Altered myelination in youth born with congenital heart disease.

Brain injury and dysmaturation is common in fetuses and neonates with congenital heart disease (CHD) and is hypothesized to result in persistent myelination deficits. This study aimed to quantify and compare myelin content in vivo between youth born with CHD and healthy controls. Youth aged 16 to 24 years born with CHD and healthy age- and sex-matched controls underwent brain magnetic resonance imaging including multicomponent driven equilibrium single pulse observation of T and T (mcDESPOT).

Tumor blood flow and apparent diffusion coefficient histogram analysis for differentiating malignant salivary tumors from pleomorphic adenomas and Warthin's tumors.

We aimed to assess the combined diagnostic value of apparent diffusion coefficient (ADC) and tumor blood flow (TBF) obtained by pseudocontinuous arterial spin labeling (pCASL) for differentiating malignant tumors (MTs) in salivary glands from pleomorphic adenomas (PAs) and Warthin's tumors (WTs). We used pCASL imaging and ADC map to evaluate 65 patients, including 16 with MT, 30 with PA, and 19 with WT. We evaluated all tumors by histogram analyses and compared various characteristics by one-way analysis of variance followed by Tukey post-hoc tests.

Brain microstructural antecedents of visual difficulties in infants born very preterm.

Infants born very preterm (VPT) are at risk of later visual problems. Although neonatal screening can identify ophthalmologic abnormalities, subtle perinatal brain injury and/or delayed brain maturation may be significant contributors to complex visual-behavioral problems. Our aim was to assess the micro and macrostructural antecedents of early visual-behavioral difficulties in VPT infants by using diffusion MRI (dMRI) at term-equivalent age.

ConCeptCNN: A novel multi-filter convolutional neural network for the prediction of neurodevelopmental disorders using brain connectome.

Background: Deep convolutional neural network (CNN) and its derivatives have recently shown great promise in the prediction of brain disorders using brain connectome data. Existing deep CNN methods using single global row and column convolutional filters have limited ability to extract discriminative information from brain connectome for prediction tasks.

Purpose: This paper presents a novel deep Connectome-Inception CNN (ConCeptCNN) model, which is developed based on multiple convolutional filters.

Pediatric Xe Gas-Transfer MRI-Feasibility and Applicability.

Background: Xe gas-transfer MRI provides regional measures of pulmonary gas exchange in adults and separates xenon in interstitial lung tissue/plasma (barrier) from xenon in red blood cells (RBCs). The technique has yet to be demonstrated in pediatric populations or conditions.

Purpose/hypothesis: To perform an exploratory analysis of Xe gas-transfer MRI in children.

Long-Term Stability of Gradient Characteristics Warrants Model-Based Correction of Diffusion Weighting Bias.

The study aims to test the long-term stability of gradient characteristics for model-based correction of diffusion weighting (DW) bias in an apparent diffusion coefficient (ADC) for multisite imaging trials. Single spin echo (SSE) DWI of a long-tube ice-water phantom was acquired quarterly on six MR scanners over two years for individual diffusion gradient channels, along with B0 mapping, as a function of right-left (RL) and superior-inferior (SI) offsets from the isocenter. Additional double spin-echo (DSE) DWI was performed on two systems.

Performance of C-SENSE Accelerated Rapid Liver Shear Stiffness Measurement Using Displacement Wave Polarity-Inversion Motion Encoding: An Evaluation Study.

Background: Liver shear stiffness measurement using magnetic resonance elastography (MRE) aids in the noninvasive diagnosis and staging of liver fibrosis. Inadequate breath-holds can lead to inaccurate stiffness estimation and/or failed MRE exams.

Purpose: To prospectively evaluate the performance of compressed sensitivity encoding (C-SENSE) accelerated rapid MRE measurement of liver shear stiffness using displacement wave polarity-inversion motion encoding.

Abdominal motion tracking with free-breathing XD-GRASP acquisitions using spatio-temporal geodesic trajectories.

Free-breathing external beam radiotherapy remains challenging due to the complex elastic or irregular motion of abdominal organs, as imaging moving organs leads to the creation of motion blurring artifacts. In this paper, we propose a radial-based MRI reconstruction method from 3D free-breathing abdominal data using spatio-temporal geodesic trajectories, to quantify motion during radiotherapy. The prospective study was approved by the institutional review board and consent was obtained from all participants.

A deep convolutional neural network-based automatic detection of brain metastases with and without blood vessel suppression.

Objectives: To develop an automated model to detect brain metastases using a convolutional neural network (CNN) and volume isotropic simultaneous interleaved bright-blood and black-blood examination (VISIBLE) and to compare its diagnostic performance with the observer test.

Methods: This retrospective study included patients with clinical suspicion of brain metastases imaged with VISIBLE from March 2016 to July 2019 to create a model. Images with and without blood vessel suppression were used for training an existing CNN (DeepMedic).

Sexual dimorphism in the cerebrovascular network: Brain MRI shows lower arterial density in women.

Background And Purpose: Accumulating evidence suggests that there is a sexual dimorphism in brain health, with women exhibiting greater disability following strokes of comparable size and having a higher prevalence of cognitive impairment later in life. Despite the critical implication of the cerebrovascular architecture in brain perfusion and brain health, it remains unclear whether structural differences in vessel density exist across the sexes.

Methods: In this study, we used high-density MRI imaging to characterize the intracerebral arterial and venous density of 28 (14 women) sex-matched healthy young volunteers in vivo.

A deep learning algorithm for white matter hyperintensity lesion detection and segmentation.

Purpose: White matter hyperintensity (WMHI) lesions on MR images are an important indication of various types of brain diseases that involve inflammation and blood vessel abnormalities. Automated quantification of the WMHI can be valuable for the clinical management of patients, but existing automated software is often developed for a single type of disease and may not be applicable for clinical scans with thick slices and different scanning protocols. The purpose of the study is to develop and validate an algorithm for automatic quantification of white matter hyperintensity suitable for heterogeneous MRI data with different disease types.

Quantitative differentiation of tendon and ligament using magnetic resonance imaging ultrashort echo time T2* mapping of normal knee joint.

Background: Ligaments and tendons are difficult to differentiate on conventional magnetic resonance imaging (MRI). Ligaments and tendons are different histologically, and tendon graft ligamentization is known to occur after anterior cruciate ligament (ACL) reconstruction.

Purpose: To quantify and differentiate the ultrashort echo time T2* (UTE-T2*) values of normal knee ligaments and tendons using a 1.

Improved prospective frequency correction for macromolecule-suppressed GABA editing with metabolite cycling at 3T.

Purpose: To combine metabolite cycling with J-difference editing (MC MEGA) to allow for prospective frequency correction at each transient without additional acquisitions and compare it to water-suppressed MEGA-PRESS (WS MEGA) editing with intermittent prospective frequency correction.

Methods: Macromolecule-suppressed gamma aminobutyric acid (GABA)-edited experiments were performed in a phantom and in the occipital lobe (OCC) (n = 12) and medial prefrontal cortex (mPFC) (n = 8) of the human brain. Water frequency consistency and average offset over acquisition time were compared.

Human upper-airway respiratory airflow: In vivo comparison of computational fluid dynamics simulations and hyperpolarized 129Xe phase contrast MRI velocimetry.

Computational fluid dynamics (CFD) simulations of respiratory airflow have the potential to change the clinical assessment of regional airway function in health and disease, in pulmonary medicine and otolaryngology. For example, in diseases where multiple sites of airway obstruction occur, such as obstructive sleep apnea (OSA), CFD simulations can identify which sites of obstruction contribute most to airway resistance and may therefore be candidate sites for airway surgery. The main barrier to clinical uptake of respiratory CFD to date has been the difficulty in validating CFD results against a clinical gold standard.

Robust arterial input function surrogate measurement from the superior sagittal sinus complex signal for fast dynamic contrast-enhanced MRI in the brain.

Purpose: Accurately estimating the arterial input function for dynamic contrast-enhanced MRI is challenging. An arterial input function is typically determined from signal magnitude changes related to a contrast agent, often leading to underestimation of peak concentrations. Alternatively, signal phase recovers the accurate peak concentration for straight vessels but suffers from high noise.

An off-resonance insensitive orthogonal CSPAMM sequence (ORI-O-CSPAMM) for the acquisition of CSPAMM and MICSR grids in half scan time.

Purpose: To develop an Off-Resonance Insensitive Orthogonal CSPAMM sequence (ORI-O-CSPAMM) for the acquisition of CSPAMM and MICSR grids in half of the acquisition time.

Methods: Phantom and mid-level left ventricle short-axis tagged images were acquired using CSPAMM, ORI-CSPAMM, O-CSPAMM, and the proposed ORI-O-CPAMM sequences to interrogate and compare its behavior under off-resonance effects produced by vegetable oil and subcutaneous and epicardial fat. The images were compared in terms of signal and the capacity to obtain complex difference and MICSR images.

Lorentz force induced shear waves for magnetic resonance elastography applications.

Quantitative mechanical properties of biological tissues can be mapped using the shear wave elastography technique. This technology has demonstrated a great potential in various organs but shows a limit due to wave attenuation in biological tissues. An option to overcome the inherent loss in shear wave magnitude along the propagation pathway may be to stimulate tissues closer to regions of interest using alternative motion generation techniques.

Empirical validation of gradient field models for an accurate ADC measured on clinical 3T MR systems in body oncologic applications.

Purpose: To empirically corroborate vendor-provided gradient nonlinearity (GNL) characteristics and demonstrate efficient GNL bias correction for human brain apparent diffusion coefficient (ADC) across 3T MR systems and spatial locations.

Methods: Spatial distortion vector fields (DVF) were mapped in 3D using a surface fiducial array phantom for individual gradient channels on three 3T MR platforms from different vendors. Measured DVF were converted into empirical 3D GNL tensors and compared with their theoretical counterparts derived from vendor-provided spherical harmonic (SPH) coefficients.