Quantifying the Effects of Weapon Weight on Lethality through Holistic Modeling

Though it is widely known that weapon weight affects shooter stability, the quantitative effects on lethality and survivability are not well known. This issue stems from weapon lethality primarily being captured by equipment properties. A more holistic analysis can be performed by treating the soldier as a system by incorporating human factors with equipment performance specifications. This analysis requires the building of human factor models to appropriately capture lethality. The model development effort started with the collecting of data from experiments where the shot group accuracy was measured for weighted rifles. The resulting data was used to generate a mathematical model. This model, along with other human factor models, was integrated into the Weapon Lethality Service (WLS), a cloud-based simulation. The WLS was then set up to represent possible combat situations; the results were used to quantify the change in soldier lethality and survivability from changing the weapon weight

2-Deoxy-2[F-18]FDG-PET for Detection of Recurrent Laryngeal Carcinoma after Radiotherapy: Interobserver Variability in Reporting

Purpose: To evaluate accuracy and interobserver variability in the assessment of 2-deoxy-2[F-18]fluoro-d-glucose-positron emission tomography (FDG-PET) for detection of recurrent laryngeal carcinoma after radiotherapy. Procedures: Eleven experienced nuclear physicians from eight centres assessed 30 FDG-PET scans on the appearance of local recurrence (negative/equivocal/positive). Conservative (equivocal analysed as negative) and sensitive (equivocal analysed as positive) assessment strategies were compared to the reference standard (recurrence within 6months after PET). Results: Seven patients had proven recurrences. For the conservative and sensitive strategy, the mean sensitivity was 87% and 97%, specificity 81% and 63%, positive predictive values 61% and 46% and negative predictive values 96% and 99%, respectively. Interobserver variability showed a reasonable relation in comparison to the reference standard (kappa = 0.55). Conclusions: FDG-PET has acceptable interobserver agreement and yields good negative predictive value for detection of recurrent laryngeal carcinoma. It could therefore be used as first diagnostic step and may reduce futile invasive diagnostics

Kernel regression estimation of fiber orientation mixtures in Diffusion MRI

We present and evaluate a method for kernel regression estimation of fiber orientations and associated volume fractions for diffusion MR tractography and population-based atlas construction in clinical imaging studies of brain white matter. This is a model-based image processing technique in which representative fiber models are estimated from collections of component fiber models in model-valued image data. This extends prior work in nonparametric image processing and multi-compartment processing to provide computational tools for image interpolation, smoothing, and fusion with fiber orientation mixtures. In contrast to related work on multi-compartment processing, this approach is based on directional measures of divergence and includes data-adaptive extensions for model selection and bilateral filtering. This is useful for reconstructing complex anatomical features in clinical datasets analyzed with the ball-and-sticks model, and our framework’s data-adaptive extensions are potentially useful for general multi-compartment image processing. We experimentally evaluate our approach with both synthetic data from computational phantoms and in vivo clinical data from human subjects. With synthetic data experiments, we evaluate performance based on errors in fiber orientation, volume fraction, compartment count, and tractography-based connectivity. With in vivo data experiments, we first show improved scan-rescan reproducibility and reliability of quantitative fiber bundle metrics, including mean length, volume, streamline count, and mean volume fraction. We then demonstrate the creation of a multi-fiber tractography atlas from a population of 80 human subjects. In comparison to single tensor atlasing, our multi-fiber atlas shows more complete features of known fiber bundles and includes reconstructions of the lateral projections of the corpus callosum and complex fronto-parietal connections of the superior longitudinal fasciculus I, II, and III

A Comparative Evaluation of Voxel-based Spatial Mapping in Diffusion Tensor Imaging

This paper presents a comparative evaluation of methods for automated voxel-based spatial mapping in diffusion tensor imaging studies. Such methods are an essential step in computational pipelines and provide anatomically comparable measurements across a population in atlas-based studies. To better understand their strengths and weaknesses, we tested a total of eight methods for voxel-based spatial mapping in two types of diffusion tensor templates. The methods were evaluated with respect to scan-rescan reliability and an application to normal aging. The methods included voxel-based analysis with and without smoothing, two types of region-based analysis, and combinations thereof with skeletonization. The templates included a study-specific template created with DTI-TK and the IIT template serving as a standard template. To control for other factors in the pipeline, the experiments used a common dataset, acquired at 1.5T with a single shell high angular resolution diffusion MR imaging protocol, and tensor-based spatial normalization with DTI-TK. Scan-rescan reliability was assessed using the coefficient of variation (CV) and intraclass correlation (ICC) in eight subjects with three scans each. Sensitivity to normal aging was assessed in a population of 80 subjects aged 25 to 65 years old, and methods were compared with respect to the anatomical agreement of significant findings and the R(2) of the associated models of fractional anisotropy. The results show that reliability depended greatly on the method used for spatial mapping. The largest differences in reliability were found when adding smoothing and comparing voxel-based and region-based analyses. Skeletonization and template type were found to have either a small or negligible effect on reliability. The aging results showed agreement among the methods in nine brain areas, with some methods showing more sensitivity than others. Skeletonization and smoothing were not major factors affecting sensitivity to aging, but the standard template showed higher R(2) in several conditions. A structural comparison of the templates showed that large deformations between them may be related to observed differences in patterns of significant voxels. Most areas showed significantly higher R(2) with voxel-based analysis, particularly when clusters were smaller than the available regions-of-interest. Looking forward, these results can potentially help to interpret results from existing white matter imaging studies, as well as provide a resource to help in planning future studies to maximize reliability and sensitivity with regard to the scientific goals at hand

A Systems Approach for Analyzing Operational Energy Requirements for the Warfighter

Warfighters are carrying increasing amounts of electronics to provide them a tactical edge. These electronics are now imposing a substantial operational energy burden where missions are often constrained by energy requirements. Current operational energy analyses typically only look at the power draw of individual equipment. However, a systems approach more holistically captures these operational energy requirements. A system is defined to consist of the following three components: the soldier, their equipment, and the mission. This analysis then defines each component and then evaluates the interactions between them. These definitions and interactions are captured through a series of tables that can be built in Microsoft Excel which allows for tradespace analysis. This paper outlines this process and presents two case studies. The first case study evaluates adding energy harvesters to a dismounted rifle squad during a 72-hour movement to contact. The second case study evaluates adding a solar blanket to power electronics in a military vehicle during a 24-hour overwatch mission

Quantifying the Effects of Weapon Weight on Lethality through Holistic Modeling

Though it is widely known that weapon weight affects shooter stability, the quantitative effects on lethality and survivability are not well known. This issue stems from weapon lethality primarily being captured by equipment properties. A more holistic analysis can be performed by treating the soldier as a system by incorporating human factors with equipment performance specifications. This analysis requires the building of human factor models to appropriately capture lethality. The model development effort started with the collecting of data from experiments where the shot group accuracy was measured for weighted rifles. The resulting data was used to generate a mathematical model. This model, along with other human factor models, was integrated into the Weapon Lethality Service (WLS), a cloud-based simulation. The WLS was then set up to represent possible combat situations; the results were used to quantify the change in soldier lethality and survivability from changing the weapon weight