Guy Cloutier

Bio: Guy Cloutier is an academic researcher from Université de Montréal. The author has contributed to research in topics: Elastography & Ultrasound. The author has an hindex of 15, co-authored 39 publications receiving 767 citations.

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

Abstract: 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.

Assessment of Carotid Artery Plaque Components With Machine Learning Classification Using Homodyned-K Parametric Maps and Elastograms

Abstract: Quantitative ultrasound (QUS) imaging methods, including elastography, echogenicity analysis, and speckle statistical modeling, are available from a single ultrasound (US) radio-frequency data acquisition. Since these US imaging methods provide complementary quantitative tissue information, characterization of carotid artery plaques may gain from their combination. Sixty-six patients with symptomatic ( $n = 26$ ) and asymptomatic ( $n = 40$ ) carotid atherosclerotic plaques were included in the study. Of these, 31 underwent magnetic resonance imaging (MRI) to characterize plaque vulnerability and quantify plaque components. US radio-frequency data sequence acquisitions were performed on all patients and were used to compute noninvasive vascular US elastography and other QUS features. Additional QUS features were computed from three types of images: homodyned-K (HK) parametric maps, Nakagami parametric maps, and log-compressed B-mode images. The following six classification tasks were performed: detection of 1) a small area of lipid; 2) a large area of lipid; 3) a large area of calcification; 4) the presence of a ruptured fibrous cap; 5) differentiation of MRI-based classification of nonvulnerable carotid plaques from neovascularized or vulnerable ones; and 6) confirmation of symptomatic versus asymptomatic patients. Feature selection was first applied to reduce the number of QUS parameters to a maximum of three per classification task. A random forest machine learning algorithm was then used to perform classifications. Areas under receiver-operating curves (AUCs) were computed with a bootstrap method. For all tasks, statistically significant higher AUCs were achieved with features based on elastography, HK parametric maps, and B-mode gray levels, when compared to elastography alone or other QUS alone ( $p ). For detection of a large area of lipid, the combination yielding the highest AUC (0.90, 95% CI 0.80–0.92, $p ) was based on elastography, HK, and B-mode gray-level features. To detect a large area of calcification, the highest AUC (0.95, 95% CI 0.94–0.96, $p ) was based on HK and B-mode gray level features. For other tasks, AUCs varied between 0.79 and 0.97. None of the best combinations contained Nakagami features. This study shows the added value of combining different features computed from a single US acquisition with machine learning to characterize carotid artery plaques.

Endovascular Shear Strain Elastography for the Detection and Characterization of the Severity of Atherosclerotic Plaques: In Vitro Validation and In Vivo Evaluation

Abstract: This work explores the potential of shear strain elastograms to identify vulnerable atherosclerotic plaques. The Lagrangian speckle model estimator (LSME) elasticity imaging method was further developed to estimate shear strain elasticity (SSE). Three polyvinyl alcohol cryogel vessel phantoms were imaged with an intravascular ultrasound (IVUS) scanner. The estimated SSE maps were validated against finite-element results. Atherosclerosis was induced in carotid arteries of eight Sinclair mini-pigs using a combination of surgical techniques, diabetes and a high-fat diet. IVUS images were acquired in vivo in 14 plaques before euthanasia and histology. All plaques were characterized by high magnitudes in SSE maps that correlated with American Heart Association atherosclerosis stage classifications (r = 0.97, p < 0.001): the worse the plaque condition the higher was the absolute value of SSE, i.e. |SSE| (e.g., mean |SSE| was 3.70 ± 0.40% in Type V plaques, whereas it was reduced to 0.11 ± 0.01% in normal walls). This study indicates the feasibility of using SSE to highlight atherosclerotic plaque vulnerability characteristics.

Carotid Artery Plaque Vulnerability Assessment Using Noninvasive Ultrasound Elastography: Validation With MRI.

Abstract: OBJECTIVE. Vulnerable and nonvulnerable carotid artery plaques have different tissue morphology and composition that may affect plaque biomechanics. The objective of this study is to evaluate plaque vulnerability with the use of ultrasound noninvasive vascular elastography (NIVE). MATERIALS AND METHODS. Thirty-one patients (mean [± SD] age, 69 ± 7 years) with stenosis of the internal carotid artery of 50% or greater were enrolled in this cross-sectional study. Elastography parameters quantifying axial strain, shear strain, and translation motion were used to characterize carotid artery plaques as nonvulnerable, neovascularized, and vulnerable. Maximum axial strain, cumulated axial strain, mean shear strain, cumulated shear strain, cumulated axial translation, and cumulated lateral translations were measured. Cumulated measurements were summed over a cardiac cycle. The ratio of cumulated axial strain to cumulated axial translation was also evaluated. The reference method used to characterize plaques was hi...

Fast‐marching segmentation of three‐dimensional intravascular ultrasound images: A pre‐ and post‐intervention study

Abstract: Purpose: Intravascular ultrasound (IVUS) is a vascular imaging technique that is used to study atherosclerosis since it has the ability to show the lumen and the vessel wall. Cross-sectional images of blood vessels are produced and they provide quantitative assessment of the vascular wall, information about the nature of atherosclerotic lesions, as well as the plaque shape and size. Due to the ultrasound speckle, catheter artifacts, or calcification shadows, the automated analysis of large IVUS data sets represents an important challenge. Methods: A multiple interface 3D fast-marching method is presented for the detection of the lumen and external vessel wall boundaries. The segmentation is based on a combination of region and contour information, namely, the gray level probability density functions of the vessel structures and the intensity gradient. The detection of the lumen boundary is fully automatic. The segmentation method includes an interactive initialization procedure of the external vessel wall border. The segmentation method was applied to 20 in vivo IVUS data sets acquired from femoral arteries. This database contained three subgroups: Pullbacks acquired before balloon angioplasty ( n = 7 ) , after the intervention ( n = 7 ) , and at a 1 yr follow-up examination ( n = 6 ) . Results were compared to validation contours that were manually traced by two experts on more than 1500 individual frames. Results: For all subgroups, no significant difference was found between the area measurements of the segmentation and validation contours for the lumen and external vessel wall. Moreover, high intraclass correlation coefficients ( > 0.96 ) between the area of the manually traced contours and detected boundaries with the fast-marching method were obtained for both vessel layers over the whole database. The segmentation performance was also evaluated with point-to-point contour distances between segmentation results and manually traced contours. A good overall accuracy was obtained with average distances 0.13 mm and maximum distances 0.46 mm , indicating a good performance in regions lacking information or containing artifacts. Only small differences of less than a pixel (0.02 mm) were observed between the average distance metrics of each subgroup, which prove the segmentation consistency. Conclusions: This new IVUS segmentation method provides accurate results that correspond well to the experts’ manually traced contours, but requires much less manual interactions and is faster.

Ultrasound image segmentation: a survey

Abstract: This paper reviews ultrasound segmentation methods, in a broad sense, focusing on techniques developed for medical B-mode ultrasound images. First, we present a review of articles by clinical application to highlight the approaches that have been investigated and degree of validation that has been done in different clinical domains. Then, we present a classification of methodology in terms of use of prior information. We conclude by selecting ten papers which have presented original ideas that have demonstrated particular clinical usefulness or potential specific to the ultrasound segmentation problem

Photoacoustic imaging in biomedicine

Abstract: Photoacoustic imaging is a promising method for visualizing biological tissues with optical absorbers. This article provides an overview of the rapidly developing field of photoacoustic imaging. Photoacoustics, the physical basis of photoacoustic imaging, is analyzed briefly. The merits of photoacoustic technology, compared with optical imaging and ultrasonic imaging, are described. Various imaging techniques are also discussed, including scanning tomography, computed tomography and original detection of photoacoustic imaging. Finally, some biomedical applications of photoacoustic imaging are summarized.

Species richness, hotspots, and the scale dependence of range maps in ecology and conservation

Abstract: Most studies examining continental-to-global patterns of species richness rely on the overlaying of extent-of-occurrence range maps. Because a species does not occur at all locations within its geographic range, range-map-derived data represent actual distributional patterns only at some relatively coarse and undefined resolution. With the increasing availability of high-resolution climate and land-cover data, broad-scale studies are increasingly likely to estimate richness at high resolutions. Because of the scale dependence of most ecological phenomena, a significant mismatch between the presumed and actual scale of ecological data may arise. This may affect conclusions regarding basic drivers of diversity and may lead to errors in the identification of diversity hotspots. Here, we examine avian range maps of 834 bird species in conjunction with geographically extensive survey data sets on two continents to determine the spatial resolutions at which range-map data actually characterize species occurrences and patterns of species richness. At resolutions less than 2° (≈200 km), range maps overestimate the area of occupancy of individual species and mischaracterize spatial patterns of species richness, resulting in up to two-thirds of biodiversity hotspots being misidentified. The scale dependence of range-map accuracy poses clear limitations on broad-scale ecological analyses and conservation assessments. We suggest that range-map data contain less information than is generally assumed and provide guidance about the appropriate scale of their use.

The EFSUMB Guidelines and Recommendations for the Clinical Practice of Elastography in Non-Hepatic Applications: Update 2018

Abstract: This manuscript describes the use of ultrasound elastography, with the exception of liver applications, and represents an update of the 2013 EFSUMB (European Federation of Societies for Ultrasound in Medicine and Biology) Guidelines and Recommendations on the clinical use of elastography.

Accuracy assessment protocols for elektromagnetic tracking systems.

Abstract: Electromagnetic tracking systems have found increasing use in medical applications during the last few years. As with most non-trivial spatial measurement systems, the complex determination of positions and orientations from their underlying raw sensor measurements results in complicated, non-uniform error distributions over the specified measurement volume. This makes it difficult to unambiguously determine accuracy and performance assessments that allow users to judge the suitability of these systems for their particular needs. Various assessment protocols generally emphasize different measurement aspects that typically arise in clinical use. This can easily lead to inconclusive or even contradictory conclusions. We examine some of the major issues involved and discuss three useful calibration protocols. The measurement accuracy of a system can be described in terms of its 'trueness' and its 'precision'. Often, the two are strongly coupled and cannot be easily determined independently. We present a method that allows the two to be disentangled, so that the resultant trueness properly represents the systematic, non-reducible part of the measurement error, and the resultant precision (or repeatability) represents only the statistical, reducible part. Although the discussion is given largely within the context of electromagnetic tracking systems, many of the results are applicable to measurement systems in general.