Adaptation of the proximal humerus to physical activity: a within-subject controlled study in baseball players

The proximal humerus is a common, yet understudied site for osteoporotic fracture. The current study explored the impact of prolonged physical activity on proximal humerus bone health by comparing bone properties between the throwing and nonthrowing arms within professional baseball players. The proximal humerus in throwing arms had 28.1% (95% CI, 17.8 to 38.3%) greater bone mass compared to nonthrowing arms, as assessed using dual-energy x-ray absorptiometry. At the level of the surgical neck, computed tomography revealed 12.0% (95% CI, 8.2 to 15.8%) greater total cross-sectional area and 31.0% (95% CI, 17.8 to 44.2%) greater cortical thickness within throwing arms, which contributed to 56.8% (95% CI, 44.9 to 68.8%) greater polar moment of inertia (i.e., estimated ability to resist torsional forces) compared to nonthrowing arms. Within the humeral head and greater tubercle regions, throwing arms had 3.1% (95% CI, 1.1 to 5.1%) more trabecular bone, as assessed using high-resolution magnetic resonance imaging. Three-dimensional mapping of voxel- and vertex-wise differences between arms using statistical parametric mapping techniques revealed throwing arms had adaptation within much of the proximal diaphysis, especially the posterolateral cortex. The pattern of proximal diaphysis adaptation approximated the pattern of strain energy distribution within the proximal humerus during a fastball pitch derived from a musculoskeletal and finite element model in a representative player. These data demonstrate the adaptive ability of the proximal humerus to physical activity-related mechanical loads. It remains to be established how they translate to exercise prescription to improve bone health within the proximal humerus, however, they provide unique insight into the relationship between prolonged loading and skeletal adaptation at a clinically relevant osteoporotic site

Heterogeneous Spatial and Strength Adaptation of the Proximal Femur to Physical Activity: A Within-Subject Controlled Cross-Sectional Study

Physical activity (PA) enhances proximal femur bone mass, as assessed using projectional imaging techniques. However, these techniques average data over large volumes obscuring spatially heterogeneous adaptations. The current study used quantitative computed tomography, statistical parameter mapping, and subject-specific finite element (FE) modeling to explore spatial adaptation of the proximal femur to PA. In particular, we were interested in adaptation occurring at the superior femoral neck and improving strength under loading from a fall onto the greater trochanter. High/long jump athletes (n=16) and baseball pitchers (n=16) were utilized as within-subject controlled models as they preferentially load their takeoff leg and leg contralateral to their throwing arm, respectively. Controls (n=15) were included, but did not show any dominant-to-nondominant (D-to-ND) leg differences. Jumping athletes showed some D-to-ND leg differences, but less than pitchers. Pitchers had 5.8% (95% CI, 3.9–7.6%) D-to-ND leg differences in total hip volumetric bone mineral density (vBMD), with increased vBMD in the cortical compartment of the femoral neck, and trochanteric cortical and trabecular compartments. Voxel-based morphometry analyses and cortical bone mapping showed pitchers had D-to-ND leg differences within the regions of the primary compressive trabeculae, inferior femoral neck, and greater trochanter, but not the superior femoral neck. FE modeling revealed pitchers had 4.1% (95%CI, 1.4–6.7%) D-to-ND leg differences in ultimate strength under single-leg stance loading, but no differences in ultimate strength to a fall onto the greater trochanter. These data indicate the asymmetrical loading associated with baseball induces proximal femur adaptation in regions associated with weight bearing and muscle contractile forces, and increases strength under single-leg stance loading. However, there were no benefits evident at the superior femoral neck and no measurable improvement in ultimate strength to common injurious loading during aging (i.e. fall onto the greater trochanter) raising questions as to how to better target these variables with PA

Normalized cuts in 3-d for spinal mri segmentation

Abstract—Segmentation of medical images has become an indispensable process to perform quantitative analysis of images of human organs and their functions. Normalized Cuts is a spectral graph theoretic method that readily admits combinations of different features for image segmentation. The computational demand imposed by Normalized Cuts has been successfully alleviated with the Nyström approximation method for applications different than medical imaging. In this paper we discuss the application of Normalized Cuts with the Nyström approximation method to segment vertebral bodies from sagittal T1-weighted magnetic resonance images of the spine. The magnetic resonance images were pre-processed by the anisotropic diffusion algorithm, and 3D local histograms of brightness was chosen as the segmentation feature. Results of the segmentation as well as limitations and challenges in this area are presented. Index Terms — Magnetic resonance imaging (MRI), Normalized Cuts (NCut), Nyström approximation method, segmentation, spine

Quantitative assessment of morphology, T1ρ, and T2 of shoulder cartilage using MRI

ObjectivesThe aim of this study was to assess the feasibility of quantifying shoulder cartilage morphology and relaxometry in a clinically feasible scan time comparing different pulse sequences and assessing their reproducibility at 3 Tesla.MethodsThree pulse sequences were compared for morphological assessments of shoulder cartilage thickness and volume (SPGR, MERGE, FIESTA), while a combined T1ρ-T2 sequence was optimized for relaxometry measurements. The shoulders of six healthy subjects were scanned twice with repositioning, and the cartilage was segmented and quantified. The degree of agreement between the three morphological sequences was assessed using Bland-Altman plots, while the morphological and relaxometry reproducibility were assessed with root-mean-square coefficients of variation (RMS-CVs) RESULTS: Bland-Altman plots indicated good levels of agreement between the morphological assessments of the three sequences. The reproducibility of morphological assessments yielded RMS-CVs between 4.0 and 17.7 %. All sequences correlated highly (R > 0.9) for morphologic assessments with no statistically significant differences. For relaxometry assessments of humeral cartilage, RMS-CVs of 6.4 and 10.6 % were found for T1ρ and T2, respectively.ConclusionsThe assessment of both cartilage morphology and relaxometry is feasible in the shoulder with SPGR, humeral head, and T1ρ being the more reproducible morphological sequence, anatomic region, and quantitative sequence, respectively.Key points• The thin cartilage morphology can be assessed in the shoulder in vivo. • Non-invasive biochemical assessment of shoulder cartilage is feasible in vivo using MRI

Global and Spatial Compartmental Interrelationships of Bone Density, Microstructure, Geometry and Biomechanics in the Distal Radius in a Colles' Fracture Study Using HR-pQCT.

BackgroundBone parameters derived from HR-pQCT have been investigated on a parameter-by-parameter basis for different clinical conditions. However, little is known regarding the interrelationships of bone parameters and the spatial distribution of these interrelationships. In this work: 1) we investigate compartmental interrelationships of bone parameters; 2) assess the spatial distribution of interrelationships of bone parameters; and 3) compare interrelationships of bone parameters between postmenopausal women with and without a recent Colles' fracture.MethodsImages from the unaffected radius in fracture cases (n=84), and from the non-dominant radius of controls (n=98) were obtained using HR-pQCT. Trabecular voxel-based maps of local bone volume fraction (L.Tb.BV/TV), homogenized volumetric bone mineral density (H.Tb.BMD), homogenized μFEA-derived strain energy density (H.Tb.SED), and homogenized inter-trabecular distances (H.Tb.1/N) were generated; as well as surface-based maps of apparent cortical bone thickness (Surf.app.Ct.Th), porosity-weighted cortical bone thickness (Surf.Ct.SIT), mean cortical BMD (Surf.Ct.BMD), and mean cortical SED (Surf.Ct.SED). Anatomical correspondences across the parametric maps in the study were established via spatial normalization to a common template. Mean values of the parametric maps before spatial normalization were used to assess compartmental Spearman's rank partial correlations of bone parameters (e.g., between H.Tb.BMD and L.Tb.BV/TV or between Surf.Ct.BMD and Surf.app.Ct.Th). Spearman's rank partial correlations were also assessed for each voxel and vertex of the spatially normalized parametric maps, thus generating maps of Spearman's rank partial correlation coefficients. Correlations were performed independently within each group, and compared between groups using the Fisher's Z transformation.ResultsAll within-group global trabecular and cortical Spearman's rank partial correlations were significant; and the correlations of H.Tb.BMD-L.Tb.BV/TV, H.Tb.BMD-H.Tb.1/N, L.Tb.BV/TV-H.Tb.1/N, Surf.Ct.BMD-Surf.Ct.SED and Surf.Ct.SIT-Surf.Ct.SED were significantly different between controls and fracture cases. The spatial analyses revealed significant heterogeneous voxel- and surface-based correlation coefficient maps across the distal radius for both groups; and the correlation maps of H.Tb.BMD-L.Tb.BV/TV, H.Tb.BMD-H.Tb.1/N, L.Tb.BV/TV-H.Tb.1/N, H.Tb.1/N-H.Tb.SED and Surf.app.Ct.Th - Surf.Ct.SIT yielded small clusters of significant correlation differences between groups.DiscussionThe heterogeneous spatial distribution of interrelationships of bone parameters assessing density, microstructure, geometry and biomechanics, along with their global and local differences between controls and fracture cases, may help us further understand different bone mechanisms of bone fracture

Structural analysis of cortical porosity applied to HR‐pQCT data

PurposeThe investigation of cortical porosity is an important aspect of understanding biological, pathoetiological, and biomechanical processes occurring within the skeleton. With the emergence of HR-pQCT as a noninvasive tool suitable for clinical use, cortical porosity at appendicular sites can be directly visualized in vivo. The aim of this study was to introduce a novel topological analysis of the cortical pore network for HR-pQCT data and determine the influence of resolution on measures of cortical pore network microstructure and topology.MethodsCadaveric radii were scanned using HR-pQCT at two different voxel sizes (41 and 82 μm) and also using μCT at a voxel size of 18 μm. HR-pQCT and μCT image sets were spatially coregistered. Segmentation and quantification of cortical porosity (Ct.Po) and mean pore diameter (Ct.Po.Dm) were achieved using an established extended cortical analysis technique. Topological classification of individual pores was performed using topology-preserving skeletonization and multicolor dilation algorithms. Based on the pore skeleton topological classification, the following parameters were quantified: total number of planar surface-skeleton canals (N.Slabs), tubular curve-skeleton canals (N.Tubes), and junction elements (N.Junctions), mean slab volume (Slab.Vol), mean tube volume (Tube.Vol), mean slab orientation (Slab.θ), mean tube orientation (Tube.θ), N.Slabs/N.Tubes, and integral (total) slab volume/integral tube volume (iSlab.Vol/iTube.Vol). An in vivo reproducibility study was also conducted to assess short-term precision of the topology parameters. Precision error was characterized using root mean square coefficient of variation (RMSCV%).ResultsCorrelations to μCT values for Ct.Po were significant for both the 41 and 82 μm HR-pQCT data (41: r(2) = 0.82, p < 0.001, 82: r(2) = 0.75, p < 0.001). For Ct.Po.Dm, only the 41 μm data were significantly predictive of μCT values (r(2) = 0.72, p < 0.01) Data at both HR-pQCT voxel sizes were strongly predictive of the μCT values for N.Slabs (41: r(2) = 0.93, p < 0.001; 82: r(2) = 0.84, p < 0.001), N.Tubes (41: r(2) = 0.94, p < 0.001; 82: r(2) = 0.84, p < 0.001), and N.Junctions (41: r(2) = 0.93, p < 0.001; 82: r(2) = 0.78, p < 0.001), though proportional bias was evident in these correlations. Weak correlations were seen for iSlab.Vol/iTube.Vol at both voxel sizes (41: r(2) = 0.52, p < 0.01; 82: r(2) = 0.39, p < 0.05). Slab.Vol was significantly correlated to μCT data at 41 μm (r(2) = 0.60, p < 0.01) but not at 82 μm, while Tube.Vol was significantly correlated at both voxel sizes (41: r(2) = 0.79, p < 0.001; 82: r(2) = 0.68, p < 0.01). In vivo precision error for these parameters ranged from 2.31 to 9.68 RMSCV%.ConclusionsStrong correlations between μCT- and HR-pQCT-derived measurements were found, particularly in HR-pQCT images obtained at 41 μm. These data are in agreement with our previous study investigating the effect of voxel size on standard HR-pQCT metrics of trabecular and cortical microstructure, and extend our previous findings to include topological descriptors of the cortical pore network