Biomedical subjects

Marvin M Doyley

Publications and source records attributed to Marvin M Doyley.

10 recordsLinked to original sources

PubMed2006

Anthropomorphic breast phantoms for testing elastography systems.

Two equivalent anthropomorphic breast phantoms were constructed, one for use in ultrasound elastography and the other in magnetic resonance (MR) elastography. A complete description of the manufacturing methods is provided. The materials used were oil-in-gelatin dispersions, where the volume percent oil differentiates the materials, primarily according to Young's moduli. Values of Young's moduli are in agreement with in vitro ranges for the corresponding normal and abnormal breast tissues. Ultrasound and nuclear magnetic resonance (NMR) properties are reasonably well represented. Phantoms of the type described promise to aid researchers who are developing hardware and software for elastography. Examples of ultrasound and MR elastograms of the phantoms are included to demonstrate the utility of the phantoms. Also, the level of stability of elastic properties of the component materials is quantified over a 15-month period. Such phantoms can serve as performance-assessing intermediaries between simple phantoms (consisting, for example, of homogeneous cylindrical inclusions in a homogeneous background) and a full-scale clinical trial. Thus, premature clinical trials may be avoided.

Anthropometry↗

PubMed2005

Enhancing the performance of model-based elastography by incorporating additional a priori information in the modulus image reconstruction process.

Model-based elastography is fraught with problems owing to the ill-posed nature of the inverse elasticity problem. To overcome this limitation, we have recently developed a novel inversion scheme that incorporates a priori information concerning the mechanical properties of the underlying tissue structures, and the variance incurred during displacement estimation in the modulus image reconstruction process. The information was procured by employing standard strain imaging methodology, and introduced in the reconstruction process through the generalized Tikhonov approach. In this paper, we report the results of experiments conducted on gelatin phantoms to evaluate the performance of modulus elastograms computed with the generalized Tikhonov (GTK) estimation criterion relative to those computed by employing the un-weighted least-squares estimation criterion, the weighted least-squares estimation criterion and the standard Tikhonov method (i.e., the generalized Tikhonov method with no modulus prior). The results indicate that modulus elastograms computed with the generalized Tikhonov approach had superior elastographic contrast discrimination and contrast recovery. In addition, image reconstruction was more resilient to structural decorrelation noise when additional constraints were imposed on the reconstruction process through the GTK method.

Algorithms↗

PubMed2005

Comparative evaluation of strain-based and model-based modulus elastography.

Elastography based on strain imaging currently endures mechanical artefacts and limited contrast transfer efficiency. Solving the inverse elasticity problem (IEP) should obviate these difficulties; however, this approach to elastography is often fraught with problems because of the ill-posed nature of the IEP. The aim of the present study was to determine how the quality of modulus elastograms computed by solving the IEP compared with those produced using standard strain imaging methodology. Strain-based modulus elastograms (i.e., modulus elastograms computed by simply inverting strain elastograms based on the assumption of stress uniformity) and model-based modulus elastograms (i.e., modulus elastograms computed by solving the IEP) were computed from a common cohort of simulated and gelatin-based phantoms that contained inclusions of varying size and modulus contrast. The ensuing elastograms were evaluated by employing the contrast-to-noise ratio (CNR(e)) and the contrast transfer efficiency (CTE(e)) performance metrics. The results demonstrated that, at a fixed spatial resolution, the CNR(e) of strain-based modulus elastograms was statistically equivalent to those computed by solving the IEP. At low modulus contrast, the CTE(e) of both elastographic imaging approaches was comparable; however, at high modulus, the CTE(e) of model-based modulus elastograms was superior.

Algorithms↗

PubMed2005

A three-parameter mechanical property reconstruction method for MR-based elastic property imaging.

A reconstruction process featuring full parameterization of the three dimensional, time-harmonic equations of linear elasticity is developed and reconstructed property images are presented from simulation-based investigation. While interesting in its own right through the potential for increased adaptability of these reconstructive elastic imaging techniques, this study also presents a set of analysis tools used to study the poor convergence behavior found in the case of tissue like conditions (i.e. nearly incompressible materials). The choice of elastic properties for imaging in elastography research remains an open question at this point; the use of the stability and sensitivity-based analytical methods described here will help to predict and understand the value and reliability of different parameterizations of elasticity imaging. Additionally, though results indicate significant work needs to be done to achieve effective multiparameter reconstructive imaging, the methods detailed here offer the promise of increased flexibility and sophistication in elastographic imaging techniques.

Algorithms↗

PubMed2004

Evaluation of the adjoint equation based algorithm for elasticity imaging.

Recently a new adjoint equation based iterative method was proposed for evaluating the spatial distribution of the elastic modulus of tissue based on the knowledge of its displacement field under a deformation. In this method the original problem was reformulated as a minimization problem, and a gradient-based optimization algorithm was used to solve it. Significant computational savings were realized by utilizing the solution of the adjoint elasticity equations in calculating the gradient. In this paper, we examine the performance of this method with regard to measures which we believe will impact its eventual clinical use. In particular, we evaluate its abilities to (1) resolve geometrically the complex regions of elevated stiffness; (2) to handle noise levels inherent in typical instrumentation; and (3) to generate three-dimensional elasticity images. For our tests we utilize both synthetic and experimental displacement data, and consider both qualitative and quantitative measures of performance. We conclude that the method is robust and accurate, and a good candidate for clinical application because of its computational speed and efficiency.

Algorithms↗

PubMed2004

Breast deformation modelling for image reconstruction in near infrared optical tomography.

Near infrared tomography (NIR) is a novel imaging technique that can be used to reconstruct tissue optical properties from measurements of light propagation through tissue. More specifically NIR measurements over a range of wavelengths can be used to obtain internal images of physiologic parameters and these images can be used to detect and characterize breast tumour. To obtain good NIR measurements, it is essential to have good contact between the optical fibres and the breast which in-turn results in the deformation of the breast due to the soft plasticity of the tissue. In this work, a tissue deformation model of the female breast is presented that will account for the altered shape of the breast during clinical NIR measurements. Using a deformed model of a breast, simulated NIR data were generated and used to reconstruct images of tissue absorption and reduced scatter using several assumptions about the imaging domain. Using either a circular or irregular 2D geometry for image reconstruction produces good localization of the absorbing anomaly, but it leads to degradation of the image quality. By modifying the assumptions about the imaging domain to a 3D conical model, with the correct diameter at the plane of NIR measurement, significantly improves the quality of reconstructed images and helps reduce image artefacts. Finally, assuming a non-deformed breast shape for image reconstruction is shown to lead to poor quality images since the geometry of the breast is greatly altered, whereas using the correct deformed geometry produces the best images.

Algorithms↗

PubMed2004

Automated region detection based on the contrast-to-noise ratio in near-infrared tomography.

The contrast-to-noise ratio (CNR) was used to determine the detectability of objects within reconstructed images from diffuse near-infrared tomography. It was concluded that there was a maximal value of CNR near the location of an object within the image and that the size of the true region could be estimated from the CNR. Experimental and simulation studies led to the conclusion that objects can be automatically detected with CNR analysis and that our current system has a spatial resolution limit near 4 mm and a contrast resolution limit near 1.4. A new linear convolution method of CNR calculation was developed for automated region of interest (ROI) detection.

Artifacts↗

PubMed2004

Shear modulus estimation using parallelized partial volumetric reconstruction.

Magnetic resonance elastography can be limited by the computationally intensive nonlinear inversion schemes that are sometimes employed to estimate shear modulus from externally induced internal tissue displacements. Consequently, we have developed a parallelized partial volume reconstruction approach to overcome this limitation. In this paper, we report results from experiments conducted on breast phantoms and human volunteers to validate the proposed technique. More specifically, we demonstrate that computational cost is linearly related to the number of subzones used during image recovery and that both subzone parallelization and partial volume domain reduction decrease execution time accordingly. Importantly, elastograms computed based on the parallelized partial volume technique are not degraded in terms of either image quality or accuracy relative to their full volume counterparts provided that the estimation domain is sufficiently large to negate the effects of boundary conditions. The clinical results presented in this paper are clearly preliminary; however, the parallelized partial volume reconstruction approach performs sufficiently well to warrant more in-depth clinical evaluation.

Breast Neoplasms↗

PubMed2003

Initial in vivo experience with steady-state subzone-based MR elastography of the human breast.

PURPOSE: To describe initial in vivo experiences with a subzone-based, steady-state MR elastography (MRE) method. This sparse collection of in vivo results is intended to shed light on some of the strengths and weaknesses of existing clinical MRE approaches and to indicate important areas of future research. MATERIALS AND METHODS: Elastic property reconstruction results are compared with data compiled from the limited existing body of published studies in breast elasticity. Mechanical parameter distributions are also investigated in terms of their implications for the nature of biological soft tissue. Additionally, a derivation of the statistical variance of the elastic parameter reconstruction is given and the resulting confidence intervals (CIs) for different parameter solutions are examined. RESULTS: By comparison with existing estimates of the elastic properties of breast tissue, the subzone-based, steady-state MRE method is seen to produce reasonable estimates for the mechanical properties of in vivo tissue. CONCLUSION: MRE shows potential as an effective way to determine the elastic properties of breast tissue, and may be of significant clinical interest.

Adipose Tissue↗

PubMed2003

Thresholds for detecting and characterizing focal lesions using steady-state MR elastography.

An objective contrast-detail analysis was performed in this study to assess the low contrast detectability of a clinical prototype harmonic magnetic resonance elastographic imaging system. Elastographic imaging was performed on gelatin phantoms containing spherical inclusions of varying size and modulus contrast. The results demonstrate that lesions as small as 5 mm can be detected with a minimum modulus contrast of 14 dB. However, the shear modulus of such small lesions was not accurately recovered. In general, the shear modulus of larger focal lesions was accurately (i.e., within 25% of the true value) recovered. The minimum modulus contrast needed to detect focal lesions was observed to decrease with increasing lesion size.

Algorithms↗