Tristan Whitmarsh

Reconstructing the 3D Shape and Bone Mineral Density Distribution of the Proximal Femur From Dual-Energy X-Ray Absorptiometry

The accurate diagnosis of osteoporosis has gained increasing importance due to the aging of our society. Areal bone mineral density (BMD) measured by dual-energy X-ray absorptiometry (DXA) is an established criterion in the diagnosis of osteoporosis. This measure, however, is limited by its two-dimensionality. This work presents a method to reconstruct both the 3D bone shape and 3D BMD distribution of the proximal femur from a single DXA image used in clinical routine. A statistical model of the combined shape and BMD distribution is presented, together with a method for its construction from a set of quantitative computed tomography (QCT) scans. A reconstruction is acquired in an intensity based 3D-2D registration process whereby an instance of the model is found that maximizes the similarity between its projection and the DXA image. Reconstruction experiments were performed on the DXA images of 30 subjects, with a model constructed from a database of QCT scans of 85 subjects. The accuracy was evaluated by comparing the reconstructions with the same subject QCT scans. The method presented here can potentially improve the diagnosis of osteoporosis and fracture risk assessment from the low radiation dose and low cost DXA devices currently used in clinical routine.

A High-Resolution Atlas and Statistical Model of the Human Heart From Multislice CT

Atlases and statistical models play important roles in the personalization and simulation of cardiac physiology. For the study of the heart, however, the construction of comprehensive atlases and spatio-temporal models is faced with a number of challenges, in particular the need to handle large and highly variable image datasets, the multi-region nature of the heart, and the presence of complex as well as small cardiovascular structures. In this paper, we present a detailed atlas and spatio-temporal statistical model of the human heart based on a large population of 3D+time multi-slice computed tomography sequences, and the framework for its construction. It uses spatial normalization based on nonrigid image registration to synthesize a population mean image and establish the spatial relationships between the mean and the subjects in the population. Temporal image registration is then applied to resolve each subject-specific cardiac motion and the resulting transformations are used to warp a surface mesh representation of the atlas to fit the images of the remaining cardiac phases in each subject. Subsequently, we demonstrate the construction of a spatio-temporal statistical model of shape such that the inter-subject and dynamic sources of variation are suitably separated. The framework is applied to a 3D+time data set of 138 subjects. The data is drawn from a variety of pathologies, which benefits its generalization to new subjects and physiological studies. The obtained level of detail and the extendability of the atlas present an advantage over most cardiac models published previously.

Hip fracture discrimination from dual-energy X-ray absorptiometry by statistical model registration

Although the areal Bone Mineral Density (BMD) measurements from dual-energy X-ray absorptiometry (DXA) are able to discriminate between hip fracture cases and controls, the femoral strength is largely determined by the 3D bone structure. In a previous work a statistical model was presented which parameterizes the 3D shape and BMD distribution of the proximal femur. In this study the parameter values resulting from the registration of the model onto DXA images are evaluated for their hip fracture discrimination ability with respect to regular DXA derived areal BMD measurements. The statistical model was constructed from a large database of QCT scans of females with an average age of 67.8 ± 17.0 years. This model was subsequently registered onto the DXA images of a fracture and control group. The fracture group consisted of 175 female patients with an average age of 66.4 ± 9.9 years who suffered a fracture on the contra lateral femur. The control group consisted of 175 female subjects with an average age of 65.3 ± 10.0 years and no fracture history. The discrimination ability of the resulting model parameter values, as well as the areal BMD measurements extracted from the DXA images were evaluated using a logistic regression analysis. The area under the receiver operating curve (AUC) of the combined model parameters and areal BMD values was 0.840 (95% CI 0.799-0.881), whilst using only the areal BMD values resulted in an AUC of 0.802 (95% CI 0.757-0.848). These results indicate that the discrimination ability of the areal BMD values is improved by supplementing them with the model parameter values, which give a more complete representation of the subject specific shape and internal bone distribution. Thus, the presented method potentially allows for an improved hip fracture risk estimation whilst maintaining DXA as the current standard modality.

A statistical model of shape and bone mineral density distribution of the proximal femur for fracture risk assessment

This work presents a statistical model of both the shape and Bone Mineral Density (BMD) distribution of the proximal femur for fracture risk assessment. The shape and density model was built from a dataset of Quantitative Computed Tomography scans of fracture patients and a control group. Principal Component Analysis and Horns parallel analysis were used to reduce the dimensionality of the shape and density model to the main modes of variation. The input data was then used to analyze the model parameters for the optimal separation between the fracture and control group. Feature selection using the Fisher criterion determined the parameters with the best class separation, which were used in Fisher Linear Discriminant Analysis to find the direction in the parameter space that best separates the fracture and control group. This resulted in a Fisher criterion value of 6.70, while analyzing the Dual-energy X-ray Absorptiometry derived femur neck areal BMD of the same subjects resulted in a Fisher criterion value of 0.98. This indicates that a fracture risk estimation approach based on the presented model might improve upon the current standard clinical practice.

3D reconstruction of both shape and Bone Mineral Density distribution of the femur from DXA images

The diagnosis of osteoporosis and the prevention of femur fractures is a major challenge for our society. However, the diagnosis performed in clinical routine from Dual Energy X-ray Absorptiometry (DXA) images is limited. This paper proposes a 3D reconstruction method of both the shape and the Bone Mineral Density (BMD) distribution of the proximal femur from routinely used DXA images. The reconstruction accuracy that can be obtained from single-view and multi-view DXA devices was assessed. This evaluation, from 20 bone specimens and simulated DXA images, highlighted a mean shape accuracy of 1.3mm and a BMD accuracy of 4.4% from a single-view DXA image. A multi-view configuration with 2 views (frontal-sagittal) appeared as a good compromise (mean shape accuracy of 0.9mm and BMD accuracy of 3.2%). We are currently using this method for in vivo clinical studies in order to improve the diagnosis of osteoporosis and the prevention of femur fractures.

3D bone mineral density distribution and shape reconstruction of the proximal femur from a single simulated DXA image: an in vitro study

Area Bone Mineral Density (aBMD) measured by Dual-energy X-ray Absorptiometry (DXA) is an established criterion in the evaluation of hip fracture risk. The evaluation from these planar images, however, is limited to 2D while it has been shown that proper 3D assessment of both the shape and the Bone Mineral Density (BMD) distribution improves the fracture risk estimation. In this work we present a method to reconstruct both the 3D bone shape and 3D BMD distribution of the proximal femur from a single DXA image. A statistical model of shape and a separate statistical model of the BMD distribution were automatically constructed from a set of Quantitative Computed Tomography (QCT) scans. The reconstruction method incorporates a fully automatic intensity based 3D-2D registration process, maximizing the similarity between the DXA and a digitally reconstructed radiograph of the combined model. For the construction of the models, an in vitro dataset of QCT scans of 60 anatomical specimens was used. To evaluate the reconstruction accuracy, experiments were performed on simulated DXA images from the QCT scans of 30 anatomical specimens. Comparisons between the reconstructions and the same subject QCT scans showed a mean shape accuracy of 1.2mm, and a mean density error of 81mg/cm3. The results show that this method is capable of accurately reconstructing both the 3D shape and 3D BMD distribution of the proximal femur from DXA images used in clinical routine, potentially improving the diagnosis of osteoporosis and fracture risk assessments at a low radiation dose and low cost.

A groupwise mutual information metric for cost efficient selection of a suitable reference in cardiac computational atlas construction

Computational atlases based on nonrigid registration have found much use in the medical imaging community. To avoid bias to any single element of the training set, there are two main approaches: using a (random) subject to serve as an initial reference and posteriorly removing bias, and a true groupwise registration with a constraint of zero average transformation for direct computation of the atlas. Major drawbacks are the possible selection of an outlier on one side, and an initialization with an invalid instance on the other. In both cases there is great potential for affecting registration performance, and producing a final average image in which the structure of interest deviates from the central anatomy of the population under study. We propose an inexpensive means of reference selection based on a groupwise correspondence measure, which avoids the selection of an outlier and is independent from the atlas construction approach that follows. Thus, it improves tractability of reference selection and robustness of automated atlas construction. We illustrate the method using a set of 20 cardiac multislice computed tomography volumes.

Technical Note: Comparison between single and multiview simulated DXA configurations for reconstructing the 3D shape and bone mineral density distribution of the proximal femur

PURPOSE Dual-energy x-ray absorptiometry (DXA) is used in clinical routine to provide a two-dimensional (2D) analysis of the bone mineral density (BMD). 3D reconstruction methods from 2D DXA images could improve the BMD analysis. To find the optimal configuration that should be used in clinical routine, this paper relies on a 3D reconstruction method from DXA images to compare the accuracy that can be obtained from one single-view and from multiview DXA images (two to four projections). METHODS The 3D reconstruction method uses a statistical model and a nonrigid registration technique to recover in 3D the shape and the BMD distribution of the proximal femur. The accuracy was evaluated in vivo by comparing 3D reconstructions obtained from simulated DXA images of 30 patients (using between one and four DXA views) with quantitative computed tomography reconstructions. RESULTS This comparison showed that the use of one single DXA provides accurate 3D reconstructions (mean shape accuracy of 1.0 mm and BMD distribution errors of 7.0%). Among the multiview configurations, the use of two views (0° and 45°) was the best compromise, increasing the accuracy of pose (mean accuracy of 0.7°/1.2°/0.9° against 1.0°/3.5°/3.3° for the single view), reducing slightly the BMD errors (5.7%) while maintaining the same shape accuracy. CONCLUSIONS The use of two views constitutes an interesting configuration when multiview DXA devices are available in clinical routine. However, the use of only one single view remains an accurate solution to recover the shape and the BMD distribution in 3D, with the advantage of a higher potential for clinical translation.

3D reconstruction of intervertebral discs from T1-weighted magnetic resonance images

Low back pain is a current and increasing problem closely related to intervertebral disc degeneration, which is responsible for over 90% of spinal surgical procedures. In clinical routine, clinicians base their diagnosis of disc degeneration on 2D analysis of Magnetic Resonance (MR) images. In this work, an automatic 3D segmentation method, based on active shape models, is presented for both degenerated and normal intervertebral discs. A database of 25 intervertebral discs was used to semi-automatically build a shape statistical model and intensity models. Then, a 3D reconstruction was achieved by using those models to deform an initial shape. The method was evaluated using the 25 intervertebral discs and a leave-one-out cross validation, resulting in a mean shape accuracy of 1.6mm and a mean dice similarity index of 83.6%. This automatic and accurate 3D reconstruction method opens the way for an improved diagnosis of disc degeneration.

Age-Related changes in vertebral morphometry by statistical shape analysis

The morphological changes of the vertebrae associated with normal aging are still subject of debate, whereas this knowledge is important in detecting vertebral fractures and degenerative shape changes. The aim of this study is to present a method to statistically analyze the vertebral shape and determining the morphometric changes related to normal aging. The analysis is performed on the L2 lumbar vertebrae from a large dataset of Computed Tomography scans. The surface meshes of all vertebrae, with a groupwise vertex correspondence between them, are first acquired by an intensity based registration process onto a segmented reference. Principal component analysis then reduces the dimensionality to the main modes of variation which were subsequently analyzed by multiple linear regression to acquire the global shape variations with respect to the age of the subjects. In addition, the correlation with age of the deformation at each mesh vertex is analyzed, giving a significance map of the age related changes. This analysis shows several shape changes which are in agreement with previous studies while also giving a more detailed global shape analysis. Understanding the normal shape changes allows for a better diagnosis of vertebral fractures and spinal pathologies.