No abstract

Purpose The composition of the subchondral bone marrow and cartilage endplate (CEP) could affect intervertebral disc health by influencing vertebral perfusion and nutrient diffusion. However, the relative contributions of these factors to disc degeneration in patients with chronic low back pain (cLBP) have not been quantified. The goal of this study was to use compositional biomarkers derived from quantitative MRI to establish how CEP composition (surrogate for permeability) and vertebral bone marrow fat fraction (BMFF, surrogate for perfusion) relate to disc degeneration. Methods MRI data from 60 patients with cLBP were included in this prospective observational study (28 female, 32 male; age = 40.0 ± 11.9 years, 19–65 [mean ± SD, min–max]). Ultra-short echo-time MRI was used to calculate CEP T2* relaxation times (reflecting biochemical composition), water-fat MRI was used to calculate vertebral BMFF, and T1ρ MRI was used to calculate T1ρ relaxation times in the nucleus pulposus (NP T1ρ, reflecting proteoglycan content and degenerative grade). Univariate linear regression was used to assess the independent effects of CEP T2* and vertebral BMFF on NP T1ρ. Mixed effects multivariable linear regression accounting for age, sex, and BMI was used to assess the combined relationship between variables. Results CEP T2* and vertebral BMFF were independently associated with NP T1ρ (p = 0.003 and 0.0001, respectively). After adjusting for age, sex, and BMI, NP T1ρ remained significantly associated with CEP T2* (p = 0.0001) but not vertebral BMFF (p = 0.43). Conclusion Poor CEP composition plays a significant role in disc degeneration severity and can affect disc health both with and without deficits in vertebral perfusion.

The modern concept of geoengineering as a response to anthropogenic climate change evolved from much earlier proposals to modify the climate. The welldocumented history of weather modification provides a much-needed historical perspective on geoengineering in the face of current climate anxiety and the need for responsive action. Drawing on material from the mid-20th century until today, this paper asserts the importance of looking at geoengineering holistically-of integrating social considerations with technical promise, and scientific study with human and moral dimensions. While the debate is often couched in scientific terms, the consequences of geoengineering the climate stretch far beyond the world of science into the realms of ethics, legality, and society. Studying the history of geoengineering can help produce fresh insights about what has happened and about what may happen, and can help frame important decisions that will soon be made as to whether geoengineering is a feasible alternative to mitigation, a possible partner, or a dangerous experiment with our fragile planet.

Background Paraspinal musculature (PSM) is increasingly recognized as a contributor to low back pain (LBP), but with conventional MRI sequences, assessment is limited. Chemical shift encoding‐based water–fat MRI (CSE‐MRI) enables the measurement of PSM fat fraction (FF), which may assist investigations of chronic LBP. Purpose To investigate associations between PSM parameters from conventional MRI and CSE‐MRI and between PSM parameters and pain. Study Type Prospective, cross‐sectional. Population Eighty‐four adults with chronic LBP (44.6 ± 13.4 years; 48 males). Field Strength/Sequence 3‐T, T1‐weighted fast spin‐echo and iterative decomposition of water and fat with echo asymmetry and least squares estimation sequences. Assessment T1‐weighted images for Goutallier classification (GC), muscle volume, lumbar indentation value, and muscle‐fat index, CSE‐MRI for FF extraction (L1/2–L5/S1). Pain was self‐reported using a visual analogue scale (VAS). Intra‐ and/or interreader agreement was assessed for MRI‐derived parameters. Statistical Tests Mixed‐effects and linear regression models to 1) assess relationships between PSM parameters (entire cohort and subgroup with GC grades 0 and 1; statistical significance α = 0.0025) and 2) evaluate associations of PSM parameters with pain (α = 0.05). Intraclass correlation coefficients (ICCs) for intra‐ and/or interreader agreement. Results The FF showed excellent intra‐ and interreader agreement (ICC range: 0.97–0.99) and was significantly associated with GC at all spinal levels. Subgroup analysis suggested that early/subtle changes in PSM are detectable with FF but not with GC, given the absence of significant associations between FF and GC (P‐value range: 0.036 at L5/S1 to 0.784 at L2/L3). Averaged over all spinal levels, FF and GC were significantly associated with VAS scores. Data Conclusion In the absence of FF, GC may be the best surrogate for PSM quality. Given the ability of CSE‐MRI to detect muscle alterations at early stages of PSM degeneration, this technique may have potential for further investigations of the role of PSM in chronic LBP. Level of Evidence 2 Technical Efficacy Stage 2

Adverse clinical outcomes for total disc arthroplasty (TDA), including subsidence, heterotopic ossification, and adjacent‐level vertebral fracture, suggest problems with the underlying biomechanics. To gain insight, we investigated the role of size and stiffness of TDA implants on load‐transfer within a vertebral body. Uniquely, we accounted for the realistic multi‐scale geometric features of the trabecular micro‐architecture and cortical shell. Using voxel‐based finite element analysis derived from a micro‐computed tomography scan of one human L1 vertebral body (74‐μm‐sized elements), a series of generic elliptically shaped implants were analyzed. We parametrically modeled three implant sizes (small, medium [a typical clinical size], and large) and three implant materials (metallic, E = 100 GPa; polymeric, E = 1 GPa; and tissue‐engineered, E = 0.01 GPa). Analyses were run for two load cases: 800 N in uniform compression and flexion‐induced anterior impingement. Results were compared to those of an intact model without an implant and loaded instead via a disc‐like material. We found that TDA implantation increased stress in the bone tissue by over 50% in large portions of the vertebra. These changes depended more on implant size than material, and there was an interaction between implant size and loading condition. For the small implant, flexion increased the 98th‐percentile of stress by 32 ± 24% relative to compression, but the overall stress distribution and trabecular‐cortical load‐sharing were relatively insensitive to loading mode. In contrast, for the medium and large implants, flexion increased the 98th‐percentile of stress by 42 ± 9% and 87 ± 29%, respectively, and substantially re‐distributed stress within the vertebra; in particular overloading the anterior trabecular centrum and cortex. We conclude that TDA implants can substantially alter stress deep within the lumbar vertebra, depending primarily on implant size. For implants of typical clinical size, bending‐induced impingement can substantially increase stress in local regions and may therefore be one factor driving subsidence in vivo.

Background T2* relaxation times in the spinal cartilage endplate (CEP) measured using ultra-short echo time magnetic resonance imaging (UTE MRI) reflect aspects of biochemical composition that influence the CEP’s permeability to nutrients. Deficits in CEP composition measured using T2* biomarkers from UTE MRI are associated with more severe intervertebral disc degeneration in patients with chronic low back pain (cLBP). The goal of this study was to develop an objective, accurate, and efficient deep-learning-based method for calculating biomarkers of CEP health using UTE images. Methods Multi-echo UTE MRI of the lumbar spine was acquired from a prospectively enrolled cross-sectional and consecutive cohort of 83 subjects spanning a wide range of ages and cLBP-related conditions. CEPs from the L4-S1 levels were manually segmented on 6,972 UTE images and used to train neural networks utilizing the u-net architecture. CEP segmentations and mean CEP T2* values derived from manually- and model-generated segmentations were compared using Dice scores, sensitivity, specificity, Bland-Altman, and receiver-operator characteristic (ROC) analysis. Signal-to-noise (SNR) and contrast-to-noise (CNR) ratios were calculated and related to model performance. Results Compared with manual CEP segmentations, model-generated segmentations achieved sensitives of 0.80–0.91, specificities of 0.99, Dice scores of 0.77–0.85, area under the receiver-operating characteristic curve values of 0.99, and precision-recall (PR) AUC values of 0.56–0.77, depending on spinal level and sagittal image position. Mean CEP T2* values and principal CEP angles derived from the model-predicted segmentations had low bias in an unseen test dataset (T2* bias =0.33±2.37 ms, angle bias =0.36±2.65°). To simulate a hypothetical clinical scenario, the predicted segmentations were used to stratify CEPs into high, medium, and low T2* groups. Group predictions had diagnostic sensitivities of 0.77–0.86 and specificities of 0.86–0.95. Model performance was positively associated with image SNR and CNR. Conclusions The trained deep learning models enable accurate, automated CEP segmentations and T2* biomarker computations that are statistically similar to those from manual segmentations. These models address limitations with inefficiency and subjectivity associated with manual methods. Such techniques could be used to elucidate the role of CEP composition in disc degeneration etiology and guide emerging therapies for cLBP.

No abstract

A cemented, cast CoCr alloy, Omnifit Plus femoral stem was retrieved following mid-stem fracture after 24 years in vivo. The patient was an active 55-year-old male with a high body mass index (31.3) and no traumatic incidents before stem fracture. Fractographic and fatigue-based failure analyses were performed to illuminate the etiology of fracture and retrospectively predict the device lifetime. The fracture surfaces show evidence of a coarse grain microstructure, intergranular fracture, and regions of porosity. The failure analysis suggests that stems with similar metallurgical characteristics, biomechanical environments, and in vivo durations may be abutting their functioning lifetimes, raising the possibility of an increased revision burden.