Pulmonary Vascular Disease Unit

Sheffield, United Kingdom

Pulmonary Vascular Disease Unit

Sheffield, United Kingdom

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Lungu A.,University of Sheffield | Wild J.,University of Sheffield | Swift A.,University of Sheffield | Capener D.,University of Sheffield | And 2 more authors.
IFMBE Proceedings | Year: 2014

Pulmonary hypertension (PH), a disease with a high mortality rate, is currently diagnosed by invasive right heart catheterization (RHC). Quantification of wave reflections can offer information about the status of the pulmonary circulation in health and disease, and can be achieved by simultaneous measurement of flow and pressure at the same anatomical site. In practice such measurements are obtained using different acquisition techniques which needs to be synchronized in order to satisfy the simultaneity criterion. We hypothesis that combining the advantages of mathematical modelling with non-invasive Magnetic Resonance Imaging (MRI) measurements of flow and anatomy could offer totally non-invasive modalities for characterizing PH. Our preliminary work was focused on the development of automatic tools to determine accurately flow Q(t) and area A(t) measurements directly from MRI DICOM images, ultimately to support a novel characterisation protocol although the latter is beyond the scope of this paper. © 2014, Springer International Publishing Switzerland.


Lungu A.,University of Sheffield | Wild J.M.,University of Sheffield | Capener D.,University of Sheffield | Kiely D.G.,Pulmonary Vascular Disease Unit | And 2 more authors.
Journal of Biomechanics | Year: 2014

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. © 2014 The Authors.


PubMed | University of Sheffield and Pulmonary Vascular Disease Unit
Type: Journal Article | Journal: Journal of biomechanics | Year: 2014

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.

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