The human thorax is commonly injured in motor vehicle crashes, and despite advancements in occupant safety rib fractures are highly prevalent. The objective of this study was to quantify the ability of gross and cross-sectional geometry, separately and in combination, to explain variation of human rib structural properties. One hundred and twenty-two whole mid-level ribs from 76 fresh post-mortem human subjects were tested in a dynamic frontal impact scenario. Structural properties (peak force and stiffness) were successfully predicted (p<0.001) by rib cross-sectional geometry obtained via direct histological imaging (total area, cortical area, and section modulus) and were improved further when utilizing a combination of cross-sectional and gross geometry (robusticity, whole bone strength index). Additionally, preliminary application of a novel, adaptive thresholding technique, allowed for total area and robusticity to be measured on a subsample of standard clinical CT scans with varied success. These results can be used to understand variation in individual rib response to frontal loading as well as identify important geometric parameters, which could ultimately improve injury criteria as well as the biofidelity of anthropomorphic test devices (ATDs) and finite element (FE) models of the human thorax.
Static flexion-extension x-rays are the most common clinical tool used to assess abnormal motion of the cervical spine. Despite their widespread use (over 168,000 cases per year), the clinical efficacy of flexion-extension radiographs of the cervical spine has yet to be proven1. Limitations of static flexion-extension x-rays include data collection during static positions that may not accurately represent dynamic behavior, and the fact that data is collected at end range of motion positions, not in more frequently encountered mid-range positions. Consequently, static x-rays may not reveal movement abnormalities that occur during activities of daily living and lead to pain and degeneration. Therefore, it may be advantageous to analyze cervical spine kinematic data collected during dynamic, functional movements performed through an entire range of motion (not just the endpoints). Furthermore, the literature confirms there is substantial variability in “normal” range of motion and translation during flexion-extension1, making it difficult to reliably identify abnormal motion. Therefore, it may also be beneficial to evaluate alternative motion parameters that may reliably identify abnormal motion.
<div class="section abstract"><div class="htmlview paragraph">Knee airbags (KABs) are one countermeasure in newer vehicles that could influence lower extremity (LEX) injury, the most frequently injured body region in frontal crashes. To determine the effect of KABs on LEX injury for drivers in frontal crashes, the analysis examined moderate or greater LEX injury (AIS 2+) in two datasets. Logistic regression considered six main effect factors (KAB deployment, BMI, age, sex, belt status, driver compartment intrusion). Eighty-five cases with KAB deployment from the Crash Injury Research and Engineering Network (CIREN) database were supplemented with 8 cases from the International Center for Automotive Medicine (ICAM) database and compared to 289 CIREN non-KAB cases. All cases evaluated drivers in frontal impacts (11 to 1 o’clock Principal Direction of Force) with known belt use in 2004 and newer model year vehicles. Results of the CIREN/ICAM dataset were compared to analysis of a similar dataset from NASS-CDS (5441 total cases, 418 KAB-deployed). KABs were associated with a reduced rate of LEX injury in the CIREN/ICAM dataset (OR = 0.612, p=0.065), but were inconclusive in the NASS-CDS dataset (OR=0.946, p=0.761). KABs were associated with a reduced rate of knee/thigh/hip injury in CIREN/ICAM (OR = 0.555, p = 0.035) but had no measurable effect on below knee injury in CIREN/ICAM (OR = 0.928, p = 0.765) or NASS-CDS (OR=1.102, p=0.641). In conclusion, KABs were associated with reduced rates of LEX and knee/thigh/hip injury in the CIREN/ICAM dataset and had no measurable effect on below knee injury for drivers in frontal crashes in either dataset.</div></div>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.