Analysis Of Intravascular Ultrasound Images Research Articles

Performance analysis of various denoising filters on intravascular ultrasound coronary artery images

Accurate diagnosis of atherosclerotic coronary artery stenosis largely depends on intravascular ultrasound (IVUS) image quality. Coherent sources present during IVUS acquisition generates speckle noise and obstructs the clear view of the artery. Denoising aims to remove speckle noise while preserving edges and other important features. Accordingly, speckle noise suppression serves as an important preprocessing step for IVUS image analysis. This paper presents a performance analysis of various despeckling filters such as Median, Wiener, Speckle Reducing Anisotropic Diffusion (SRAD) filter, Wavelet, Non-local means (NLM) and curvelet based non-local means (CNLM) for IVUS images. To evaluate the efficacy, each filter is evaluated for three categories of cross-sectional IVUS images, that is, healthy, mild calcification, and dense calcification of real pullbacks from four patients. As it is challenging to denoise the IVUS images with complex lesions, that is, calcified arc >180°, in this performance analysis, the denoising performance for different denoising filters is considered not only for the healthy IVUS but also for complex lesions. Various measures such as peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), feature similarity index (FSIM), and expert evaluation are used to compare these approaches. The results depict that the CNLM denoising filter outperforms others in terms of PSNR and FSIM for speckle noise suppression for IVUS images while preserving the essential edge and feature details for better image visualization and diagnosis.

TCT-2 Deep IVUS: A machine learning framework for fully automatic IVUS segmentation

Segmentation of intravascular ultrasound (IVUS) is a time intensive process requiring a high level of expertise to process the images. This challenge restricts analysis of IVUS images to core laboratories and limits cardiac catheterization laboratory adoption. From a Volcano 20MHz IVUS catheter the

Subintimal guidewire tracking during successful percutaneous therapy for chronic coronary total occlusions: Insights from an intravascular ultrasound analysis

We sought to determine the frequency of subintimal guidewire tracking during successful percutaneous coronary intervention (PCI) for chronic coronary total occlusions (CTOs) and to better understand the procedural implications of this event. Successful PCI for chronic CTO is associated with improved outcomes in patients with ischemia. While subintimal guidewire tracking resulting in failure to cross is recognized as the major mode of failure for CTO PCI, the implications of subintimal guidewire tracking during successful CTO PCI are unknown. Between March 2007 and October 2007, 26 consecutive patients, each with one de-novo CTO lesion successfully crossed with a guidewire were included in the analysis. Intravascular ultrasound (IVUS) was performed in each CTO vessel after guidewire crossing. Cases were classified as having definite subintimal wire tracking or no clear evidence of subintimal wire tracking based on analysis of IVUS images. Subintimal wire tracking occurred in 45% of cases. In cases where subintimal wire tracking was present, a previous attempt at CTO PCI was more common (42% vs. 7%, P ≤ 0.05). Subintimal wire tracking was also associated with significantly longer final mean stent length (71 vs. 50 mm), procedure time (122 vs. 69 min), fluoroscopy time (47 vs. 22 min), and contrast dose (300 vs. 199 mL, P ≤ 0.05 for all). There was one perforation in the subintimal group which was successfully treated with stent placement. Subintimal wire tracking occurs frequently during successful PCI for CTO and is associated with increased lesion and procedural complexity.

Automatic segmentation of calcified plaques and vessel borders in IVUS images

Objective Intravascular ultrasound (IVUS) is a diagnostic imaging technique for tomographic visualization of coronary arteries. Automatic analysis of IVUS images is difficult due to speckle noise, artifacts of the catheter, and shadows generated by calcifications. We designed and implemented a system for automated segmentation of coronary artery IVUS images. Methods Two methods for automatic detection of the intima and the media-adventitia borders in IVUS coronary artery images were developed and compared. Thefirst method uses the parametric deformable models, while the second method is based on the geometric deformable models. The initial locations of the borders are approximated using two different edge detection methods. The final borders are then defined using the two deformable models. Finally, the calcified regions between the extracted borders are identified using a Bayesian classifier. The performance of the proposed methods was evaluated using 60 different IVUS images obtained from 7 patients. Results Segmented images were compared with manually outlined contours. We compared the performance of calcifiedregioncharacterizationmethodsusingROCanalysisand

Texture Analysis and Radial Basis Function Approximation for IVUS Image Segmentation

>Intravascular ultrasound (IVUS) has become in the last years an important tool in both clinical and research applications. The detection of lumen and media-adventitia borders in IVUS images represents a first necessary step in the utilization of the IVUS data for the 3D reconstruction of human coronary arteries and the reliable quantitative assessment of the atherosclerotic lesions. To serve this goal, a fully automated technique for the detection of lumen and media-adventitia boundaries has been developed. This comprises two different steps for contour initialization, one for each corresponding contour of interest, based on the results of texture analysis, and a procedure for approximating the initialization results with smooth continuous curves. A multilevel Discrete Wavelet Frames decomposition is used for texture analysis, whereas Radial Basis Function approximation is employed for producing smooth contours. The proposed method shows promising results compared to a previous approach for texture-based IVUS image analysis.

Texture Analysis and Radial Basis Function Approximation for IVUS Image Segmentation

>Intravascular ultrasound (IVUS) has become in the last years an important tool in both clinical and research applications. The detection of lumen and media-adventitia borders in IVUS images represents a first necessary step in the utilization of the IVUS data for the 3D reconstruction of human coronary arteries and the reliable quantitative assessment of the atherosclerotic lesions. To serve this goal, a fully automated technique for the detection of lumen and media-adventitia boundaries has been developed. This comprises two different steps for contour initialization, one for each corresponding contour of interest, based on the results of texture analysis, and a procedure for approximating the initialization results with smooth continuous curves. A multilevel Discrete Wavelet Frames decomposition is used for texture analysis, whereas Radial Basis Function approximation is employed for producing smooth contours. The proposed method shows promising results compared to a previous approach for texture-based IVUS image analysis.

Automatic segmentation and 3D reconstruction of intravascular ultrasound images for a fast preliminar evaluation of vessel pathologies

Intravascular ultrasound (IVUS) imaging is used along with X-ray coronary angiography to detect vessel pathologies. Manual analysis of IVUS images is slow and time-consuming and it is not feasible for clinical purposes. A semi-automated method is proposed to generate 3D reconstructions from IVUS video sequences, so that a fast diagnose can be easily done, quantifying plaque length and severity as well as plaque volume of the vessels under study. The methodology described in this work has four steps: a pre-processing of IVUS images, a segmentation of media–adventitia contour, a detection of intima and plaque and a 3D reconstruction of the vessel. Preprocessing is intended to remove noise from the images without blurring the edges. Segmentation of media–adventitia contour is achieved using active contours (snakes). In particular, we use the gradient vector flow (GVF) as external force for the snakes. The detection of lumen border is obtained taking into account gray-level information of the inner part of the previously detected contours. A knowledge-based approach is used to determine which level of gray corresponds statistically to the different regions of interest: intima, plaque and lumen. The catheter region is automatically discarded. An estimate of plaque type is also given. Finally, 3D reconstruction of all detected regions is made. The suitability of this methodology has been verified for the analysis and visualization of plaque length, stenosis severity, automatic detection of the most problematic regions, calculus of plaque volumes and a preliminary estimation of plaque type obtaining for automatic measures of lumen and vessel area an average error smaller than 1 mm 2 (equivalent aproximately to 10% of the average measure), for calculus of plaque and lumen volume errors smaller than 0.5 mm 3 (equivalent approximately to 20% of the average measure) and for plaque type estimates a mismatch of less than 8% in the analysed frames.

Impact of Preinterventional Arterial Remodeling on In-Stent Neointimal Hyperplasia and In-Stent Restenosis After Coronary Stent Implantation-An Intravascular Ultrasound Study-

Patterns of arterial remodeling during the course of plaque development have been shown to play an important role in both the progression of de novo atherosclerosis and in the restenotic process following coronary intervention. The aim of the present prospective study was to evaluate the effect of pre-interventional arterial remodeling on in-stent neointimal hyperplasia (NIH) and in-stent restenosis (ISR) after stenting. Pre-interventional arterial remodeling was assessed in 85 native coronary lesions by using intravascular ultrasound (IVUS). The remodeling index (RI) was 1.09+/-0.20 in the positive remodeling (PR)/intermediate remodeling (IR) group and 0.84+/-0.12 in the negative remodeling (NR) group. The plaque plus media cross sectional area (P&M CSA) at pre-intervention and NIH CSA at follow-up in the minimal lumen CSA were significantly larger in the PR/IR group (9.2+/-2.9 mm2 vs 6.2+/-1.8 mm2, 3.3+/-1.2 mm2 vs 1.5+/-0.9 mm2; p = 0.001, p = 0.001, respectively). On 3-dimensional analysis of IVUS images at follow-up, the lumen volume was significantly smaller in the PR/IR group than that in the NR group (62+/-15 mm3 vs 75 +/-20 mm3; p = 0.001), and neointima hyperplasia volume was significantly larger in the PR/IR group than that in the NR group (46+/-15 mm3 vs 26+/-10 mm3; p = 0.001). A significant positive correlation was found between pre-interventional RI and follow-up NIH CSA (r = 0.25, p = 0.022). The incidence of ISR and repeat intervention was significantly higher in the PR/IR group (30.8% vs 18.2%, 28.8% vs 15.2%; p = 0.032, 0.035, respectively). Measuring pre-interventional arterial remodeling patterns by IVUS may be helpful to stratify lesions at high-risk of ISR.

Validation of automated contour analysis of intravascular ultrasound images after vascular intervention

The purpose of this study was to determine the feasibility of automated contour analysis of intravascular ultrasound images obtained after vascular intervention. This was a descriptive study. Intravascular ultrasound images obtained from patients after balloon angioplasty (n = 10), stent (n = 10), or stent graft placement (n = 10) were analyzed. A comparison was made between lumen area measured with an automated and a manual system. The location showing the smallest lumen area derived from the automated system was compared with the smallest lumen area selected by visual estimation. Images containing a dissection as a result of balloon angioplasty could not be analyzed by the automated system. The coefficient of variation between the lumen area measurements obtained with the automated system and the manual tracing system of images with a stent (n = 76) or stent graft (n = 79) was 2.7% and 2.1%, respectively. Correlation between the two systems was high (r = 1.00, p < 0.01) both for images containing stents or stent grafts. Minimum lumen area measured with the automated analysis system was smaller than minimum lumen area selected by visual estimation (mean difference 0.8 mm2 (4.9%) for stents and 2.4 mm2 (10.9%) for stent grafts). The location of the smallest lumen area determined with both systems was the same (<1 cm) in 16 cases and differed more than 1 cm in 4 other cases. The automated analysis system shows good agreement with manual contour analysis of lumen area in images with a stent or stent graft and is a reliable tool for determination of the smallest lumen area. The system is not able to analyze an irregular-shaped lumen area caused by a dissection.

Interobserver reproducibility of qualitative and quantitative analysis of intravascular ultrasound images before and after peripheral balloon angioplasty

In this study, interobserver agreement on intravascular ultrasound data obtained before and after balloon angioplasty (PTA) of the superficial femoral artery was assessed. Two observers analyzed intravascular ultrasound cross-sections from 38 patients. Interobserver agreement was good for soft and hard lesions, dissection and vascular damage (kappa values 0.61, 0.67, 0.69 and 0.66, respectively); moderate for eccentric lesions (kappa 0.45); fair for media ruptures (kappa 0.25); and poor for lipid deposits and plaque ruptures (kappa 0.0 and 0.04, respectively). Differences for the are of normal wall and hard lesion were not significant, but were for dissection. There were no significant interobserver differences between area measurements. The coefficient of variation for free lumen area and media-bounded area before PTA was 17.2% and 10.5% and after PTA 11.2% and 9.2%, respectively. This study identified the intravascular ultrasound parameters that are reproducible.

The contribution of tissue removal to lumen improvement after directional coronary atherectomy

The contribution of tissue removal to lumen improvement after directional coronary atherectomy remains controversial. The purpose of this study was to validate the intravascular ultrasound measurement of plaque volume and use it to study the contribution of tissue removal to lumen improvement after directional coronary atherectomy. With use of intravascular ultrasound, 12 human coronary vessels were imaged in vitro. With use of computer-assisted planimetry, the external elastic membrane and lumen cross-sectional areas were manually traced and the plaque + media area was calculated at 1 mm axial intervals. Then, plaque + media volume was calculated by Simpson's rule. After imaging, ultrasound measurements of plaque + media volume were compared with histologic measurements. Similarly, volumetric intravascular ultrasound imaging was performed before and after directional atherectomy in 47 patients. In vitro, the mean plaque + media volume measured by intravascular ultrasound was 134.0 ± 94.8 mm3 and compared well with that derived by histology (187.4 ± 128.8 mm3, r = 0.96, p < 0.001). In vivo, the lumen volume increased from 27.2 ± 12.3 to 58.7 ± 30.3 mm3, and the mean plaque + media volume decreased from 122.0 ± 74.0 to 97.5 ± 63.5 mm3. The mean intravascular ultrasound atherectomy index was 76 ± 23%. In 11 of the 47 patients (23.4%), tissue removal alone accounted for lumen improvement. Volumetric intravascular ultrasound image analysis indicates that the mechanism of directional coronary atherectomy primarily is tissue removal. As a result, the contribution of arterial remodeling (expansion and dissection) probably is less important.

Validation of quantitative analysis of intravascular ultrasound images

This study investigated the accuracy and reproducibility of a computer-aided method for quantification of intravascular ultrasound. The computer analysis system was developed on an IBM compatible PC/AT equipped with a framegrabber. The quantitative assessment of lumen area, lesion area and percent area obstruction was performed by tracing the boundaries of the free lumen and original lumen. Accuracy of the analysis system was tested in a phantom study. Echographic measurements of lumen and lesion area derived from 16 arterial specimens were compared with data obtained by histology. The differences in lesion area measurements between histology and ultrasound were minimal (mean +/- SD: -0.27 +/- 1.79 mm2, p greater than 0.05). Lumen area measurements from histology were significantly smaller than those with ultrasound due to mechanical deformation of histologic specimens (-5.38 +/- 5.09 mm2, p less than 0.05). For comparison with angiography, 18 ultrasound cross-sections were obtained in vivo from 8 healthy peripheral arteries. Luminal areas obtained by angiography were similar to those by ultrasound (-0.52 +/- 5.15 mm2, p greater than 0.05). Finally, intra- and interobserver variability of our quantitative method was evaluated in measurements of 100 in vivo ultrasound images. The results showed that variations in lumen area measurements were low (5%) whereas variations in lesion area and percent area obstruction were relatively high (13%, 10%, respectively). Results of this study indicate that our quantitative method provides accurate and reproducible measurements of lumen and lesion area. Thus, intravascular ultrasound can be used for clinical investigation, including assessment of vascular stenosis and evaluation of therapeutic intervention.