Registration Methods for IVUS: Transversal and Longitudinal Transducer Motion Compensation

Talou, Gonzalo D. Maso; Blanco, Pablo; Larrabide, Ignacio; Bezerra, Cristiano Guedes; Lemos, Pedro A.; Feijóo, Raúl A.

doi:10.1109/tbme.2016.2581583

Cited by 19 publications

(20 citation statements)

References 45 publications

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“…A processing methodology was employed to generate a three‐dimensional model of the arterial lumen of the interrogated vessel (hereafter simply referred as mesh) . In brief, for each study, gating of IVUS images was performed to retrieve a end‐diastolic phase from the IVUS dataset .…”

Section: Methodsmentioning

confidence: 99%

“…In brief, for each study, gating of IVUS images was performed to retrieve a end‐diastolic phase from the IVUS dataset . In addition, longitudinal and transversal registrations were performed to obtain a time and space coherent definition of the vessel . The vessel geometry was initially defined in the system of intrinsic coordinates posed by the transducer.…”

Section: Methodsmentioning

confidence: 99%

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Coronary fractional flow reserve derived from intravascular ultrasound imaging: Validation of a new computational method of fusion between anatomy and physiology

Bezerra

Hideo‐Kajita

Bulant

et al. 2018

Cathet Cardio Intervent

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Objectives: To evaluate the diagnostic performance of a novel computational algorithm based on three-dimensional intravascular ultrasound (IVUS) imaging in estimating fractional flow reserve (IVUS FR ), compared to gold-standard invasive measurements (FFR INVAS ).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 FFR INVAS 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 IVUS FR was obtained from patient-level morphological definition of arterial districts and from territory-specific boundary conditions. FFR INVAS measurements were dichotomized at the 0.80 threshold to define hemodynamically significant lesions.Results: A total of 24 patients with 34 vessels were analyzed. IVUS FR significantly correlated (r = 0.79; P < 0.001) and showed good agreement with FFR INVAS , with a mean difference of −0.008 AE 0.067 (P = 0.47). IVUS FR 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 IVUS FR 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. K E Y W O R D Scomputational fluid dynamics, coronary blood flow/physiology/microvascular function, coronary artery disease, fractional flow reserve, imaging intravascular ultrasound, interventional devices/innovation, quantitative coronary angiography, three-dimensional coronary models

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Coronary fractional flow reserve derived from intravascular ultrasound imaging: Validation of a new computational method of fusion between anatomy and physiology

Bezerra

Hideo‐Kajita

Bulant

et al. 2018

Cathet Cardio Intervent

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“…Hence, the extraction of the frames at a particular location is hindered due to the motion of the IVUS transducer exerted by the myocardium contraction. To overcome this issue, gating and registration procedures are performed using methods previously presented in Maso Talou et al ( 2015 , 2017 ). To retrieve the displacement field, a modified optical flow method is applied to the extracted frames at the site of interest.…”

Section: Methodsmentioning

confidence: 99%

“…Finally, given the site of interest at the n -th frame of the end-diastolic phase volume, the set of frames that constitutes a sequence along the cardiac cycle at this site is

, where

is the n -th frame of the phase-coherent volume corresponding to phase s after transversal and axial registration. The reader is directed to Maso Talou et al ( 2017 ) and Maso Talou ( 2017 ) for further details of the registration methods.…”

Section: Methodsmentioning

confidence: 99%

“…Importantly, it is considered that the arterial vessel corresponding to the diastolic phase is at equilibrium with a certain diastolic pressure level, and it is further subjected to a given axial stretch at that phase. By using gating, registration and optical flow methods developed in previous works (Maso Talou et al, 2015 , 2017 ; Maso Talou, 2017 ), the displacement field of the vessel wall is estimated along the cardiac cycle. Then, the ROUKF is exploited as a data assimilation procedure in which the previously obtained displacement field is supplied as observational data, while the material parameter of the Neo-Hookean models are the target parameters to be estimated.…”

Section: Introductionmentioning

confidence: 99%

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Mechanical Characterization of the Vessel Wall by Data Assimilation of Intravascular Ultrasound Studies

et al. 2018

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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.

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End‐diastolic segmentation of intravascular ultrasound images enables more reproducible volumetric analysis of atheroma burden

Erdoğan

Huang

Jain

et al. 2021

Cathet Cardio Intervent

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Background: Volumetric intravascular ultrasound (IVUS) analysis is currently performed at a fixed frame interval, neglecting the cyclic changes in vessel dimensions occurring during the cardiac cycle that can affect the reproducibility of the results.Analysis of end-diastolic (ED) IVUS frames has been proposed to overcome this limitation. However, at present, there is lack of data to support its superiority over conventional IVUS.Objectives: The present study aims to compare the reproducibility of IVUS volumetric analysis performed at a fixed frame interval and at the ED frames, identified retrospectively using a novel deep-learning methodology.Methods: IVUS data acquired from 97 vessels were included in the present study; each vessel was segmented at 1 mm interval (conventional approach) and at ED frame twice by an expert analyst. Reproducibility was tested for the following

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Registration Methods for IVUS: Transversal and Longitudinal Transducer Motion Compensation

Abstract: The proposed registration sorts the IVUS frames for spatial location, which is crucial for a correct interpretation of the vessel wall kinematics along the cardiac phases.

Cited by 19 publications

References 45 publications

Coronary fractional flow reserve derived from intravascular ultrasound imaging: Validation of a new computational method of fusion between anatomy and physiology

Coronary fractional flow reserve derived from intravascular ultrasound imaging: Validation of a new computational method of fusion between anatomy and physiology

Mechanical Characterization of the Vessel Wall by Data Assimilation of Intravascular Ultrasound Studies

End‐diastolic segmentation of intravascular ultrasound images enables more reproducible volumetric analysis of atheroma burden

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