Morphology and Composition of Lumbar Intervertebral Discs: Comparative Analyses of Manual Measurement and Computer-Assisted Algorithms.

BACKGROUND: The morphology and internal composition, particularly the nucleus-to-cross sectional area (NP-to-CSA) ratio of the lumbar intervertebral discs (IVDs), is important information for finite element models (FEMs) of spinal loadings and biomechanical behaviors, and, yet, this has not been well investigated and reported. METHODS: Anonymized MRI scans were retrieved from a previously established database, including a total of 400 lumbar IVDs from 123 subjects (58 F and 65 M). Measurements were conducted manually by a spine surgeon and using two computer-assisted segmentation algorithms, i.e., fuzzy C-means (FCM) and region growing (RG). The respective results were compared. The influence of gender and spinal level was also investigated. RESULTS: Ratios derived from manual measurements and the two computer-assisted algorithms (FCM and RG) were 46%, 39%, and 38%, respectively. Ratios derived manually were significantly larger. CONCLUSIONS: Computer-assisted methods provide reliable outcomes that are traditionally difficult for the manual measurement of internal composition. FEMs should consider the variability of NP-to-CSA ratios when studying the biomechanical behavior of the spine.

Safety sign comprehension of fiberboard industry employees.

Safety signs are very important communication tools for accident prevention, fire safety, health hazard information, and emergency evacuation. They are helpful when properly designed and understood by employees. The purpose of the present study was to investigate fiberboard industry employees' understanding of safety signs. 139 participants were asked to indicate the meaning of a series of 22 commonly used safety signs. The mean comprehension score for 22 signs was 66.6% (min. 22.5% and max. 98.6%). The mean score for warning signs was the lowest, prohibition signs was the highest. Poor comprehension score (less than 40%) was noted for the toxic material, automated external heart defibrillator, overhead obstacle, and disconnect mains plug from electrical outlet signs. These low comprehension scores indicate that some symbols may not effectively convey the message to the audience. Safety practitioners and trainers should pay more attention to teach the actual meaning of those signs.

Validation of a pre-existing safety climate scale for the Turkish furniture manufacturing industry.

Understanding the safety climate level is essential to implement a proactive safety program. The objective of this study is to explore the possibility of having a safety climate scale for the Turkish furniture manufacturing industry since there has not been any scale available. The questionnaire recruited 783 subjects. Confirmatory factor analysis (CFA) tested a pre-existing safety scale's fit to the industry. The CFA indicated that the structures of the model present a non-satisfactory fit with the data (χ 2 = 2033.4, df = 314, p ≤ 0.001; root mean square error of approximation = 0.08, normed fit index = 0.65, Tucker-Lewis index = 0.65, comparative fit index = 0.69, parsimony goodness-of-fit index = 0.68). The results suggest that a new scale should be developed and validated to measure the safety climate level in the Turkish furniture manufacturing industry. Due to the hierarchical structure of organizations, future studies should consider a multilevel approach in their exploratory factor analyses while developing a new scale.

Regression Models for the Erector Spinae Muscle Mass (ESMM) Cross-Sectional Area: Asymptomatic Populations.

Understanding low back muscle morphology is critical to understanding spinal loading and the underlying injury mechanisms, which help in characterizing risk and, therefore, minimize low back pain injuries. Individualized erector spinae muscle mass (ESMM) cross-sectional area (CSA) allows biomechanics practitioners to calculate individualized force generating capacities and spinal loadings for given tasks. The objective is to perform morphological analyses and then provide regression models to estimate the ESMM CSA of an individual with his/her subject characteristics. Thirty-five subjects (13 females and 22 males) without low back pain (LBP) history were included in this magnetic resonance imaging (MRI) study. Axial-oblique scans of low back region were used to measure the ESMM CSA. Subject demographics and anthropometrics were obtained and regressed over the ESMM CSA. Best-subset regression analyses were performed. Lean body mass (LBM) and the ankle, wrist, and head indexes were the most frequent predictive variables. Regression models with easy-to-measure variables showed smaller predictive power and increased estimation error compared to other regression models. Practitioners should consider this trade-off between model accuracy and complexity. An individual's ESMM CSA could be estimated by his/her individual characteristics, which enables biomechanical practitioners to estimate individualized low back force capacity and spinal loading.

Morphometry of the lower lumbar intervertebral discs and endplates: comparative analyses of new MRI data with previous findings.

PURPOSE: Variability of the human lower lumbar geometry is related to complications of disc arthroplasty surgery. Accurate morphometric descriptions are essential for the design of artificial intervertebral discs to ensure good prothesis-vertebra contact and better load distribution, and can improve spinal biomechanics. Unfortunately, current knowledge of the lower lumbar geometry is limited either in the representativeness of sample populations or the accuracy and comprehensiveness of measurements. The objective of this study was to establish an accurate and reliable measurement protocol, provide a comprehensive database of lower lumbar geometry, and compare and summarize geometric data as reported in the literature. METHODS: T2-weighted magnetic resonance imaging (MRI) scans of lower lumbar spine (L3-S1), taken from 109 adult subjects, were anonymized from the digital archive of a local hospital. A total of 318 intervertebral discs and 590 endplates met the inclusion criteria and were studied. Linear and planar measurements were performed using OsiriX software, and analyzed using split plot factorial (SPF) analysis of variance (ANOVA), independent student t tests, paired sample t tests, and Tukey's honest significant difference (HSD) post hoc tests. RESULTS: Excellent intra- and inter-observer reliabilities were achieved using the proposed measurement protocol. The results of this study indicated that male subjects had significantly larger geometric dimensions. L5/S1 discs had the smallest geometric dimensions compared to the discs at other two levels. Significant craniocaudal differences were found in endplate morpohometry. The error associated with using ellipsoid methods was quantified at each lower lumbar level. A large comprehensive database compiling lower lumbar geometry from many studies was established. This study provides geometric data for the female subjects at the L5/S1 level, previously lacking in the literature. CONCLUSION: This study demonstrates the potential of using MRI data to establish a standard measurement protocol for morphometric quantification of the lower lumbar intervertebral discs and vertebral endplates. These results are invaluable in characterizing comprehensive lower lumbar morphometry, which may provide crucial information for planning spinal surgeries, designing artificial intervertebral discs, and for biomechanical modeling of the low lack.

Prediction models for the erector spinae muscle cross-sectional area.

Accurate and reliable "individualized" low back erector spinae muscle (ESM) data are of importance to estimate its force producing capacity. Knowing the force producing capacity, along with spinal loading, enhances the understanding of low back injury mechanisms. The objective of this study was to build regression models to estimate the ESM cross-sectional area (CSA). Measurements were taken from axial-oblique magnetic resonance imaging (MRI) scans of a large historical population [54 females and 53 males at L3/L4, 50 females and 44 males at L4/L5, and 41 females and 35 males at L5/S1 levels]. Results suggest that an individual's ESM CSA can be accurately estimated based on his/her gender, height, and weight. Results further show that there is no significant difference between the measured and estimated ESM CSAs, and expected absolute error is less than 15%.