Graphical Model-Based Vertebra Identification from X-Ray Image(s)

Automated identification of vertebrae from X-ray image(s) is an important step for various medical image computing tasks such as 2D/3D rigid and non-rigid registration. In this chapter we present a graphical model-based solution for automated vertebra identification from X-ray image(s). Our solution does not ask for a training process using training data and has the capability to automatically determine the number of vertebrae visible in the image(s). This is achieved by combining a graphical model-based maximum a posterior probability (MAP) estimate with a mean-shift based clustering. Experiments conducted on simulated X-ray images as well as on a low-dose low quality X-ray spinal image of a scoliotic patient verified its performance.

Articulated Statistical Shape Model-Based 2D-3D Reconstruction of a Hip Joint

In this paper, reconstruction of three-dimensional (3D) patient-specific models of a hip joint from two-dimensional (2D) calibrated X-ray images is addressed. Existing 2D-3D reconstruction techniques usually reconstruct a patient-specific model of a single anatomical structure without considering the relationship to its neighboring structures. Thus, when those techniques would be applied to reconstruction of patient-specific models of a hip joint, the reconstructed models may penetrate each other due to narrowness of the hip joint space and hence do not represent a true hip joint of the patient. To address this problem we propose a novel 2D-3D reconstruction framework using an articulated statistical shape model (aSSM). Different from previous work on constructing an aSSM, where the joint posture is modeled as articulation in a training set via statistical analysis, here it is modeled as a parametrized rotation of the femur around the joint center. The exact rotation of the hip joint as well as the patient-specific models of the joint structures, i.e., the proximal femur and the pelvis, are then estimated by optimally fitting the aSSM to a limited number of calibrated X-ray images. Taking models segmented from CT data as the ground truth, we conducted validation experiments on both plastic and cadaveric bones. Qualitatively, the experimental results demonstrated that the proposed 2D-3D reconstruction framework preserved the hip joint structure and no model penetration was found. Quantitatively, average reconstruction errors of 1.9 mm and 1.1 mm were found for the pelvis and the proximal femur, respectively.

Experimental validation of a nonlinear μ FE model based on cohesive-frictional plasticity for trabecular bone

Trabecular bone is a porous mineralized tissue playing a major load bearing role in the human body. Prediction of age-related and disease-related fractures and the behavior of bone implant systems needs a thorough understanding of its structure-mechanical property relationships, which can be obtained using microcomputed tomography-based finite element modeling. In this study, a nonlinear model for trabecular bone as a cohesive-frictional material was implemented in a large-scale computational framework and validated by comparison of μFE simulations with experimental tests in uniaxial tension and compression. A good correspondence of stiffness and yield points between simulations and experiments was found for a wide range of bone volume fraction and degree of anisotropy in both tension and compression using a non-calibrated, average set of material parameters. These results demonstrate the ability of the model to capture the effects leading to failure of bone for three anatomical sites and several donors, which may be used to determine the apparent behavior of trabecular bone and its evolution with age, disease, and treatment in the future.

Design-based stereology to quantify structural properties of artificial and natural snow using thin sections

The quantification of the structural properties of snow is traditionally based on model-based stereology. Model-based stereology requires assumptions about the shape of the investigated structure. Here, we show how the density, specific surface area, and grain boundary area can be measured using a design-based method, where no assumptions about structural properties are necessary. The stereological results were also compared to X-ray tomography to control the accuracy of the method. The specific surface area calculated with the stereological method was 19.8 ± 12.3% smaller than with X-ray tomography. For the density, the stereological method gave results that were 11.7 ± 12.1% larger than X-ray tomography. The statistical analysis of the estimates confirmed that the stereological method and the sampling used are accurate. This stereological method was successfully tested on artificially produced ice beads but also on several snow types. Combining stereology and polarisation microscopy provides a good estimate of grain boundary areas in ice beads and in natural snow, with some limitatio

Single fluoroscopic image based 2D/3D reconstruction of a scaled, patient-specific vertebral model

Purpose Accurate three-dimensional (3D) models of lumbar vertebrae can enable image-based 3D kinematic analysis. The common approach to derive 3D models is by direct segmentation of CT or MRI datasets. However, these have the disadvantages that they are expensive, timeconsuming and/or induce high-radiation doses to the patient. In this study, we present a technique to automatically reconstruct a scaled 3D lumbar vertebral model from a single two-dimensional (2D) lateral fluoroscopic image. Methods Our technique is based on a hybrid 2D/3D deformable registration strategy combining a landmark-to-ray registration with a statistical shape model-based 2D/3D reconstruction scheme. Fig. 1 shows different stages of the reconstruction process. Four cadaveric lumbar spine segments (total twelve lumbar vertebrae) were used to validate the technique. To evaluate the reconstruction accuracy, the surface models reconstructed from the lateral fluoroscopic images were compared to the associated ground truth data derived from a 3D CT-scan reconstruction technique. For each case, a surface-based matching was first used to recover the scale and the rigid transformation between the reconstructed surface model Results Our technique could successfully reconstruct 3D surface models of all twelve vertebrae. After recovering the scale and the rigid transformation between the reconstructed surface models and the ground truth models, the average error of the 2D/3D surface model reconstruction over the twelve lumbar vertebrae was found to be 1.0 mm. The errors of reconstructing surface models of all twelve vertebrae are shown in Fig. 2. It was found that the mean errors of the reconstructed surface models in comparison to their associated ground truths after iterative scaled rigid registrations ranged from 0.7 mm to 1.3 mm and the rootmean squared (RMS) errors ranged from 1.0 mm to 1.7 mm. The average mean reconstruction error was found to be 1.0 mm. Conclusion An accurate, scaled 3D reconstruction of the lumbar vertebra can be obtained from a single lateral fluoroscopic image using a statistical shape model based 2D/3D reconstruction technique. Future work will focus on applying the reconstructed model for 3D kinematic analysis of lumbar vertebrae, an extension of our previously-reported imagebased kinematic analysis. The developed method also has potential applications in surgical planning and navigation.

A system for 3-D reconstruction of a patient-specific surface model from calibrated X-ray images

This paper presents a system for 3-D reconstruction of a patient-specific surface model from calibrated X-ray images. Our system requires two X-ray images of a patient with one acquired from the anterior-posterior direction and the other from the axial direction. A custom-designed cage is utilized in our system to calibrate both images. Starting from bone contours that are interactively identified from the X-ray images, our system constructs a patient-specific surface model of the proximal femur based on a statistical model based 2D/3D reconstruction algorithm. In this paper, we present the design and validation of the system with 25 bones. An average reconstruction error of 0.95 mm was observed.

Automated detection of fiducial screws from CT/DVT volume data for image-guided ENT surgery

This paper presents an automated solution for precise detection of fiducial screws from three-dimensional (3D) Computerized Tomography (CT)/Digital Volume Tomography (DVT) data for image-guided ENT surgery. Unlike previously published solutions, we regard the detection of the fiducial screws from the CT/DVT volume data as a pose estimation problem. We thus developed a model-based solution. Starting from a user-supplied initialization, our solution detects the fiducial screws by iteratively matching a computer aided design (CAD) model of the fiducial screw to features extracted from the CT/DVT data. We validated our solution on one conventional CT dataset and on five DVT volume datasets, resulting in a total detection of 24 fiducial screws. Our experimental results indicate that the proposed solution achieves much higher reproducibility and precision than the manual detection. Further comparison shows that the proposed solution produces better results on the DVT dataset than on the conventional CT dataset.

A prediction model for assessing residential radon concentration in Switzerland

Indoor radon is regularly measured in Switzerland. However, a nationwide model to predict residential radon levels has not been developed. The aim of this study was to develop a prediction model to assess indoor radon concentrations in Switzerland. The model was based on 44,631 measurements from the nationwide Swiss radon database collected between 1994 and 2004. Of these, 80% randomly selected measurements were used for model development and the remaining 20% for an independent model validation. A multivariable log-linear regression model was fitted and relevant predictors selected according to evidence from the literature, the adjusted R², the Akaike's information criterion (AIC), and the Bayesian information criterion (BIC). The prediction model was evaluated by calculating Spearman rank correlation between measured and predicted values. Additionally, the predicted values were categorised into three categories (50th, 50th-90th and 90th percentile) and compared with measured categories using a weighted Kappa statistic. The most relevant predictors for indoor radon levels were tectonic units and year of construction of the building, followed by soil texture, degree of urbanisation, floor of the building where the measurement was taken and housing type (P-values <0.001 for all). Mean predicted radon values (geometric mean) were 66 Bq/m³ (interquartile range 40-111 Bq/m³) in the lowest exposure category, 126 Bq/m³ (69-215 Bq/m³) in the medium category, and 219 Bq/m³ (108-427 Bq/m³) in the highest category. Spearman correlation between predictions and measurements was 0.45 (95%-CI: 0.44; 0.46) for the development dataset and 0.44 (95%-CI: 0.42; 0.46) for the validation dataset. Kappa coefficients were 0.31 for the development and 0.30 for the validation dataset, respectively. The model explained 20% overall variability (adjusted R²). In conclusion, this residential radon prediction model, based on a large number of measurements, was demonstrated to be robust through validation with an independent dataset. The model is appropriate for predicting radon level exposure of the Swiss population in epidemiological research. Nevertheless, some exposure misclassification and regression to the mean is unavoidable and should be taken into account in future applications of the model.

Enhancing sealing of fetal membrane defects using tissue engineered native amniotic scaffolds in the rabbit model

OBJECTIVE: The purpose of this study was to compare the efficacy of native engineered amniotic scaffolds (AS) and polyesterurethane scaffolds (DegraPol) and document wound healing response when sealing iatrogenic fetal membrane defects in the rabbit model. STUDY DESIGN: Native AS were engineered from freshly harvested membranes of 23 days' gestational age (GA; term = 31-2 d). Acellularity of AS was assessed by histology, light and scanning electron microscopy. Fetal membrane defects were created by 14 gauge-needle puncture at GA 23 days and primarily closed with AS (n = 10) or DegraPol (n = 10) or left unclosed (positive controls; n = 10). Sixty-one sacs served as negative controls. At GA 30 days a second look hysterotomy was performed to assess presence of amniotic fluid (AF) and harvest plugging sites for microscopic evaluation. RESULTS: Engineered AS had a cell-free collagenous fiber network. AF was significantly higher only in the DegraPol group (78%; P < .05) compared to the AF in positive controls (17%). Integration of plugs in the fetal membrane defect was better with AS than DegraPol, with higher reepithelialization rates (AS: 52.5% +/- 6.5%; DegraPol: 11.6% +/- 2.6%; P < .001) and proliferation indices (AS: 0.47 +/- 0.03; DegraPol: 0.28 +/- 0.04; P = .001). In both treatment groups, cell proliferation in the myometrium was increased (P < .05). CONCLUSION: Native AS seal iatrogenic fetal membrane defects better than DegraPol. Within a week, there is abundant reepithelilization and minimal local inflammation. This yields the proof of principle that engineered native, amniotic membrane scaffolds enhance fetal membrane wound healing response.

A coronary heart disease risk model for predicting the effect of potent antiretroviral therapy in HIV-1 infected men

BACKGROUND: Many HIV-infected patients on highly active antiretroviral therapy (HAART) experience metabolic complications including dyslipidaemia and insulin resistance, which may increase their coronary heart disease (CHD) risk. We developed a prognostic model for CHD tailored to the changes in risk factors observed in patients starting HAART. METHODS: Data from five cohort studies (British Regional Heart Study, Caerphilly and Speedwell Studies, Framingham Offspring Study, Whitehall II) on 13,100 men aged 40-70 and 114,443 years of follow up were used. CHD was defined as myocardial infarction or death from CHD. Model fit was assessed using the Akaike Information Criterion; generalizability across cohorts was examined using internal-external cross-validation. RESULTS: A parametric model based on the Gompertz distribution generalized best. Variables included in the model were systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, triglyceride, glucose, diabetes mellitus, body mass index and smoking status. Compared with patients not on HAART, the estimated CHD hazard ratio (HR) for patients on HAART was 1.46 (95% CI 1.15-1.86) for moderate and 2.48 (95% CI 1.76-3.51) for severe metabolic complications. CONCLUSIONS: The change in the risk of CHD in HIV-infected men starting HAART can be estimated based on typical changes in risk factors, assuming that HRs estimated using data from non-infected men are applicable to HIV-infected men. Based on this model the risk of CHD is likely to increase, but increases may often be modest, and could be offset by lifestyle changes.

Adenovirus-mediated transforming growth factor-beta ameliorates ischemic necrosis of epigastric skin flaps in a rat model

BACKGROUND: Gene therapy has been recently introduced as a novel approach to treat ischemic tissues by using the angiogenic potential of certain growth factors. We investigated the effect of adenovirus-mediated gene therapy with transforming growth factor-beta (TGF-beta) delivered into the subdermal space to treat ischemically challenged epigastric skin flaps in a rat model. MATERIAL AND METHODS: A pilot study was conducted in a group of 5 animals pretreated with Ad-GFP and expression of green fluorescent protein in the skin flap sections was demonstrated under fluorescence microscopy at 2, 4, and 7 days after the treatment, indicating a successful transfection of the skin flaps following subdermal gene therapy. Next, 30 male Sprague Dawley rats were divided into 3 groups of 10 rats each. An epigastric skin flap model, based solely on the right inferior epigastric vessels, was used as the model in this study. Rats received subdermal injections of adenovirus encoding TGF-beta (Ad-TGF-beta) or green fluorescent protein (Ad-GFP) as treatment control. The third group (n = 10) received saline and served as a control group. A flap measuring 8 x 8 cm was outlined on the abdominal skin extending from the xiphoid process proximally and the pubic region distally, to the anterior axillary lines bilaterally. Just prior to flap elevation, the injections were given subdermally in the left upper corner of the flap. The flap was then sutured back to its bed. Flap viability was evaluated seven days after the initial operation. Digital images of the epigastric flaps were taken and areas of necrotic zones relative to total flap surface area were measured and expressed as percentages by using a software program. RESULTS: There was a significant increase in mean percent surviving area between the Ad-TGF-beta group and the two other control groups (P < 0.05). (Ad-TGF-beta: 90.3 +/- 4.0% versus Ad-GFP: 82.2 +/- 8.7% and saline group: 82.6 +/- 4.3%.) CONCLUSIONS: In this study, the authors were able to demonstrate that adenovirus-mediated gene therapy using TGF-beta ameliorated ischemic necrosis in an epigastric skin flap model, as confirmed by significant reduction in the necrotic zones of the flap. The results of this study raise the possibility of using adenovirus-mediated TGF-beta gene therapy to promote perfusion in random portion of skin flaps, especially in high-risk patients.

Vertebroplasty: experimental characterization of polymethylmethacrylate bone cement spreading as a function of viscosity, bone porosity, and flow rate

STUDY DESIGN: This is an experimental study on an artificial vertebra model and human cadaveric spine. OBJECTIVE: Characterization of polymethylmethacrylate (PMMA) bone cement distribution in the vertebral body as a function of cement viscosity, bone porosity, and injection speed. Identification of relevant parameters for improved cement flow predictability and leak prevention in vertebroplasty. SUMMARY OF BACKGROUND DATA: Vertebroplasty is an efficient procedure to treat vertebral fractures and stabilize osteoporotic bone in the spine. Severe complications result from bone cement leakage into the spinal canal or the vascular system. Cement viscosity has been identified as an important parameter for leak prevention but the influence of bone structure and injection speed remain obscure. METHODS: An artificial vertebra model based on open porous aluminum foam was used to simulate bone of known porosity. Fifty-six vertebroplasties with 4 different starting viscosity levels and 2 different injection speeds were performed on artificial vertebrae of 3 different porosities. A validation on a human cadaveric spine was executed. The experiments were radiographically monitored and the shape of the cement clouds quantitatively described with the 2 indicators circularity and mean cement spreading distance. RESULTS: An increase in circularity and a decrease in mean cement spreading distance was observed with increasing viscosity, with the most striking change occurring between 50 and 100 Pas. Larger pores resulted in significantly reduced circularity and increased mean cement spreading distance whereas the effect of injection speed on the 2 indicators was not significant. CONCLUSION: Viscosity is the key factor for reducing the risk of PMMA cement leakage and it should be adapted to the degree of osteoporosis encountered in each patient. It may be advisable to opt for a higher starting viscosity but to inject the material at a faster rate.