Recombinant Human BMP6 Applied Within Autologous Blood Coagulum Accelerates Bone Healing: Randomized Controlled Trial in High Tibial Osteotomy Patients.

Bone morphogenetic proteins (BMPs) are potent osteogenic proteins that induce new bone formation in vivo. However, their effect on bone healing in the trabecular bone surfaces remains challenging. We evaluated the safety and efficacy of recombinant human BMP6 (rhBMP6) applied within an autologous blood coagulum (ABC) in a surgically created wedge defect of the proximal tibia in patients undergoing high tibial osteotomy (HTO) for varus deformity and medial osteoarthritis of the knee. We enrolled 20 HTO patients in a randomized, placebo-controlled, double-blinded phase I/II clinical trial. RhBMP6/ABC (1.0 mg/10 mL ABC prepared from peripheral blood) or placebo (10 mL ABC containing excipients) was administered into the tibial wedge defects. Patients were followed for 0 to 24 months by clinical examination (safety) and computed tomography (CT) and serial radiographic analyses (efficacy). The results show that there were no detectable anti-rhBMP6 antibodies in the blood of any of the 20 patients at 14 weeks after implantation. During the 24 months of follow-up, there were no serious adverse reactions recorded. The CT scans from defects of patients treated with rhBMP6/ABC showed an accelerated bone healing compared with placebo at 9 weeks (47.8 ± 24.1 versus 22.2 ± 12.3 mg/cm3 ; p = 0.008) and at 14 weeks (89.7 ± 29.1 versus 53.6 ± 21.9 mg/cm3 ; p = 0.006) follow-up. Radiographic analyses at weeks 6 and 24 and months 12 and 24 suggested the advanced bone formation and remodeling in rhBMP6/ABC-treated patients. In conclusion, we show that rhBMP6/ABC at a dose of 100 µg/mL accelerated bone healing in patients undergoing HTO without serious adverse events and with a good tolerability compared with placebo alone. Overall, for the first time, a BMP-based osteogenic implant was examined against a placebo for bone healing efficacy in the trabecular bone surface, using an objective bone mineral density measurement system. © 2020 The Authors. Journal of Bone and Mineral Research published by American Society for Bone and Mineral Research.

Labeling Vertebrae with Two-dimensional Reformations of Multidetector CT Images: An Adversarial Approach for Incorporating Prior Knowledge of Spine Anatomy.

PURPOSE: To use and test a labeling algorithm that operates on two-dimensional reformations, rather than three-dimensional data to locate and identify vertebrae. MATERIALS AND METHODS: The authors improved the Btrfly Net, a fully convolutional network architecture described by Sekuboyina et al, which works on sagittal and coronal maximum intensity projections (MIPs) and augmented it with two additional components: spine localization and adversarial a priori learning. Furthermore, two variants of adversarial training schemes that incorporated the anatomic a priori knowledge into the Btrfly Net were explored. The superiority of the proposed approach for labeling vertebrae on three datasets was investigated: a public benchmarking dataset of 302 CT scans and two in-house datasets with a total of 238 CT scans. The Wilcoxon signed rank test was employed to compute the statistical significance of the improvement in performance observed with various architectural components in the authors' approach. RESULTS: On the public dataset, the authors' approach using the described Btrfly Net with energy-based prior encoding (Btrflype-eb) network performed as well as current state-of-the-art methods, achieving a statistically significant (P < .001) vertebrae identification rate of 88.5% ± 0.2 (standard deviation) and localization distances of less than 7 mm. On the in-house datasets that had a higher interscan data variability, an identification rate of 85.1% ± 1.2 was obtained. CONCLUSION: An identification performance comparable to existing three-dimensional approaches was achieved when labeling vertebrae on two-dimensional MIPs. The performance was further improved using the proposed adversarial training regimen that effectively enforced local spine a priori knowledge during training. Spine localization increased the generalizability of our approach by homogenizing the content in the MIPs.Supplemental material is available for this article.© RSNA, 2020.

Analysis and quantification of bone healing after open wedge high tibial osteotomy.

BACKGROUND: The aim of this study was to analyze radiographic imaging techniques and to quantify bone ossification in the osteotomy gap after high tibial osteotomy. MATERIAL AND METHODS: Study phase 1: high tibial osteotomy was performed on six lower extremities of human body donors and experimental X­rays and computed tomography (CT) scans were applied. Different techniques were evaluated by three specialists for best representation of the osteotomy gap. Study phase 2: optimized radiological techniques were used for follow-up on 12 patients. The radiographs were examined by 3 specialists measuring 10 different parameters. The CT scans were analyzed with semiautomatic computer software for quantification of bone ossification. RESULTS: The osteotomy gap was best represented in 30° of flexion in the knee and 20° internal rotation of the leg. There were significant changes of the medial width over time (p < 0.019) as well as of the length of fused osteotomy, the Schröter score, sclerosis, trabecular structure and zone area measurements. Sclerosis, medial width of the osteotomy and area measurements were detected as reproducible parameters. Bone mineral density was calculated using CT scans, showing a significantly higher value 12 weeks postoperatively (112.5 mg/cm3) than at baseline (54.6 mg/cm3). The ossification of the gap was visualized by color coding. CONCLUSION: Sclerosis and medial width of the osteotomy gap as well as area measurements were determined as reproducible parameters for evaluation of bone healing. Quantification of bone ossification can be calculated with CT scans using a semiautomatic computer program and should be used for research in bone healing.

Improved prediction of incident vertebral fractures using opportunistic QCT compared to DXA.

OBJECTIVES: To compare opportunistic quantitative CT (QCT) with dual energy X-ray absorptiometry (DXA) in their ability to predict incident vertebral fractures. METHODS: We included 84 patients aged 50 years and older, who had routine CT including the lumbar spine and DXA within a 12-month period (baseline) as well as follow-up imaging after at least 12 months or who sustained an incident vertebral fracture documented earlier. Patients with bone disorders aside from osteoporosis were excluded. Fracture status and trabecular bone mineral density (BMD) were retrospectively evaluated in baseline CT and fracture status was reassessed at follow-up. BMDQCT was assessed by opportunistic QCT with asynchronous calibration of multiple MDCT scanners. RESULTS: Sixteen patients had incident vertebral fractures showing lower mean BMDQCT than patients without fracture (p = 0.001). For the risk of incident vertebral fractures, the hazard ratio increased per SD in BMDQCT (4.07; 95% CI, 1.98-8.38), as well as after adjusting for age, sex, and prevalent fractures (2.54; 95% CI, 1.09-5.90). For DXA, a statistically significant increase in relative hazard per SD decrease in T-score was only observed after age and sex adjustment (1.57; 95% CI, 1.04-2.38). The predictability of incident vertebral fractures was good by BMDQCT (AUC = 0.76; 95% CI, 0.64-0.89) and non-significant by T-scores. Asynchronously calibrated CT scanners showed good long-term stability (linear drift ranging from - 0.55 to - 2.29 HU per year). CONCLUSIONS: Opportunistic screening of mainly neurosurgical and oncologic patients in CT performed for indications other than densitometry allows for better risk assessment of imminent vertebral fractures than dedicated DXA. KEY POINTS: • Opportunistic QCT predicts osteoporotic vertebral fractures better than DXA reference standard in mainly neurosurgical and oncologic patients. • More than every second patient (56%) with an incident vertebral fracture was misdiagnosed not having osteoporosis according to DXA. • Standard ACR QCT-cutoff values for osteoporosis (< 80 mg/cm 3 ) and osteopenia (≤ 120 mg/cm 3 ) can also be applied scanner independently in calibrated opportunistic QCT.

Diffusion tensor image features predict IDH genotype in newly diagnosed WHO grade II/III gliomas.

We hypothesized that machine learning analysis based on texture information from the preoperative MRI can predict IDH mutational status in newly diagnosed WHO grade II and III gliomas. This retrospective study included in total 79 consecutive patients with a newly diagnosed WHO grade II or III glioma. Local binary pattern texture features were generated from preoperative B0 and fractional anisotropy (FA) diffusion tensor imaging. Using a training set of 59 patients, a single hidden layer neural network was then trained on the texture features to predict IDH status. The model was validated based on the prediction accuracy calculated in a previously unseen set of 20 gliomas. Prediction accuracy of the generated model was 92% (54/59 cases; AUC = 0.921) in the training and 95% (19/20; AUC = 0.952) in the validation cohort. The ten most important features were comprised of tumor size and both B0 and FA texture information, underlining the joint contribution of imaging data to classification. Machine learning analysis of DTI texture information and tumor size reliably predicts IDH status in preoperative MRI of gliomas. Such information may increasingly support individualized surgical strategies, supplement pathological analysis and highlight the potential of radiogenomics.

Regional analysis of age-related local bone loss in the spine of a healthy population using 3D voxel-based modeling.

Local variations in bone loss may be of great importance to individually predict osteoporotic fractures but are neglected by current densitometry techniques. The purpose of this study was to evaluate regional variations of normal bone loss at the spine among different age groups using voxel-based morphometry. Non-contrast MDCT scans of 16 patients under the age of 40 (mean age 26years) without spinal pathology were identified as a reference cohort, where each thoracolumbar vertebra was assessed individually. For comparison, 38 patients >40years were grouped by decades in 4 cohorts of 10 patients each, except the youngest, including 8 patients only. All spines were automatically detected, segmented and non-rigidly registered for spatially normalized vertebral bodies. Afterwards, statistical and T-score mapping was performed to highlight local density differences in comparison to the reference cohort. The calculated statistical maps of significantly affected density regions (ADR) started to highlight small local changes of volumetric bone mineral density (vBMD) distribution within the vertebra of L5 (ADR: 7.9%) in the fifties cohort. Regions near the endplates were most affected. The effect dramatically increased in the sixties cohort, where bone loss was most prominent from T12 to L2. In the seventies cohort, around 50% of voxels in T10 to L5 showed significantly decreased vBMD. In conclusion, ADR and local T-score maps of the spine showed age-related local variations in a healthy population, corresponding to known areas of fracture origination and increased fracture incidence. It thus might provide a powerful tool in diagnosis of osteoporosis.

Osteoporosis Is the Most Important Risk Factor for Odontoid Fractures in the Elderly.

Traumatic odontoid fractures (TOFs) have been described as the most common injury affecting the C-spine in the elderly. Previous studies have identified degenerative changes and bone loss as important predisposing factors. However, their interaction and respective age-adjusted impact needs further clarification. We conducted a retrospective analysis of 5303 patients (aged ≥60 years) admitted to a level I trauma center between January 2008 and January 2016 who underwent CT imaging of the C-spine. Ninety-two patients with TOF and 80 patients with other cervical spine fractures (OCSF) were identified and a respective 3:1 age- and sex-matched control group without fractures after trauma was built. In all groups, cervical bone mineral density (cBMD) was determined using phantom calibration, and degenerative changes were evaluated in a qualitative manner. In all groups, the severity of degenerative changes of the C-spine increased with age (all p < 0.05) and was inversely correlated with cBMD (all p < 0.05). cBMD was the only significant predictor of a TOF in a multivariate logistic regression model (adjusted odds ratio [OR] = 3.066, 95% confidence interval [CI] 1.432-6.563 for cervical osteoporosis). An association between odontoid cysts and TOF reached significance only in Anderson and D'Alonzo (A&D) type II TOFs (aOR = 1.383; 95% CI 1.012-1.890). Patients with OCSFs, compared with patients with TOFs, were younger (median 74 versus 83 years) and had a higher cBMD (median 208 mg/mL versus 172 mg/mL). No differences were observable when comparing cBMD and grades of degenerative changes between OCSFs and their control group (all p >0.1). Decreased cBMD is the major predisposing factor for the occurrence of TOF but not for OCSF in the elderly. The severity of odontoid cysts was found to be a cBMD-independent factor associated with A&D type II TOFs. However, degenerative changes in the odontoid neighboring joints seem to be an epiphenomenon of bone loss and older age but do not independently predispose for TOF. © 2017 American Society for Bone and Mineral Research.

Diagnostic Potential of Pulsed Arterial Spin Labeling in Alzheimer's Disease.

Alzheimers disease (AD) is the most common cause of dementia. Although the underlying pathology is still not completely understood, several diagnostic methods are available. Frequently, the most accurate methods are also the most invasive. The present work investigates the diagnostic potential of Pulsed Arterial Spin Labeling (PASL) for AD: a non-invasive, MRI-based technique for the quantification of regional cerebral blood flow (rCBF). In particular, we propose a pilot computer aided diagnostic (CAD) procedure able to discriminate between healthy and diseased subjects, and at the same time, providing visual informative results. This method encompasses the creation of a healthy model, the computation of a voxel-wise likelihood function as comparison between the healthy model and the subject under examination, and the correction of the likelihood function via prior distributions. The discriminant analysis is carried out to maximize the accuracy of the classification. The algorithm has been trained on a dataset of 81 subjects and achieved a sensitivity of 0.750 and a specificity of 0.875. Moreover, in accordance with the current pathological knowledge, the parietal lobe, and limbic system are shown to be the main discriminant factors.

High-resolution peripheral quantitative CT imaging: Cortical porosity, poor trabecular bone microarchitecture, and low bone strength in lung transplant recipients.

PURPOSE: To characterize bone microarchitecture and quantify bone strength in lung transplant (LT) recipients by using high-resolution (HR) peripheral quantitative computed tomographic (CT) imaging of the ultradistal radius. MATERIALS AND METHODS: After study approval by the local ethics committee, all participants provided written informed consent. Included were 118 participants (58 LT recipients [mean age, 46.8 years ± 1.9; 30 women, 28 men] and 60 control participants [mean age, 39.9 years ± 1.9; 41 women, 19 men]) between April 2010 and May 2012. HR peripheral quantitative CT of the ultradistal radius was performed and evaluated for bone mineral density and trabecular and cortical bone microarchitecture. Mechanical competence was quantified by microfinite element analysis. Differences between LT recipients and control participants were determined by using two-way factorial analysis of covariance with age adjustment. RESULTS: Total and trabecular bone mineral density were significantly lower (-13.4% and -16.4%, respectively; P = .001) in LT recipients than in healthy control participants. LT recipients had lower trabecular number (-9.7%; P = .004) and lower trabecular thickness (-8.1%; P = .025). Trabecular separation and trabecular network heterogeneity were higher (+24.3% and +63.9%, respectively; P = .007 and P = .012, respectively) in LT recipients. Moreover, there was pronounced cortical porosity (+31.3%; P = .035) and lower cortical thickness (-10.2%, P = .005) after LT. In addition, mechanical competence was impaired, which was reflected by low stiffness (-15.0%; P < .001), low failure force (-14.8%; P < .001), and low bone strength (-14.6%; P < .001). CONCLUSION: Men and women with recent LT showed severe deficits in cortical and trabecular bone microarchitecture. Poor bone microarchitecture and low bone strength are likely to contribute to high fracture susceptibility observed in LT recipients.

Regional variations in MR relaxation of hip joint cartilage in subjects with and without femoralacetabular impingement.

The objective of this study was to analyze regional variations of magnetic resonance (MR) relaxation times (T1ρ and T2) in hip joint cartilage of healthy volunteers and subjects with femoral acetabular impingement (FAI). Morphological and quantitative images of the hip joints of 12 healthy volunteers and 9 FAI patients were obtained using a 3T MR scanner. Both femoral and acetabular cartilage layers in each joint were semi-automatically segmented on sagittal 3D high-resolution spoiled gradient echo (SPGR) images. These segmented regions of interest (ROIs) were automatically divided radially into twelve equal sub-regions (30(0) intervals) based on the fitted center of the femur head. The mean value of T1ρ/T2 was calculated in each sub-region after superimposing the divided cartilage contours on the MR relaxation (T1ρ/T2) maps to quantify the relaxation times. T1ρ and T2 relaxation times of the femoral cartilage were significantly higher in FAI subjects compared to healthy controls (39.9±3.3 msec in FAI vs. 35.4±2.3msec in controls for T1ρ (P=0.0020); 33.9±3.1 msec in FAI vs. 31.1±1.7 msec in controls for T2 (P=0.0160)). Sub-regional analysis showed significantly different T1ρ and T2 relaxation times in the anterior-superior region (R9) of the hip joint cartilage between subjects with FAI and healthy subjects, suggesting possible regional differences in cartilage matrix composition between these two groups. Receiver operating characteristic (ROC) analysis showed that sub-regional analysis in femoral cartilage was more sensitive in discriminating FAI joint cartilage from that of healthy joints than global analysis of the whole region (T1ρ: area under the curve (AUC)=0.981, P=0.0001 for R9 sub-region; AUC=0.901, P=0.002 for whole region; T2: AUC=0.976, P=0.0005 for R9 sub-region; AUC=0.808, P=0.0124 for whole region). The results of this study demonstrated regional variations in hip cartilage composition using MR relaxation times (T1ρ and T2) and suggested that analysis based on local regions was more sensitive than global measures in subjects with and without FAI.

Computational identification and quantification of trabecular microarchitecture classes by 3-D texture analysis-based clustering.

High resolution peripheral quantitative computed tomography (HR-pQCT) permits the non-invasive assessment of cortical and trabecular bone density, geometry, and microarchitecture. Although researchers have developed various post-processing algorithms to quantify HR-pQCT image properties, few of these techniques capture image features beyond global structure-based metrics. While 3D-texture analysis is a key approach in computer vision, it has been utilized only infrequently in HR-pQCT research. Motivated by high isotropic spatial resolution and the information density provided by HR-pQCT scans, we have developed and evaluated a post-processing algorithm that quantifies microarchitecture characteristics via texture features in HR-pQCT scans. During a training phase in which clustering was applied to texture features extracted from each voxel of trabecular bone, three distinct clusters, or trabecular microarchitecture classes (TMACs) were identified. These TMACs represent trabecular bone regions with common texture characteristics. The TMACs were then used to automatically segment the voxels of new data into three regions corresponding to the trained cluster features. Regional trabecular bone texture was described by the histogram of relative trabecular bone volume covered by each cluster. We evaluated the intra-scanner and inter-scanner reproducibility by assessing the precision errors (PE), intra class correlation coefficients (ICC) and Dice coefficients (DC) of the method on 14 ultradistal radius samples scanned on two HR-pQCT systems. DC showed good reproducibility in intra-scanner set-up with a mean of 0.870±0.027 (no unit). Even in the inter-scanner set-up the ICC showed high reproducibility, ranging from 0.814 to 0.964. In a preliminary clinical test application, the TMAC histograms appear to be a good indicator, when differentiating between postmenopausal women with (n=18) and without (n=18) prevalent fragility fractures. In conclusion, we could demonstrate that 3D-texture analysis and feature clustering seems to be a promising new HR-pQCT post-processing tool with good reproducibility, even between two different scanners.

Automated unsupervised multi-parametric classification of adipose tissue depots in skeletal muscle.

PURPOSE: To introduce and validate an automated unsupervised multi-parametric method for segmentation of the subcutaneous fat and muscle regions to determine subcutaneous adipose tissue (SAT) and intermuscular adipose tissue (IMAT) areas based on data from a quantitative chemical shift-based water-fat separation approach. MATERIALS AND METHODS: Unsupervised standard k-means clustering was used to define sets of similar features (k = 2) within the whole multi-modal image after the water-fat separation. The automated image processing chain was composed of three primary stages: tissue, muscle, and bone region segmentation. The algorithm was applied on calf and thigh datasets to compute SAT and IMAT areas and was compared with a manual segmentation. RESULTS: The IMAT area using the automatic segmentation had excellent agreement with the IMAT area using the manual segmentation for all the cases in the thigh (R(2): 0.96) and for cases with up to moderate IMAT area in the calf (R(2): 0.92). The group with the highest grade of muscle fat infiltration in the calf had the highest error in the inner SAT contour calculation. CONCLUSION: The proposed multi-parametric segmentation approach combined with quantitative water-fat imaging provides an accurate and reliable method for an automated calculation of the SAT and IMAT areas reducing considerably the total postprocessing time.

Multicenter precision of cortical and trabecular bone quality measures assessed by high-resolution peripheral quantitative computed tomography.

High-resolution peripheral quantitative computed tomography (HR-pQCT) has recently been introduced as a clinical research tool for in vivo assessment of bone quality. The utility of this technology to address important skeletal health questions requires translation to standardized multicenter data pools. Our goal was to evaluate the feasibility of pooling data in multicenter HR-pQCT imaging trials. Reproducibility imaging experiments were performed using structure and composition-realistic phantoms constructed from cadaveric radii. Single-center precision was determined by repeat scanning over short-term (<72 hours), intermediate-term (3-5 months), and long-term intervals (28 months). Multicenter precision was determined by imaging the phantoms at nine different HR-pQCT centers. Least significant change (LSC) and root mean squared coefficient of variation (RMSCV) for each interval and across centers was calculated for bone density, geometry, microstructure, and biomechanical parameters. Single-center short-term RMSCVs were <1% for all parameters except cortical thickness (Ct.Th) (1.1%), spatial variability in cortical thickness (Ct.Th.SD) (2.6%), standard deviation of trabecular separation (Tb.Sp.SD) (1.8%), and porosity measures (6% to 8%). Intermediate-term RMSCVs were generally not statistically different from short-term values. Long-term variability was significantly greater for all density measures (0.7% to 2.0%; p < 0.05 versus short-term) and several structure measures: cortical thickness (Ct.Th) (3.4%; p < 0.01 versus short-term), cortical porosity (Ct.Po) (15.4%; p < 0.01 versus short-term), and trabecular thickness (Tb.Th) (2.2%; p < 0.01 versus short-term). Multicenter RMSCVs were also significantly higher than short-term values: 2% to 4% for density and micro-finite element analysis (µFE) measures (p < 0.0001), 2.6% to 5.3% for morphometric measures (p < 0.001), whereas Ct.Po was 16.2% (p < 0.001). In the absence of subject motion, multicenter precision errors for HR-pQCT parameters were generally less than 5%. Phantom-based multicenter precision was comparable to previously reported in in vivo single-center precision errors, although this was approximately two to five times worse than ex vivo short-term precision. The data generated from this study will contribute to the future design and validation of standardized procedures that are broadly translatable to multicenter study designs.

Automated threshold-independent cortex segmentation by 3D-texture analysis of HR-pQCT scans.

The quantitative assessment of metabolic bone diseases relies on tissue properties such as bone mineral density (BMD) and bone microarchitecture. In spite of an increasing number of publications using high-resolution peripheral quantitative computed-tomography (HR-pQCT), the accurate and reproducible separation of cortical and trabecular bone remains challenging. In this paper, we present a novel, fully automated, threshold-independent technique for the segmentation of cortical and trabecular bone in HR-pQCT scans. This novel post-processing method is based on modeling appearance characteristics from manually annotated cases. In our experiments the algorithm automatically selected texture features with high differentiating power and trained a classifier to separate cortical and trabecular bone. From this mask, cortical thickness and tissue volume could be calculated with high accuracy. The overlap between the proposed threshold-independent segmentation tool (TIST) and manual contouring was 0.904±0.045 (Dice coefficient). In our experiments, TIST obtained higher overall accuracy in our measurements than other techniques.