Literature DB >> 25145313

MRI model-based non-invasive differential diagnosis in pulmonary hypertension.

A Lungu1, J M Wild2, D Capener3, D G Kiely4, A J Swift2, D R Hose2.   

Abstract

Pulmonary hypertension(PH) is a disorder characterised by increased mean pulmonary arterial pressure. Currently, the diagnosis of PH relies upon measurements taken during invasive right heart catheterisation (RHC). This paper describes a process to derive diagnostic parameters using only non-invasive methods based upon MRI imaging alone. Simultaneous measurements of main pulmonary artery (MPA) anatomy and flow are interpreted by 0D and 1D mathematical models, in order to infer the physiological status of the pulmonary circulation. Results are reported for 35 subjects, 27 of whom were patients clinically investigated for PH and eight of whom were healthy volunteers. The patients were divided into 3 sub-groups according to the severity of the disease state, one of which represented a negative diagnosis (NoPH), depending on the results of the clinical investigation, which included RHC and complementary MR imaging. Diagnostic indices are derived from two independent mathematical models, one based on the 1D wave equation and one based on an RCR Windkessel model. Using the first model it is shown that there is an increase in the ratio of the power in the reflected wave to that in the incident wave (Wpb/Wptotal) according to the classification of the disease state. Similarly, the second model shows an increase in the distal resistance with the disease status. The results of this pilot study demonstrate that there are statistically significant differences in the parameters derived from the proposed models depending on disease status, and thus suggest the potential for development of a non-invasive, image-based diagnostic test for pulmonary hypertension.
Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Optimisation; Pulmonary hypertension; RCR; Wave reflections

Mesh:

Year:  2014        PMID: 25145313     DOI: 10.1016/j.jbiomech.2014.07.024

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  12 in total

1.  Diagnosis of pulmonary hypertension from magnetic resonance imaging-based computational models and decision tree analysis.

Authors:  Angela Lungu; Andrew J Swift; David Capener; David Kiely; Rod Hose; Jim M Wild
Journal:  Pulm Circ       Date:  2016-06       Impact factor: 3.017

2.  Uncertainty Quantification in a Patient-Specific One-Dimensional Arterial Network Model: EnKF-Based Inflow Estimator.

Authors:  Andrea Arnold; Christina Battista; Daniel Bia; Yanina Zócalo German; Ricardo L Armentano; Hien Tran; Mette S Olufsen
Journal:  J Verif Valid Uncertain Quantif       Date:  2017-02-22

3.  A non-invasive assessment of cardiopulmonary hemodynamics with MRI in pulmonary hypertension.

Authors:  Octavia Bane; Sanjiv J Shah; Michael J Cuttica; Jeremy D Collins; Senthil Selvaraj; Neil R Chatterjee; Christoph Guetter; James C Carr; Timothy J Carroll
Journal:  Magn Reson Imaging       Date:  2015-08-14       Impact factor: 2.546

4.  Magnetic Resonance Imaging in the Prognostic Evaluation of Patients with Pulmonary Arterial Hypertension.

Authors:  Andrew J Swift; Dave Capener; Chris Johns; Neil Hamilton; Alex Rothman; Charlie Elliot; Robin Condliffe; Athanasios Charalampopoulos; Smitha Rajaram; Allan Lawrie; Michael J Campbell; Jim M Wild; David G Kiely
Journal:  Am J Respir Crit Care Med       Date:  2017-07-15       Impact factor: 21.405

Review 5.  Computational fluid dynamics modelling in cardiovascular medicine.

Authors:  Paul D Morris; Andrew Narracott; Hendrik von Tengg-Kobligk; Daniel Alejandro Silva Soto; Sarah Hsiao; Angela Lungu; Paul Evans; Neil W Bressloff; Patricia V Lawford; D Rodney Hose; Julian P Gunn
Journal:  Heart       Date:  2015-10-28       Impact factor: 5.994

6.  The Use of Biophysical Flow Models in the Surgical Management of Patients Affected by Chronic Thromboembolic Pulmonary Hypertension.

Authors:  Martina Spazzapan; Priya Sastry; John Dunning; David Nordsletten; Adelaide de Vecchi
Journal:  Front Physiol       Date:  2018-03-13       Impact factor: 4.566

7.  Building a Fast Virtual Fractional Flow Reserve: Reductionists or Dreamers?

Authors:  Morton J Kern; Jeannie H Yu; Arnold H Seto
Journal:  JACC Basic Transl Sci       Date:  2017-08-28

8.  EXPRESS: Statement on imaging and pulmonary hypertension from the Pulmonary Vascular Research Institute (PVRI).

Authors:  David G Kiely; David Levin; Paul Hassoun; David D Ivy; Pei-Ni Jone; Jumaa Bwika; Steven M Kawut; Jim Lordan; Angela Lungu; Jeremy Mazurek; Shahin Moledina; Horst Olschewski; Andrew Peacock; Goverdhan Dutt Puri; Farbod Rahaghi; Michal Schafer; Mark Schiebler; Nicholas Screaton; Merryn Tawhai; Edwin Jr Van Beek; Anton Vonk-Noordegraaf; Rebecca R Vanderpool; John Wort; Lan Zhao; Jim Wild; Jens Vogel-Claussen; Andrew J Swift
Journal:  Pulm Circ       Date:  2019-03-18       Impact factor: 3.017

9.  Fast Virtual Fractional Flow Reserve Based Upon Steady-State Computational Fluid Dynamics Analysis: Results From the VIRTU-Fast Study.

Authors:  Paul D Morris; Daniel Alejandro Silva Soto; Jeroen F A Feher; Dan Rafiroiu; Angela Lungu; Susheel Varma; Patricia V Lawford; D Rodney Hose; Julian P Gunn
Journal:  JACC Basic Transl Sci       Date:  2017-08-28

10.  Diagnosis of Pulmonary Hypertension with Cardiac MRI: Derivation and Validation of Regression Models.

Authors:  Christopher S Johns; David G Kiely; Smitha Rajaram; Catherine Hill; Steven Thomas; Kavitasagary Karunasaagarar; Pankaj Garg; Neil Hamilton; Roshni Solanki; David A Capener; Charles Elliot; Ian Sabroe; Athanasios Charalamopopoulos; Robin Condliffe; James M Wild; Andrew J Swift
Journal:  Radiology       Date:  2018-10-23       Impact factor: 29.146

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