Biomedical subjects

Roch L Maurice

Publications and source records attributed to Roch L Maurice.

6 recordsLinked to original sources

PubMed2006

Intravascular ultrasound image segmentation: a three-dimensional fast-marching method based on gray level distributions.

Intravascular ultrasound (IVUS) is a catheter based medical imaging technique particularly useful for studying atherosclerotic disease. It produces cross-sectional images of blood vessels that provide quantitative assessment of the vascular wall, information about the nature of atherosclerotic lesions as well as plaque shape and size. Automatic processing of large IVUS data sets represents an important challenge due to ultrasound speckle, catheter artifacts or calcification shadows. A new three-dimensional (3-D) IVUS segmentation model, that is based on the fast-marching method and uses gray level probability density functions (PDFs) of the vessel wall structures, was developed. The gray level distribution of the whole IVUS pullback was modeled with a mixture of Rayleigh PDFs. With multiple interface fast-marching segmentation, the lumen, intima plus plaque structure, and media layers of the vessel wall were computed simultaneously. The PDF-based fast-marching was applied to 9 in vivo IVUS pullbacks of superficial femoral arteries and to a simulated IVUS pullback. Accurate results were obtained on simulated data with average point to point distances between detected vessel wall borders and ground truth <0.072 mm. On in vivo IVUS, a good overall performance was obtained with average distance between segmentation results and manually traced contours <0.16 mm. Moreover, the worst point to point variation between detected and manually traced contours stayed low with Hausdorff distances <0.40 mm, indicating a good performance in regions lacking information or containing artifacts. In conclusion, segmentation results demonstrated the potential of gray level PDF and fast-marching methods in 3-D IVUS image processing.

Algorithms↗

PubMed2005

Non-invasive high-frequency vascular ultrasound elastography.

Non-invasive vascular elastography (NIVE) was recently introduced to characterize mechanical properties of superficial arteries. In this paper, the feasibility of NIVE and its applicability in the context of high-frequency ultrasound imaging is investigated. First, experiments were performed in vitro on vessel-mimicking phantoms. Polyvinyl alcohol cryogel was used to create two double-layer vessels with different mechanical properties. In both cases, the stiffness of the inner layer was made softer. Radial stress was applied within the lumen of the phantoms by applying incremental static pressure steps with a column of a flowing mixture of water-glycerol. The vessel phantoms were insonified at 32 MHz with an ultrasound biomicroscope to provide cross-section sequences of radio-frequency (RF) ultrasound data. The Lagrangian speckle model estimator (LSME) was used to assess the two-dimensional-strain tensors, and the composite Von Mises elastograms were computed. A new implementation of the LSME based on the optical flow equations was introduced. Deformation parameters were estimated using an inversion algorithm. For each in vitro experiment, both layers of approximately 1 mm were distinguished. Second, the use of the method for the purpose of studying small vessels (MicroNIVE) in genetically engineered rodents was introduced. Longitudinal scans of the carotid artery were performed at 40 MHz. The in vivo results give confidence in the feasibility of MicroNIVE as a potential tool to non-invasively study the impact of targeted genes on vascular remodelling in rodents.

Algorithms↗

PubMed2005

Automatic 3D segmentation of intravascular ultrasound images using region and contour information.

Intravascular ultrasound (IVUS) produces images of arteries that show the lumen in addition to the layered structure of the vessel wall. A new automatic 3D IVUS fast-marching segmentation model is presented. The method is based on a combination of region and contour information, namely the gray level probability density functions (PDFs) of the vessel structures and the image gradient. Accurate results were obtained on in-vivo and simulated data with average point to point distances between detected vessel wall boundaries and validation contours below 0.105 mm. Moreover, Hausdorff distances (that represent the worst point to point variations) resulted in values below 0.344 mm, which demonstrate the potential of combining region and contour information in a fast-marching scheme for 3D automatic IVUS image processing.

Algorithms↗

PubMed2005

On the potential of the Lagrangian speckle model estimator to characterize atherosclerotic plaques in endovascular elastography: in vitro experiments using an excised human carotid artery.

Endovascular ultrasound (US) elastography (EVE) was introduced to supplement endovascular US echograms in the assessment of vessel lesions and for endovascular therapy planning. Indeed, changes in the vascular tissue stiffness are characteristic of vessel wall pathologies and EVE appears as a very appropriate imaging technique to outline the elastic properties of vessel walls. Recently, a model-based approach was proposed to assess tissue motion in EVE. It specifically consists of a nonlinear minimization algorithm that was adapted to speckle motion estimation. Regarding the theoretical framework, such an approach considers the speckle as a material property; this assumption then led to the derivation of the optical flow equations, which were suitably combined with the Lagrangian speckle model estimator to provide the full 2-D polar strain tensor. In this study, the proposed algorithm was validated in vitro using a fresh excised human carotid artery. The experimental setup consisted of a cardiovascular imaging system (CVIS) US scanner, working with a 30-MHz mechanical rotating single-element transducer, a digital oscilloscope and a pressuring system. A sequence of radiofrequency (RF) images was collected while incrementally adjusting the intraluminal static pressure steps. The results showed the potential of this 2-D algorithm to characterize and to distinguish an atherosclerotic plaque from the normal vascular tissue. Namely, the geometry as well as some mechanical characteristics of the detected plaque were in good agreement with histology. The results also suggested that there might exist a range of intraluminal pressures for which plaque detectability is optimal.

Algorithms↗

PubMed2004

Noninvasive vascular elastography: theoretical framework.

Changes in vessel wall elasticity may be indicative of vessel pathologies. It is known, for example, that the presence of plaque stiffens the vascular wall, and that the heterogeneity of its composition may lead to plaque rupture and thrombosis. Another domain of application where ultrasound elastography may be of interest is the study of vascular wall elasticity to predict the risk of aneurysmal tissue rupture. In this paper, this technology is introduced as an approach to noninvasively characterize superficial arteries. In such a case, a linear array ultrasound transducer is applied on the skin over the region of interest, and the arterial tissue is dilated by the normal cardiac pulsation. The elastograms, the equivalent elasticity images, are computed from the assessment of the vascular tissue motion. Investigating the forward problem, it is shown that motion parameters might be difficult to interpret; that is because tissue motion occurs radially within the vessel wall while the ultrasound beam propagates axially. As a consequence of that, the elastograms are subjected to hardening and softening artefacts, which are to be counteracted. In this paper, the Von Mises (VM) coefficient is proposed as a new parameter to circumvent such mechanical artefacts and to appropriately characterize the vessel wall. Regarding the motion assessment, the Lagrangian estimator was used; that is because it provides the full two-dimensional strain tensor necessary to compute the VM coefficient. The theoretical model was validated with biomechanical simulations of the vascular wall properties. The results allow believing in the potential of the method to differentiate hard plaques and lipid pools from normal vascular tissue. Potential in vivo implementation of noninvasive vascular elastography to characterize abdominal aneurysms and superficial arteries such as the femoral and the carotid is discussed.

Algorithms↗

PubMed2004

Adapting the Lagrangian speckle model estimator for endovascular elastography: theory and validation with simulated radio-frequency data.

Intravascular ultrasound (IVUS) is known to be the reference tool for preoperative vessel lesion assessments and for endovascular therapy planning. Nevertheless, IVUS echograms only provide subjective information about vessel wall lesions. Since changes in the vascular tissue stiffness are characteristic of vessel pathologies, catheter-based endovascular ultrasound elastography (EVE) has been proposed in the literature as a method for outlining the elastic properties of vessel walls. In this paper, the Lagrangian Speckle Model Estimator (LSME) is formulated for investigations in EVE, i.e., using a polar coordinate system. The method was implemented through an adapted version of the Levenberg-Marquardt minimization algorithm, using the optical flow equations to compute the Jacobbian matrix. The theoretical framework was validated with simulated ultrasound rf data of mechanically complex vessel wall pathologies. The results, corroborated with Ansys finite element software, demonstrated the potential of EVE to provide useful information about the heterogeneous nature of atherosclerotic plaques.

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