3-D Subject-Specific Shape and Density Estimation of the Lumbar Spine From a Single Anteroposterior DXA Image Including Assessment of Cortical and Trabecular Bone

Unveiling interactions between intervertebral disc morphologies and mechanical behavior through personalized finite element modeling

Introduction: Intervertebral Disc (IVD) Degeneration (IDD) is a significant health concern, potentially influenced by mechanotransduction. However, the relationship between the IVD phenotypes and mechanical behavior has not been thoroughly explored in local morphologies where IDD originates. This work unveils the interplays among morphological and mechanical features potentially relevant to IDD through Abaqus UMAT simulations. Methods: A groundbreaking automated method is introduced to transform a calibrated, structured IVD finite element (FE) model into 169 patient-personalized (PP) models through a mesh morphing process. Our approach accurately replicates the real shapes of the patient's Annulus Fibrosus (AF) and Nucleus Pulposus (NP) while maintaining the same topology for all models. Using segmented magnetic resonance images from the former project MySpine, 169 models with structured hexahedral meshes were created employing the Bayesian Coherent Point Drift++ technique, generating a unique cohort of PP FE models under the Disc4All initiative. Machine learning methods, including Linear Regression, Support Vector Regression, and eXtreme Gradient Boosting Regression, were used to explore correlations between IVD morphology and mechanics. Results: We achieved PP models with AF and NP similarity scores of 92.06\% and 92.10\% compared to the segmented images. The models maintained good quality and integrity of the mesh. The cartilage endplate (CEP) shape was represented at the IVD-vertebra interfaces, ensuring personalized meshes. Validation of the constitutive model against literature data showed a minor relative error of 5.20%. Discussion: Analysis revealed the influential impact of local morphologies on indirect mechanotransduction responses, highlighting the roles of heights, sagittal areas, and volumes. While the maximum principal stress was influenced by morphologies such as heights, the disc's ellipticity influenced the minimum principal stress. Results suggest the CEPs are not influenced by their local morphologies but by those of the AF and NP. The generated free-access repository of individual disc characteristics is anticipated to be a valuable resource for the scientific community with a broad application spectrum.

Dataset of Finite Element Models of Normal and Deformed Thoracolumbar Spine

Adult spine deformity (ASD) is prevalent and leads to a sagittal misalignment in the vertebral column. Computational methods, including Finite Element (FE) Models, have emerged as valuable tools for investigating the causes and treatment of ASD through biomechanical simulations. However, the process of generating personalised FE models is often complex and time-consuming. To address this challenge, we present a dataset of FE models with diverse spine morphologies that statistically represent real geometries from a cohort of patients. These models are generated using EOS images, which are utilized to reconstruct 3D surface spine models. Subsequently, a Statistical Shape Model (SSM) is constructed, enabling the adaptation of a FE hexahedral mesh template for both the bone and soft tissues of the spine through mesh morphing. The SSM deformation fields facilitate the personalization of the mean hexahedral FE model based on sagittal balance measurements. Ultimately, this new hexahedral SSM tool offers a means to generate a virtual cohort of 16807 thoracolumbar FE spine models, which are openly shared in a public repository.

A novel image augmentation based on statistical shape and intensity models: application to the segmentation of hip bones from CT images

BACKGROUND

The collection and annotation of medical images are hindered by data scarcity, privacy, and ethical reasons or limited resources, negatively affecting deep learning approaches. Data augmentation is often used to mitigate this problem, by generating synthetic images from training sets to improve the efficiency and generalization of deep learning models.

METHODS

We propose the novel use of statistical shape and intensity models (SSIM) to generate augmented images with variety in both shape and intensity of imaged structures and surroundings. The SSIM uses segmentations from training images to create co-registered tetrahedral meshes of the structures and to efficiently encode image intensity in their interior with Bernstein polynomials. In the context of segmentation of hip joint (pathological) bones from retrospective computed tomography images of 232 patients, we compared the impact of SSIM-based and basic augmentations on the performance of a U-Net model.

RESULTS

In a fivefold cross-validation, the SSIM augmentation improved segmentation robustness and accuracy. In particular, the combination of basic and SSIM augmentation outperformed trained models not using any augmentation, or relying exclusively on a simple form of augmentation, achieving Dice similarity coefficient and Hausdorff distance of 0.95 [0.93-0.96] and 6.16 [4.90-8.08] mm (median [25th-75th percentiles]), comparable to previous work on pathological hip segmentation.

CONCLUSIONS

We proposed a novel augmentation varying both the shape and appearance of structures in generated images. Tested on bone segmentation, our approach is generalizable to other structures or tasks such as classification, as long as SSIM can be built from training data.

RELEVANCE STATEMENT

Our data augmentation approach produces realistic shape and appearance variations of structures in generated images, which supports the clinical adoption of AI in radiology by alleviating the collection of clinical imaging data and by improving the performance of AI applications.

KEY POINTS

• Data augmentation generally improves the accuracy and generalization of deep learning models. • Traditional data augmentation does not consider the appearance of imaged structures. • Statistical shape and intensity models (SSIM) synthetically generate variations of imaged structures. • SSIM support novel augmentation approaches, demonstrated with computed tomography bone segmentation.

Bone Mineral Density in Adult Patients with Type 1 Diabetes Mellitus Assessed by Both DXA and QCT

Purpose

Bone mineral density (BMD) was measured in uncomplicated young adult patients with type 1 diabetes mellitus (T1DM) and sex- and age-matched controls, using both dual X-ray absorptiometry (DXA) and quantitative computed tomography (QCT) to investigate their diagnostic ability in detecting abnormal values in these patients.

Methods

118 patients with T1DM (65 females, mean age 30.12 ± 8.78 years) and 94 sex- and age-matched controls were studied. BMD was assessed in all participants by DXA and QCT at lumbar spine (LS). Biochemical markers of bone metabolism were also measured.

Results

T1DM was associated with lower BMD at L1-L3 vertebrae measured by both DXA and QCT and lower bone turnover compared to sex- and age-matched controls. In T1DM subjects, QCT detected more patients with abnormal BMD values compared to DXA. BMI and HbA1c levels were the only determinants of BMD. Bone turnover markers were lower in patients with longer duration of diabetes.

Conclusion

QCT provides a higher sensitivity compared to DXA in detecting abnormal BMD values in patients with uncomplicated T1DM. In these patients, the diabetes-related decreased BMD may be present early, before it is detected by DXA, the clinical gold standard for BMD measurements, and before the presence of any other diabetes complications, stressing the importance of an early intervention for fracture prevention.

X-Ray to DRR Images Translation for Efficient Multiple Objects Similarity Measures in Deformable Model 3D/2D Registration

The robustness and accuracy of the intensity-based 3D/2D registration of a 3D model on planar X-ray image(s) is related to the quality of the image correspondences between the digitally reconstructed radiographs (DRR) generated from the 3D models (varying image) and the X-ray images (fixed target). While much effort may be devoted to generating realistic DRR that are similar to real X-rays (using complex X-ray simulation, adding densities information in 3D models, etc.), significant differences still remain between DRR and real X-ray images. Differences such as the presence of adjacent or superimposed soft tissue and bony or foreign structures lead to image matching difficulties and decrease the 3D/2D registration performance. In the proposed method, the X-ray images were converted into DRR images using a GAN-based cross-modality image-to-images translation. With this added prior step of XRAY-to-DRR translation, standard similarity measures become efficient even when using simple and fast DRR projection. For both images to match, they must belong to the same image domain and essentially contain the same kind of information. The XRAY-to-DRR translation also addresses the well-known issue of registering an object in a scene composed of multiple objects by separating the superimposed or/and adjacent objects to avoid mismatching across similar structures. We applied the proposed method to the 3D/2D fine registration of vertebra deformable models to biplanar radiographs of the spine. We showed that the XRAY-to-DRR translation enhances the registration results, by increasing the capture range and decreasing dependence on the similarity measure choice since the multi-modal registration becomes mono-modal.

The accuracy of statistical shape models in predicting bone shape: A systematic review

BACKGROUND

This systematic review aims to ascertain how accurately 3D models can be predicted from two-dimensional (2D) imaging utilising statistical shape modelling.

METHODS

A systematic search of published literature was conducted in September 2022. All papers which assessed the accuracy of 3D models predicted from 2D imaging utilising statistical shape models and which validated the models against the ground truth were eligible.

RESULTS

2127 papers were screened and a total of 34 studies were included for final data extraction. The best overall achievable accuracy was 0.45 mm (root mean square error) and 0.16 mm (average error).

CONCLUSION

Statistical shape modelling can predict detailed 3D anatomical models from minimal 2D imaging. Future studies should report the intended application domain of the model, the level of accuracy required, the underlying demographics of subjects, and the method in which accuracy was calculated, with root mean square error recommended if appropriate.

Statistical multi-level shape models for scalable modeling of multi-organ anatomies

Statistical shape modeling is an indispensable tool in the quantitative analysis of anatomies. Particle-based shape modeling (PSM) is a state-of-the-art approach that enables the learning of population-level shape representation from medical imaging data (e.g., CT, MRI) and the associated 3D models of anatomy generated from them. PSM optimizes the placement of a dense set of landmarks (i.e., correspondence points) on a given shape cohort. PSM supports multi-organ modeling as a particular case of the conventional single-organ framework via a global statistical model, where multi-structure anatomy is considered as a single structure. However, global multi-organ models are not scalable for many organs, induce anatomical inconsistencies, and result in entangled shape statistics where modes of shape variation reflect both within- and between-organ variations. Hence, there is a need for an efficient modeling approach that can capture the inter-organ relations (i.e., pose variations) of the complex anatomy while simultaneously optimizing the morphological changes of each organ and capturing the population-level statistics. This paper leverages the PSM approach and proposes a new approach for correspondence-point optimization of multiple organs that overcomes these limitations. The central idea of multilevel component analysis, is that the shape statistics consists of two mutually orthogonal subspaces: the within-organ subspace and the between-organ subspace. We formulate the correspondence optimization objective using this generative model. We evaluate the proposed method using synthetic shape data and clinical data for articulated joint structures of the spine, foot and ankle, and hip joint.

Lumbar Bone Mineral Density Estimation From Chest X-Ray Images: Anatomy-Aware Attentive Multi-ROI Modeling

Osteoporosis is a common chronic metabolic bone disease often under-diagnosed and under-treated due to the limited access to bone mineral density (BMD) examinations, e.g., via Dual-energy X-ray Absorptiometry (DXA). This paper proposes a method to predict BMD from Chest X-ray (CXR), one of the most commonly accessible and low-cost medical imaging examinations. The proposed method first automatically detects Regions of Interest (ROIs) of local CXR bone structures. Then a multi-ROI deep model with transformer encoder is developed to exploit both local and global information in the chest X-ray image for accurate BMD estimation. The proposed method is evaluated on 13719 CXR patient cases with ground truth BMD measured by the gold standard DXA. The model predicted BMD has a strong correlation with the ground truth (Pearson correlation coefficient 0.894 on lumbar 1). When applied in osteoporosis screening, it achieves a high classification performance (average AUC of 0.968). As the first effort of using CXR scans to predict the BMD, the proposed algorithm holds strong potential to promote early osteoporosis screening and public health.

Cortex or cancellous-which is early for the decrease of bone content for vertebral body in health?

OBJECTIVE

To obtain the cortex and cancellous parameter of the vertebral bone of healthy subjects using QCT. To explore which is earlier or faster for bone loss with age.

MATERIALS AND METHODS

733 physical examiners underwent chest low-dose CT examination were recruited, from April 1, 2021 to October 1, 2021. QCT sequence was used to obtain the bone mineral density of T12-L2 vertebral body without additional radiation. The mass and area of vertebral cortex and cancellous at the central level of L2 vertebral body were measured. The age -related characteristics of vertebral cortex and cancellous between male and female was analyzed and compared.

RESULTS

The vBMD of T12-L2 vertebral body decreased with age. Significant differences were found in volumetric bone mineral density (vBMD) of T12-L2 vertebral body. For female, significant differences were found in bone content involving cortical mass, cancellous mass, cortical area, cancellous area, cortical mass/cancellous mass and cortical area/cancellous area in different age groups, respectively. The cortical mass decreased with age in female. The cancellous mass of female increased and then decreased with peak at 31-40 y. The cortical area of female decreased gradually before 71 y. The cancellous area of female increased and then decreased with peak at 51-60 y. The values of mass ratio and area ratio in female showed a slowly downward trend with age. Significant differences of bone content between non-menopausal and menopausal women were found except the cancellous mass. For male, no significant differences were found in all parameters of bone content.

CONCLUSION

The changes of vertebral BMD, bone content of cortex and cancellous have different characteristics in different age. The change of cortex in female maybe earlier and faster than that of cancellous, especially in menopausal women.

Effect of transcutaneous electrical acupoint stimulation on bone metabolism in patients with immobilisation after foot and ankle fracture surgery: a randomised controlled trial study protocol

INTRODUCTION

Fracture is a disease with a high incidence worldwide. Foot and ankle fractures are common among fractures of the lower extremities. Foot and ankle fractures usually require surgical fixation and a period of fixed treatment, which can lead to decreased bone density. Although transcutaneous electrical acupoint stimulation (TEAS) is widely used for movement system diseases, there is minimal evidence to show the effectiveness of TEAS on patients after surgical fixation of ankle and foot fractures. This trial aims to evaluate whether TEAS can reduce bone loss in patients with immobilisation after ankle and foot fractures.

METHODS AND ANALYSIS

A randomised controlled trial will be conducted in which 60 patients will be randomly divided into two groups: (a) the control group will be treated according to the routine procedures of basic orthopaedics treatment; (b) in the treatment group, bilateral SP36, BL23 and ST36 will be performed on the basis of the control group, and the test will be performed for 30 min every other day for a total of 8 weeks. Bone turnover markers will be used as primary outcome. Secondary outcomes are composed of blood phosphorus, blood calcium and bone mineral density. Treatment safety will be monitored and recorded.

ETHICS AND DISSEMINATION

This trial is approved by the Ethics Committee of Beijing University of Chinese Medicine (2020BZYLL0611) and the Ethics Committee of Beijing Luhe Hospital (2020-LHKY-055-02), and inpatients who meet the following diagnostic and inclusion criteria are eligible to participate in this study.

TRIAL REGISTRATION NUMBER

ChiCTR 2000039944.

Statistical Shape and Appearance Models: Development Towards Improved Osteoporosis Care

PURPOSE OF REVIEW

Statistical models of shape and appearance have increased their popularity since the 1990s and are today highly prevalent in the field of medical image analysis. In this article, we review the recent literature about how statistical models have been applied in the context of osteoporosis and fracture risk estimation.

RECENT FINDINGS

Recent developments have increased their ability to accurately segment bones, as well as to perform 3D reconstruction and classify bone anatomies, all features of high interest in the field of osteoporosis and fragility fractures diagnosis, prevention, and treatment. An increasing number of studies used statistical models to estimate fracture risk in retrospective case-control cohorts, which is a promising step towards future clinical application. All the reviewed application areas made considerable steps forward in the past 5-6 years. Heterogeneities in validation hinder a thorough comparison between the different methods and represent one of the future challenges to be addressed to reach clinical implementation.

Association between osteoporotic femoral neck fractures and DXA-derived 3D measurements at lumbar spine: a case-control study

A case-control study assessing the association of DXA-derived 3D measurements at lumbar spine with osteoporotic hip fractures was performed. Stronger association was found between transcervical hip fractures and integral (AUC = 0.726), and cortical (AUC = 0.696) measurements at the lumbar spine compared with measurements at the trabecular bone (AUC = 0.617); although femur areal bone mineral density (aBMD) remains the referent measurement for hip fracture risk evaluation (AUC = 0.838).

PURPOSE

The aim of the present study was to evaluate the association between DXA-derived 3D measurements at lumbar spine and osteoporotic hip fractures.

METHODS

We analyzed a case-control database composed by 61 women with transcervical hip fractures and 61 age-matched women without any type of fracture. DXA scans at lumbar spine were acquired, and areal bone mineral density (aBMD) was measured. Integral, trabecular and cortical volumetric BMD (vBMD), cortical thickness, and cortical surface BMD (sBMD) at different regions of interest were assessed using a DXA-based 3D modeling software. Descriptive statistics, tests of difference, odds ratio (OR), and area under the receiver operating curve (AUC) were used to compare hip fracture and control groups.

RESULTS

Integral vBMD, cortical vBMD, cortical sBMD, and cortical thickness were the DXA-derived 3D measurements at lumbar spine that showed the stronger association with transcervical hip fractures, with AUCs in the range of 0.685-0.726, against 0.670 for aBMD. The highest AUC (0.726) and OR (2.610) at the lumbar spine were found for integral vBMD at the posterior vertebral elements. Significantly, lower AUC (0.617) and OR (1.607) were found for trabecular vBMD at the vertebral body. Overall, total femur aBMD remains the DXA-derived measurement showing the highest AUC (0.838) and OR (6.240).

CONCLUSION

This study showed the association of DXA-derived measurements at lumbar spine with transcervical hip fractures. A strong association between vBMD at the posterior vertebral elements and transcervical hip fractures was observed, probably because of global deterioration of the cortical bone. Further studies should be carried out to investigate on the relative risk of transcervical fracture in patients with long-term cortical structural deterioration.

Discrimination of osteoporosis-related vertebral fractures by DXA-derived 3D measurements: a retrospective case-control study

A retrospective case-control study assessing the association of DXA-derived 3D measurements with osteoporosis-related vertebral fractures was performed. Trabecular volumetric bone mineral density was the measurement that best discriminates between fracture and control groups.

INTRODUCTION

The aim of the present study was to evaluate the association of DXA-derived 3D measurements at the lumbar spine with osteoporosis-related vertebral fractures.

METHODS

We retrospectively analyzed a database of 74 postmenopausal women: 37 subjects with incident vertebral fractures and 37 age-matched controls without any type of fracture. DXA scans at the lumbar spine were acquired at baseline (i.e., before the fracture event for subjects in the fracture group), and areal bone mineral density (aBMD) was measured. DXA-derived 3D measurements, such as volumetric BMD (vBMD), were assessed using a DXA-based 3D modeling software (3D-SHAPER). vBMD was computed at the trabecular, cortical, and integral bone. Cortical thickness and cortical surface BMD were also measured. Differences in DXA-derived measurements between fracture and control groups were evaluated using unpaired t test. Odds ratio (OR) and area under the receiver operating curve (AUC) were also computed. Subgroup analyses according to fractured vertebra were performed.

RESULTS

aBMD of fracture group was 9.3% lower compared with control group (p < 0.01); a higher difference was found for trabecular vBMD in the vertebral body (- 16.1%, p < 0.001). Trabecular vBMD was the measurement that best discriminates between fracture and control groups, with an AUC of 0.733, against 0.682 for aBMD. Overall, similar findings were observed within the subgroup analyses. The L1 vertebral fractures subgroup had the highest AUC at trabecular vBMD (0.827), against aBMD (0.758).

CONCLUSION

This study showed the ability of cortical and trabecular measurements from DXA-derived 3D models to discriminate between fracture and control groups. Large cohorts need to be analyzed to determine if these measurements could improve fracture risk prediction in clinical practice.