Spatial assessments in texture analysis: what the radiologist needs to know

To date, studies investigating radiomics-based predictive models have tended to err on the side of data-driven or exploratory analysis of many thousands of extracted features. In particular, spatial assessments of texture have proven to be especially adept at assessing for features of intratumoral heterogeneity in oncologic imaging, which likewise may correspond with tumor biology and behavior. These spatial assessments can be generally classified as spatial filters, which detect areas of rapid change within the grayscale in order to enhance edges and/or textures within an image, or neighborhood-based methods, which quantify gray-level differences of neighboring pixels/voxels within a set distance. Given the high dimensionality of radiomics datasets, data dimensionality reduction methods have been proposed in an attempt to optimize model performance in machine learning studies; however, it should be noted that these approaches should only be applied to training data in order to avoid information leakage and model overfitting. While area under the curve of the receiver operating characteristic is perhaps the most commonly reported assessment of model performance, it is prone to overestimation when output classifications are unbalanced. In such cases, confusion matrices may be additionally reported, whereby diagnostic cut points for model predicted probability may hold more clinical significance to clinical colleagues with respect to related forms of diagnostic testing

Estimation of Bone Strength from Pediatric Radiographs of the Forearm

Objective: Bone strength is a function of both material and architectural properties. However, bone geometry or architecture, which determines the distribution of bone, is an underappreciated determinant of bone strength. The aim of the study was to evaluate the contribution of only architecture to bone strength. Methods: We used 2-D (planar) geometric information from radiographs of human radii to construct 3-D finite-element models. To transition from 2-D to 3-D (volume) space, we assumed that all bone cross-sections were elliptical in shape. The finite-element models were subjected to cantilever loading to determine the locations in the bone with the highest propensity to fracture (points of maximum stress). The finite-element-analysis results of the models generated from radiographs of both normal (18) and temporary-brittle-bone-disease (11) infants were subjected to a receiver operating curve analysis. The area under the receiver operating curve was used to evaluate the power of a given bone-strength indicator in segregating the two populations. The actual choice of the material properties (Young’s modulus or Poisson’s ratio) was not critical for this study, since the finite element analyses were designed to capture the difference in the bone strength of the two populations only based on their architecture. Therefore, the material properties were assumed to be the same in both the normal and TBBD populations. Results: The area under the curve of the bending load required to cause fracture among the two populations was 0.82. Other bone-strength indicators, such as average section modulus, cortical thickness and bone length, were associated with an area under the curve of 0.75, 0.73 and 0.63, respectively. Conclusion: The results of the finite-element-analysis suggest that the temporary-brittle-bone-disease population has an altered bone geometry, which increases susceptibility to fracture under normal bending loads

Estimation of Bone Strength from Pediatric Radiographs of the Forearm

Objective: Bone strength is a function of both material and architectural properties. However, bone geometry or architecture, which determines the distribution of bone, is an underappreciated determinant of bone strength. The aim of the study was to evaluate the contribution of only architecture to bone strength. Methods: We used 2-D (planar) geometric information from radiographs of human radii to construct 3-D finite-element models. To transition from 2-D to 3-D (volume) space, we assumed that all bone cross-sections were elliptical in shape. The finite-element models were subjected to cantilever loading to determine the locations in the bone with the highest propensity to fracture (points of maximum stress). The finite-element-analysis results of the models generated from radiographs of both normal (18) and temporary-brittle-bone-disease (11) infants were subjected to a receiver operating curve analysis. The area under the receiver operating curve was used to evaluate the power of a given bone-strength indicator in segregating the two populations. The actual choice of the material properties (Young’s modulus or Poisson’s ratio) was not critical for this study, since the finite element analyses were designed to capture the difference in the bone strength of the two populations only based on their architecture. Therefore, the material properties were assumed to be the same in both the normal and TBBD populations. Results: The area under the curve of the bending load required to cause fracture among the two populations was 0.82. Other bone-strength indicators, such as average section modulus, cortical thickness and bone length, were associated with an area under the curve of 0.75, 0.73 and 0.63, respectively. Conclusion: The results of the finite-element-analysis suggest that the temporary-brittle-bone-disease population has an altered bone geometry, which increases susceptibility to fracture under normal bending loads