Probabilistic Finite Element Analysis of Human Rib Biomechanics: A Framework for Improved Generalizability.

In dynamic impact events, thoracic injuries often involve rib fractures, which are closely related to injury severity. Previous studies have investigated the behavior of isolated ribs under impact loading conditions, but often neglected the variability in anatomical shape and tissue material properties. In this study, we used probabilistic finite element analysis and statistical shape modeling to investigate the effect of population-wide variability in rib cortical bone tissue mechanical properties and rib shape on the biomechanical response of the rib to impact loading. Using the probabilistic finite element analysis results, a response surface model was generated to rapidly investigate the biomechanical response of an isolated rib under dynamic anterior-posterior load given the variability in rib morphometry and tissue material properties. The response surface was used to generate pre-fracture force-displacement computational corridors for the overall population and a population sub-group of older mid-sized males. When compared to the experimental data, the computational mean response had a RMSE of 4.28N (peak force 94N) and 6.11N (peak force 116N) for the overall population and sub-group respectively, whereas the normalized area metric when comparing the experimental and computational corridors ranged from 3.32% to 22.65% for the population and 10.90% to 32.81% for the sub-group. Furthermore, probabilistic sensitivities were computed in which the contribution of uncertainty and variability of the parameters of interest was quantified. The study found that rib cortical bone elastic modulus, rib morphometry and cortical thickness are the random variables that produce the largest variability in the predicted force-displacement response. The proposed framework offers a novel approach for accounting biological variability in a representative population and has the potential to improve the generalizability of findings in biomechanical studies.

Investigating the Impact of Blunt Force Trauma: A Probabilistic Study of Behind Armor Blunt Trauma Risk.

Evaluating Behind Armor Blunt Trauma (BABT) is a critical step in preventing non-penetrating injuries in military personnel, which can result from the transfer of kinetic energy from projectiles impacting body armor. While the current NIJ Standard-0101.06 standard focuses on preventing excessive armor backface deformation, this standard does not account for the variability in impact location, thorax organ and tissue material properties, and injury thresholds in order to assess potential injury. To address this gap, Finite Element (FE) human body models (HBMs) have been employed to investigate variability in BABT impact conditions by recreating specific cases from survivor databases and generating injury risk curves. However, these deterministic analyses predominantly use models representing the 50th percentile male and do not investigate the uncertainty and variability inherent within the system, thus limiting the generalizability of investigating injury risk over a diverse military population. The DoD-funded I-PREDICT Future Naval Capability (FNC) introduces a probabilistic HBM, which considers uncertainty and variability in tissue material and failure properties, anthropometry, and external loading conditions. This study utilizes the I-PREDICT HBM for BABT simulations for three thoracic impact locations-liver, heart, and lower abdomen. A probabilistic analysis of tissue-level strains resulting from a BABT event is used to determine the probability of achieving a Military Combat Incapacitation Scale (MCIS) for organ-level injuries and the New Injury Severity Score (NISS) is employed for whole-body injury risk evaluations. Organ-level MCIS metrics show that impact at the heart can cause severe injuries to the heart and spleen, whereas impact to the liver can cause rib fractures and major lacerations in the liver. Impact at the lower abdomen can cause lacerations in the spleen. Simulation results indicate that, under current protection standards, the whole-body risk of injury varies between 6 and 98% based on impact location, with the impact at the heart being the most severe, followed by impact at the liver and the lower abdomen. These results suggest that the current body armor protection standards might result in severe injuries in specific locations, but no injuries in others.

Controlled Antenatal Thyroid Screening Study III: Effects of gestational thyroid status on adolescent brain morphology.

CONTEXT: Children born to mothers with gestational hypo- or hyperthyroidism may have increased risk of adverse neurodevelopmental outcomes. However, the effects of maternal thyroid status on offspring brain development are unclear. OBJECTIVE: To establish whether adolescent brain morphology is affected by suboptimal gestational thyroid function (SGTF). DESIGN AND SETTING: The Controlled Antenatal Thyroid Screening (CATS) study randomized mothers with SGTF to levothyroxine or no supplementation from ∼12 weeks' gestation. At age 9, children born to mothers who were over-treated with levothyroxine had a higher risk of conduct and hyperactivity traits. For the current CATS III study, children underwent neuroimaging studies, including T1-weighted structural magnetic resonance imaging (MRI). PARTICIPANTS: A total of 85 children aged 11-16 years had usable T1-weighted MRI data (exposed to untreated SGTF (n=21), normal GTF (n=24), or treated SGTF (optimally-treated (n=21), over-treated (n=20)). MAIN OUTCOME MEASURES: Primary outcome: to examine the association of SGTF and its treatment with global brain volumes. Secondary and exploratory outcomes: to investigate the association of maternal TSH and free T4 levels with global and subregional brain volumes. Results were adjusted for age, sex and pubertal scores. RESULTS: There were no significant differences in global brain volumetric measures between groups, including total gray matter volume (p=0.373). Weak positive correlations were found between maternal TSH, but not FT4, levels and several brain volumes, but these did not survive testing for multiple comparisons. CONCLUSIONS: We found no evidence that SGTF was associated with differences in adolescent brain morphology, and no impact of levothyroxine supplementation.

The I-PREDICT 50th Percentile Male Warfighter Finite Element Model: Development and Validation of the Thoracolumbar Spine.

Military personnel are commonly at risk of lower back pain and thoracolumbar spine injury. Human volunteers and postmortem human subjects have been used to understand the scenarios where injury can occur and the tolerance of the warfighter to these loading regimes. Finite element human body models (HBMs) can accurately simulate the mechanics of the human body and are a useful tool for understanding injury. In this study, a HBM thoracolumbar spine was developed and hierarchically ï»¿validated as part of the Incapacitation Prediction for Readiness in Expeditionary Domains: an Integrated Computational Tool (I-PREDICT) program. Constitutive material models were sourced from literature and the vertebrae and intervertebral discs were hexahedrally meshed from a 50th percentile male CAD dataset. Ligaments were modeled through attaching beam elements at the appropriate anatomical insertion sites. 94 simulations were replicated from experimental PMHS tests at the vertebral body, functional spinal unit (FSU), and regional lumbar spine levels. The BioRank (BRS) biofidelity ranking system was used to assess the response of the I-PREDICT model. At the vertebral body level, the I-PREDICT model showed good agreement with experimental results. The I-PREDICT FSUs showed good agreement in tension and compression and had comparable stiffness values in flexion, extension, and axial rotation. The regional lumbar spine exhibited "good" biofidelity when tested in tension, compression, extension, flexion, posterior shear, and anterior shear (BRS regional average = 1.05). The validated thoracolumbar spine of the I-PREDICT model can be used to better understand and mitigate injury risk to the warfighter.

In vivo diffusion MRI of the human heart using a 300 mT/m gradient system.

PURPOSE: This work reports for the first time on the implementation and application of cardiac diffusion-weighted MRI on a Connectom MR scanner with a maximum gradient strength of 300 mT/m. It evaluates the benefits of the increased gradient performance for the investigation of the myocardial microstructure. METHODS: Cardiac diffusion-weighted imaging (DWI) experiments were performed on 10 healthy volunteers using a spin-echo sequence with up to second- and third-order motion compensation ( M 2 $$ {M}_2 $$ and M 3 $$ {M}_3 $$ ) and b = 100 , 450 $$ b=100,450 $$ , and 1000 s / m m 2 $$ \mathrm{s}/\mathrm{m}{\mathrm{m}}^2 $$ (twice the b max $$ {b}_{\mathrm{max}} $$ commonly used on clinical scanners). Mean diffusivity (MD), fractional anisotropy (FA), helix angle (HA), and secondary eigenvector angle (E2A) were calculated for b = [100, 450] s / m m 2 $$ \mathrm{s}/\mathrm{m}{\mathrm{m}}^2 $$ and b = [100, 1000] s / m m 2 $$ \mathrm{s}/\mathrm{m}{\mathrm{m}}^2 $$ for both M 2 $$ {M}_2 $$ and M 3 $$ {M}_3 $$ . RESULTS: The MD values with M 3 $$ {M}_3 $$ are slightly higher than with M 2 $$ {M}_2 $$ with Δ MD = 0 . 05 ± 0 . 05 [ × 1 0 - 3 mm 2 / s ] ( p = 4 e - 5 ) $$ \Delta \mathrm{MD}=0.05\pm 0.05\kern0.3em \left[\times 1{0}^{-3}\kern0.3em {\mathrm{mm}}^2/\mathrm{s}\right]\kern0.3em \left(p=4e-5\right) $$ for b max = 450 s / mm 2 $$ {b}_{\mathrm{max}}=450\kern0.3em \mathrm{s}/{\mathrm{mm}}^2 $$ and Δ MD = 0 . 03 ± 0 . 03 [ × 1 0 - 3 mm 2 / s ] ( p = 4 e - 4 ) $$ \Delta \mathrm{MD}=0.03\pm 0.03\kern0.3em \left[\times \kern0.3em 1{0}^{-3}\kern0.3em {\mathrm{mm}}^2/\mathrm{s}\right]\kern0.3em \left(p=4e-4\right) $$ for b max = 1000 s / mm 2 $$ {b}_{\mathrm{max}}=1000\kern0.3em \mathrm{s}/{\mathrm{mm}}^2 $$ . A reduction in MD is observed by increasing the b max $$ {b}_{\mathrm{max}} $$ from 450 to 1000 s / mm 2 $$ \mathrm{s}/{\mathrm{mm}}^2 $$ ( Δ MD = 0 . 06 ± 0 . 04 [ × 1 0 - 3 mm 2 / s ] ( p = 1 . 6 e - 9 ) $$ \Delta \mathrm{MD}=0.06\pm 0.04\kern0.3em \left[\times \kern0.3em 1{0}^{-3}\kern0.3em {\mathrm{mm}}^2/\mathrm{s}\right]\kern0.3em \left(p=1.6e-9\right) $$ for M 2 $$ {M}_2 $$ and Δ MD = 0 . 08 ± 0 . 05 [ × 1 0 - 3 mm 2 / s ] ( p = 1 e - 9 ) $$ \Delta \mathrm{MD}=0.08\pm 0.05\kern0.3em \left[\times \kern0.3em 1{0}^{-3}\kern0.3em {\mathrm{mm}}^2/\mathrm{s}\right]\kern0.3em \left(p=1e-9\right) $$ for M 3 $$ {M}_3 $$ ). The difference between FA, E2A, and HA was not significant in different schemes ( p > 0 . 05 $$ p>0.05 $$ ). CONCLUSION: This work demonstrates cardiac DWI in vivo with higher b-value and higher order of motion compensated diffusion gradient waveforms than is commonly used. Increasing the motion compensation order from M 2 $$ {M}_2 $$ to M 3 $$ {M}_3 $$ and the maximum b-value from 450 to 1000 s / mm 2 $$ \mathrm{s}/{\mathrm{mm}}^2 $$ affected the MD values but FA and the angular metrics (HA and E2A) remained unchanged. Our work paves the way for cardiac DWI on the next-generation MR scanners with high-performance gradient systems.

Update on Blindness From Filler: Review of Prognostic Factors, Management Approaches, and a Century of Published Cases.

BACKGROUND: Vision loss secondary to aesthetic filler treatment is a rare but disastrous complication. OBJECTIVES: The aim was to update the published cases of blindness after filler injection that have occurred since our group published reviews of 98 cases in 2015 and an additional 48 cases in 2019. METHODS: A literature review was performed to identify all cases of visual complications caused by filler injection published between September 2018 and March 2023. The cases were analyzed independently and in combination with previously reviewed cases. Analyses are based on the number of cases with data available. RESULTS: 365 new cases of partial or complete vision loss after filler injection were identified. The sites that were highest risk were the nose (40.6%), forehead (27.7%), and glabella (19.0%). The filler injected was hyaluronic acid in 79.6% of cases. The most common associated signs were ptosis (56.2%), ophthalmoplegia (44.1%), pain (31.2%), and skin changes (73.2%). Stroke-like features were seen in 19.2% of cases. Of the cases reporting visual outcomes (318), 6.0% experienced complete vision recovery, 25.8% had partial improvement in visual acuity, and 68.2% had no vision recovery. Partially preserved visual acuity at onset was a significant predictor of visual improvement (p < .001). The three most common treatments were subcutaneous hyaluronidase at or near the filler site (70.1%), systemic steroids (57.3%), and intra-arterial thrombolytic therapy (56.0%). No treatments were significantly associated with visual improvement (p > .05). CONCLUSIONS: Although blindness and stroke from fillers is a rare complication, practitioners who inject filler should have a thorough knowledge of prevention and management strategies.

A Multicenter, Randomized, Evaluator-Blinded Study to Examine the Safety and Effectiveness of Hyaluronic Acid Filler in the Correction of Infraorbital Hollows.

BACKGROUND: Hyaluronic acid injections are increasingly used for correction of infraorbital hollows (IOHs). OBJECTIVES: Examination of effectiveness (IOH correction) and safety of Restylane® EyelightTM hyaluronic acid (HAEYE, Galderma, Uppsala, Sweden) injections. METHODS: Subjects with moderate/severe IOHs, assessed using the Galderma infraorbital hollows scale (GIHS), were randomized to HAEYE injections (via needle/cannula) (Day 1+optional Month-1 touch up) or no-treatment control. Primary endpoint was blinded evaluator-reported Month-3 response, defined as ≥1-point GIHS improvement from baseline (both sides, concurrently). Other endpoints examined investigator-reported aesthetic improvement (GAIS), subject-reported satisfaction (FACE-Q™ satisfaction with outcome; satisfaction questionnaire), and adverse events. RESULTS: Overall, 333 subjects were randomized. Month 3 GIHS responder rate was significantly higher with HA-EYE (87.4%) versus control (17.7%; p<0.001), and comparable between HA-EYE-needle and HA-EYE-cannula groups (p=0.967). HAEYE GAIS responder rate was 87.5-97.7% (Months 3-12). Mean FACE-Q Rasch-transformed scores were 64.3-73.5 (HAEYE) versus 14.1-16.2 (control) through Month 12. Subjects reported looking younger (≥71%) and less tired (≥79%) with reduced under-eye shadows (≥76%) and recovered within 3-5 hours, post-treatment. Efficacy was maintained through Month 12 (63.5% GIHS responders) and through Month 18, after Month-12 retreatment (80.3% GIHS responders; 99.4% GAIS responders; FACE-Q scores: 72.5-72.8). Forty subjects (12.7%) reported typically mild adverse events (4.9% HAEYE-needle; 20.9% HAEYE-cannula). CONCLUSION: HAEYE treatment was effective in correcting moderate/severe IOHs at the primary endpoint (Month 3). Efficacy was sustained through Month 12 after first treatment for 63.5% and through Month 18 for 80.3% (after one retreatment) with needle or cannula administration. Safety outcomes were reassuring.

"Efficacy and Safety of OnabotulinumtoxinA for the Treatment of Platysma Prominence: A Randomized Phase 2 Dose-Ranging Study".

BACKGROUND: With aging, repetitive contraction of the platysma leads to an increase in platysma prominence (PP) characterized by the accentuation of vertical neck bands and blunting of the jawline's contour. METHODS: This multicenter, double-blind, phase 2 study evaluated onabotulinumtoxinA (onabotA) treatment in adults with Moderate to Severe PP. Participants were randomized to receive 1 treatment of onabotA low dose (LD), onabotA high dose (HD), or placebo, and were followed for 4 months. Efficacy endpoints were the achievement of a ≥ 1-grade improvement on both the left and right sides at Day 14 at maximum contraction as assessed by the investigator (primary) or by participants (secondary) using validated scales. Safety was evaluated throughout. RESULTS: Participants in the modified intent-to-treat population (N = 164) had a mean age of 50 years; 95.1% were female and 93.9% were White. The primary endpoint was met for both onabotA groups, with investigator-assessed ≥ 1-grade improvement in 77.8% (LD) and 88.2% (HD) vs 12.0% (placebo) of participants on Day 14 (P < 0.0001 vs placebo). Based on participant self-assessment, 75.9% (LD) and 88.2% (HD) vs 18.0% (placebo) achieved ≥ 1-grade improvement on Day 14 (P < 0.0001 vs placebo). Most treatment-related adverse events (AEs) were procedure-related, transient, and mild in severity. The most frequent onabotA-related AE was neck muscle weakness, reported in the HD group. CONCLUSIONS: OnabotA was effective in improving the appearance of PP based on both investigators' and participants' ratings. Treatment was well tolerated.

Optimisation of quantitative brain diffusion-relaxation MRI acquisition protocols with physics-informed machine learning.

Diffusion-relaxation MRI aims to extract quantitative measures that characterise microstructural tissue properties such as orientation, size, and shape, but long acquisition times are typically required. This work proposes a physics-informed learning framework to extract an optimal subset of diffusion-relaxation MRI measurements for enabling shorter acquisition times, predict non-measured signals, and estimate quantitative parameters. In vivo and synthetic brain 5D-Diffusion-T1-T2∗-weighted MRI data obtained from five healthy subjects were used for training and validation, and from a sixth participant for testing. One fully data-driven and two physics-informed machine learning methods were implemented and compared to two manual selection procedures and Cramér-Rao lower bound optimisation. The physics-informed approaches could identify measurement-subsets that yielded more consistently accurate parameter estimates in simulations than other approaches, with similar signal prediction error. Five-fold shorter protocols yielded error distributions of estimated quantitative parameters with very small effect sizes compared to estimates from the full protocol. Selected subsets commonly included a denser sampling of the shortest and longest inversion time, lowest echo time, and high b-value. The proposed framework combining machine learning and MRI physics offers a promising approach to develop shorter imaging protocols without compromising the quality of parameter estimates and signal predictions.

Longitudinal effects of prenatal alcohol exposure on visual neurodevelopment over infancy.

Prenatal alcohol exposure (PAE) affects neurodevelopment in over 59 million individuals globally. Prior studies using dichotomous categorization of alcohol use and comorbid substance exposures provide limited knowledge of how prenatal alcohol specifically impacts early human neurodevelopment. In this longitudinal cohort study from Cape Town, South Africa, PAE is measured continuously-characterizing timing, dose, and drinking patterns (i.e., binge drinking). High-density electroencephalography (EEG) during a visual-evoked potential (VEP) task was collected from infants aged 8 to 52 weeks with prenatal exposure exclusively to alcohol and matched on sociodemographic factors to infants with no substance exposure in utero. First trimester alcohol exposure related to altered timing of the P1 VEP component over the first 6 months postnatally, and first trimester binge drinking exposure altered timing of the P1 VEP components such that increased exposure was associated with longer VEP latencies while increasing age was related to shorter VEP latencies (n = 108). These results suggest alcohol exposure in the first trimester may alter visual neurodevelopmental timing in early infancy. Exploratory individual-difference analysis across infants with and without PAE tested the relation between VEP latencies and myelination for a subsample of infants with usable magnetic resonance imaging (MRI) T1w and T2w scans collected at the same time point as EEG (n = 47). Decreased MRI T1w/T2w ratios (an indicator of myelin) in the primary visual cortex (n = 47) were linked to longer P1 VEP latencies. Results from these two sets of analyses suggest that prenatal alcohol and postnatal myelination may both separately impact VEP latency over infancy. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Neutrophilic dermatosis in a patient with an IKZF1 variant and a review of monogenic autoinflammatory disorders presenting with neutrophilic dermatoses.

Monogenic diseases of immune dysregulation should be considered in the evaluation of children presenting with recurrent neutrophilic dermatoses in association with systemic signs of inflammation, autoimmune disease, hematologic abnormalities, and opportunistic or recurrent infections. We report the case of a 2-year-old boy presenting with a neutrophilic dermatosis, found to have a novel likely pathogenic germline variant of the IKAROS Family Zinc Finger 1 (IKZF1) gene; the mutation likely results in a loss of function dimerization defective protein based on reports and studies of similar variants. IKZF1 variants could potentially lead to aberrant neutrophil chemotaxis and development of neutrophilic dermatoses. Long-term surveillance is required to monitor the development of hematologic malignancy, autoimmunity, immunodeficiency, and infection in patients with pathogenic IKZF1 germline variants.

Pore size estimation in axon-mimicking microfibers with diffusion-relaxation MRI.

PURPOSE: This study aims to evaluate two distinct approaches for fiber radius estimation using diffusion-relaxation MRI data acquired in biomimetic microfiber phantoms that mimic hollow axons. The methods considered are the spherical mean power-law approach and a T2-based pore size estimation technique. THEORY AND METHODS: A general diffusion-relaxation theoretical model for the spherical mean signal from water molecules within a distribution of cylinders with varying radii was introduced, encompassing the evaluated models as particular cases. Additionally, a new numerical approach was presented for estimating effective radii (i.e., MRI-visible mean radii) from the ground truth radii distributions, not reliant on previous theoretical approximations and adaptable to various acquisition sequences. The ground truth radii were obtained from scanning electron microscope images. RESULTS: Both methods show a linear relationship between effective radii estimated from MRI data and ground-truth radii distributions, although some discrepancies were observed. The spherical mean power-law method overestimated fiber radii. Conversely, the T2-based method exhibited higher sensitivity to smaller fiber radii, but faced limitations in accurately estimating the radius in one particular phantom, possibly because of material-specific relaxation changes. CONCLUSION: The study demonstrates the feasibility of both techniques to predict pore sizes of hollow microfibers. The T2-based technique, unlike the spherical mean power-law method, does not demand ultra-high diffusion gradients, but requires calibration with known radius distributions. This research contributes to the ongoing development and evaluation of neuroimaging techniques for fiber radius estimation, highlights the advantages and limitations of both methods, and provides datasets for reproducible research.

Macro- and micro-structural insights into primary dystonia: a UK Biobank study.

BACKGROUND: Dystonia is a hyperkinetic movement disorder with key motor network dysfunction implicated in pathophysiology. The UK Biobank encompasses > 500,000 participants, of whom 42,565 underwent brain MRI scanning. This study applied an optimized pre-processing pipeline, aimed at better accounting for artifact and improving data reliability, to assess for grey and white matter structural MRI changes between individuals diagnosed with primary dystonia and an unaffected control cohort. METHODS: Individuals with dystonia (n = 76) were identified from the UK Biobank using published algorithms, alongside an age- and sex-matched unaffected control cohort (n = 311). Grey matter morphometric and diffusion measures were assessed, together with white matter diffusion tensor and diffusion kurtosis metrics using tractography and tractometry. Post-hoc Neurite Orientation and Density Distribution Imaging (NODDI) was also undertaken for tracts in which significant differences were observed. RESULTS: Grey matter tremor-specific striatal differences were observed, with higher radial kurtosis. Tractography identified no white matter differences, however segmental tractometry identified localised differences, particularly in the superior cerebellar peduncles and anterior thalamic radiations, including higher fractional anisotropy and lower orientation distribution index in dystonia, compared to controls. Additional tremor-specific changes included lower neurite density index in the anterior thalamic radiations. CONCLUSIONS: Analysis of imaging data from one of the largest dystonia cohorts to date demonstrates microstructural differences in cerebellar and thalamic white matter connections, with architectural differences such as less orientation dispersion potentially being a component of the morphological structural changes implicated in dystonia. Distinct tremor-related imaging features are also implicated in both grey and white matter.

Self-calibrated subspace reconstruction for multidimensional MR fingerprinting for simultaneous relaxation and diffusion quantification.

PURPOSE: To propose a new reconstruction method for multidimensional MR fingerprinting (mdMRF) to address shading artifacts caused by physiological motion-induced measurement errors without navigating or gating. METHODS: The proposed method comprises two procedures: self-calibration and subspace reconstruction. The first procedure (self-calibration) applies temporally local matrix completion to reconstruct low-resolution images from a subset of under-sampled data extracted from the k-space center. The second procedure (subspace reconstruction) utilizes temporally global subspace reconstruction with pre-estimated temporal subspace from low-resolution images to reconstruct aliasing-free, high-resolution, and time-resolved images. After reconstruction, a customized outlier detection algorithm was employed to automatically detect and remove images corrupted by measurement errors. Feasibility, robustness, and scan efficiency were evaluated through in vivo human brain imaging experiments. RESULTS: The proposed method successfully reconstructed aliasing-free, high-resolution, and time-resolved images, where the measurement errors were accurately represented. The corrupted images were automatically and robustly detected and removed. Artifact-free T1, T2, and ADC maps were generated simultaneously. The proposed reconstruction method demonstrated robustness across different scanners, parameter settings, and subjects. A high scan efficiency of less than 20 s per slice has been achieved. CONCLUSION: The proposed reconstruction method can effectively alleviate shading artifacts caused by physiological motion-induced measurement errors. It enables simultaneous and artifact-free quantification of T1, T2, and ADC using mdMRF scans without prospective gating, with robustness and high scan efficiency.

Maximizing SNR per unit time in diffusion MRI with multiband T-Hex spirals.

PURPOSE: The characterization of tissue microstructure using diffusion MRI (dMRI) signals is rapidly evolving, with increasing sophistication of signal representations and microstructure models. However, this progress often requires signals to be acquired with very high b-values (e.g., b > 30 ms/µm2 ), along many directions, and using multiple b-values, leading to long scan times and extremely low SNR in dMRI images. The purpose of this work is to boost the SNR efficiency of dMRI by combining three particularly efficient spatial encoding techniques and utilizing a high-performance gradient system (Gmax ≤ 300 mT/m) for efficient diffusion encoding. METHODS: Spiral readouts, multiband imaging, and sampling on tilted hexagonal grids (T-Hex) are combined and implemented on a 3T MRI system with ultra-strong gradients. Image reconstruction is performed through an iterative cg-SENSE algorithm incorporating static off-resonance distributions and field dynamics as measured with an NMR field camera. Additionally, T-Hex multiband is combined with a more conventional EPI-readout and compared with state-of-the-art blipped-CAIPIRINHA sampling. The advantage of the proposed approach is furthermore investigated for clinically available gradient performance and diffusion kurtosis imaging. RESULTS: High fidelity in vivo images with b-values up to 40 ms/µm2 are obtained. The approach provides superior SNR efficiency over other state-of-the-art multiband diffusion readout schemes. CONCLUSION: The demonstrated gains hold promise for the widespread dissemination of advanced microstructural scans, especially in clinical populations.

In Vivo Myelin Water Quantification Using Diffusion-Relaxation Correlation MRI: A Comparison of 1D and 2D Methods.

Multidimensional Magnetic Resonance Imaging (MRI) is a versatile tool for microstructure mapping. We use a diffusion weighted inversion recovery spin echo (DW-IR-SE) sequence with spiral readouts at ultra-strong gradients to acquire a rich diffusion-relaxation data set with sensitivity to myelin water. We reconstruct 1D and 2D spectra with a two-step convex optimization approach and investigate a variety of multidimensional MRI methods, including 1D multi-component relaxometry, 1D multi-component diffusometry, 2D relaxation correlation imaging, and 2D diffusion-relaxation correlation spectroscopic imaging (DR-CSI), in terms of their potential to quantify tissue microstructure, including the myelin water fraction (MWF). We observe a distinct spectral peak that we attribute to myelin water in multi-component T1 relaxometry, T1-T2 correlation, T1-D correlation, and T2-D correlation imaging. Due to lower achievable echo times compared to diffusometry, MWF maps from relaxometry have higher quality. Whilst 1D multi-component T1 data allows much faster myelin mapping, 2D approaches could offer unique insights into tissue microstructure and especially myelin diffusion.

Practical considerations of diffusion-weighted MRS with ultra-strong diffusion gradients.

Introduction: Diffusion-weighted magnetic resonance spectroscopy (DW-MRS) offers improved cellular specificity to microstructure-compared to water-based methods alone-but spatial resolution and SNR is severely reduced and slow-diffusing metabolites necessitate higher b-values to accurately characterize their diffusion properties. Ultra-strong gradients allow access to higher b-values per-unit time, higher SNR for a given b-value, and shorter diffusion times, but introduce additional challenges such as eddy-current artefacts, gradient non-uniformity, and mechanical vibrations. Methods: In this work, we present initial DW-MRS data acquired on a 3T Siemens Connectom scanner equipped with ultra-strong (300 mT/m) gradients. We explore the practical issues associated with this manner of acquisition, the steps that may be taken to mitigate their impact on the data, and the potential benefits of ultra-strong gradients for DW-MRS. An in-house DW-PRESS sequence and data processing pipeline were developed to mitigate the impact of these confounds. The interaction of TE, b-value, and maximum gradient amplitude was investigated using simulations and pilot data, whereby maximum gradient amplitude was restricted. Furthermore, two DW-MRS voxels in grey and white matter were acquired using ultra-strong gradients and high b-values. Results: Simulations suggest T2-based SNR gains that are experimentally confirmed. Ultra-strong gradient acquisitions exhibit similar artefact profiles to those of lower gradient amplitude, suggesting adequate performance of artefact mitigation strategies. Gradient field non-uniformity influenced ADC estimates by up to 4% when left uncorrected. ADC and Kurtosis estimates for tNAA, tCho, and tCr align with previously published literature. Discussion: In conclusion, we successfully implemented acquisition and data processing strategies for ultra-strong gradient DW-MRS and results indicate that confounding effects of the strong gradient system can be ameliorated, while achieving shorter diffusion times and improved metabolite SNR.

Exploring the preparedness of newly qualified general practitioners for independent practice in Ireland.

BACKGROUND: Newly qualified general practitioners' (NQGPs) experiences of transition to independent practice are varied. Most Irish GP graduates see themselves as either assistant GPs, salaried GPs or locum GPs one year post-qualification, yet anticipate partnership ten years post-qualification. Research into GP trainees' transition to independent practice is scarce, yet perceived lack of preparedness can be associated with emotional exhaustion and burnout. AIMS: To explore NQGPs experience of their transition to independent practice in Ireland. METHODS: A qualitative approach was taken, using virtual, semi-structured, one-to-one interviews with NQGPs within five years of graduation, practising in Ireland. Descriptive demographics of participants were obtained. Audio recordings of interviews were analysed using thematic analysis. RESULTS: NQGPs reported preparedness for their clinical role, but most did not feel prepared for their non-clinical role. While NQGPs regarded independent practice as an intensive step-up from GP training, they drew on the support of GP colleagues during this transition. The decision on job selection centred largely on practice factors including location, ethos, support, and career prospects. Participants continued to develop in their identity as a GP within this transitionary period. CONCLUSION: This research provides a unique insight into the experiences of NQGPs in Ireland. Specialist GP training schemes are influential in how NQGPs perceive their preparedness for independent practice; however, external factors including  their place of work and alignment of professional goals play a part in this stage of NQGPs career.

Advances in Computational Approaches for Estimating Passive Permeability in Drug Discovery.

Passive permeation of cellular membranes is a key feature of many therapeutics. The relevance of passive permeability spans all biological systems as they all employ biomembranes for compartmentalization. A variety of computational techniques are currently utilized and under active development to facilitate the characterization of passive permeability. These methods include lipophilicity relations, molecular dynamics simulations, and machine learning, which vary in accuracy, complexity, and computational cost. This review briefly introduces the underlying theories, such as the prominent inhomogeneous solubility diffusion model, and covers a number of recent applications. Various machine-learning applications, which have demonstrated good potential for high-volume, data-driven permeability predictions, are also discussed. Due to the confluence of novel computational methods and next-generation exascale computers, we anticipate an exciting future for computationally driven permeability predictions.