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Artigo em Inglês | MEDLINE | ID: mdl-30277641


OBJECTIVES: To evaluate the diagnostic performance of a novel computational algorithm based on three-dimensional intravascular ultrasound (IVUS) imaging in estimating fractional flow reserve (IVUSFR), compared to gold-standard invasive measurements (FFRINVAS). BACKGROUND: IVUS provides accurate anatomical evaluation of the lumen and vessel wall and has been validated as a useful tool to guide percutaneous coronary intervention. However, IVUS poorly represents the functional status (i.e., flow-related information) of the imaged vessel. METHODS: Patients with known or suspected stable coronary disease scheduled for elective cardiac catheterization underwent FFRINVAS measurement and IVUS imaging in the same procedure to evaluate intermediate lesions. A processing methodology was applied on IVUS to generate a computational mesh condensing the geometric characteristics of the vessel. Computation of IVUSFR was obtained from patient-level morphological definition of arterial districts and from territory-specific boundary conditions. FFRINVAS measurements were dichotomized at the 0.80 threshold to define hemodynamically significant lesions. RESULTS: A total of 24 patients with 34 vessels were analyzed. IVUSFR significantly correlated (r = 0.79; P < 0.001) and showed good agreement with FFRINVAS, with a mean difference of -0.008 ± 0.067 (P = 0.47). IVUSFR presented an overall accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 91%, 89%, 92%, 80%, and 96%, respectively, to detect significant stenosis. CONCLUSION: The computational processing of IVUSFR is a new method that allows the evaluation of the functional significance of coronary stenosis in an accurate way, enriching the anatomical information of grayscale IVUS.

Front Physiol ; 9: 292, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29643815


Atherosclerotic plaque rupture and erosion are the most important mechanisms underlying the sudden plaque growth, responsible for acute coronary syndromes and even fatal cardiac events. Advances in the understanding of the culprit plaque structure and composition are already reported in the literature, however, there is still much work to be done toward in-vivo plaque visualization and mechanical characterization to assess plaque stability, patient risk, diagnosis and treatment prognosis. In this work, a methodology for the mechanical characterization of the vessel wall plaque and tissues is proposed based on the combination of intravascular ultrasound (IVUS) imaging processing, data assimilation and continuum mechanics models within a high performance computing (HPC) environment. Initially, the IVUS study is gated to obtain volumes of image sequences corresponding to the vessel of interest at different cardiac phases. These sequences are registered against the sequence of the end-diastolic phase to remove transversal and longitudinal rigid motions prescribed by the moving environment due to the heartbeat. Then, optical flow between the image sequences is computed to obtain the displacement fields of the vessel (each associated to a certain pressure level). The obtained displacement fields are regarded as observations within a data assimilation paradigm, which aims to estimate the material parameters of the tissues within the vessel wall. Specifically, a reduced order unscented Kalman filter is employed, endowed with a forward operator which amounts to address the solution of a hyperelastic solid mechanics model in the finite strain regime taking into account the axially stretched state of the vessel, as well as the effect of internal and external forces acting on the arterial wall. Due to the computational burden, a HPC approach is mandatory. Hence, the data assimilation and computational solid mechanics computations are parallelized at three levels: (i) a Kalman filter level; (ii) a cardiac phase level; and (iii) a mesh partitioning level. To illustrate the capabilities of this novel methodology toward the in-vivo analysis of patient-specific vessel constituents, mechanical material parameters are estimated using in-silico and in-vivo data retrieved from IVUS studies. Limitations and potentials of this approach are exposed and discussed.

IEEE Trans Biomed Eng ; 62(12): 2867-77, 2015 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-26111388


UNLABELLED:   GOAL: Coronary intravascular ultrasound (IVUS) is a fundamental imaging technique for atherosclerotic plaque assessment. However, volume-based data retrieved from IVUS studies can be misleading due to the artifacts generated by the cardiac motion, hindering diagnostic, and visualization of the vessel condition. Then, we propose an image-based gating method that improves the performance of the preexisting methods, delivering a gating in an appropriate time for clinical practice. METHODS: We propose a fully automatic method to synergically integrate motion signals from different gating methods to improve the cardiac phase estimation. Additionally, we present a local extrema identification method that provides a more accurate extraction of a cardiac phase and, also, a scheme for multiple phase extraction mandatory for elastography-type studies. RESULTS: A comparison with three state-of-the-art methods is performed over 61 in-vivo IVUS studies including a wide range of physiological situations. The results show that the proposed strategy offers: 1) a more accurate cardiac phase extraction; 2) a lower frame oversampling and/or omission in the extracted phase data (error of 1.492 ±0.977 heartbeats per study, mean ± SD); 3) a more accurate and robust heartbeat period detection with a Bland-Altman coefficient of reproducibility (RPC) of 0.23 s, while the second closest method presents an RPC of 0.36 s. SIGNIFICANCE: The integration of motion signals performed by our method shown an improvement of the gating accuracy and reliability.

Ecocardiografia/métodos , Frequência Cardíaca/fisiologia , Processamento de Sinais Assistido por Computador , Ultrassonografia de Intervenção/métodos , Vasos Coronários/diagnóstico por imagem , Coração/fisiologia , Humanos