Thoracoabdominal Organ Volumes for Small Women

<div><p><b>Objective:</b> Thoracoabdominal injuries commonly occur as a result of motor vehicle crashes. In order to design occupant protection systems that reduce risk of injury, researchers are using a variety of tools, including computational human body models. Though research has been conducted to provide morphological and volumetric data for the thoracoabdominal cavity of the average male, there is currently an interest in developing models for a wider range of occupants. One particular cohort of interest is the small female by stature and weight because of their use in restraint system development. Geometric data on thoracoabdominal organs are needed to construct accurate representations of female occupants. This study aimed to gather information on organ volumes from clinical medical imaging studies of small females.</p><p><b>Methods:</b> Anonymized clinical computed tomography (CT) and magnetic resonance images were used to segment organs relevant to crash-induced injuries: namely, the liver, spleen, left kidney, right kidney, pancreas, gallbladder, lungs, and heart. Segmentations were conducted using semi-automatic techniques. Additionally, diametric measurements of the vena cava, aorta, trachea, and colon were obtained from the medical images at discrete locations using linear measurement tools.</p><p><b>Results:</b> A total of 14 adult scans were selected with stature and weight ranges of 145.0 to 162.6 cm and 43.7 to 65.5 kg, respectively. The following are the average thoracoabdominal organ volumes: liver (1,224.5 ± 220.7 mL), spleen (151.6 ± 42.1 mL), left kidney (123.7 ± 20.1 mL), right kidney (115.4 ± 20.9 mL), heart (417.8 ± 36.6 mL), pancreas (54.1 ± 11.8 mL), and gallbladder (20.6 ± 13.4 mL). The average diameters were 19.7 ± 3.2 mm and 17.7 ± 5.1 mm for the vena cava and aorta, respectively. The colon had an average diameter of 37.9 ± 7.1 mm.</p><p><b>Conclusion:</b> Data characterizing the small female are important to validate the geometries used in computational models, including models derived from scaling techniques and those developed using subject-specific medical imaging. The goal of this study was to use a sample of subjects anthropometrically representative of small females to evaluate the average volume for organs commonly injured in motor vehicle crashes. Based on these data, the right and left lungs were strongly correlated with stature and the heart was strongly correlated with weight. Ultimately, these measurements will be useful for the validation of computational models of the small female.</p></div

Modular use of human body models of varying levels of complexity: Validation of head kinematics

<p><b>Objective</b>: The significant computational resources required to execute detailed human body finite-element models has motivated the development of faster running, simplified models (e.g., GHBMC M50-OS). Previous studies have demonstrated the ability to modularly incorporate the validated GHBMC M50-O brain model into the simplified model (GHBMC M50-OS+B), which allows for localized analysis of the brain in a fraction of the computation time required for the detailed model. The objective of this study is to validate the head and neck kinematics of the GHBMC M50-O and M50-OS (detailed and simplified versions of the same model) against human volunteer test data in frontal and lateral loading. Furthermore, the effect of modular insertion of the detailed brain model into the M50-OS is quantified.</p> <p><b>Methods</b>: Data from the Navy Biodynamics Laboratory (NBDL) human volunteer studies, including a 15<i>g</i> frontal, 8<i>g</i> frontal, and 7<i>g</i> lateral impact, were reconstructed and simulated using LS-DYNA. A five-point restraint system was used for all simulations, and initial positions of the models were matched with volunteer data using settling and positioning techniques. Both the frontal and lateral simulations were run with the M50-O, M50-OS, and M50-OS+B with active musculature for a total of nine runs.</p> <p><b>Results</b>: Normalized run times for the various models used in this study were 8.4 min/ms for the M50-O, 0.26 min/ms for the M50-OS, and 0.97 min/ms for the M50-OS+B, a 32- and 9-fold reduction in run time, respectively. Corridors were reanalyzed for head and T1 kinematics from the NBDL studies. Qualitative evaluation of head rotational accelerations and linear resultant acceleration, as well as linear resultant T1 acceleration, showed reasonable results between all models and the experimental data. Objective evaluation of the results for head center of gravity (CG) accelerations was completed via ISO TS 18571, and indicated scores of 0.673 (M50-O), 0.638 (M50-OS), and 0.656 (M50-OS+B) for the 15<i>g</i> frontal impact. Scores at lower <i>g</i> levels yielded similar results, 0.667 (M50-O), 0.675 (M50-OS), and 0.710 (M50-OS+B) for the 8<i>g</i> frontal impact. The 7<i>g</i> lateral simulations also compared fairly with an average ISO score of 0.565 for the M50-O, 0.634 for the M50-OS, and 0.606 for the M50-OS+B. The three HBMs experienced similar head and neck motion in the frontal simulations, but the M50-O predicted significantly greater head rotation in the lateral simulation.</p> <p><b>Conclusion</b>: The greatest departure from the detailed occupant models were noted in lateral flexion, potentially indicating the need for further study. Precise modeling of the belt system however was limited by available data. A sensitivity study of these parameters in the frontal condition showed that belt slack and muscle activation have a modest effect on the ISO score. The reduction in computation time of the M50-OS+B reduces the burden of high computational requirements when handling detailed HBMs. Future work will focus on harmonizing the lateral head response of the models and studying localized injury criteria within the brain from the M50-O and M50-OS+B.</p

MMP-9 inhibitor 1 and melatonin pretreatment attenuates IL-1β treatment- induced MMP-9 activity.

<p>MMP-9 inhibitor 1 (n = 4) and melatonin (n = 5) pretreatment attenuated IL-1β treatment-induced MMP-9 activity in RBMECs. MMP-9 activity is expressed as relative fluorescence units (RFU), plotted on the Y-axis. Data are expressed as mean ± SEM. ‘*a’ indicates significant increase compared to the control group; ‘*b’ indicates significant decrease compared to the IL-1β (10 ng/mL; 2 hours) treatment group. <i>p</i><0.05 was considered statistically significant.</p

IL-1β treatment induces dose and time dependent increase in monolayer hyperpermeability.

<p>In Panel A, IL-1β treatment at doses 10, 50 and 100 ng/mL for 2 hours are shown to significantly increase BBB permeability compared to the control group (n = 4; <i>p</i><0.05). Panel B indicates significant increase in IL-1β induced BBB permeability at 2, 3 and 4 hours compared to the control (n = 4; <i>p</i><0.05). Monolayer permeability is expressed as a percentage control of FITC-dextran-10 kDa fluorescent intensity, plotted on the Y-axis. Data are expressed as mean ± % SEM. ‘*a’ indicates significant increase compared to the control group.</p

Melatonin Preserves Blood-Brain Barrier Integrity and Permeability via Matrix Metalloproteinase-9 Inhibition - Fig 9

<p>Melatonin pretreatment attenuates TBI-induced BBB hyperpermeability studied by Evans blue dye extravasation method (Panel A). Pictorial representation of the brain tissue from various groups is shown in Panel 9B. Sham injury group was used as the baseline for all comparisons. Melatonin (10 μg/gram body weight of the animal) pretreatment significantly attenuated TBI-induced Evans blue leakage into the extravascular tissue space (<i>p</i><0.05). Animals were divided into sham (n = 6), vehicle + sham (n = 6), vehicle + TBI (n = 5) and melatonin + TBI (n = 6). Data are expressed as ng/brain cortex ± SEM. ‘*’ indicates statistical significance. ‘a’ indicates significant increase compared to the sham injury/vehicle + sham injury group and ‘b’ indicates significant decrease compared to the vehicle + TBI group.</p

IL-1β treatment does not induce cell death.

<p>IL-1β (10 ng/mL; 2 hours) treatment had no effect on cell viability (n = 5). Hydrogen peroxide (used as a positive control) treatment decreases cell viability significantly (<i>p<</i>0.05). Data are expressed as mean ± % SEM. ‘*’ indicates statistical significance. ‘*a’ indicates significant decrease compared to the control group.</p

GM6001, MMP-9 inhibitor 1 and melatonin pretreatment attenuates IL-1β treatment-induced monolayer hyperpermeability.

<p>Panel A indicates the effect of GM6001 (broad-spectrum MMP inhibitor; n = 4); while Panels B and C employ MMP-9 specific inhibitors: MMP-9 inhibitor 1 (n = 4) and melatonin (n = 6) pretreatment on IL-1β (10 ng/mL; 2 hours)—induced monolayer hyperpermeability. Monolayer permeability is expressed as a percentage control of FITC-dextran-10 kDa fluorescence intensity, plotted on the Y-axis. Data are expressed as mean ± % SEM. ‘*a’ indicates significant increase compared to control group; ‘*b’ indicates significant decrease compared to the IL-1β treated group. <i>p</i><0.05 was considered statistically significant.</p

Knockdown of MMP-9 by siRNA attenuates IL-1β treatment-induced monolayer hyperpermeability.

<p>Monolayer permeability is expressed as percentage flux of FITC-dextran-10 kDa fluorescence intensity, plotted on the Y-axis. Data are expressed as mean ± % SEM. ‘*a’ indicates significant increase compared to the control group; ‘*b’ indicates significant decrease compared to the IL-1β (10 ng/mL; 2 hours) treatment group. siRNA transfected groups were compared to control siRNA transfected group (n = 4; p<0.05).</p

MMP-9 inhibitor 1 and melatonin pretreatment protects against IL-1β treatment-induced loss of ZO-1 junctional integrity.

<p>IL-1β (10 ng/mL; 2 hours) treatment-induced ZO-1 junctional disruption (white arrows) was decreased on pretreatment with MMP-9 inhibitor 1 (n = 4) and melatonin (n = 4).</p

IL-1β treatment does not induce ZO-1 mRNA or protein expression.

<p>IL-1β (10 ng/mL; 2 hours) treatment neither induces ZO-1/MMP-9 mRNA expression (n = 3) nor alter ZO-1 protein expression (n = 4). RT-PCR data plotted on the Y-axis are expressed as relative expression of ZO-1 normalized to GAPDH. Data are represented as mean ± SEM.</p