Inter-scanner differences in in vivo QCT measurements of the density and strength of the proximal femur remain after correction with anthropomorphic standardization phantoms

The effect of defect size and location on the fracture risk of proximal tibia, following tumor curettage and cementation: An in-silico investigation

Even though, proximal tibia is a common site of giant cell tumor and bone fractures, following tumor removal, nonetheless very little attention has been paid to affecting factors on the fracture risk. Here, nonlinear voxel-based finite element models based on computed tomography images were developed to predict bone fracture load with defects with different sizes, which were located in the medial, lateral, anterior, and posterior region of the proximal tibia. Critical defect size was identified using One-sample t-test to assess if the mean difference between the bone strength for a defect size was significantly different from the intact bone strength. Then, the defects larger than critical size were reconstructed with cement and the mechanics of the bone-cement interface (BCI) was investigated to find the regions prone to separation at BCI. A significant increase in fracture risk was observed for the defects larger than 20 mm, which were located in the medial, lateral and anterior regions, and defects larger than 25 mm for those located in the posterior region of the proximal tibia. Furthermore, it was found that the highest and lowest fracture risks were associated with defects located in the medial and posterior regions, respectively, highlighting the importance of selecting the initial location of a cortical window for tumor removal by the surgeon. The results of the BCI analysis showed that the location and size of the cement had a direct impact on the extent of damage and its distribution. Identification of critical regions susceptible to separation at BCI, can provide critical comments to surgeons in selecting the optimal cement augmentation technique, which may ultimately prevent unnecessary surgical intervention, such as using screws and pins.

Automated vertebral bone mineral density measurement with phantomless internal calibration in chest LDCT scans using deep learning

OBJECTIVE

To develop and evaluate a fully automated method based on deep learning and phantomless internal calibration for bone mineral density (BMD) measurement and opportunistic low BMD (osteopenia and osteoporosis) screening using chest low-dose CT (LDCT) scans.

METHODS

A total of 1175 individuals were enrolled in this study, who underwent both chest LDCT and BMD examinations with quantitative computed tomography (QCT), by two different CT scanners (Siemens and GE). Two convolutional neural network (CNN) models were employed for vertebral body segmentation and labeling, respectively. A histogram technique was applied for vertebral BMD calculation using paraspinal muscle and surrounding fat as references. 195 cases (by Siemens scanner) as fitting cohort were used to build the calibration function. 698 cases as validation cohort I (VCI, by Siemens scanner) and 282 cases as validation cohort II (VCII, by GE scanner) were performed to evaluate the performance of the proposed method, with QCT as the standard for analysis.

RESULTS

The average BMDs from the proposed method were strongly correlated with QCT (in VCI: r = 0.896, in VCII: r = 0.956, p < 0.001). Bland-Altman analysis showed a small mean difference of 1.1 mg/cm3, and large interindividual differences as seen by wide 95% limits of agreement (-29.9 to +32.0 mg/cm3) in VCI. The proposed method measured BMDs were higher than QCT measured BMDs in VCII (mean difference = 15.3 mg/cm3, p < 0.001). Osteoporosis and low BMD were diagnosed by proposed method with AUCs of 0.876 and 0.903 in VCI, 0.731 and 0.794 in VCII, respectively. The AUCs of the proposed method were increased to over 0.920 in both VCI and VCII after adjusting the cut-off.

CONCLUSION

Without manual selection of the region of interest of body tissues, the proposed method based on deep learning and phantomless internal calibration has the potential for preliminary screening of patients with low BMD using chest LDCT scans. However, the agreement between the proposed method and QCT is insufficient to allow them to be used interchangeably in BMD measurement.

ADVANCES IN KNOWLEDGE

This study proposed an automated vertebral BMD measurement method based on deep learning and phantomless internal calibration with paraspinal muscle and fat as reference.

A Patient-Specific Fracture Risk Assessment Tool for Femoral Bone Metastases: Using the Bone Strength (BOS) Score in Clinical Practice

Patients with femoral metastases are at risk of fracturing bones. It is important to prevent fractures in order to maintain mobility and quality of life. The BOne Strength (BOS) score is based on a computed tomography (CT)-based patient-specific finite element (FE) computer model that objectively calculates bone strength. In this pilot study, the added clinical value of the BOS score towards treatment-related decision making was assessed. In December 2019, the BOS score was implemented in four radiotherapy centers. The BOS scores and fracture risks of individual patients were calculated and returned to the physician to assist in treatment decisions. The physicians filled out a questionnaire, which was qualitatively analyzed. A follow-up to identify fractures and/or death was performed after six months. Until June 2021, 42 BOS scores were delivered (20 high, 9 moderate, and 13 low fracture risk). In 48%, the BOS score led to an adaptation of treatment plans. Physicians indicated that the BOS score provided objective insight into fracture risk, was reassuring for physicians and patients, and improved multidisciplinary discussions and shared decision making. In conclusion, the BOS score is an objective tool to assess fracture risk in femoral bone metastases and aids physicians and patients in making a more informed decision regarding the most appropriate treatment.

The effect of variations in CT scan protocol on femoral finite element failure load assessment using phantomless calibration

Recently, it was shown that fracture risk assessment in patients with femoral bone metastases using Finite Element (FE) modeling can be performed using a calibration phantom or air-fat-muscle calibration and that non-patient-specific calibration was less favorable. The purpose of this study was to investigate if phantomless calibration can be used instead of phantom calibration when different CT protocols are used. Differences in effect of CT protocols on Hounsfield units (HU), calculated bone mineral density (BMD) and FE failure loads between phantom and two methods of phantomless calibrations were studied. Five human cadaver lower limbs were scanned atop a calibration phantom according to a standard scanning protocol and seven additional commonly deviating protocols including current, peak kilovoltage (kVp), slice thickness, rotation time, field of view, reconstruction kernel, and reconstruction algorithm. The HUs of the scans were calibrated to BMD (in mg/cm³) using the calibration phantom as well as using air-fat-muscle and non-patient-specific calibration, resulting in three models for each scan. FE models were created, and failure loads were calculated by simulating an axial load on the femur. HU, calculated BMD and failure load of all protocols were compared between the three calibration methods. The different protocols showed little variation in HU, BMD and failure load. However, compared to phantom calibration, changing the kVp resulted in a relatively large decrease of approximately 10% in mean HU and BMD of the trabecular and cortical region of interest (ROI), resulting in a 13.8% and 13.4% lower failure load when air-fat-muscle and non-patient-specific calibrations were used, respectively. In conclusion, while we observed significant correlations between air-fat-muscle calibration and phantom calibration as well as between non-patient-specific calibration and phantom calibration, our sample size was too small to prove that either of these calibration approaches was superior. Further studies are necessary to test whether air-fat-muscle or non-patient-specific calibration could replace phantom calibration in case of different scanning protocols.

Sources of error in bone mineral density estimates from quantitative CT

Bone mineral density (BMD) estimates from quantitative computed tomography (QCT) have proven useful for opportunistic screening of osteoporosis, treatment monitoring, and bone strength measurement. These estimates are subject to bias and variance from a variety of sources related to the imaging equipment, methods applied in the estimation procedure, and the patients themselves. In this article, we review the literature to describe the sources and sizes of error in spine and hip BMD estimates from single-energy QCT that can result from factors related to the scanner, imaging techniques, imaging subject, calibration phantom, and calibration approach. We also describe the baseline variance that can be expected based on repeatability and reproducibility studies. Though reproducible BMD estimates may be achievable with QCT, a thorough understanding of the potential sources of error and their size relative to the diagnostic task is essential to their appropriate and meaningful interpretation.

Fracture Risk of Long Bone Metastases: A Review of Current and New Decision-Making Tools for Prophylactic Surgery

Simple Summary

Long bone metastases are frequently a pivotal point in the oncological history of patients. Weakening of the bone results in pathologic fractures that not only compromise patient function but also their survival. Therefore, the main issue for tumor boards remains timely assessment of the risk of fracture, as this is a key consideration in providing preventive surgery while also avoiding overtreatment. As the Mirels scoring system takes into account both the radiological and the clinical criteria, it has been used worldwide since the 1990s. However, due to increasing concern regarding the lack of accuracy, new thresholds have been defined for the identification of impending fractures that require prophylactic surgery, on the basis of axial cortical involvement and biomechanical models involving quantitative computed tomography. The aim of this review is to establish a state-of-the-art of the risk assessment of long bone metastases fractures, from simple radiologic scores to more complex multidimensional bone models, in order to define new decision-making tools.

Abstract

Long bone pathological fractures very much reflect bone metastases morbidity in many types of cancer. Bearing in mind that they not only compromise patient function but also survival, identifying impending fractures before the actual event is one of the main concerns for tumor boards. Indeed, timely prophylactic surgery has been demonstrated to increase patient quality of life as well as survival. However, early surgery for long bone metastases remains controversial as the current fracture risk assessment tools lack accuracy. This review first focuses on the gold standard Mirels rating system. It then explores other unique imaging thresholds such as axial or circumferential cortical involvement and the merits of nuclear imaging tools. To overcome the lack of specificity, other fracture prediction strategies have focused on biomechanical models based on quantitative computed tomography (CT): computed tomography rigidity analysis (CT-RA) and finite element analysis (CT-FEA). Despite their higher specificities in impending fracture assessment, their limited availability, along with a need for standardization, have limited their use in everyday practice. Currently, the prediction of long bone pathologic fractures is a multifactorial process. In this regard, machine learning could potentially be of value by taking into account clinical survival prediction as well as clinical and improved CT-RA/FEA data.

Effect of CT imaging on the accuracy of the finite element modelling in bone

The finite element (FE) analysis is a highly promising tool to simulate the behaviour of bone. Skeletal FE models in clinical routine rely on the information about the geometry and bone mineral density distribution from quantitative computed tomography (CT) imaging systems. Several parameters in CT imaging have been reported to affect the accuracy of FE models. FE models of bone are exclusively developed in vitro under scanning conditions deviating from the clinical setting, resulting in variability of FE results (< 10%). Slice thickness and field of view had little effect on FE predicted bone behaviour (≤ 4%), while the reconstruction kernels showed to have a larger effect (≤ 20%). Due to large interscanner variations (≤ 20%), the translation from an experimental model into clinical reality is a critical step. Those variations are assumed to be mostly caused by different “black box” reconstruction kernels and the varying frequency of higher density voxels, representing cortical bone. Considering the low number of studies together with the significant effect of CT imaging on the finite element model outcome leading to high variability in the predicted behaviour, we propose further systematic research and validation studies, ideally preceding multicentre and longitudinal studies.

Image-based finite-element modeling of the human femur

Fracture is considered a critical clinical endpoint in skeletal pathologies including osteoporosis and bone metastases. However, current clinical guidelines are limited with respect to identifying cases at high risk of fracture, as they do not account for many mechanical determinants that contribute to bone fracture. Improving fracture risk assessment is an important area of research with clear clinical relevance. Patient-specific numerical musculoskeletal models generated from diagnostic images are widely used in biomechanics research and may provide the foundation for clinical tools used to quantify fracture risk. However, prior to clinical translation, in vitro validation of predictions generated from such numerical models is necessary. Despite adopting radically different models, in vitro validation of image-based finite element (FE) models of the proximal femur (predicting strains and failure loads) have shown very similar, encouraging levels of accuracy. The accuracy of such in vitro models has motivated their application to clinical studies of osteoporotic and metastatic fractures. Such models have demonstrated promising but heterogeneous results, which may be explained by the lack of a uniform strategy with respect to FE modeling of the human femur. This review aims to critically discuss the state of the art of image-based femoral FE modeling strategies, highlighting principal features and differences among current approaches. Quantitative results are also reported with respect to the level of accuracy achieved from in vitro evaluations and clinical applications and are used to motivate the adoption of a standardized approach/workflow for image-based FE modeling of the femur.

Fracture risk assessment and clinical decision making for patients with metastatic bone disease

Metastatic breast, prostate, lung, and other cancers often affect bone, causing pain, increasing fracture risk, and decreasing function. Management of metastatic bone disease (MBD) is clinically challenging when there is potential but uncertain risk of pathological fracture. Management of MBD has become a major focus within orthopedic oncology with respect to fracture and impending fracture care. If impending skeletal-related events (SREs), particularly pathologic fracture, could be predicted, increasing evidence suggests that prophylactic surgical treatment improves patient outcomes. However, current fracture risk assessment and radiographic metrics do not have high accuracy and have not been combined with relevant patient survival tools. This review first explores the prevalence, incidence, and morbidity of MBD and associated SREs for different cancer types. Strengths and limitations of current fracture risk scoring systems for spinal stability and long bone fracture are highlighted. More recent computed tomography (CT)-based structural rigidity analysis (CTRA) and finite element (FE) analysis methods offer advantages of increased specificity (true negative rate), but are limited in availability. Other fracture prediction approaches including parametric response mapping and positron emission tomography/computed tomography measures show early promise. Substantial new information to inform clinical decision-making includes measures of survival, clinical benefits, and economic analysis of prophylactic treatment compared to after-fracture stabilization. Areas of future research include use of big data and machine learning to predict SREs, greater access and refinement of CTRA/FE approaches, combination of clinical survival prediction tools with radiographically based fracture risk assessment, and net benefit analysis for fracture risk assessment and prophylactic treatment.

Patient-specific finite element computer models improve fracture risk assessments in cancer patients with femoral bone metastases compared to clinical guidelines

PURPOSE

To determine whether patient-specific finite element (FE) computer models are better at assessing fracture risk for femoral bone metastases compared to clinical assessments based on axial cortical involvement on conventional radiographs, as described in current clinical guidelines.

METHODS

Forty-five patients with 50 femoral bone metastases, who were treated with palliative radiotherapy for pain, were included (64% single fraction (8Gy), 36% multiple fractions (5 or 6x4Gy)) and were followed for six months to determine whether they developed a pathological femoral fracture. All plain radiographs available within a two month period prior to radiotherapy were obtained. Patient-specific FE models were constructed based on the geometry and bone density obtained from the baseline quantitative CT scans used for radiotherapy planning. Femoral failure loads normalized for body weight (BW) were calculated. Patients with a failure load of 7.5 x BW or lower were identified as having high fracture risk, whereas patients with a failure load higher than 7.5 x BW were classified as low fracture risk. Experienced assessors measured axial cortical involvement on conventional radiographs. Following clinical guidelines, patients with lesions larger than 30mm were identified as having a high fracture risk. FE predictions were compared to clinical assessments by means of diagnostic accuracy values (sensitivity, specificity and positive (PPV) and negative predictive values (NPV)).

RESULTS

Seven femurs (14%) fractured during follow-up. Median time to fracture was 8 weeks. FE models were better at assessing fracture risk in comparison to axial cortical involvement (sensitivity 100% vs. 86%, specificity 74% vs. 42%, PPV 39% vs. 19%, and NPV 100% vs. 95%, for the FE computer model vs. axial cortical involvement, respectively).

CONCLUSIONS

Patient-specific FE computer models improve fracture risk assessments of femoral bone metastases in advanced cancer patients compared to clinical assessments based on axial cortical involvement, which is currently used in clinical guidelines.

Calibration with or without phantom for fracture risk prediction in cancer patients with femoral bone metastases using CT-based finite element models

The objective of this study was to develop a new calibration method that enables calibration of Hounsfield units (HU) to bone mineral densities (BMD) without the use of a calibration phantom for fracture risk prediction of femurs with metastases using CT-based finite element (FE) models. Fifty-seven advanced cancer patients (67 femurs with bone metastases) were CT scanned atop a separate calibration phantom using a standardized protocol. Non-linear isotropic FE models were constructed based on the phantom calibration and on two phantomless calibration methods: the “air-fat-muscle” and “non-patient-specific” calibration. For air-fat-muscle calibration, peaks for air, fat and muscle tissue were extracted from a histogram of the HU in a standardized region of interest including the patient’s right leg and surrounding air. These CT peaks were linearly fitted to reference “BMD” values of the corresponding tissues to obtain a calibration function. For non-patient-specific calibration, an average phantom calibration function was used for all patients. FE failure loads were compared between phantom and phantomless calibrations. There were no differences in failure loads between phantom and air-fat-muscle calibration (p = 0.8), whereas there was a significant difference between phantom and non-patient-specific calibration (p<0.001). Although this study was not designed to investigate this, in four patients who were scanned using an aberrant reconstruction kernel, the effect of the different kernel seemed to be smaller for the air-fat-muscle calibration compared to the non-patient-specific calibration. With the air-fat-muscle calibration, clinical implementation of the FE model as tool for fracture risk assessment will be easier from a practical and financial viewpoint, since FE models can be made using everyday clinical CT scans without the need of concurrent scanning of calibration phantoms.

The Influence of Reconstruction Kernel on Bone Mineral and Strength Estimates Using Quantitative Computed Tomography and Finite Element Analysis

Quantitative computed tomography has been posed as an alternative imaging modality to investigate osteoporosis. We examined the influence of computed tomography convolution back-projection reconstruction kernels on the analysis of bone quantity and estimated mechanical properties in the proximal femur. Eighteen computed tomography scans of the proximal femur were reconstructed using both a standard smoothing reconstruction kernel and a bone-sharpening reconstruction kernel. Following phantom-based density calibration, we calculated typical bone quantity outcomes of integral volumetric bone mineral density, bone volume, and bone mineral content. Additionally, we performed finite element analysis in a standard sideways fall on the hip loading configuration. Significant differences for all outcome measures, except integral bone volume, were observed between the 2 reconstruction kernels. Volumetric bone mineral density measured using images reconstructed by the standard kernel was significantly lower (6.7%, p < 0.001) when compared with images reconstructed using the bone-sharpening kernel. Furthermore, the whole-bone stiffness and the failure load measured in images reconstructed by the standard kernel were significantly lower (16.5%, p < 0.001, and 18.2%, p < 0.001, respectively) when compared with the image reconstructed by the bone-sharpening kernel. These data suggest that for future quantitative computed tomography studies, a standardized reconstruction kernel will maximize reproducibility, independent of the use of a quantitative calibration phantom.

Can patient-specific finite element models better predict fractures in metastatic bone disease than experienced clinicians?: Towards computational modelling in daily clinical practice

OBJECTIVES

In this prospective cohort study, we investigated whether patient-specific finite element (FE) models can identify patients at risk of a pathological femoral fracture resulting from metastatic bone disease, and compared these FE predictions with clinical assessments by experienced clinicians.

METHODS

A total of 39 patients with non-fractured femoral metastatic lesions who were irradiated for pain were included from three radiotherapy institutes. During follow-up, nine pathological fractures occurred in seven patients. Quantitative CT-based FE models were generated for all patients. Femoral failure load was calculated and compared between the fractured and non-fractured femurs. Due to inter-scanner differences, patients were analyzed separately for the three institutes. In addition, the FE-based predictions were compared with fracture risk assessments by experienced clinicians.

RESULTS

In institute 1, median failure load was significantly lower for patients who sustained a fracture than for patients with no fractures. In institutes 2 and 3, the number of patients with a fracture was too low to make a clear distinction. Fracture locations were well predicted by the FE model when compared with post-fracture radiographs. The FE model was more accurate in identifying patients with a high fracture risk compared with experienced clinicians, with a sensitivity of 89% versus 0% to 33% for clinical assessments. Specificity was 79% for the FE models versus 84% to 95% for clinical assessments.

CONCLUSION

FE models can be a valuable tool to improve clinical fracture risk predictions in metastatic bone disease. Future work in a larger patient population should confirm the higher predictive power of FE models compared with current clinical guidelines.Cite this article: F. Eggermont, L. C. Derikx, N. Verdonschot, I. C. M. van der Geest, M. A. A. de Jong, A. Snyers, Y. M. van der Linden, E. Tanck. Can patient-specific finite element models better predict fractures in metastatic bone disease than experienced clinicians? Towards computational modelling in daily clinical practice. Bone Joint Res 2018;7:430-439. DOI: 10.1302/2046-3758.76.BJR-2017-0325.R2.

Practical considerations for obtaining high quality quantitative computed tomography data of the skeletal system

Quantitative CT (QCT) analysis involves the calculation of specific parameters such as bone volume and density from CT image data, and can be a powerful tool for understanding bone quality and quantity. However, without careful attention to detail during all steps of the acquisition and analysis process, data can be of poor- to unusable-quality. Good quality QCT for research requires meticulous attention to detail and standardization of all aspects of data collection and analysis to a degree that is uncommon in a clinical setting. Here, we review the literature to summarize practical and technical considerations for obtaining high quality QCT data, and provide examples of how each recommendation affects calculated variables. We also provide an overview of the QCT analysis technique to illustrate additional opportunities to improve data reproducibility and reliability. Key recommendations include: standardizing the scanner and data acquisition settings, minimizing image artifacts, selecting an appropriate reconstruction algorithm, and maximizing repeatability and objectivity during QCT analysis. The goal of the recommendations is to reduce potential sources of error throughout the analysis, from scan acquisition to the interpretation of results.

Effect of different CT scanners and settings on femoral failure loads calculated by finite element models

In a multi-center patient study, using different CT scanners, CT-based finite element (FE) models are utilized to calculate failure loads of femora with metastases. Previous studies showed that using different CT scanners can result in different outcomes. This study aims to quantify the effects of (i) different CT scanners; (ii) different CT protocols with variations in slice thickness, field of view (FOV), and reconstruction kernel; and (iii) air between calibration phantom and patient, on Hounsfield Units (HU), bone mineral density (BMD), and FE failure load. Six cadaveric femora were scanned on four CT scanners. Scans were made with multiple CT protocols and with or without an air gap between the body model and calibration phantom. HU and calibrated BMD were determined in cortical and trabecular regions of interest. Non-linear isotropic FE models were constructed to calculate failure load. Mean differences between CT scanners varied up to 7% in cortical HU, 6% in trabecular HU, 6% in cortical BMD, 12% in trabecular BMD, and 17% in failure load. Changes in slice thickness and FOV had little effect (≤4%), while reconstruction kernels had a larger effect on HU (16%), BMD (17%), and failure load (9%). Air between the body model and calibration phantom slightly decreased the HU, BMD, and failure loads (≤8%). In conclusion, this study showed that quantitative analysis of CT images acquired with different CT scanners, and particularly reconstruction kernels, can induce relatively large differences in HU, BMD, and failure loads. Additionally, if possible, air artifacts should be avoided. © 2018 Orthopaedic Research Society. © 2018 The Authors. Journal of Orthopaedic Research® Published by Wiley Periodicals, Inc. on behalf of the Orthopaedic Research Society. J Orthop Res.

Phantomless calibration of CT scans for measurement of BMD and bone strength-Inter-operator reanalysis precision

Patient-specific phantomless calibration of computed tomography (CT) scans has the potential to simplify and expand the use of pre-existing clinical CT for quantitative bone densitometry and bone strength analysis for diagnostic and monitoring purposes. In this study, we quantified the inter-operator reanalysis precision errors for a novel implementation of patient-specific phantomless calibration, using air and either aortic blood or hip adipose tissue as internal calibrating reference materials, and sought to confirm the equivalence between phantomless and (traditional) phantom-based measurements. CT scans of the spine and hip for 25 women and 15 men (mean±SD age of 67±9years, range 41-86years), one scan per anatomic site per patient, were analyzed independently by two analysts using the VirtuOst software (O.N. Diagnostics, Berkeley, CA). The scans were acquired at 120kVp, with a slice thickness/increment of 3mm or less, on nine different CT scanner models across 24 different scanners. The main parameters assessed were areal bone mineral density (BMD) at the hip (total hip and femoral neck), trabecular volumetric BMD at the spine, and vertebral and femoral strength by finite element analysis; other volumetric BMD measures were also assessed. We found that the reanalysis precision errors for all phantomless measurements were ≤0.5%, which was as good as for phantom calibration. Regression analysis indicated equivalence of the phantom- versus phantomless-calibrated measurements (slope not different than unity, R²≥0.98). Of the main parameters assessed, non-significant paired mean differences (n=40) between the two measurements ranged from 0.6% for hip areal BMD to 1.1% for mid-vertebral trabecular BMD. These results indicate that phantom-equivalent measurements of both BMD and finite element-derived bone strength can be reliably obtained from CT scans using patient-specific phantomless calibration.

The Estimation of Second-Generation HR-pQCT From First-Generation HR-pQCT Using In Vivo Cross-Calibration

Second-generation high-resolution peripheral quantitative computed tomography (HR-pQCT) provides the highest resolution in vivo to assess bone density and microarchitecture in 3D. Although strong agreement of most outcomes measured with first- (XCTI) and second- (XCTII) generation HR-pQCT has been demonstrated, the ability to use the two systems interchangeably is unknown. From in vivo measurements, we determined the limits of estimating XCTII data from XCTI scans conducted in vivo and whether that estimation can be improved by linear cross-calibration equations. These data are crucial as the research field transitions to the new technology. Our study design established cross-calibration equations by scanning 62 individuals on both systems on the same day and then tested those cross-calibrations on the same cohort 6 months later so that estimated (denoted as XCTII*) and "true" XCTII parameters could be compared. We calculated the generalized least-significant change (GLSC) for those predictions. There was strong agreement between both systems for density (R²  > 0.94), macroarchitecture (R²  > 0.95), and most microarchitecture outcomes with the exception of trabecular thickness (Tb.Th, R²  = 0.51 to 0.67). Linear regression equations largely eliminated the systematic error between XCTII and XCTII* and produced a good estimation of most outcomes, with individual error estimates between 0.2% and 3.4%, with the exception of Tt.BMD. Between-system GLSC was similar to within-XCTI LSC (eg, 8.3 to 41.9 mg HA/cm³ for density outcomes). We found that differences between outcomes assessed with XCTI and XCTII can be largely eliminated by cross-calibration. Tb.Th is poorly estimated because it is measured more accurately by XCTII than XCTI. It may be possible to use cross-calibration for most outcomes when both scanner generations are used for multicenter and longitudinal studies. © 2017 American Society for Bone and Mineral Research.

Quantitative Computed Tomography-Current Status and New Developments

This review focuses on new developments and current controversies in the field of quantitative computed tomography. Recent positions of the International Society for Clinical Densitometry acknowledged the clinical value of quantitative computed tomography of the spine and the hip using clinical whole-body computed tomography (CT) scanners. Opportunistic screening summarizes a number of new approaches describing the dual use of clinical CT scans. For example, CT scans may have been taken for tumor diagnosis but may also be used for the prediction of high or low fracture risks as an additional benefit for the patient. The assessment of the cortical parameters is another topic of current research. In CT images of the spine and the hip, a number of techniques have been developed to determine the thickness, mass, and bone density of the cortex. In higher-spatial resolution peripheral CT images of the radius and tibia obtained from special purpose scanners, 1 focus is the measurement of cortical porosity. Two different approaches, one based on the direct segmentation of the pores and one based on cortical density, will be reviewed.

Multicenter analysis of CIREN occupant lumbar bone mineral density and correlation with age and fracture incidence

OBJECTIVE

This study aimed to quantify lumbar volumetric bone mineral density (vBMD) for 873 seriously injured Crash Injury Research and Engineering Network (CIREN) motor vehicle crash occupants (372 male, 501 female) from 8 centers using phantomless computed tomography scans and to associate vBMD with age, fracture incidence, and osteopenia/osteoporosis diagnoses. The novelty of this work is that it associates vBMD with region of injury by applying an established method for vBMD measurement using phantomless computed tomography (CT).

METHODS

A validated phantomless CT calibration method that uses patient-specific fat and muscle measurements to calibrate vBMD measured from the L1-L5 trabeculae was applied on 873 occupants from various CIREN centers. CT-measured lumbar vBMD < 145 mg/cc is indicative of osteopenia using a published threshold. CIREN occupant lumbar vBMD in milligrams per cubic centimeter was regressed against age, osteopenia/osteoporosis comorbidities, height, weight, body mass index (BMI), and the incidence of fracture in vertebral (cervical, thoracic, lumbar) and rib/sternum regions.

RESULTS

Among the 873 occupants analyzed, 11% (92 occupants) were diagnosed as osteopenic in CIREN. Of these 92 occupants, 42% (39 occupants) had normal vBMD measures (≥145 mg/cc), suggesting possible misclassification in CIREN. Of the 134 occupants classified as osteopenic in vBMD analysis, 60% were not classified as osteopenic in CIREN, suggesting undiagnosed osteopenia, and 40% were correctly classified in CIREN. Age was negatively correlated with vBMD (P <.0001) and occupants with <145 mg/cc vBMD sustained a median number of 2 rib/sternum fractures compared to a median value of 0 rib/sternum fractures for the ≥145 mg/cc vBMD group (P <.0001). Vertebral fracture analysis revealed that the thoracolumbar region was the most common region of injury in the spine. Though the incidence of fracture was not significantly different in the thoracic (10% versus 6%, P =.122) and lumbar (16% versus 13%, P =.227) regions between the 2 bone quality groups, the proportion of thoracolumbar fractures was significantly higher in occupants with <145 mg/cc vBMD versus occupants with ≥145 mg/cc vBMD (24% versus 17%, P =.043).

CONCLUSIONS

Low lumbar vertebral bone quality is associated with an increased number of rib/sternum fractures and a greater incidence of thoracolumbar vertebral body fractures within the CIREN population analyzed.

Novel anthropomorphic hip phantom corrects systemic interscanner differences in proximal femoral vBMD

Quantitative computed tomography (QCT) is increasingly used in osteoporosis studies to assess volumetric bone mineral density (vBMD), bone quality and strength. However, QCT is confronted by technical issues in the clinical research setting, such as potentially confounding effects of body size on vBMD measurements and lack of standard approaches to scanner cross-calibration, which affects measurements of vBMD in multicenter settings. In this study, we addressed systematic inter-scanner differences and subject-dependent body size errors using a novel anthropomorphic hip phantom, containing a calibration hip to estimate correction equations, and a contralateral test hip to assess the quality of the correction. We scanned this phantom on four different scanners and we applied phantom-derived corrections to in vivo images of 16 postmenopausal women scanned on two scanners. From the phantom study, we found that vBMD decreased with increasing phantom size in three of four scanners and that inter-scanner variations increased with increasing phantom size. In the in vivo study, we observed that inter-scanner corrections reduced systematic inter-scanner mean vBMD differences but that the inter-scanner precision error was still larger than expected from known intra-scanner precision measurements. In conclusion, inter-scanner corrections and body size influence should be considered when measuring vBMD from QCT images.