Correlation of Calcification on Excised Aortic Valves by Micro-Computed Tomography with Severity of Aortic Stenosis

Background and aim of the study: The quantification of incidentally found aortic valve calcification on computed tomography (CT) is not performed routinely, as data relating to the accuracy of aortic valve calcium for estimating the severity of aortic stenosis (AS) is neither consistent nor validated. As aortic valve calcium quantification by CT is confounded by wall and coronary ostial calcification, as well as motion artifact, the ex-vivo micro-computed tomography (micro-CT) of stenotic aortic valves allows a precise measurement of the amounts of calcium present. The study aim, using excised aortic valves from patients with confirmed AS, was to determine if the amount of calcium on micro-CT correlated with the severity of AS. Methods: Each of 35 aortic valves that had been excised from patients during surgical valve replacement were examined using micro-CT imaging. The amount of calcium present was determined by absolute and proportional values of calcium volume in the specimen. Subsequently, the correlation between calcium volume and preoperative mean aortic valve gradient (MAVG), peak transaortic velocity (V-max), and aortic valve area (AVA) on echocardiography, was evaluated. Results: The mean calcium volume across all valves was 603.2 +/- 398.5 mm(3), and the mean ratio of calcium volume to total valve volume was 0.36 +/- 0.16. The mean aortic valve gradient correlated positively with both calcium volume and ratio (r = 0.72, p <0.001). V-max also correlated positively with the calcium volume and ratio (r = 0.69 and 0.76 respectively; p <0.001). A logarithmic curvilinear model proved to be the best fit to the correlation. A calcium volume of 480 mm(3) showed sensitivity and specificity of 0.76 and 0.83, respectively, for a diagnosis of severe AS, while a calcium ratio of 0.37 yielded sensitivity and specificity of 0.82 and 0.94, respectively. Conclusion: A radiological estimation of calcium amount by volume, and its proportion to the total valve volume, were shown to serve as good predictive parameters for severe AS. An estimation of the calcium volume may serve as a complementary measure for determining the severity of AS when aortic valve calcification is identified on CT imaging. The Journal of Heart Valve Disease 2012;21:320-327

Biocompatibility property of 100% strontium-substituted SiO2-Al2O3-P2O5-CaO-CaF2 glass ceramics over 26 weeks implantation in rabbit model: Histology and micro-Computed Tomography analysis

One of the desired properties for any new biomaterial composition is its long-term stability in a suitable animal model and such property cannot be appropriately assessed by performing short-term implantation studies. While hydroxyapatite (HA) or bioglass coated metallic biomaterials are being investigated for in vivo biocompatibility properties, such study is not extensively being pursued for bulk glass ceramics. In view of their inherent brittle nature, the implant stability as well as impact of long-term release of metallic ions on bone regeneration have been a major concern. In this perspective, the present article reports the results of the in vivo implantation experiments carried out using 100% strontium (Sr)-substituted glass ceramics with the nominal composition of 4.5 SiO2-3Al(2)O(3)-1.5P(2)O(5)-3SrO-2SrF(2) for 26 weeks in cylindrical bone defects in rabbit model. The combination of histological and micro-computed tomography analysis provided a qualitative and quantitative understanding of the bone regeneration around the glass ceramic implants in comparison to the highly bioactive HA bioglass implants (control). The sequential polychrome labeling of bone during in vivo osseointegration using three fluorochromes followed by fluorescence microscopy observation confirmed homogeneous bone formation around the test implants. The results of the present study unequivocally confirm the long-term implant stability as well as osteoconductive property of 100% Sr-substituted glass ceramics, which is comparable to that of a known bioactive implant, that is, HA-based bioglass. (c) 2014 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 103B: 1168-1179, 2015.

A Method for Delineation of Bone Surfaces in Photoacoustic Computed Tomography of the Finger

Photoacoustic (PA) imaging of interphalangeal peripheral joints is of interest in the context of using the synovial membrane as a surrogate marker of rheumatoid arthritis. Previous work has shown that ultrasound (US) produced by absorption of light at the epidermis reflects on the bone surfaces within the finger. When the reflected signals are backprojected in the region of interest, artifacts are produced, confounding interpretation of the images. In this work, we present an approach where the PA signals known to originate from the epidermis are treated as virtual US transmitters, and a separate reconstruction is performed as in US reflection imaging. This allows us to identify the bone surfaces. Furthermore, the identification of the joint space is important as this provides a landmark to localize a region-of-interest in seeking the inflamed synovial membrane. The ability to delineate bone surfaces allows us to identify not only the artifacts but also the interphalangeal joint space without recourse to new US hardware or a new measurement. We test the approach on phantoms and on a healthy human finger.

Macropores generated during shrinkage in two paddy soils using X-ray micro-computed tomography

Soil shrinkage curve represents a decrease of total porosity or an increase of bulk density with water loss. However, our knowledge of the dynamics of pores and their geometry during soil shrinkage is scarce, partially due to lack of reliable methods for determining soil pores in relation to change in soil water. This study aimed to investigate the dynamics of macropores (>30 mu m) of paddy soils during shrinkage. Two, paddy soils, which were sampled from one paddy field cultivated for 20 years (YPF) and the other one for over 100 years (OPF), represented difference in crack geometry in the field. Macropore parameters (volume, connectivity, and orientation of pores) and soil shrinkage parameters were determined on the same undisturbed soil cores by X-ray microtomography and shrinkage curve, respectively. Macroporosity was on average four times larger in the YPF than in the OPF whereas the shrinkage capacity was lower in the YPF as compared to the OPF (0.09 vs. 0.15 COLE). Soil shrinkage increased the volume of pores by 3.7% in the YPF and by 1.6% in the OPF as well as their connectivity. The formation of macropores occurred mostly in the proportional shrinkage phase. As a result, the slope of the proportional shrinkage phase was smaller in the YPF (0.65) than in the OPF (0.89). New macropores were cracks and extended pre-existing pores in the range of 225-1215 pm size without any preferential orientation. This work provides image evidences that in paddy soils with high shrinkage capacity more macropores are generated in the soil presenting a smaller proportional shrinkage slope. (C) 2015 Elsevier B.V. All rights reserved.

Cryogenically cured hydroxyapatite-gelatin nanobiocomposite for bovine serum albumin protein adsorption and release

This research paper presents the first results on the protein adsorption and release kinetics and in vitro biodegradability of cryogenically cured hydroxyapatite-gelatin based micro/macroporous scaffolds (CHAMPS). While the adsorption and release of bovine serum albumin (BSA) protein exhibits steady state behavior over an incubation period of up to 10 days, Fourier transform infrared (FT-IR) analysis importantly confirms the absence of any change in the secondary structure of BSA proteins due to interaction with the CHAMPS scaffold. The compression properties of the CHAMPS scaffold with interconnected porosity (pore size similar to 50-200 mm) is characterized by a non-linear stress-strain response with a strength close to 5 MPa and a maximum strain of up to 24%. The slow but systematic increase in weight loss over a period of 7 days as well as apatite layer formation indicates its good bioactivity. The extensive micro-computed tomography (micro-CT) analysis establishes cancellous bone-like highly interconnected and complex porous architecture of the CHAMPS scaffold. Importantly, the excellent adsorption (up to 50%) and release (up to 60% of adsorbed protein) of BSA has been uniquely attributed to the inherent porous microstructure of the CHAMPS scaffold. Overall, the present study provides an assessment of the interaction of protein with the gelatin-hydroxyapatite macroporous scaffold in vitro, as well as reporting for the first time the efficacy of such scaffolds to release 60% of BSA loaded onto the scaffold in vitro, which is significantly higher than earlier literature reports.

A MatLAB Based Virtual Phantom for 2D Electrical Impedance Tomography (MatVP2DEIT): Studying the Medical Electrical Impedance Tomography Reconstruction in Computer

Electrical Impedance Tomography (EIT) is a computerized medical imaging technique which reconstructs the electrical impedance images of a domain under test from the boundary voltage-current data measured by an EIT electronic instrumentation using an image reconstruction algorithm. Being a computed tomography technique, EIT injects a constant current to the patient's body through the surface electrodes surrounding the domain to be imaged (Omega) and tries to calculate the spatial distribution of electrical conductivity or resistivity of the closed conducting domain using the potentials developed at the domain boundary (partial derivative Omega). Practical phantoms are essentially required to study, test and calibrate a medical EIT system for certifying the system before applying it on patients for diagnostic imaging. Therefore, the EIT phantoms are essentially required to generate boundary data for studying and assessing the instrumentation and inverse solvers a in EIT. For proper assessment of an inverse solver of a 2D EIT system, a perfect 2D practical phantom is required. As the practical phantoms are the assemblies of the objects with 3D geometries, the developing of a practical 2D-phantom is a great challenge and therefore, the boundary data generated from the practical phantoms with 3D geometry are found inappropriate for assessing a 2D inverse solver. Furthermore, the boundary data errors contributed by the instrumentation are also difficult to separate from the errors developed by the 3D phantoms. Hence, the errorless boundary data are found essential to assess the inverse solver in 2D EIT. In this direction, a MatLAB-based Virtual Phantom for 2D EIT (MatVP2DEIT) is developed to generate accurate boundary data for assessing the 2D-EIT inverse solvers and the image reconstruction accuracy. MatVP2DEIT is a MatLAB-based computer program which simulates a phantom in computer and generates the boundary potential data as the outputs by using the combinations of different phantom parameters as the inputs to the program. Phantom diameter, inhomogeneity geometry (shape, size and position), number of inhomogeneities, applied current magnitude, background resistivity, inhomogeneity resistivity all are set as the phantom variables which are provided as the input parameters to the MatVP2DEIT for simulating different phantom configurations. A constant current injection is simulated at the phantom boundary with different current injection protocols and boundary potential data are calculated. Boundary data sets are generated with different phantom configurations obtained with the different combinations of the phantom variables and the resistivity images are reconstructed using EIDORS. Boundary data of the virtual phantoms, containing inhomogeneities with complex geometries, are also generated for different current injection patterns using MatVP2DEIT and the resistivity imaging is studied. The effect of regularization method on the image reconstruction is also studied with the data generated by MatVP2DEIT. Resistivity images are evaluated by studying the resistivity parameters and contrast parameters estimated from the elemental resistivity profiles of the reconstructed phantom domain. Results show that the MatVP2DEIT generates accurate boundary data for different types of single or multiple objects which are efficient and accurate enough to reconstruct the resistivity images in EIDORS. The spatial resolution studies show that, the resistivity imaging conducted with the boundary data generated by MatVP2DEIT with 2048 elements, can reconstruct two circular inhomogeneities placed with a minimum distance (boundary to boundary) of 2 mm. It is also observed that, in MatVP2DEIT with 2048 elements, the boundary data generated for a phantom with a circular inhomogeneity of a diameter less than 7% of that of the phantom domain can produce resistivity images in EIDORS with a 1968 element mesh. Results also show that the MatVP2DEIT accurately generates the boundary data for neighbouring, opposite reference and trigonometric current patterns which are very suitable for resistivity reconstruction studies. MatVP2DEIT generated data are also found suitable for studying the effect of the different regularization methods on reconstruction process. Comparing the reconstructed image with an original geometry made in MatVP2DEIT, it would be easier to study the resistivity imaging procedures as well as the inverse solver performance. Using the proposed MatVP2DEIT software with modified domains, the cross sectional anatomy of a number of body parts can be simulated in PC and the impedance image reconstruction of human anatomy can be studied.

DECT evaluation of noncalc fied coronary artery plaque

Purpose: Composition of the coronary artery plaque is known to have critical role in heart attack. While calcified plaque can easily be diagnosed by conventional CT, it fails to distinguish between fibrous and lipid rich plaques. In the present paper, the authors discuss the experimental techniques and obtain a numerical algorithm by which the electron density (rho(e)) and the effective atomic number (Z(eff)) can be obtained from the dual energy computed tomography (DECT) data. The idea is to use this inversion method to characterize and distinguish between the lipid and fibrous coronary artery plaques. Methods: For the purpose of calibration of the CT machine, the authors prepare aqueous samples whose calculated values of (rho(e), Z(eff)) lie in the range of (2.65 x 10(23) <= rho(e) <= 3.64 x 10(23)/cm(3)) and (6.80 <= Z(eff) <= 8.90). The authors fill the phantom with these known samples and experimentally determine HU(V-1) and HU(V-2), with V-1,V-2 = 100 and 140 kVp, for the same pixels and thus determine the coefficients of inversion that allow us to determine (rho(e), Z(eff)) from the DECT data. The HU(100) and HU(140) for the coronary artery plaque are obtained by filling the channel of the coronary artery with a viscous solution of methyl cellulose in water, containing 2% contrast. These (rho(e), Z(eff)) values of the coronary artery plaque are used for their characterization on the basis of theoretical models of atomic compositions of the plaque materials. These results are compared with histopathological report. Results: The authors find that the calibration gives Pc with an accuracy of 3.5% while Z(eff) is found within 1% of the actual value, the confidence being 95%. The HU(100) and HU(140) are found to be considerably different for the same plaque at the same position and there is a linear trend between these two HU values. It is noted that pure lipid type plaques are practically nonexistent, and microcalcification, as observed in histopathology, has to be taken into account to explain the nature of the observed (rho(e), Z(eff)) data. This also enables us to judge the composition of the plaque in terms of basic model which considers the plaque to be composed of fibres, lipids, and microcalcification. Conclusions: This simple and reliable method has the potential as an effective modality to investigate the composition of noncalcified coronary artery plaques and thus help in their characterization. In this inversion method, (rho(e), Z(eff)) of the scanned sample can be found by eliminating the effects of the CT machine and also by ensuring that the determination of the two unknowns (rho(e), Z(eff)) does not interfere with each other and the nature of the plaque can be identified in terms of a three component model. (C) 2015 American Association of Physicists in Medicine.