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Background: Obesity influences the development of osteoarthritis via low-grade inflammation. Progression of local inflammation (= synovitis) increased with weight gain in overweight and obese women compared to stable weight. Synovitis could be associated with subcutaneous fat (SCF) around the knee. Purpose of the study was to investigate the effect of weight loss on synovitis progression and to assess whether SCF around the knee mediates the relationship between weight loss and synovitis progression., Methods: We included 234 overweight and obese participants (body mass index [BMI] ≥ 25 kg/m 2 ) from the Osteoarthritis Initiative (OAI) with > 10% weight loss (n = 117) or stable overweight (< ± 3% change, n = 117) over 48 months matched for age and sex. In magnetic resonance imaging (MRI) at baseline and 48 months, effusion-synovitis and Hoffa-synovitis using the MRI Osteoarthritis Knee Score (MOAKS) and average joint-adjacent SCF (ajSCF) were assessed. Odds-ratios (ORs) for synovitis progression over 48 months (≥ 1 score increase) were calculated in logistic regression models adjusting for age, sex, baseline BMI, Physical Activity Scale for the Elderly (PASE), and baseline SCF measurements. Mediation of the effect of weight loss on synovitis progression by local SCF change was assessed., Results: Odds for effusion-synovitis progression decreased with weight loss and ajSCF decrease (odds ratio [OR] = 0.61 and 0.56 per standard deviation [SD] change, 95% confidence interval [CI] 0.44, 0.83 and 0.40, 0.79, p = 0.002 and 0.001, respectively), whereas odds for Hoffa-synovitis progression increased with weight loss and ajSCF decrease (OR = 1.47 and 1.48, CI 1.05, 2.04 and 1.02, 2.13, p = 0.024 and 0.038, respectively). AjSCF decrease mediated 39% of the effect of weight loss on effusion-synovitis progression., Conclusions: Effusion-synovitis progression was slowed by weight loss and decrease in local subcutaneous fat. Hoffa-synovitis characterized by fluid in the infrapatellar fat pad increased at the same time, suggesting a decreasing fat pad rather than active synovitis. Decrease in local subcutaneous fat partially mediated the systemic effect of weight loss on synovitis., (© 2024. The Author(s).)

Introduction: Fracture risk is elevated in type 2 diabetes (T2D) despite normal or even high bone mineral density (BMD). Microvascular disease (MVD) is a diabetic complication, but also associated with other diseases, for example chronic kidney disease. We hypothesize that increased fracture risk in T2D could be due to increased cortical porosity (Ct.Po) driven by expansion of the vascular network in MVD. The purpose of this study was to investigate associations of T2D and MVD with cortical microstructure and intracortical vessel parameters., Methods: The study group consisted of 75 participants (38 with T2D and 37 without T2D). High-resolution peripheral quantitative CT (HR-pQCT) and dynamic contrast-enhanced MRI (DCE-MRI) of the ultra-distal tibia were performed to assess cortical bone and intracortical vessels (outcomes). MVD was defined as ≥1 manifestation including neuropathy, nephropathy, or retinopathy based on clinical exams in all participants. Adjusted means of outcomes were compared between groups with/without T2D or between participants with/without MVD in both groups using linear regression models adjusting for age, sex, BMI, and T2D as applicable., Results: MVD was found in 21 (55 %) participants with T2D and in 9 (24 %) participants without T2D. In T2D, cortical pore diameter (Ct.Po.Dm) and diameter distribution (Ct.Po.Dm.SD) were significantly higher by 14.6 μm (3.6 %, 95 % confidence interval [CI]: 2.70, 26.5 μm, p  = 0.017) and by 8.73 μm (4.8 %, CI: 0.79, 16.7 μm, p  = 0.032), respectively. In MVD, but not in T2D, cortical porosity was significantly higher by 2.25 % (relative increase = 12.9 %, CI: 0.53, 3.97 %, p  = 0.011) and cortical BMD (Ct.BMD) was significantly lower by -43.6 mg/cm 3 (2.6 %, CI: -77.4, -9.81 mg/cm 3 , p  = 0.012). In T2D, vessel volume and vessel diameter were significantly higher by 0.02 mm 3 (13.3 %, CI: 0.004, 0.04 mm 3 , p  = 0.017) and 15.4 μm (2.9 %, CI: 0.42, 30.4 μm, p  = 0.044), respectively. In MVD, vessel density was significantly higher by 0.11 mm -3 (17.8 %, CI: 0.01, 0.21 mm -3 , p  = 0.033) and vessel volume and diameter were significantly lower by -0.02 mm 3 (13.7 %, CI: -0.04, -0.004 mm 3 , p  = 0.015) and - 14.6 μm (2.8 %, CI: -29.1, -0.11 μm, p  = 0.048), respectively., Conclusions: The presence of MVD, rather than T2D, was associated with increased cortical porosity. Increased porosity in MVD was coupled with a larger number of smaller vessels, which could indicate upregulation of neovascularization triggered by ischemia. It is unclear why higher variability and average diameters of pores in T2D were accompanied by larger vessels., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Galateia J. Kazakia reports financial support was provided by the 10.13039/100000002National Institutes of Health., (© 2024 Published by Elsevier Inc.)

Objectives: To quantitatively investigate the age- and sex-related longitudinal changes in trabecular volumetric bone mineral density (vBMD) and vertebral body volume at the thoracolumbar spine in adults., Methods: We retrospectively included 168 adults (mean age 58.7 ± 9.8 years, 51 women) who received ≥7 MDCT scans over a period of ≥6.5 years (mean follow-up 9.0 ± 2.1 years) for clinical reasons. Level-wise vBMD and vertebral body volume were extracted from 22720 thoracolumbar vertebrae using a convolutional neural network (CNN)-based framework with asynchronous calibration and correction of the contrast media phase. Human readers conducted semiquantitative assessment of fracture status and bony degenerations., Results: In the 40-60 years age group, women had a significantly higher trabecular vBMD than men at all thoracolumbar levels (p<0.05 to p<0.001). Conversely, men, on average, had larger vertebrae with lower vBMD. This sex difference in vBMD did not persist in the 60-80 years age group. While the lumbar (T12-L5) vBMD slopes in women only showed a non-significant trend of accelerated decline with age, vertebrae T1-11 displayed a distinct pattern, with women demonstrating a significantly accelerated decline compared to men (p<0.01 to p<0.0001). Between baseline and last follow-up examinations, the vertebral body volume slightly increased in women (T1-12: 1.1 ± 1.0 cm 3 ; L1-5: 1.0 ± 1.4 cm 3 ) and men (T1-12: 1.2 ± 1.3 cm 3 ; L1-5: 1.5 ± 1.6 cm 3 ). After excluding vertebrae with bony degenerations, the residual increase was only small in women (T1-12: 0.6 ± 0.6 cm 3 ; L1-5: 0.7 ± 0.7 cm 3 ) and men (T1-12: 0.7 ± 0.6 cm 3 ; L1-5: 1.2 ± 0.8 cm 3 ). In non-degenerated vertebrae, the mean change in volume was <5% of the respective vertebral body volumes., Conclusion: Sex differences in thoracolumbar vBMD were apparent before menopause, and disappeared after menopause, likely attributable to an accelerated and more profound vBMD decline in women at the thoracic spine. In patients without advanced spine degeneration, the overall volumetric changes in the vertebral body appeared subtle., Competing Interests: The authors of this manuscript declare relationships with the following companies: JK, SR, and MH have equity in Bonescreen GmbH. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Rühling, Dittmann, Müller, Husseini, Bodden, Hernandez Petzsche, Löffler, Sollmann, Baum, Seifert-Klauss, Wostrack, Zimmer and Kirschke.)

Background: To investigate reproducibility of texture features and volumetric bone mineral density (vBMD) extracted from trabecular bone in the thoracolumbar spine in routine clinical multi-detector computed tomography (MDCT) data in a single scanner environment., Methods: Patients who underwent two routine clinical thoraco-abdominal MDCT exams at a single scanner with a time interval of 6 to 26 months (n=203, 131 males; time interval mean, 13 months; median, 12 months) were included in this observational study. Exclusion criteria were metabolic and hematological disorders, bone metastases, use of bone-active medications, and history of osteoporotic vertebral fractures (VFs) or prior diagnosis of osteoporosis. A convolutional neural network (CNN)-based framework was used for automated spine labeling and segmentation (T5-L5), asynchronous Hounsfield unit (HU)-to-BMD calibration, and correction for the intravenous contrast medium phase. Vertebral vBMD and six texture features [variance global , entropy, short-run emphasis (SRE), long-run emphasis (LRE), run-length non-uniformity (RLN), and run percentage (RP)] were extracted for mid- (T5-T8) and lower thoracic (T9-T12), and lumbar vertebrae (L1-L5), respectively. Relative annual changes were calculated in texture features and vBMD for each vertebral level and sorted by sex, and changes were checked for statistical significance (P<0.05) using paired t -tests. Root mean square coefficient of variation (RMSCV) and root mean square error (RMSE) were calculated as measures of variability., Results: SRE, LRE, RLN, and RP exhibited substantial reproducibility with RMSCV-values below 2%, for both sexes and at all spine levels, while vBMD was less reproducible (RMSCV =11.9-16.2%). Entropy showed highest variability (RMSCV =4.34-7.69%) due to statistically significant increases [range, mean ± standard deviation: (4.40±5.78)% to (8.36±8.66)%, P<0.001]. RMSCV of variance global ranged from 1.60% to 3.03%., Conclusions: Opportunistic assessment of texture features in a single scanner environment using the presented CNN-based framework yields substantial reproducibility, outperforming vBMD reproducibility. Lowest scan-rescan variability was found for higher-order texture features. Further studies are warranted to determine, whether microarchitectural changes to the trabecular bone may be assessed through texture features., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-23-19/coif). JSK is co-founder of bonescreen GmbH, received funding by the Deutsche Forschungsgemeinschaft and honoraria for lectures on multiple sclerosis by Novartis. TB received funding by the Deutsche Forschungsgemeinschaft. The other authors have no conflicts of interest to declare., (2023 Quantitative Imaging in Medicine and Surgery. All rights reserved.)

Objectives: Opportunistic quantitative computed tomography (oQCT) derived from non-dedicated routine CT has demonstrated high accuracy in diagnosing osteoporosis and predicting incident vertebral fractures (VFs). We aimed to investigate the cost-effectiveness of oQCT screening compared to dual-energy X-ray absorptiometry (DXA) as the standard of care for osteoporosis screening., Methods: Three screening strategies ("no osteoporosis screening", "oQCT screening", and "DXA screening") after routine CT were simulated in a state-transition model for hypothetical cohorts of 1,000 patients (women and men aged 65 years) over a follow-up period of 5 years (base case). The primary outcomes were the cumulative costs and the quality-adjusted life years (QALYs) estimated from a U.S. health care perspective for the year 2022. Cost-effectiveness was assessed based on a willingness-to-pay (WTP) threshold of $70,249 per QALY. The secondary outcome was the number of prevented VFs. Deterministic and probabilistic sensitivity analyses were conducted to test the models' robustness., Results: Compared to DXA screening, oQCT screening increased QALYs in both sexes (additional 2.40 per 1,000 women and 1.44 per 1,000 men) and resulted in total costs of $3,199,016 and $950,359 vs. $3,262,934 and $933,077 for women and men, respectively. As a secondary outcome, oQCT screening prevented 2.6 and 2.0 additional VFs per 1,000 women and men, respectively. In the probabilistic sensitivity analysis, oQCT screening remained cost-effective in 88.3% (women) and 90.0% (men) of iterations., Conclusion: oQCT screening is a cost-effective ancillary approach for osteoporosis screening and has the potential to prevent a substantial number of VFs if considered in daily clinical practice., Competing Interests: The authors of this manuscript declare relationships with the following companies: JK and SR have equity in Bonescreen GmbH. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Rühling, Schwarting, Froelich, Löffler, Bodden, Hernandez Petzsche, Baum, Wostrack, Aftahy, Seifert-Klauss, Sollmann, Zimmer, Kirschke and Tollens.)

Objectives: To investigate vertebral osteoporotic fracture (VF) prediction by automatically extracted trabecular volumetric bone mineral density (vBMD) from routine CT, and to compare the model with fracture prevalence-based prediction models., Methods: This single-center retrospective study included patients who underwent two thoraco-abdominal CT scans during clinical routine with an average inter-scan interval of 21.7 ± 13.1 months (range 5-52 months). Automatic spine segmentation and vBMD extraction was performed by a convolutional neural network framework (anduin.bonescreen.de). Mean vBMD was calculated for levels T5-8, T9-12, and L1-5. VFs were identified by an expert in spine imaging. Odds ratios (ORs) for prevalent and incident VFs were calculated for vBMD (per standard deviation decrease) at each level, for baseline VF prevalence (yes/no), and for baseline VF count (n) using logistic regression models, adjusted for age and sex. Models were compared using Akaike's and Bayesian information criteria (AIC & BIC)., Results: 420 patients (mean age, 63 years ± 9, 276 males) were included in this study. 40 (25 female) had prevalent and 24 (13 female) had incident VFs. Individuals with lower vBMD at any spine level had higher odds for VFs (L1-5, prevalent VF: OR,95%-CI,p: 2.2, 1.4-3.5,p=0.001; incident VF: 3.5, 1.8-6.9,p<0.001). In contrast, VF status (2.15, 0.72-6.43,p=0.170) and count (1.38, 0.89-2.12,p=0.147) performed worse in incident VF prediction. Information criteria revealed best fit for vBMD-based models (AIC vBMD=165.2; VF status=181.0; count=180.7)., Conclusions: VF prediction based on automatically extracted vBMD from routine clinical MDCT outperforms prediction models based on VF status and count. These findings underline the importance of opportunistic quantitative osteoporosis screening in clinical routine MDCT data., Competing Interests: JK, MH and AS are Cofounders of Bonescreen GmbH. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Bodden, Dieckmeyer, Sollmann, Burian, Rühling, Löffler, Sekuboyina, El Husseini, Zimmer, Kirschke and Baum.)

Background: Chronic back pain is a major health problem worldwide. Although its causes can be diverse, biomechanical factors leading to spinal degeneration are considered a central issue. Numerical biomechanical models can identify critical factors and, thus, help predict impending spinal degeneration. However, spinal biomechanics are subject to significant interindividual variations. Therefore, in order to achieve meaningful findings on potential pathologies, predictive models have to take into account individual characteristics. To make these highly individualized models suitable for systematic studies on spinal biomechanics and clinical practice, the automation of data processing and modeling itself is inevitable. The purpose of this study was to validate an automatically generated patient-specific musculoskeletal model of the spine simulating static loading tasks. Methods: CT imaging data from two patients with non-degenerative spines were processed using an automated deep learning-based segmentation pipeline. In a semi-automated process with minimal user interaction, we generated patient-specific musculoskeletal models and simulated various static loading tasks. To validate the model, calculated vertebral loadings of the lumbar spine and muscle forces were compared with in vivo data from the literature. Finally, results from both models were compared to assess the potential of our process for interindividual analysis. Results: Calculated vertebral loads and muscle activation overall stood in close correlation with data from the literature. Compression forces normalized to upright standing deviated by a maximum of 16% for flexion and 33% for lifting tasks. Interindividual comparison of compression, as well as lateral and anterior-posterior shear forces, could be linked plausibly to individual spinal alignment and bodyweight. Conclusion: We developed a method to generate patient-specific musculoskeletal models of the lumbar spine. The models were able to calculate loads of the lumbar spine for static activities with respect to individual biomechanical properties, such as spinal alignment, bodyweight distribution, and ligament and muscle insertion points. The process is automated to a large extent, which makes it suitable for systematic investigation of spinal biomechanics in large datasets., Competing Interests: JK and AS are Co-Founders of Bonescreen GmbH. All other authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Lerchl, El Husseini, Bayat, Sekuboyina, Hermann, Nispel, Baum, Löffler, Senner and Kirschke.)

Opportunistic osteoporosis screening in nondedicated routine computed tomography (CT) is of increasing importance. The purpose of this study was to compare lumbar volumetric bone mineral density (vBMD) assessed by a convolutional neural network (CNN)-based framework in routine CT to vBMD from dedicated quantitative CT (QCT), and to evaluate the ability of vBMD and surrogate measurements of Hounsfield units (HU) to distinguish between patients with and without osteoporotic vertebral fractures (VFs). A total of 144 patients (median age: 70.7 years, 93 females) with clinical routine CT (eight different CT scanners, 120 kVp or 140 kVp, with and without intravenous contrast medium) and dedicated QCT acquired within ≤30 days were included. Vertebral measurements included (i) vBMD from the CNN-based approach including automated vertebral body labeling, segmentation, and correction of the contrast media phase for routine CT data (vBMD&#95;OPP), (ii) vBMD from dedicated QCT (vBMD&#95;QCT), and (iii) noncalibrated HU from vertebral bodies of routine CT data as previously proposed for immanent opportunistic osteoporosis screening based on CT attenuation. The intraclass correlation coefficient (ICC) for vBMD&#95;QCT versus vBMD&#95;OPP indicated better agreement (ICC = 0.913) than the ICC for vBMD&#95;QCT versus noncalibrated HU (ICC = 0.704). Bland-Altman analysis showed data points from 137 patients (95.1%) within the limits of agreement (LOA) of -23.2 to 25.0 mg/cm 3 for vBMD&#95;QCT versus vBMD&#95;OPP. Osteoporosis (vBMD <80 mg/cm 3 ) was detected in 89 patients (vBMD&#95;QCT) and 88 patients (vBMD&#95;OPP), whereas no patient crossed the diagnostic thresholds from normal vBMD to osteoporosis or vice versa. In a subcohort of 88 patients (thoracolumbar spine covered by imaging for VF reading), 69 patients showed one or more prevalent VFs, and the performance for discrimination between patients with and without VFs was best for vBMD&#95;OPP (area under the curve [AUC] = 0.862; 95% confidence interval [CI], 0.771-0.953). In conclusion, automated opportunistic osteoporosis screening in routine CT of various scanner setups is feasible and may demonstrate high diagnostic accuracy for prevalent VFs. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR)., (© 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).)

Purpose: To establish and evaluate the diagnostic accuracy of volumetric bone mineral density (vBMD) threshold values at different spinal levels, derived from opportunistic quantitative computed tomography (QCT), for the prediction of incident vertebral fractures (VF)., Materials and Methods: In this case-control study, 35 incident VF cases (23 women, 12 men; mean age: 67 years) and 70 sex- and age-matched controls were included, based on routine multi detector CT (MDCT) scans of the thoracolumbar spine. Trabecular vBMD was measured from routine baseline CT scans of the thoracolumbar spine using an automated pipeline including vertebral segmentation, asynchronous calibration for HU-to-vBMD conversion, and correction of intravenous contrast medium (https://anduin.bonescreen.de). Threshold values at T1-L5 were calculated for the optimal operating point according to the Youden index and for fixed sensitivities (60 - 85%) in receiver operating characteristic (ROC) curves., Results: vBMD at each single level of the thoracolumbar spine was significantly associated with incident VFs (odds ratio per SD decrease [OR], 95% confidence interval [CI] at T1-T4: 3.28, 1.66-6.49; at T5-T8: 3.28, 1.72-6.26; at T9-T12: 3.37, 1.78-6.36; and at L1-L4: 3.98, 1.97-8.06), independent of adjustment for age, sex, and prevalent VF. AUC showed no significant difference between vertebral levels and was highest at the thoracolumbar junction (AUC = 0.75, 95%-CI = 0.63 - 0.85 for T11-L2). Optimal threshold values increased from lumbar (L1-L4: 52.0 mg/cm³) to upper thoracic spine (T1-T4: 69.3 mg/cm³). At T11-L2, T12-L3 and L1-L4, a threshold of 80.0 mg/cm³ showed sensitivities of 85 - 88%, and specificities of 41 - 49%. To achieve comparable sensitivity (85%) at more superior spinal levels, resulting thresholds were higher: 114.1 mg/cm³ (T1-T4), 92.0 mg/cm³ (T5-T8), 88.2 mg/cm³ (T9-T12)., Conclusions: At all levels of the thoracolumbar spine, lower vBMD was associated with incident VFs in an elderly, predominantly oncologic patient population. Automated opportunistic osteoporosis screening of vBMD along the entire thoracolumbar spine allows for risk assessment of imminent VFs. We propose level-specific vBMD threshold at the thoracolumbar spine to identify individuals at high fracture risk., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Dieckmeyer, Löffler, El Husseini, Sekuboyina, Menze, Sollmann, Wostrack, Zimmer, Baum and Kirschke.)

Purpose: To identify long-term reproducible texture features (TFs) of spinal computed tomography (CT), and characterize variations with regard to gender, age and vertebral level using our automated quantification framework., Methods: We performed texture analysis (TA) on baseline and follow-up CT (follow-up duration: 30-90 days) of 21 subjects (8 females, 13 males, age at baseline 61.2 ± 9.2 years) to determine long-term reproducibility. TFs with a long-term reproducibility error Δ rel <5% were further analyzed for an association with age and vertebral level in a cohort of 376 patients (129 females, 247 males, age 62.5 ± 9.2 years). Automated analysis comprised labeling and segmentation of vertebrae into subregions using a convolutional neural network, calculation of volumetric bone mineral density (vBMD) with asynchronous calibration and TF extraction. Variance global measures the spread of the gray-level distribution in an image while Entropy reflects the uniformity of gray-levels. Short-run emphasis (SRE), Long-run emphasis (LRE), Run-length non-uniformity (RLN) and Run percentage (RP) contain information on consecutive voxels of a particular grey-level, or grey-level range, in a particular direction. Long runs (LRE) represent coarse texture while short runs (SRE) represent fine texture. RLN reflects similarities in the length of runs while RP reflects distribution and homogeneity of runs with a specific direction., Results: Six of the 24 extracted TFs had Δ rel <5% (Variance global , Entropy, SRE, LRE, RLN, RP), and were analyzed further in 4716 thoracolumbar vertebrae. Five TFs (Variance global ,SRE,LRE, RLN,RP) showed a significant difference between genders (p<0.001), potentially being caused by a finer and more directional vertebral trabecular microstructure in females compared to males. Variance global and Entropy showed a significant increase from the thoracic to the lumbar spine (p<0.001), indicating a higher degree and earlier initiation of trabecular microstructure deterioration at lower spinal levels. The four higher-order TFs showed significant variations between spine regions without a clear directional gradient (p ≤ 0.001-0.012). No TF showed a clear age dependence. vBMD differed significantly between genders, age groups and spine regions (p ≤ 0.001-0.002)., Conclusion: Long-term reproducible CT-based TFs of the thoracolumbar spine were established and characterized in a predominantly older adult study population. The gender-, age- and vertebral-level-specific values may serve as foundation for osteoporosis diagnostics and facilitate future studies investigating vertebral microstructure., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Dieckmeyer, Sollmann, El Husseini, Sekuboyina, Löffler, Zimmer, Kirschke, Subburaj and Baum.)

With the advent of deep learning algorithms, fully automated radiological image analysis is within reach. In spine imaging, several atlas- and shape-based as well as deep learning segmentation algorithms have been proposed, allowing for subsequent automated analysis of morphology and pathology. The first "Large Scale Vertebrae Segmentation Challenge" (VerSe 2019) showed that these perform well on normal anatomy, but fail in variants not frequently present in the training dataset. Building on that experience, we report on the largely increased VerSe 2020 dataset and results from the second iteration of the VerSe challenge (MICCAI 2020, Lima, Peru). VerSe 2020 comprises annotated spine computed tomography (CT) images from 300 subjects with 4142 fully visualized and annotated vertebrae, collected across multiple centres from four different scanner manufacturers, enriched with cases that exhibit anatomical variants such as enumeration abnormalities (n = 77) and transitional vertebrae (n = 161). Metadata includes vertebral labelling information, voxel-level segmentation masks obtained with a human-machine hybrid algorithm and anatomical ratings, to enable the development and benchmarking of robust and accurate segmentation algorithms., (© 2021. The Author(s).)

Background: Osteoporosis is a systemic skeletal disease that is characterized by low bone mass and microarchitectural deterioration, predisposing affected individuals to fragility fractures. Yet, standard measurement of areal bone mineral density (BMD) in dual-energy X-ray absorptiometry (DXA) as the current reference standard has limitations for correctly detecting osteoporosis and fracture risk, with opportunistic osteoporosis screening using computed tomography (CT) showing increasing importance. This study's objective is to compare finite element analysis (FEA)-based vertebral failure load with parameters of texture analysis (TA) derived from multi-detector CT (MDCT)., Methods: MDCT data of seven subjects (mean age: 71.9±7.4 years) were included for FEA and TA. Manual segmentation was performed for the vertebral bodies T11, T12, L1, and L2 and the intervertebral discs (IVDs) T11/12, T12/L1, L1/2, and L2/3. Correlation analyses between FEA-derived failure loads and parameters of TA for the single vertebrae and two functional spinal units (FSUs) were calculated, defining FSU-1 as T11-IVD-T12-IVD-L1 and FSU-2 as T12-IVD-L1-IVD-L2. Furthermore, multivariate regressions were performed to identify the texture parameters that predicted the failure load best., Results: For single vertebrae, the strongest correlations were observed for skewnessglobal, kurtosisglobal, and gray level variance (rho =-0.7668 to -0.7362; P<0.001), while for FSUs, SumAverage, long-run emphasis, long-run low gray-level emphasis, homogeneity, and energy showed the strongest correlations (rho =-0.8187 to 0.8407; P<0.05) to failure loads. SumAverage best predicted the failure load for single vertebrae (R 2 adj =0.523, P<0.001). For the two FSUs, kurtosisglobal (FSU-1: R 2 adj =0.611, P=0.001) and skewnessglobal (FSU-2: R 2 adj =0.579, P=0.002) were the best predictors., Conclusions: TA using MDCT data of the spine was significantly associated with FEA-derived failure loads of both, single vertebrae and FSUs. Texture parameters predicted failure loads of FSUs as a more realistic in-vivo scenario equally well as compared to single vertebrae analyses. TA may reflect a less complex and time-consuming approach to accurately and non-invasively evaluate vertebral bone strength., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/qims-20-1156). Dr. JSK reports grants from European Research Council (ERC, grant agreement No 637164), grants from Deutsche Forschungsgemeinschaft, project 432290010, during the conduct of the study; personal fees from Philips Healthcare, outside the submitted work. The other authors have no conflicts of interest to declare., (2021 Quantitative Imaging in Medicine and Surgery. All rights reserved.)

Assessment of osteoporosis-associated fracture risk during clinical routine is based on the evaluation of clinical risk factors and T-scores, as derived from measurements of areal bone mineral density (aBMD). However, these parameters are limited in their ability to identify patients at high fracture risk. Finite element models (FEMs) have shown to improve bone strength prediction beyond aBMD. This study aims to investigate whether FEM measurements at the lumbar spine can predict the biomechanical strength of functional spinal units (FSUs) with incidental osteoporotic vertebral fractures (VFs) along the thoracolumbar spine. Multi-detector computed tomography (MDCT) data of 11 patients (5 females and 6 males, median age: 67 years) who underwent MDCT twice (median interval between baseline and follow-up MDCT: 18 months) and sustained an incidental osteoporotic VF between baseline and follow-up scanning were used. Based on baseline MDCT data, two FSUs consisting of vertebral bodies and intervertebral discs (IVDs) were modeled: one standardly capturing L1-IVD-L2-IVD-L3 (FSU&#95;L1-L3) and one modeling the incidentally fractured vertebral body at the center of the FSU (FSU&#95;F). Furthermore, volumetric BMD (vBMD) derived from MDCT, FEM-based displacement, and FEM-based load of the single vertebrae L1 to L3 were determined. Statistically significant correlations (adjusted for a BMD ratio of fracture/L1-L3 segments) were revealed between the FSU&#95;F and mean load of L1 to L3 (r = 0.814, p = 0.004) and the mean vBMD of L1 to L3 (r = 0.745, p = 0.013), whereas there was no statistically significant association between the FSU&#95;F and FSU&#95;L1-L3 or between FSU&#95;F and the mean displacement of L1 to L3 ( p > 0.05). In conclusion, FEM measurements of single vertebrae at the lumbar spine may be able to predict the biomechanical strength of incidentally fractured vertebral segments along the thoracolumbar spine, while FSUs seem to predict only segment-specific fracture risk.

Purpose: To investigate the feasibility of using routine clinical multidetector computed tomography (MDCT) scans for conducting finite element (FE) analysis to predict vertebral bone strength for opportunistic osteoporosis screening., Methods: Routine abdominal MDCT with and without intravenous contrast medium (IVCM) of seven subjects (five male; two female; mean age: 71.86 ± 7.40 years) without any bone disease were used. FE analysis was performed on individual vertebrae (T11, T12, L1, and L2) including the posterior elements to investigate the effect of IVCM and slice thickness (1 and 3 mm) on vertebral bone strength. Another subset of data from subjects with vs . without osteoporotic vertebral fractures (n = 9 age and gender-matched pairs) was analyzed for investigating the ability of FE-analysis to differentiate the two cohorts. Bland-Altman plots, box plots, and coefficient of correlation (R 2 ) were calculated to determine the variations in FE-predicted failure loads for different conditions., Results: The FE-predicted failure loads obtained from routine MDCT scans were strongly correlated with those from without IVCM (R 2 = 0.91 for 1mm; R 2 = 0.92 for 3mm slice thickness, respectively) and different slice thicknesses (R 2 = 0.93 for 1mm vs . 3mm with IVCM). Furthermore, a good correlation was observed for 3mm slice thickness with IVCM vs . 1mm without IVCM (R 2 = 0.87). Significant difference between FE-predicted failure loads of healthy and fractured patients was observed (4,705 ± 1,238 vs . 4,010 ± 1,297 N; p=0.026)., Conclusion: Routine clinical MDCT scans could be reliably used for assessment of fracture risk based on FE analysis and may be beneficial for patients who are at increased risk for osteoporotic fractures., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Rayudu, Dieckmeyer, Löffler, Noël, Kirschke, Baum and Subburaj.)

Objective: Decreased bone mineral density (BMD) impairs screw purchase in trabecular bone and can cause screw loosening following spinal instrumentation. Existing computed tomography (CT) scans could be used for opportunistic osteoporosis screening for decreased BMD. Purpose of this case-control study was to investigate the association of opportunistically assessed BMD with the outcome after spinal surgery with semi-rigid instrumentation for lumbar degenerative instability., Methods: We reviewed consecutive patients that had primary surgery with semi-rigid instrumentation in our hospital. Patients that showed screw loosening in follow-up imaging qualified as cases. Patients that did not show screw loosening or-if no follow-up imaging was available (n = 8)-reported benefit from surgery ≥ 6 months after primary surgery qualified as controls. Matching criteria were sex, age, and surgical construct. Opportunistic BMD screening was performed at L1 to L4 in perioperative CT scans by automatic spine segmentation and using asynchronous calibration. Processing steps of this deep learning-driven approach can be reproduced using the freely available online-tool Anduin (https://anduin.bonescreen.de). Area under the curve (AUC) was calculated for BMD as a predictor of screw loosening., Results: Forty-six elderly patients (69.9 ± 9.1 years)-23 cases and 23 controls-were included. The majority of surgeries involved three spinal motion segments (n = 34). Twenty patients had low bone mass and 13 had osteoporotic BMD. Cases had significantly lower mean BMD (86.5 ± 29.5 mg/cm³) compared to controls (118.2 ± 32.9 mg/cm³, p = 0.001), i.e. patients with screw loosening showed reduced BMD. Screw loosening was best predicted by a BMD < 81.8 mg/cm³ (sensitivity = 91.3%, specificity = 56.5%, AUC = 0.769, p = 0.002)., Conclusion: Prevalence of osteoporosis or low bone mass (BMD ≤ 120 mg/cm³) was relatively high in this group of elderly patients undergoing spinal surgery. Screw loosening was associated with BMD close to the threshold for osteoporosis (< 80 mg/cm³). Opportunistic BMD screening is feasible using the presented approach and can guide the surgeon to take measures to prevent screw loosening and to increase favorable outcomes., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Löffler, Sollmann, Burian, Bayat, Aftahy, Baum, Meyer, Ryang and Kirschke.)

Published under a CC BY 4.0 license. Supplemental material is available for this article ., Competing Interests: Disclosures of Conflicts of Interest: M.T.L. Activities related to the present article: institution received European Research Council starting grant from European Union’s Horizon 2020 research and innovation program (grant agreement no. 637164 — iBack —ERC-2014-STG). Activities not related to the present article: disclosed no relevant relationships. Other relationships: disclosed no relevant relationships. A. Sekuboyina Activities related to the present article: institution received ERC grant (637164). Activities not related to the present article: disclosed no relevant relationships. Other relationships: disclosed no relevant relationships. A.J. disclosed no relevant relationships. A.L.G. disclosed no relevant relationships. A. Scharr disclosed no relevant relationships. M.E.H. Activities related to the present article: institution received ERC grant (637164). Activities not related to the present article: disclosed no relevant relationships. Other relationships: disclosed no relevant relationships. M.K. disclosed no relevant relationships. C.Z. Activities related to the present article: institution received ERC grant (637164). Activities not related to the present article: disclosed no relevant relationships. Other relationships: author has received speaker honoraria from Bayer-Schering and Philips; institution has received research support and investigator fees for clinical studies from Biogen Idec, Quintiles, MSD Sharp & Dome, Boehringer Ingelheim, Inventive Health Clinical UK Ltd. Advance Cor, Brainsgate, Pfizer, Bayer-Schering, Novartis, Roche, Servier, Penumbra, WCT GmbH, Syngis, SSS International Clinical Research, PPD Germany GmbH, Worldwide Clinical Trials Ltd., Phenox, Covidien, Actelion, Medivation, Medtronic, Harrison Clinical Research, Concentric, Pharmtrace, Reverse Medical Corp., Premier Research Germany Ltd., Surpass Medical Ltd., GlaxoSmithKline, AXON Neuroscience, Bristol-Myers Squibb, Genentech, Acandis, EISAI, NeuroRx, Italfarmaco, Bioclinica, MIAC and IXICO. T.B. disclosed no relevant relationships. J.S.K. Activities related to the present article: institution received ERC grant (637164) and grant from Nvidia. Activities not related to the present article: author paid for lectures by Philips Healthcare. Other relationships: disclosed no relevant relationships., (2020 by the Radiological Society of North America, Inc.)