On the potential of ultrasound elastography for pressure ulcer early detection.

PURPOSE: Pressure ulcers are areas of soft tissue breakdown induced by a sustained mechanical stress that damages the skin and underlying tissues. They represent a considerable burden to the society in terms of health care and cost. Yet, techniques for prevention and detection of pressure ulcers still remain very limited. In this article, the authors investigated the potential of ultrasound elastography for pressure ulcer early detection. Elastography is an imaging technique providing local information on biological tissue mechanical properties. It is relevant for pressure ulcer detection as this pathology is associated with a gradual stiffening of damaged tissues, beginning in the deeper tissues and progressing toward the skin surface. METHODS: A 2D ultrasound elastography method was proposed and its ability in terms of pressure ulcer detection was validated through numerical simulations and physical acquisitions on pressure ulcer mimicking phantoms. In vivo experiments on a rat model are also reported. A maintained pressure was applied on the animal thigh, with a view to generate a pressure ulcer, and ultrasound data were acquired and processed before and after application of this pressure. RESULTS: Numerical simulations demonstrated that a pressure ulcer can theoretically be detected at a very early stage with ultrasound elastography. Even when the ulcer region was characterized by a low stiffening (ratio of 1.8 relative to normal tissues), the corresponding elastogram clearly underlined the pathological area. This observation was confirmed by the results obtained on a physical phantom mimicking a pressure ulcer at an early stage. Computed elastograms showed strain differences between areas mimicking healthy and pathological tissues. Results corresponding to in vivo experiments revealed a difference in the way tissues behaved before and after the pressure was applied on the animal thigh, which strongly suggests the presence of a pathological area. CONCLUSIONS: Experiments demonstrated that ultrasound elastography is a promising technique for pressure ulcer detection, especially at an early stage of the pathology, when the disease is still visually undetectable. In the absence of any gold standard method, this is also a first step toward the development of a quantitative technique.

A compensative model for the angle-dependence of motion estimates in noninvasive vascular elastography.

PURPOSE: Atherosclerosis of peripheral cerebral arteries can lead to stroke either by stenosis formation or plaque rupture. This pathology is initiated by the alteration of arterial wall mechanical properties shown to be assessable by ultrasound elastography. Recently, noninvasive vascular elastography (NIVE) was introduced for noninvasive imaging of the mechanical properties of superficial arteries as markers of vulnerable plaques. However, NIVE motion estimates are angle-dependent, with optimal scanning angle being represented by the alignment of tissue motion with ultrasound beam orientation. The objective of this study was to introduce a model that compensates for such angle-dependence in order to reduce the bias on strain estimates, namely, when investigating longitudinal vessel segments. METHODS: The model is based on the Lagrangian speckle model estimator (LSME) because the LSME assesses the 2D-deformation matrix required to compute the scanning angle. RESULTS: Experiments on vessel-mimicking phantoms indicated that such a model enables the estimation of scanning angle with less than 3-degrees error. The method was also validated in vivo in human carotid arteries where less than 4-degrees error was observed. In both cases, the compensative model estimated the inclination angles with low variability. CONCLUSION: Angle-dependence may be an important factor to consider in avoiding potentially distort clinical diagnoses. Results, reported in this article, suggest that the LSME-based compensative model might be considered as a very interesting and promising clinical tool for NIVE applications.

3D estimation of soft biological tissue deformation from radio-frequency ultrasound volume acquisitions.

The current research and development of 2D (matrix-shaped) transducer arrays to acquire 3D ultrasound data sets provides new insights into medical ultrasound applications and in particular into elastography. Until very recently, tissue strain estimation techniques commonly used in elastography were mainly 1D or 2D methods. In this paper, a 3D technique estimating biological soft tissue deformation under load from ultrasound radiofrequency volume acquisitions is introduced. This method locally computes axial strains, while considering lateral and elevational motions. Optimal deformation parameters are estimated as those maximizing a similarity criterion, defined as the normalized correlation coefficient, between an initial region and its deformed version, when the latter is compensated for according to these parameters. The performance of our algorithm was assessed with numerical data reproducing the configuration of breast cancer, as well as a physical phantom mimicking a pressure ulcer. Simulation results show that the estimated strain fields are very close to the theoretical values, perfectly discriminating between the harder lesion and the surrounding medium. Experimental strain images of the physical phantom demonstrated the different structures of the medium, even though they are not all detectable on the ultrasound scans. Finally, both simulated and experimental results demonstrate the ability of our algorithm to provide good-quality elastograms, even in the conditions of significant out-of-plane motion.

2-D locally regularized tissue strain estimation from radio-frequency ultrasound images: theoretical developments and results on experimental data.

In this paper, a 2-D locally regularized strain estimation method for imaging deformation of soft biological tissues from radio-frequency (RF) ultrasound (US) data is introduced. Contrary to most 2-D techniques that model the compression-induced local displacement as a 2-D shift, our algorithm also considers a local scaling factor in the axial direction. This direction-dependent model of tissue motion and deformation is induced by the highly anisotropic resolution of RF US images. Optimal parameters are computed through the constrained maximization of a similarity criterion defined as the normalized correlation coefficient. Its value at the solution is then used as an indicator of estimation reliability, the probability of correct estimation increasing with the correlation value. In case of correlation loss, the estimation integrates an additional constraint, imposing local continuity within displacement and strain fields. Using local scaling factors and regularization increase the method's robustness with regard to decorrelation noise, resulting in a wider range of precise measurements. Results on simulated US data from a mechanically homogeneous medium subjected to successive uniaxial loadings demonstrate that our method is theoretically able to accurately estimate strains up to 17%. Experimental strain images of phantom and cut specimens of bovine liver clearly show the harder inclusions.

Locally regularized strain field estimation for freehand elastography.

This paper focuses on strain estimation methods in ultrasound elastography. We recently developed a 2D locally regularized strain estimation algorithm, whose performance was assessed with simulations and experimental data, but in the case of a well controlled medium deformation. In this study, we investigate the robustness of our algorithm to image tissue deformation during freehand scanning. Results on an elastography dedicated phantom and biological tissue ex vivo demonstrate the ability of our algorithm to provide good-quality strain maps, even in more complex loading conditions.

3D ultrasound elastography for early detection of lesions. evaluation on a pressure ulcer mimicking phantom.

A pressure ulcer is a damaged tissue area induced by an unrelieved pressure compressing the tissue during a prolonged period of immobility. The lack of information and studies on the development of this pathology makes its prevention difficult. However, it is both acknowledged that lesions initiate in the deep muscular tissues before they expand to the skin, and that lesions are harder than healthy tissues. Elastography is therefore an interesting tool for an early detection of the pathology. A 3D strain estimation algorithm is presented and evaluated on a PVA-cryogel phantom, mimicking a pressure ulcer at an early stage.