Cargando…

Inconsistency in aortic stenosis severity between CT and echocardiography: prevalence and insights into mechanistic differences using computational fluid dynamics

OBJECTIVES: The aims of this study were to evaluate the inconsistency of aortic stenosis (AS) severity between CT aortic valve area (CT-AVA) and echocardiographic Doppler parameters, and to investigate potential underlying mechanisms using computational fluid dynamics (CFD). METHODS: A total of 450...

Descripción completa

Detalles Bibliográficos
Autores principales: Mittal, Tarun Kumar, Reichmuth, Luise, Bhattacharyya, Sanjeev, Jain, Manish, Baltabaeva, Aigul, Rahman Haley, Shelley, Mirsadraee, Saeed, Panoulas, Vasileios, Kabir, Tito, Nicol, Edward David, Dalby, Miles, Long, Quan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6667934/
https://www.ncbi.nlm.nih.gov/pubmed/31413845
http://dx.doi.org/10.1136/openhrt-2019-001044
_version_ 1783440128230817792
author Mittal, Tarun Kumar
Reichmuth, Luise
Bhattacharyya, Sanjeev
Jain, Manish
Baltabaeva, Aigul
Rahman Haley, Shelley
Mirsadraee, Saeed
Panoulas, Vasileios
Kabir, Tito
Nicol, Edward David
Dalby, Miles
Long, Quan
author_facet Mittal, Tarun Kumar
Reichmuth, Luise
Bhattacharyya, Sanjeev
Jain, Manish
Baltabaeva, Aigul
Rahman Haley, Shelley
Mirsadraee, Saeed
Panoulas, Vasileios
Kabir, Tito
Nicol, Edward David
Dalby, Miles
Long, Quan
author_sort Mittal, Tarun Kumar
collection PubMed
description OBJECTIVES: The aims of this study were to evaluate the inconsistency of aortic stenosis (AS) severity between CT aortic valve area (CT-AVA) and echocardiographic Doppler parameters, and to investigate potential underlying mechanisms using computational fluid dynamics (CFD). METHODS: A total of 450 consecutive eligible patients undergoing transcatheter AV implantation assessment underwent CT cardiac angiography (CTCA) following echocardiography. CT-AVA derived by direct planimetry and echocardiographic parameters were used to assess severity. CFD simulation was performed in 46 CTCA cases to evaluate velocity profiles. RESULTS: A CT-AVA>1 cm(2) was present in 23% of patients with echocardiographic peak velocity≥4 m/s (r=−0.33) and in 15% patients with mean Doppler gradient≥40 mm Hg (r=−0.39). Patients with inconsistent severity grading between CT and echocardiography had higher stroke volume index (43 vs 38 mL/m(2), p<0.003) and left ventricular outflow tract (LVOT) flow rate (235 vs 192 cm(3)/s, p<0.001). CFD simulation revealed high flow, either in isolation (p=0.01), or when associated with a skewed velocity profile (p=0.007), as the main cause for inconsistency between CT and echocardiography. CONCLUSION: Severe AS by Doppler criteria may be associated with a CT-AVA>1 cm(2) in up to a quarter of patients. CFD demonstrates that haemodynamic severity may be exaggerated on Doppler analysis due to high LVOT flow rates, with or without skewed velocity profiles, across the valve orifice. These factors should be considered before making a firm diagnosis of severe AS and evaluation with CT can be helpful.
format Online
Article
Text
id pubmed-6667934
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher BMJ Publishing Group
record_format MEDLINE/PubMed
spelling pubmed-66679342019-08-14 Inconsistency in aortic stenosis severity between CT and echocardiography: prevalence and insights into mechanistic differences using computational fluid dynamics Mittal, Tarun Kumar Reichmuth, Luise Bhattacharyya, Sanjeev Jain, Manish Baltabaeva, Aigul Rahman Haley, Shelley Mirsadraee, Saeed Panoulas, Vasileios Kabir, Tito Nicol, Edward David Dalby, Miles Long, Quan Open Heart Valvular Heart Disease OBJECTIVES: The aims of this study were to evaluate the inconsistency of aortic stenosis (AS) severity between CT aortic valve area (CT-AVA) and echocardiographic Doppler parameters, and to investigate potential underlying mechanisms using computational fluid dynamics (CFD). METHODS: A total of 450 consecutive eligible patients undergoing transcatheter AV implantation assessment underwent CT cardiac angiography (CTCA) following echocardiography. CT-AVA derived by direct planimetry and echocardiographic parameters were used to assess severity. CFD simulation was performed in 46 CTCA cases to evaluate velocity profiles. RESULTS: A CT-AVA>1 cm(2) was present in 23% of patients with echocardiographic peak velocity≥4 m/s (r=−0.33) and in 15% patients with mean Doppler gradient≥40 mm Hg (r=−0.39). Patients with inconsistent severity grading between CT and echocardiography had higher stroke volume index (43 vs 38 mL/m(2), p<0.003) and left ventricular outflow tract (LVOT) flow rate (235 vs 192 cm(3)/s, p<0.001). CFD simulation revealed high flow, either in isolation (p=0.01), or when associated with a skewed velocity profile (p=0.007), as the main cause for inconsistency between CT and echocardiography. CONCLUSION: Severe AS by Doppler criteria may be associated with a CT-AVA>1 cm(2) in up to a quarter of patients. CFD demonstrates that haemodynamic severity may be exaggerated on Doppler analysis due to high LVOT flow rates, with or without skewed velocity profiles, across the valve orifice. These factors should be considered before making a firm diagnosis of severe AS and evaluation with CT can be helpful. BMJ Publishing Group 2019-07-29 /pmc/articles/PMC6667934/ /pubmed/31413845 http://dx.doi.org/10.1136/openhrt-2019-001044 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Valvular Heart Disease
Mittal, Tarun Kumar
Reichmuth, Luise
Bhattacharyya, Sanjeev
Jain, Manish
Baltabaeva, Aigul
Rahman Haley, Shelley
Mirsadraee, Saeed
Panoulas, Vasileios
Kabir, Tito
Nicol, Edward David
Dalby, Miles
Long, Quan
Inconsistency in aortic stenosis severity between CT and echocardiography: prevalence and insights into mechanistic differences using computational fluid dynamics
title Inconsistency in aortic stenosis severity between CT and echocardiography: prevalence and insights into mechanistic differences using computational fluid dynamics
title_full Inconsistency in aortic stenosis severity between CT and echocardiography: prevalence and insights into mechanistic differences using computational fluid dynamics
title_fullStr Inconsistency in aortic stenosis severity between CT and echocardiography: prevalence and insights into mechanistic differences using computational fluid dynamics
title_full_unstemmed Inconsistency in aortic stenosis severity between CT and echocardiography: prevalence and insights into mechanistic differences using computational fluid dynamics
title_short Inconsistency in aortic stenosis severity between CT and echocardiography: prevalence and insights into mechanistic differences using computational fluid dynamics
title_sort inconsistency in aortic stenosis severity between ct and echocardiography: prevalence and insights into mechanistic differences using computational fluid dynamics
topic Valvular Heart Disease
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6667934/
https://www.ncbi.nlm.nih.gov/pubmed/31413845
http://dx.doi.org/10.1136/openhrt-2019-001044
work_keys_str_mv AT mittaltarunkumar inconsistencyinaorticstenosisseveritybetweenctandechocardiographyprevalenceandinsightsintomechanisticdifferencesusingcomputationalfluiddynamics
AT reichmuthluise inconsistencyinaorticstenosisseveritybetweenctandechocardiographyprevalenceandinsightsintomechanisticdifferencesusingcomputationalfluiddynamics
AT bhattacharyyasanjeev inconsistencyinaorticstenosisseveritybetweenctandechocardiographyprevalenceandinsightsintomechanisticdifferencesusingcomputationalfluiddynamics
AT jainmanish inconsistencyinaorticstenosisseveritybetweenctandechocardiographyprevalenceandinsightsintomechanisticdifferencesusingcomputationalfluiddynamics
AT baltabaevaaigul inconsistencyinaorticstenosisseveritybetweenctandechocardiographyprevalenceandinsightsintomechanisticdifferencesusingcomputationalfluiddynamics
AT rahmanhaleyshelley inconsistencyinaorticstenosisseveritybetweenctandechocardiographyprevalenceandinsightsintomechanisticdifferencesusingcomputationalfluiddynamics
AT mirsadraeesaeed inconsistencyinaorticstenosisseveritybetweenctandechocardiographyprevalenceandinsightsintomechanisticdifferencesusingcomputationalfluiddynamics
AT panoulasvasileios inconsistencyinaorticstenosisseveritybetweenctandechocardiographyprevalenceandinsightsintomechanisticdifferencesusingcomputationalfluiddynamics
AT kabirtito inconsistencyinaorticstenosisseveritybetweenctandechocardiographyprevalenceandinsightsintomechanisticdifferencesusingcomputationalfluiddynamics
AT nicoledwarddavid inconsistencyinaorticstenosisseveritybetweenctandechocardiographyprevalenceandinsightsintomechanisticdifferencesusingcomputationalfluiddynamics
AT dalbymiles inconsistencyinaorticstenosisseveritybetweenctandechocardiographyprevalenceandinsightsintomechanisticdifferencesusingcomputationalfluiddynamics
AT longquan inconsistencyinaorticstenosisseveritybetweenctandechocardiographyprevalenceandinsightsintomechanisticdifferencesusingcomputationalfluiddynamics