153 research outputs found

    Dedicated bifurcation analysis: basic principles

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    Over the last several years significant interest has arisen in bifurcation stenting, in particular stimulated by the European Bifurcation Club. Traditional straight vessel analysis by QCA does not satisfy the requirements for such complex morphologies anymore. To come up with practical solutions, we have developed two models, a Y-shape and a T-shape model, suitable for bifurcation QCA analysis depending on the specific anatomy of the coronary bifurcation. The principles of these models are described in this paper, as well as the results of validation studies carried out on clinical materials. It can be concluded that the accuracy, precision and applicability of these new bifurcation analyses are conform the general guidelines that have been set many years ago for conventional QCA-analyses

    New approaches for the assessment of vessel sizes in quantitative (cardio-)vascular X-ray analysis

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    This paper presents new approaches for the assessment of the arterial and reference diameters in (cardio-)vascular X-ray images, designed to overcome the problems experienced in conventional quantitative coronary and vascular angiography approaches. In single or “straight” vessel segments, the arterial and reference diameter directions were made independent of each other in order to be able to measure the minimal lumen diameter (MLD) more accurately, especially in curved vessel segments. For ostial segments, an extension of this approach was used, to allow measurement of ostial lesions in sidebranches more proximal than using conventional methods. Furthermore, two new bifurcation approaches were developed. The validation study shows that the straight segment approach results in significant smaller MLDs (on average 0.032 mm) and the ostial approach achieves on average an increase in %DS of 3.8% and an increase in lesion length of 0.59 mm due to loosening the directional constraint. The validation of our new bifurcation approaches in phantom data as well as clinical data shows only small differences between pre- and post-intervention measurements of the reference diameters outside the bifurcation core (errors smaller than 0.06 mm) and the bifurcation core area (errors smaller than 1.4% for phantom data). In summary, these new approaches have led to further improvements in the quantitative analyses of (cardio-)vascular X-ray angiographies

    Three-dimensional reconstruction of myocardial contrast perfusion from biplane cineangiograms by means of linear programming techniques

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    The assessment of coronary flow reserve from the instantaneous distribution of the contrast agent within the coronary vessels and myocardial muscle at the control state and at maximal flow has been limited by the superimposition of myocardial regions of interest in the two-dimensional images. To overcome these limitations, we are in the process of developing a three-dimensional (3D) reconstruction technique to compute the contrast distribution in cross sections of the myocardial muscle from two orthogonal cineangiograms. To limit the number of feasible solutions in the 3D-reconstruction space, the 3D-geometry of the endo- and epicardial boundaries of the myocardium must be determined. For the geometric reconstruction of the epicardium, the centerlines of the left coronary arterial tree are manually or automatically traced in the biplane views. Next, the bifurcations are detected automatically and matched in these two views, allowing a 3D-representation of the coronary tree. Finally, the circumference of the left ventricular myocardium in a selected cross section can be computed from the intersection points of this cross section with the 3D coronary tree using B-splines. For the geometric reconstruction of the left ventricular cavity, we envision to apply the elliptical approximation technique using the LV boundaries defined in the two orthogonal views, or by applying more complex 3D-reconstruction techniques including densitometry. The actual 3D-reconstruction of the contrast distribution in the myocardium is based on a linear programming technique (Transportation model) using cost coefficient matrices. Such a cost coefficient matrix must contain a maximum amount of a priori information, provided by a computer generated model and updated with actual data from the angiographic views. We have only begun to solve this complex problem. However, based on our first experimental results we expect that the linear programming approach with advanced cost coefficient matrices and computed model will lead to a

    Coronary angiography enhancement for visualization

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    High quality visualization on X-ray angiograms is of great significance both for the diagnosis of vessel abnormalities and for coronary interventions. Algorithms for improving the visualization of detailed vascular structures without significantly increasing image noise are currently demanded in the market. A new algorithm called stick-guided lateral inhibition (SGLI) is presented for increasing the visibility of coronary vascular structures. A validation study was set up to compare the SGLI algorithm with the conventional unsharp masking (UM) algorithm on 20 still frames of coronary angiographic images. Ten experienced QCA analysts and nine cardiologists from various centers participated in the validation. Sample scoring value (SSV) and observer agreement value (OAV) were defined to evaluate the validation result, in terms of enhancing performance and observer agreement, respectively. The mean of SSV was concluded to be 77.1 ± 11.9%, indicating that the SGLI algorithm performed significantly better than the UM algorithm (P-value < 0.001). The mean of the OAV was concluded to be 70.3%, indicating that the average agreement with respect to a senior cardiologist was 70.3%. In conclusion, this validation study clearly demonstrates the superiority of the SGLI algorithm in the visualization of coronary arteries from X-ray angiograms

    Echogenicity as a surrogate for bioresorbable everolimus-eluting scaffold degradation: analysis at 1-, 3-, 6-, 12- 18, 24-, 30-, 36- and 42-month follow-up in a porcine model

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    The objective of the study is to validate intravascular quantitative echogenicity as a surrogate for molecular weight assessment of poly-l-lactide-acid (PLLA) bioresorbable scaffold (Absorb BVS, Abbott Vascular, Santa Clara, California). We analyzed at 9 time points (from 1- to 42-month follow-up) a population of 40 pigs that received 97 Absorb scaffolds. The treated regions were analyzed by echogenicity using adventitia as reference, and were categorized as more (hyperechogenic or upperechogenic) or less bright (hypoechogenic) than the reference. The volumes of echogenicity categories were correlated with the measurements of molecular weight (Mw) by gel permeation chromatography. Scaffold struts appeared as high echogenic structures. The quantification of grey level intensity in the scaffold-vessel compartment had strong correlation with the scaffold Mw: hyperechogenicity (correlation coefficient = 0.75; P < 0.01), upperechogenicity (correlation coefficient = 0.63; P < 0.01) and hyper + upperechogenicity (correlation coefficient = 0.78; P < 0.01). In the linear regression, the R2 for high echogenicity and Mw was 0.57 for the combination of hyper and upper echogenicity. IVUS high intensity grey level quantification is correlated to Absorb BVS residual molecular weight and can be used as a surrogate for the monitoring of the degradation of semi-crystalline polymers scaffolds

    Novel near-infrared spectroscopy-intravascular ultrasound-based deep-learning methodology for accurate coronary computed tomography plaque quantification and characterization.

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    AIMS: Coronary computed tomography angiography (CCTA) is inferior to intravascular imaging in detecting plaque morphology and quantifying plaque burden. We aim to, for the first time, train a deep-learning (DL) methodology for accurate plaque quantification and characterization in CCTA using near-infrared spectroscopy-intravascular ultrasound (NIRS-IVUS). METHODS AND RESULTS: Seventy patients were prospectively recruited who underwent CCTA and NIRS-IVUS imaging. Corresponding cross sections were matched using an in-house developed software, and the estimations of NIRS-IVUS for the lumen, vessel wall borders, and plaque composition were used to train a convolutional neural network in 138 vessels. The performance was evaluated in 48 vessels and compared against the estimations of NIRS-IVUS and the conventional CCTA expert analysis. Sixty-four patients (186 vessels, 22 012 matched cross sections) were included. Deep-learning methodology provided estimations that were closer to NIRS-IVUS compared with the conventional approach for the total atheroma volume (ΔDL-NIRS-IVUS: -37.8 ± 89.0 vs. ΔConv-NIRS-IVUS: 243.3 ± 183.7 mm3, variance ratio: 4.262, P < 0.001) and percentage atheroma volume (-3.34 ± 5.77 vs. 17.20 ± 7.20%, variance ratio: 1.578, P < 0.001). The DL methodology detected lesions more accurately than the conventional approach (Area under the curve (AUC): 0.77 vs. 0.67, P < 0.001) and quantified minimum lumen area (ΔDL-NIRS-IVUS: -0.35 ± 1.81 vs. ΔConv-NIRS-IVUS: 1.37 ± 2.32 mm2, variance ratio: 1.634, P < 0.001), maximum plaque burden (4.33 ± 11.83% vs. 5.77 ± 16.58%, variance ratio: 2.071, P = 0.004), and calcific burden (-51.2 ± 115.1 vs. -54.3 ± 144.4, variance ratio: 2.308, P < 0.001) more accurately than conventional approach. The DL methodology was able to segment a vessel on CCTA in 0.3 s. CONCLUSIONS: The DL methodology developed for CCTA analysis from co-registered NIRS-IVUS and CCTA data enables rapid and accurate assessment of lesion morphology and is superior to expert analysts (Clinicaltrials.gov: NCT03556644)

    In vivo comparison of arterial lumen dimensions assessed by co-registered three-dimensional (3D) quantitative coronary angiography, intravascular ultrasound and optical coherence tomography

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    This study sought to compare lumen dimensions as assessed by 3D quantitative coronary angiography (QCA) and by intravascular ultrasound (IVUS) or optical coherence tomography (OCT), and to assess the association of the discrepancy with vessel curvature. Coronary lumen dimensions often show discrepancies when assessed by X-ray angiography and by IVUS or OCT. One source of error concerns a possible mismatch in the selection of corresponding regions for the comparison. Therefore, we developed a novel, real-time co-registration approach to guarantee the point-to-point correspondence between the X-ray, IVUS and OCT images. A total of 74 patients with indication for cardiac catheterization were retrospectively included. Lumen morphometry was performed by 3D QCA and IVUS or OCT. For quantitative analysis, a novel, dedicated approach for co-registration and lumen detection was employed allowing for assessment of lumen size at multiple positions along the vessel. Vessel curvature was automatically calculated from the 3D arterial vessel centerline. Comparison of 3D QCA and IVUS was performed in 519 distinct positions in 40 vessels. Correlations were r = 0.761, r = 0.790, and r = 0.799 for short diameter (SD), long diameter (LD), and area, respectively. Lumen sizes were larger by IVUS (P < 0.001): SD, 2.51 ± 0.58 mm versus 2.34 ± 0.56 mm; LD, 3.02 ± 0.62 mm versus 2.63 ± 0.58 mm; Area, 6.29 ± 2.77 mm2versus 5.08 ± 2.34 mm2. Comparison of 3D QCA and OCT was performed in 541 distinct positions in 40 vessels. Correlations were r = 0.880, r = 0.881, and r = 0.897 for SD, LD, and area, respectively. Lumen sizes were larger by OCT (P < 0.001): SD, 2.70 ± 0.65 mm versus 2.57 ± 0.61 mm; LD, 3.11 ± 0.72 mm versus 2.80 ± 0.62 mm; Area 7.01 ± 3.28 mm2versus 5.93 ± 2.66 mm2. The vessel-based discrepancy between 3D QCA and IVUS or OCT long diameters increased with increasing vessel curvature. In conclusion, our comparison of co-registered 3D QCA and invasive imaging data suggests a bias towards larger lume
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