Neonatal head and torso vibration exposure during inter-hospital transfer

Inter-hospital transport of premature infants is increasingly common, given the centralisation of neonatal intensive care. However, it is known to be associated with anomalously increased morbidity, most notably brain injury, and with increased mortality from multifactorial causes. Surprisingly, there have been relatively few previous studies investigating the levels of mechanical shock and vibration hazard present during this vehicular transport pathway. Using a custom inertial datalogger, and analysis software, we quantify vibration and linear head acceleration. Mounting multiple inertial sensing units on the forehead and torso of neonatal patients and a preterm manikin, and on the chassis of transport incubators over the duration of inter-site transfers, we find that the resonant frequency of the mattress and harness system currently used to secure neonates inside incubators is ~9Hz. This couples to vehicle chassis vibration, increasing vibration exposure to the neonate. The vibration exposure per journey (A(8) using the ISO 2631 standard) was at least 20% of the action point value of current European Union regulations over all 12 neonatal transports studied, reaching 70% in two cases. Direct injury risk from linear head acceleration (HIC15) was negligible. Although the overall hazard was similar, vibration isolation differed substantially between sponge and air mattresses, with a manikin. Using a Global Positioning System datalogger alongside inertial sensors, vibration increased with vehicle speed only above 60 km/h. These preliminary findings suggest there is scope to engineer better systems for transferring sick infants, thus potentially improving their outcomes

End to end stroke triage using cerebrovascular morphology and machine learning

Background: Rapid and accurate triage of acute ischemic stroke (AIS) is essential for early revascularization and improved patient outcomes. Response to acute reperfusion therapies varies significantly based on patient-specific cerebrovascular anatomy that governs cerebral blood flow. We present an end-to-end machine learning approach for automatic stroke triage. Methods: Employing a validated convolutional neural network (CNN) segmentation model for image processing, we extract each patient’s cerebrovasculature and its morphological features from baseline non-invasive angiography scans. These features are used to detect occlusion’s presence and the site automatically, and for the first time, to estimate collateral circulation without manual intervention. We then use the extracted cerebrovascular features along with commonly used clinical and imaging parameters to predict the 90 days functional outcome for each patient. Results: The CNN model achieved a segmentation accuracy of 94% based on the Dice similarity coefficient (DSC). The automatic stroke detection algorithm had a sensitivity and specificity of 92% and 94%, respectively. The models for occlusion site detection and automatic collateral grading reached 96% and 87.2% accuracy, respectively. Incorporating the automatically extracted cerebrovascular features significantly improved the 90 days outcome prediction accuracy from 0.63 to 0.83. Conclusion: The fast, automatic, and comprehensive model presented here can improve stroke diagnosis, aid collateral assessment, and enhance prognostication for treatment decisions, using cerebrovascular morphology. Copyright © 2023 Deshpande, Elliott, Jiang, Tahsili-Fahadan, Kidwell, Wintermark and Laksari.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Neuroimaging, wearable sensors, and blood-based biomarkers reveal hyperacute changes in the brain after sub-concussive impacts

Impacts in mixed martial arts (MMA) have been studied mainly in regard to the long-term effects of concussions. However, repetitive sub-concussive head impacts at the hyperacute phase (minutes after impact), are not understood. The head experiences rapid acceleration similar to a concussion, but without clinical symptoms. We utilize portable neuroimaging technology – transcranial Doppler (TCD) ultrasound and functional near infrared spectroscopy (fNIRS) – to estimate the extent of pre- and post-differences following contact and non-contact sparring sessions in nine MMA athletes. In addition, the extent of changes in neurofilament light (NfL) protein biomarker concentrations, and neurocognitive/balance parameters were determined following impacts. Athletes were instrumented with sensor-based mouth guards to record head kinematics. TCD and fNIRS results demonstrated significantly increased blood flow velocity (p = 0.01) as well as prefrontal (p = 0.01) and motor cortex (p = 0.04) oxygenation, only following the contact sparring sessions. This increase after contact was correlated with the cumulative angular acceleration experienced during impacts (p = 0.01). In addition, the NfL biomarker demonstrated positive correlations with angular acceleration (p = 0.03), and maximum principal and fiber strain (p = 0.01). On average athletes experienced 23.9 ± 2.9 g peak linear acceleration, 10.29 ± 1.1 rad/s peak angular velocity, and 1,502.3 ± 532.3 rad/s2 angular acceleration. Balance parameters were significantly increased following contact sparring for medial-lateral (ML) center of mass (COM) sway, and ML ankle angle (p = 0.01), illustrating worsened balance. These combined results reveal significant changes in brain hemodynamics and neurophysiological parameters that occur immediately after sub-concussive impacts and suggest that the physical impact to the head plays an important role in these changes. Statement of significance: : Brain injuries sustained during sport participation have received much attention since it is a common occurrence among participants. Although protective technologies have been developed over the years, the mechanism of injury is still unclear. There is less focus on the repetitive exposure to sub-concussive impacts on the functional integrity of the brain. Sub-concussive impacts are defined as a lesser impact force resulting in acceleration of the head without symptoms of concussion. Diminished neurocognitive performance has been associated with increased sparring exposure in amateur MMA/boxers suggesting that repeated sub-concussive blows may be just as harmful. However, no one has studied the potential effect of repeated sub-concussive head impacts at the hyperacute level defined as within minutes after impact. We apply novel mobile sensing tools such as head impact sensors and portable neuroimaging devices that allow us to examine possible physiological effects taking place within minutes of sub-concussive impacts which are generally transient, and have not been captured before due to limitations with clinical imaging. Based on previous studies, we developed a protocol to test real-world sub-concussive head impact effects on cerebral blood flow and activation patterns and demonstrate that significant changes can be observed immediately after impacts occur, which could lead to improved monitoring and management of injury risk in sport participation. © 2023 The AuthorsOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Ultrasound, photoacoustic, and magnetic resonance imaging to study hyperacute pathophysiology of traumatic and vascular brain injury

Background and Purpose: Cerebrovascular dynamics and pathomechanisms that evolve in the minutes and hours following traumatic vascular injury in the brain remain largely unknown. We investigated the pathophysiology evolution in mice within the first 3 hours after closed-head traumatic brain injury (TBI) and subarachnoid hemorrhage (SAH), two significant traumatic vascular injuries. Methods: We took a multimodal imaging approach using photoacoustic imaging, color Doppler ultrasound, and MRI to track injury outcomes using a variety of metrics. Results: Brain oxygenation and velocity-weighted volume of blood flow (VVF) values significantly decreased from baseline to 15 minutes after both TBI and SAH. TBI resulted in 19.2% and 41.0% ipsilateral oxygenation and VVF reductions 15 minutes postinjury, while SAH resulted in 43.9% and 85.0% ipsilateral oxygenation and VVF reduction (p <.001). We found partial recovery of oxygenation from 15 minutes to 3 hours after injury for TBI but not SAH. Hemorrhage, edema, reduced perfusion, and altered diffusivity were evident from MRI scans acquired 90-150 minutes after injury in both injury models, although the spatial distribution was mostly focal for TBI and diffuse for SAH. Conclusions: The results reveal that the cerebral oxygenation deficits immediately following injuries are reversible for TBI and irreversible for SAH. Our findings can inform future studies on mitigating these early responses to improve long-term recovery. © 2023 The Authors. Journal of Neuroimaging published by Wiley Periodicals LLC on behalf of American Society of Neuroimaging.Open access articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Automatic segmentation, feature extraction and comparison of healthy and stroke cerebral vasculature.

Accurate segmentation of cerebral vasculature and a quantitative assessment of its morphology is critical to various diagnostic and therapeutic purposes and is pertinent to studying brain health and disease. However, this is still a challenging task due to the complexity of the vascular imaging data. We propose an automated method for cerebral vascular segmentation without the need of any manual intervention as well as a method to skeletonize the binary segmented map to extract vascular geometric features and characterize vessel structure. We combine a Hessian-based probabilistic vessel-enhancing filtering with an active-contour-based technique to segment magnetic resonance and computed tomography angiograms (MRA and CTA) and subsequently extract the vessel centerlines and diameters to calculate the geometrical properties of the vasculature. Our method was validated using a 3D phantom of the Circle-of-Willis region, demonstrating 84% mean Dice similarity coefficient (DSC) and 85% mean Pearson's correlation coefficient (PCC) with minimal modified Hausdorff distance (MHD) error (3 surface pixels at most), and showed superior performance compared to existing segmentation algorithms upon quantitative comparison using DSC, PCC and MHD. We subsequently applied our algorithm to a dataset of 40 subjects, including 1) MRA scans of healthy subjects (n = 10, age = 30 ± 9), 2) MRA scans of stroke patients (n = 10, age = 51 ± 15), 3) CTA scans of healthy subjects (n = 10, age = 62 ± 12), and 4) CTA scans of stroke patients (n = 10, age = 68 ± 11), and obtained a quantitative comparison between the stroke and normal vasculature for both imaging modalities. The vascular network in stroke patients compared to age-adjusted healthy subjects was found to have a significantly (p &lt; 0.05) higher tortuosity (3.24 ± 0.88 rad/cm vs. 7.17 ± 1.61 rad/cm for MRA, and 4.36 ± 1.32 rad/cm vs. 7.80 ± 0.92 rad/cm for CTA), higher fractal dimension (1.36 ± 0.28 vs. 1.71 ± 0.14 for MRA, and 1.56 ± 0.05 vs. 1.69 ± 0.20 for CTA), lower total length (3.46 ± 0.99 m vs. 2.20 ± 0.67 m for CTA), lower total volume (61.80 ± 18.79 ml vs. 34.43 ± 22.9 ml for CTA), lower average diameter (2.4 ± 0.21 mm vs. 2.18 ± 0.07 mm for CTA), and lower average branch length (4.81 ± 1.97 mm vs. 8.68 ± 2.03 mm for MRA), respectively. We additionally studied the change in vascular features with respect to aging and imaging modality. While we observed differences between features as a result of aging, statistical analysis did not show any significant differences, whereas we found that the number of branches were significantly different (p &lt; 0.05) between the two imaging modalities (201 ± 73 for MRA vs. 189 ± 69 for CTA). Our segmentation and feature extraction algorithm can be applied on any imaging modality and can be used in the future to automatically obtain the 3D segmented vasculature for diagnosis and treatment planning as well as to study morphological changes due to stroke and other cerebrovascular diseases (CVD) in the clinic

Palmitoylethanolamide as adjunctive therapy for autism: Efficacy and safety results from a randomized controlled trial

Inflammation as well as glutamate excitotoxicity have been proposed to participate in the propagation of autism. Palmitoylethanolamide (PEA) is an endocannabinoid proven to prevent glutamatergic toxicity and inhibit inflammatory responses simultaneously. The present randomized, parallel group, double-blind placebo-controlled trial is the first study depicted to probe the efficacy of co-treatment with risperidone and PEA over 10 weeks in children with autism. Seventy children (aged 4�12 years) with autism and moderate to severe symptoms of irritability were randomly assigned to two treatment regimens. The study outcomes were measured using the Aberrant Behavior Checklist-Community Edition (ABC-C). At trial endpoint (week 10), combination of PEA and risperidone had superior efficacy in ameliorating the ABC-irritability and hyperactivity/noncompliance symptoms (Cohen's d, 95 confidence interval (CI) = 0.94, 0.41 to 1.46, p = 0.001) compared with a risperidone plus placebo regimen. Interestingly, effect of combination treatment on hyperactivity symptoms was also observed at trial midpoint (week 5) but with a smaller effect size (d = 0.53, p = 0.04) than that at the endpoint (d = 0.94, p = 0.001). Meanwhile, there was a trend toward significance for superior effect of risperidone plus PEA over risperidone plus placebo on inappropriate speech at trial endpoint (d = 0.51, p = 0.051). No significant differences existed between the two treatment groups for the other two ABC-C subscales (lethargy/social withdrawal and stereotypic behavior). The findings suggest that PEA may augment therapeutic effects of risperidone on autism-related irritability and hyperactivity. Future studies are warranted to investigate whether PEA can serve as a stand-alone treatment for autism. © 2018 Elsevier Lt