High Performance Computing of Personalized Cardio Component Models

NCT ID: NCT02235883

Last Updated: 2018-04-25

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

94 participants

Study Classification

OBSERVATIONAL

Study Start Date

2014-08-31

Study Completion Date

2017-01-31

Brief Summary

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The objective of the HEART Study is to develop a multiscale model of the coronary circulation based on multimodal imaging data (angiography, echocardiography). The predictive comprehensive multi-scale model, developed during this proof-of-concept study, will be used for analyzing functional aspects of coronary artery disease. Model validation is performed against invasive measurements

Detailed Description

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The main objective of HEART is the development and validation of a patient-specific multiscale computational model of the coronary circulation with high predictive power in healthy and diseased vessels:

* Comprehensive modeling of the anatomical and hemodynamic phenomena in the coronary circulation based on input data acquired from both angiography and echocardiography;
* Assessment of functional parameters and subsequent validation of the models;
* High performance computing architecture for efficiently addressing the multi-scale complexity, which is a critical requirement for translation into clinical decision making.

Patient measurements used as input data for the multiscale models, or for validating the computational results include:

* Angiography: targeted angiographic views include LAO 30, LAO 30/20 cranial, LAO 30/20 caudal, RAO 30 (RCA views) and RAO 25/25 caudal, RAO 0/40 caudal, RAO 10/40 cranial, LAO 50/20 cranial, LAO 50/20 caudal (LCA views)
* Echocardiography:

* Standard apical acquisitions (2D harmonic 4-chamber, 2-chamber, 3-chamber)
* Color flow Doppler/spectral Doppler (MR, AI, TR evaluation; CW and PW spectral Doppler)
* Three-dimensional imaging (From apical 4-chamber view one ECG-triggered real time complete full volume acquisition including LV and LA - 1 acquisition at low volume per second (VPS) rate and one at high VPS, real time volumetric color flow Doppler, cover MV and AV).
* Non-invasive pressure measurements: cuff-based measurements at the left and right arm, before echocardiography and angiography
* Invasive pressure measurements: rest - aortic pressure (Pa), distal pressure (Pd), Pd/Pa ratio; hyperemia - aortic pressure (Pa), distal pressure (Pd), FFR (Pd/Pa)

Conditions

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Coronary Artery Disease

Study Design

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Observational Model Type

CASE_ONLY

Study Time Perspective

PROSPECTIVE

Eligibility Criteria

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Inclusion Criteria

* age \>18 years
* providing written informed consent
* scheduled to undergo clinically-indicated non-emergent invasive coronary angiography (ICA)
* likelihood of stenosis in one of the main coronary epicardial vessels (LAD, LCx, RCA)

Exclusion Criteria

* prior PCI
* prior bypass surgery
* prior valve surgery or replacement
* significant arrhythmia
* very low systolic BP (\<90 mmHg)
* abnormally high HR (\>120 bpm)
* significant Left Main disease
* STEMI or NSTEMI
* suspected microvascular disease
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Spitalul Clinic de Urgenţǎ Bucureşti

UNKNOWN

Sponsor Role collaborator

Siemens Corporate Technology Romania

INDUSTRY

Sponsor Role collaborator

Universitatea Politehnica Bucureşti

UNKNOWN

Sponsor Role collaborator

Transilvania University of Brasov

OTHER

Sponsor Role lead

Responsible Party

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Lucian Itu

Conf. dr. ing. Constantin Suciu

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Constantin Suciu, Conf. dr. ing.

Role: PRINCIPAL_INVESTIGATOR

Siemens Corporate Technology Romania

Locations

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Spitalul Clinic de Urgenţǎ Bucureşti

Bucharest, , Romania

Site Status

Countries

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Romania

Related Links

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Other Identifiers

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130_2012

Identifier Type: -

Identifier Source: org_study_id

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