Apparent diffusion coefficients for differentiation of cerebellar tumors in children.

BACKGROUND AND PURPOSE: Diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) maps provide information at MR imaging that may reflect cell attenuation and integrity. We hypothesized that cerebellar tumors in children can be differentiated by their ADC values. METHODS: Brain MR imaging studies that included ADC maps were retrospectively reviewed in 32 patients with histologically proved cerebellar neoplasm. There were 17 juvenile pilocytic astrocytomas (JPA), 8 medulloblastomas, 5 ependymomas, and 2 rhabdoid (atypical teratoid/rhabdoid tumor [AT/RT]) tumors. Absolute ADC values of contrast-enhancing solid tumor regions and ADC ratios (ADC of solid tumor to ADC of normal-appearing white matter) were compared with the histologic diagnosis. ADC values and ratios of JPAs, medulloblastomas, and ependymomas were compared by using a 2-tailed t test and one-way analysis of variance (ANOVA). RESULTS: ADC values were significantly higher in pilocytic astrocytomas (1.65 +/- 0.27) (mean +/- SD) than in ependymomas (1.10 +/- 0.11) (P = .0003) and medulloblastomas (0.66 +/- 0.15) (P < .0001). Ependymomas demonstrated significantly higher ADC values than medulloblastomas (P = .0005). The observed differences were statistically significant on ANOVA (P < .001). ADC ratios were also significantly different among these 3 tumor types. AT/RT ADC values were similar to medulloblastoma. The range of ADC values and ratios within JPAs and ependymomas did not overlap with that of medulloblastomas. CONCLUSION: Assessment of ADC values of enhancing solid tumor is a simple and reliable technique for preoperative differentiation of cerebellar tumors in pediatric patients. Our cutoff values of >1.4 x 10(3) mm(2)/s for JPA and <0.9 x 10(3) mm(2)/s for medulloblastoma were 100% specific.

The influence of surface padding properties on head and neck injury risk.

A validated computational head-neck model was used to understand the mechanical relationships between surface padding characteristics and injury risk during impacts near the head vertex. The study demonstrated that injury risk can be decreased by maximizing the energy-dissipating ability of the pad, choosing a pad stiffness that maximizes pad deformation without bottoming out, maximizing pad thickness, and minimizing surface friction. That increasing pad thickness protected the head without increasing neck loads suggests that the increased cervical spine injury incidence previously observed in cadaveric impacts to padded surfaces relative to lubricated rigid surfaces was due to increased surface friction rather than pocketing of the head in the pad.

Inertial properties and loading rates affect buckling modes and injury mechanisms in the cervical spine.

Cervical spine injuries continue to be a costly societal problem. Future advancements in injury prevention depend on improved physical and computational models which, in turn, are predicated on a better understanding of the responses of the neck during dynamic loading. Previous studies have shown that the tolerance of the neck is dependent on its initial position and its buckling behavior. This study uses a computational model to examine the mechanical factors influencing buckling behavior during impact to the neck. It was hypothesized that the inertial properties of the cervical spine influence the dynamics during compressive axial loading. The hypothesis was tested by performing parametric analyses of vertebral mass, mass moments of inertia, motion segment stiffness, and loading rate. Increases in vertebral mass resulted in increasingly complex kinematics and larger peak loads and impulses. Similar results were observed for increases in stiffness. Faster loading rates were associated with higher peak loads and higher-order buckling modes. The results demonstrate that mass has a great deal of influence on the buckling behavior of the neck, particularly with respect to the expression of higher-order modes. Injury types and mechanisms may be substantially altered by loading rate because inertial effects may influence whether the cervical spine fails in a compressive mode, or a bending mode.

Tensile properties of the human muscular and ligamentous cervical spine.

Tensile neck injuries are amongst the most serious cervical injuries. However, because neither reliable human cervical tensile tolerance data nor tensile structural data are currently available, the quantification of tensile injury risk is limited. The purpose of this study is to provide previously unavailable kinetic and tolerance data for the ligamentous cervical spine and determine the effect of neck muscle on tensile load response and tolerance. Using six male human cadaver specimens, isolated ligamentous cervical spine tests (occiput - T1) were conducted to quantify the significant differences in kinetics due to head end condition and anteroposterior eccentricity of the tensile load. The spine was then separated into motion segments for tension failure testing. The upper cervical spine tolerance of 2400 +/- 270 N (occiput-C2) was found to be significantly greater (p < 0.01) than the lower cervical spine tolerance of 1780 +/- 230 N (C4-C5 and C6-C7 segments). Data from these experiments were used to develop and validate a computational model of the ligamentous spine. The model predicted the end condition and eccentricity responses for the tensile force-displacement relationship. Cervical muscular geometry data derived from cadaver dissection and MRI imaging were used to incorporate a muscular response into the model. The cervical musculature under maximal stimulation increased the tolerance of the cervical spine from 1800 N to 4160 N. In addition, the cervical musculature resulted in a shift in the site of injury from the lower cervical spine to the upper cervical spine and offers an explanation for the mechanism of upper cervical spine tension injuries observed clinically. The results from this study predict a range in tensile tolerance from 1.8 - 4.2 kN based on the varying role of the cervical musculature.

Surface friction in near-vertex head and neck impact increases risk of injury.

A computational head-neck model was developed to test the hypothesis that increases in friction between the head and impact surface will increase head and neck injury risk during near-axial impact. The model consisted of rigid vertebrae interconnected by assemblies of nonlinear springs and dashpots, and a finite element shell model of the skull. For frictionless impact surfaces, the model reproduced the kinematics and kinetics observed in near-axial impacts to cadaveric head-neck specimens. Increases in the coefficient of friction between the head and impact surface over a range from 0.0 to 1.0 resulted in increases of up to 40, 113, 9.8, and 43% in peak post-buckled resultant neck forces, peak moment at the occiput-C1 joint, peak resultant head accelerations, and HIC values, respectively. The most dramatic increases in injury-predicting quantities occurred for COF increases from 0.0 to 0.2, while further COF increases above 0.5 generally produced only nominal changes. These data suggest that safety equipment and impact environments which minimize the friction between the head and impact surface may reduce the risk of head and neck injury in near-vertex head impact.

An improved method for finite element mesh generation of geometrically complex structures with application to the skullbase.

An automated method has been developed to generate finite element meshes of geometrically complex structures from CT images using solely hexahedral elements. This technique improves upon previous voxel-based mesh reconstruction approaches by smoothing the irregular boundaries at model surfaces and material interfaces. Over a range of mesh densities, RMS error in surface Von Mises stress was higher in the unsmoothed circular ring models (0.11-0.24 MPa) than in the smoothed models (0.080-0.15 MPa) at each mesh density. The element-to-element oscillation in surface element stress, as measured by the average second spatial derivative of Von Mises stress along the outer surface of the ring, was higher in the unsmoothed models (11.5-15.0 kPa mm-2) than in the smoothed models (4.0-6.8 kPa mm-2). Similarly, in a human skullbase model, the element-to-element oscillation in surface Von Mises stress was higher in the unsmoothed model (5.52 kPa mm-2) than in the smoothed model (1.83 kPa mm-2). Using this technique, finite element models of complex geometries can be rapidly reconstructed which produce less error at the surface than voxel-based models with discontinuous surfaces.