Shape/image registration for medical imaging : novel algorithms and applications.

This dissertation looks at two different categories of the registration approaches: Shape registration, and Image registration. It also considers the applications of these approaches into the medical imaging field. Shape registration is an important problem in computer vision, computer graphics and medical imaging. It has been handled in different manners in many applications like shapebased segmentation, shape recognition, and tracking. Image registration is the process of overlaying two or more images of the same scene taken at different times, from different viewpoints, and/or by different sensors. Many image processing applications like remote sensing, fusion of medical images, and computer-aided surgery need image registration. This study deals with two different applications in the field of medical image analysis. The first one is related to shape-based segmentation of the human vertebral bodies (VBs). The vertebra consists of the VB, spinous, and other anatomical regions. Spinous pedicles, and ribs should not be included in the bone mineral density (BMD) measurements. The VB segmentation is not an easy task since the ribs have similar gray level information. This dissertation investigates two different segmentation approaches. Both of them are obeying the variational shape-based segmentation frameworks. The first approach deals with two dimensional (2D) case. This segmentation approach starts with obtaining the initial segmentation using the intensity/spatial interaction models. Then, shape model is registered to the image domain. Finally, the optimal segmentation is obtained using the optimization of an energy functional which integrating the shape model with the intensity information. The second one is a 3D simultaneous segmentation and registration approach. The information of the intensity is handled by embedding a Willmore flow into the level set segmentation framework. Then the shape variations are estimated using a new distance probabilistic model. The experimental results show that the segmentation accuracy of the framework are much higher than other alternatives. Applications on BMD measurements of vertebral body are given to illustrate the accuracy of the proposed segmentation approach. The second application is related to the field of computer-aided surgery, specifically on ankle fusion surgery. The long-term goal of this work is to apply this technique to ankle fusion surgery to determine the proper size and orientation of the screws that are used for fusing the bones together. In addition, we try to localize the best bone region to fix these screws. To achieve these goals, the 2D-3D registration is introduced. The role of 2D-3D registration is to enhance the quality of the surgical procedure in terms of time and accuracy, and would greatly reduce the need for repeated surgeries; thus, saving the patients time, expense, and trauma

Detection of osteoporosis in lumbar spine [L1-L4] trabecular bone: a review article

The human bones are categorized based on elemental micro architecture and porosity. The porosity of the inner trabecular bone is high that is 40-95% and the nature of the bone is soft and spongy where as the cortical bone is harder and is less porous that is 5 to 15%. Osteoporosis is a disease that normally affects women usually after their menopause. It largely causes mild bone fractures and further stages lead to the demise of an individual. This analysis is on the basis of bone mineral density (BMD) standards obtained through a variety of scientific methods experimented from different skeletal regions. The detection of osteoporosis in lumbar spine has been widely recognized as a promising way to frequent fractures. Therefore, premature analysis of osteoporosis will estimate the risk of the bone fracture which prevents life threats. This paper focuses on the advanced technology in imaging systems and fracture probability analysis of osteoporosis detection. The various segmentation techniques are explored to examine osteoporosis in particular region of the image and further significant attributes are extracted using different methods to classify normal and abnormal (osteoporotic) bones. The limitations of the reviewed papers are more in feature dimensions, lesser accuracy and expensive imaging modalities like computed tomography (CT), magnetic resonance imaging (MRI), and DEXA. To overcome these limitations it is suggested to have less feature dimensions, more accuracy and cost-effective imaging modality like X-ray. This is required to avoid bone fractures and to improve BMD with precision which further helps in the diagnosis of osteoporosis

An Analysis by Synthesis Approach for Automatic Vertebral Shape Identification in Clinical QCT

Quantitative computed tomography (QCT) is a widely used tool for osteoporosis diagnosis and monitoring. The assessment of cortical markers like cortical bone mineral density (BMD) and thickness is a demanding task, mainly because of the limited spatial resolution of QCT. We propose a direct model based method to automatically identify the surface through the center of the cortex of human vertebra. We develop a statistical bone model and analyze its probability distribution after the imaging process. Using an as-rigid-as-possible deformation we find the cortical surface that maximizes the likelihood of our model given the input volume. Using the European Spine Phantom (ESP) and a high resolution \mu CT scan of a cadaveric vertebra, we show that the proposed method is able to accurately identify the real center of cortex ex-vivo. To demonstrate the in-vivo applicability of our method we use manually obtained surfaces for comparison.Comment: Presented on German Conference on Pattern Recognition (GCPR) 2018 in Stuttgar

Probabilistic and geometric shape based segmentation methods.

Image segmentation is one of the most important problems in image processing, object recognition, computer vision, medical imaging, etc. In general, the objective of the segmentation is to partition the image into the meaningful areas using the existing (low level) information in the image and prior (high level) information which can be obtained using a number of features of an object. As stated in [1,2], the human vision system aims to extract and use as much information as possible in the image including but not limited to the intensity, possible motion of the object (in sequential images), spatial relations (interaction) as the existing information, and the shape of the object which is learnt from the experience as the prior information. The main objective of this dissertation is to couple the prior information with the existing information since the machine vision system cannot predict the prior information unless it is given. To label the image into meaningful areas, the chosen information is modelled to fit progressively in each of the regions by an optimization process. The intensity and spatial interaction (as the existing information) and shape (as the prior information) are modeled to obtain the optimum segmentation in this study. The intensity information is modelled using the Gaussian distribution. Spatial interaction that describes the relation between neighboring pixels/voxels is modelled by assuming that the pixel intensity depends on the intensities of the neighboring pixels. The shape model is obtained using occurrences of histogram of training shape pixels or voxels. The main objective is to capture the shape variation of the object of interest. Each pixel in the image will have three probabilities to be an object and a background class based on the intensity, spatial interaction, and shape models. These probabilistic values will guide the energy (cost) functionals in the optimization process. This dissertation proposes segmentation frameworks which has the following properties: i) original to solve some of the existing problems, ii) robust under various segmentation challenges, and iii) fast enough to be used in the real applications. In this dissertation, the models are integrated into different methods to obtain the optimum segmentation: 1) variational (can be considered as the spatially continuous), and 2) statistical (can be considered as the spatially discrete) methods. The proposed segmentation frameworks start with obtaining the initial segmentation using the intensity / spatial interaction models. The shape model, which is obtained using the training shapes, is registered to the image domain. Finally, the optimal segmentation is obtained using the optimization of the energy functionals. Experiments show that the use of the shape prior improves considerably the accuracy of the alternative methods which use only existing or both information in the image. The proposed methods are tested on the synthetic and clinical images/shapes and they are shown to be robust under various noise levels, occlusions, and missing object information. Vertebral bodies (VBs) in clinical computed tomography (CT) are segmented using the proposed methods to help the bone mineral density measurements and fracture analysis in bones. Experimental results show that the proposed solutions eliminate some of the existing problems in the VB segmentation. One of the most important contributions of this study is to offer a segmentation framework which can be suitable to the clinical works

Simulation of fracture strength improvements of a human proximal femur using finite element analysis.

The most common hip fracture in the elderly occurs as a result of a fall to the side with impact over the greater trochanter resulting in a fracture of the proximal femur. The fracture usually involves the femoral neck or the intertrochanteric region. It has recently been determined that the fracture crack of a hip fracture typically initiates on the superior-lateral cortex of the femoral neck and then propagates across the femoral neck, resulting in a complete fracture. The strength of the superior-lateral cortex of the femoral neck is likely determined by the combined properties of the generally thin cortex (outer layer) and the underlying trabecular bone in this region. The objective of this study was to determine the relative effects of increasing or decreasing the thickness of these bone tissues on the overall failure strength of the proximal femur. The clinical significance of this work relates to hip fracture risk with various potential treatment options to improve either cortical or trabecular bone quality. A human femur obtained from a 68 year old female donor was scanned using computed tomography at 60-micron voxel resolution and a series of high-resolution finite element models were generated. The models were constructed with a base-element dimension of 120 microns and models included a basic model with cortical and trabecular thicknesses representative of the cadaver specimen from the original scan. Other models used a standardized algorithm to either dilate or erode the trabecular and cortical bone compartments of the femoral neck so that a total of nine models were created including the basic model. Each model was used to simulate a fall-to-the-side loading condition with appropriate boundary and loading conditions as used in previous models and experiments. An experimental test of the cadaver femur was also performed with three strain gauges placed on the proximal femur: on the superior-lateral cortex, on the inferior-medial cortex, and on the medial cortex positioned distal to the lesser trochanter. This femur was loaded at a rate of 100 mm/s until fracture of the femoral neck using a standard fall-to-the-side setup and the applied load and gauge strains were recorded. The femur neck fractured at a load of 2140 N. To validate the basic finite element model, the strain gauge strains at the load levels of 1000 N and 2000 N were compared to the calculated strains from the basic model at the same loads and same location as the gauge on the cadaver femur. After the basic model was validated, a failure criterion was determined as the volume percentage of the elements in the model that had exceeded 7000 µε at the failure load corresponding to the load at which the cadaver femur failed. Subsequently, this failure criterion was applied to the other eight models as a parametric analysis to estimate the increase or decrease in failure strength caused by the changes in cortical and trabecular thickness. The validation test results showed that the basic finite element model calculated strain on the superolateral cortex was within 2.1% of the experimentally measured strain at 1000 N loading. The validated basic model was then used to determine that the percentage of finite elements (by volume of the model) in excess of 7000 µε at the failure load was 4.2%. This failure criterion was then used to estimate the failure load for the other eight models with different combinations of either thicker (+120 µm) or thinner (-120 µm) cortex and trabeculae in the femoral neck. The calculated failure loads ranged from 324 N for the model with thinned cortex and thinned trabeculae to 3336 N for the model with thickened cortex and thickened trabeculae. The model with normal cortex and thickened trabeculae had a failure load of 3242 N, which is only 2.8% less than the strongest case. The largest single parameter effect on proximal femoral strength is realized by an increase in trabecular thickness. This is somewhat surprising considering that cortical bone is typically stronger than cancellous bone. However, the spatial arrangement of trabecular bone and the buttress support it provides to the thin cortex apparently plays an important role in the ability of a global increase in thickness to have a significant beneficial effect

Prediction of vertebral fractures under axial compression and anterior flexion

Vertebral fractures affect at least 12-20% of men and women over the age of 50, and the risk of fracture increases exponentially with age. Despite their high prevalence, the failure mechanisms leading to these fractures are not well understood. For example, clinical observations of fractured vertebra often note that one or both vertebral endplates have collapsed, but the precise involvement of the endplates in the initiation and progression of failure has not yet been defined. The mechanisms of failure may also relate to spatial variations in the density and microstructure of the porous trabecular bone within the vertebra as well as to the health of the adjacent intervertebral discs (IVDs) which transfer loads directly to the vertebral endplates. Delineating the contributions of these factors would shed light on the etiology of vertebral fractures and would aid in development of clinically feasible, patient-specific finite element (FE) models of the vertebra. These models are built from a patient's quantitative computed tomography (QCT) scan and have shown tremendous promise for accurate, patient-specific estimates of bone strength and fracture risk. Further validation studies are required to assess the impact of the choices of material properties and boundary conditions, as a prerequisite for broad implementation of these FE models in clinical care. The overall goal of this work was to define the failure processes involved in vertebral fractures and to evaluate the accuracy of patient-specific FE models in simulating these processes. Mechanical testing of human spine segments, in conjunction with micro-computed tomography, enabled the assessment of deformation at the vertebral endplate and deformation throughout the entire bone, as the vertebra was loaded to failure under both axial compression and anterior flexion. These data were compared against predictions of vertebral deformation obtained from QCT-based FE models. The impact of the choice of boundary conditions was specifically examined by comparing the accuracy of the FE predictions between models that simulated applied loads based on measured distributions of pressure within IVDs and models that used highly idealized boundary conditions. The results of these studies demonstrated that sudden and non-recoverable endplate deflection is a defining feature of biomechanical failure of the vertebra, for both compression and flexion loading. The locations of endplate collapse as vertebral failure progressed were associated with the porosity of the endplate and the microstructure of the underlying trabecular bone. FE analyses incorporating the experimentally observed endplate deflections as boundary conditions provided more accurate predictions of displacements throughout the rest of the vertebra when compared to FE models with highly idealized boundary conditions. Under anterior flexion, the use of boundary conditions informed by measurements of IVD pressure mitigated, but did not eliminate, the inaccuracy of the idealized boundary conditions. No further improvement in accuracy was found when using boundary conditions based on pressure measurements corresponding only to IVDs whose level of degeneration matched that observed in the IVDs adjacent to the vertebra being modeled. Overall, the accuracy of the FE predictions of vertebral deformation was only moderate, particularly near the locations of endplate collapse. The outcomes of this work indicate that the vertebral endplate is principally involved in vertebral fractures and that current methods for QCT-based FE models do not adequately capture this failure mechanism. These outcomes provide a biomechanical rationale for clinical diagnoses of vertebral fracture based on endplate collapse. These outcomes also emphasize that future studies of patient-specific FE models should incorporate physiologically relevant loading conditions and also material properties that more accurately represent the vertebral endplate in order to obtain higher fidelity predictions of vertebral failure

The Effects of Vertebral Variation on the Mechanical Outcomes of Vertebroplasty

Osteoporotic vertebral compression fractures are a commonly encountered clinical problem that causes a reduced quality of life for a large proportion of those affected. One of the treatments for this type of fracture is vertebroplasty, where the injection of bone cement into the vertebral body aims to stabilise the vertebra and relieve pain. Despite being a frequently used treatment a number of studies and randomised clinical trials have questioned the efficacy of the procedure. These clinical trials and studies have suggested that the procedure is no more effective than a placebo in terms of pain relief. Finite Element (FE) models allow an investigation into the structural and geometric variation that affect the response to augmentation. However, current specimen specific FE models are limited due to the poor reproduction of cement augmentation behaviour. The aims of this thesis were to develop new methods of modelling the vertebral body in an augmented state, using these models as an input to a statistical shape and appearance model (SSAM). Methods were developed for experimental testing, cement augmentation and modelling through a specimen specific modelling approach to create and solve FE models. These methods were initially used with bovine tail vertebrae and then refined for the use of human lumbar vertebrae. These latter models formed the input set for the creation of a SSAM, where vertebral and augmentation variables were examined. Models of augmentation in human lumbar vertebrae achieved a good agreement with their experimental counterparts through the development of novel modelling techniques. A new SSAM method has been developed for human lumbar vertebrae and applied to evaluate the mechanical performance of vertebroplasty. The tools developed can now be applied to examine wider patient cohorts and other clinical therapies

RELATIONSHIPS OF LONG-TERM BISPHOSPHONATE TREATMENT WITH MEASURES OF BONE MICROARCHITECTURE AND MECHANICAL COMPETENCE

Oral bisphosphonate drug therapy is a common and effective treatment for osteoporosis. Little is known about the long-term effects of bisphosphonates on bone quality. This study examined the structural and mechanical properties of trabecular bone following 0-16 years of bisphosphonate treatment. Fifty-three iliac crest bone samples of Caucasian women diagnosed with low turnover osteoporosis were identified from the Kentucky Bone Registry. Forty-five were treated with oral bisphosphonates for 1 to 16 years while eight were treatment naive. A section of trabecular bone was chosen from a micro-computed tomography (Scanco µCT 40) scan of each sample for a uniaxial linearly elastic compression simulation using finite element analysis (ANSYS 14.0). Morphometric parameters (BV/TV, SMI, Tb.Sp., etc.) were computed using µCT. Apparent modulus, effective modulus and estimated failure stress were calculated. Biomechanical and morphometric parameters improved with treatment duration, peaked around 7 years, and then declined independently of age. The findings suggest a limit to the benefits associated with bisphosphonate treatment and that extended continuous bisphosphonate treatment does not continue to improve bone quality. Bone quality, and subsequently bone strength, may eventually regress to a state poorer than at the onset of treatment. Treatment duration limited to less than 7 years is recommended

Hand X-ray absorptiometry for measurement of bone mineral density on a slot-scanning X-ray imaging system

Includes bibliographical references.Bone mineral density (BMD) is an indicator of bone strength. While femoral and spinal BMDs are traditionally used in the management of osteoporosis, BMD at peripheral sites such as the hand has been shown to be useful in evaluating fracture risk for axial sites. These peripheral locations have been suggested as alternatives to the traditional sites for BMD measurement. Dual-energy X-ray absorptiometry (DXA) is the gold standard for measuring BMD due to low radiation dose, high accuracy and proven ability to evaluate fracture risk. Computed digital absorptiometry (CDA) has also been shown to be very effective at measuring the bone mass in hand bones using an aluminium step wedge as a calibration reference. In this project, the aim was to develop algorithm s for accurate measurement of BMD in hand bones on a slot - scanning digital radiography system. The project assess e d the feasibility of measuring bone mineral mass in hand bones using CDA on the current system. Images for CDA - based measurement were acquired using the default settings on the system for a medium sized patient. A method for automatic processing of the hand images to detect the aluminium step wedge, included in the scan for calibration, was developed and the calibration accuracy of the step wedge was evaluated. The CDA method was used for computation of bone mass with units of equivalent aluminium thickness (mmA1). The precision of the method was determined by taking three measurements in each of 1 6 volunteering subjects and computing the root - mean - square coefficient of variation (CV) of the measurements. The utility of the method was assessed by taking measurements of excised bones and assessing the correlation between the measured bone mass and ash weight obtained by incinerating the bones. The project also assessed the feasibility of implementing a DXA technique using two detectors in a slot-scanning digital radiography system to acquire dual-energy X-ray images for measuring areal and volumetric BMD of the middle phalanx of the middle finger. The dual-energy images were captured in two consecutive scans. The first scan captured the low- energy image using the detector in its normal set-up. The second scan captured the high- energy image with the detector modified to include an additional scintillator to simulate the presence of a second detector that would capture the low-energy image in a two-detector system. Scan parameters for acquisition of the dual-energy images were chosen to optimise spectral separation, entrance dose and image quality. Simulations were carried out to evaluate the spectral separation of the low- and high-energy spectra

Validation of Subject Specific Computed Tomography-based Finite Element Models of the Human Proximal Tibia using Full-field Experimental Displacement Measurements from Digital Volume Correlation

Quantitative computed tomography-based finite element (QCT-FE) modeling is a computational tool for predicting bone’s response to applied load, and is used by musculoskeletal researchers to better understand bone mechanics and their role in joint health. Decisions made at the modeling stage, such as the method for assigning material properties, can dictate model accuracy. Predictions of surface strains/stiffness from QCT-FE models of the proximal tibia have been validated against experiment, yet it is unclear whether these models accurately predict internal bone mechanics (displacement). Digital volume correlation (DVC) can measure internal bone displacements and has been used to validate FE models of bone; though, its use has been limited to small specimens. The objectives of this study were to 1) establish a methodology for high-resolution peripheral QCT (HR-pQCT) scan acquisition and image processing resulting in low DVC displacement measurement error in long human bones, and 2) apply different density-modulus relationships and material models from the literature to QCT-FE models of the proximal tibia and identify those approaches which best predicted experimentally measured internal bone displacements and related external reaction forces, with highest explained variance and least error. Using a modified protocol for HR-pQCT, DVC displacement errors for large scan volumes were less than 19μm (0.5 voxels). Specific trabecular and cortical models from the literature were identified which resulted in the most accurate QCT-FE predictions of internal displacements (RMSE%=3.9%, R2>0.98) and reaction forces (RMSE%=12.2%, R2=0.78). This study is the first study to quantify experimental displacements inside a long human bone using DVC. It is also the first study to assess the accuracy of QCT-FE predicted internal displacements in the tibia. Our results indicate that QCT-FE models of the tibia offer reasonably accurate predictions of internal bone displacements and reaction forces for use in studying bone mechanics and joint health