETOM Skyra). Three musculoskeletal radiologists (MSKRs) prospectively and independently reviewed the studies with graded surveys comparing image and diagnostic quality. Tissue-specific signal-to-noise ratios (SNR) and contrast-to-noise ratios (CNR) were also compared. Results MSKR-perceived diagnostic quality of cartilage was significantly higher for CS-SPACE than for SPACE and 2D sequences ( p  < 0.001). Assessment of diagnostic quality of menisci and synovial fluid was higher for CS-SPACE than for SPACE ( p  < 0.001). CS-SPACE was not significantly different from SPACE but had lower assessments than 2D sequences for evaluation of bones, ligaments, muscles, and fat ( p  ≤ 0.004). 3D sequences had higher spatial resolution, but lower overall assessed contrast ( p  < 0.001). Overall image quality from CS-SPACE was assessed as higher than SPACE ( p  = 0.007), but lower than 2D sequences ( p  < 0.001). Compared to SPACE, CS-SPACE had higher fluid SNR and CNR against all other tissues (all p  < 0.001). Conclusions The CS-SPACE prototype allows for faster isotropic acquisitions of knee MRIs over currently used protocols. High fluid-to-cartilage CNR and higher spatial resolution over routine 2D sequences may present a valuable role for CS-SPACE in the evaluation of cartilage and menisci.

Patients with deep brain stimulation devices highly benefit from postoperative MRI exams, however MRI is not readily accessible to these patients due to safety risks associated with RF heating of the implants. Recently we introduced a patient-adjustable reconfigurable coil technology that substantially reduced local SAR at tips of single isolated DBS leads during MRI at 1.5 T in 9 realistic patient models. This contribution extends our work to higher fields by demonstrating the feasibility of scaling the technology to 3T and assessing its performance in patients with bilateral leads as well as fully implanted systems. We developed patient-derived models of bilateral DBS leads and fully implanted DBS systems from postoperative CT images of 13 patients and performed finite element simulations to calculate SAR amplification at electrode contacts during MRI with a reconfigurable rotating coil at 3T. Compared to a conventional quadrature body coil, the reconfigurable coil system reduced the SAR on average by 83% for unilateral leads and by 59% for bilateral leads. A simple surgical modification in trajectory of implanted leads was demonstrated to increase the SAR reduction efficiency of the rotating coil to >90% in a patient with a fully implanted bilateral DBS system. Thermal analysis of temperature-rise around electrode contacts during typical brain exams showed a 15-fold heating reduction using the rotating coil, generating <1°C temperature rise during ∼4-min imaging with high-SAR sequences where a conventional CP coil generated >10°C temperature rise in the tissue for the same flip angle. •Reconfigurable MRI technology for low-SAR imaging of deep brain stimulation implants.•Patient-adjustable MRI coils.•RF safety of bilateral isolated DBS leads and fully-implanted systems.•DBS surgical lead management for MRI safety.