Microsphere flow quantification and bias detection with a porcine coronary model
Cardiovascular disease (CVD) is the single largest cause of death in the world, accounting for nearly 30% of mortalities each year. Coronary artery disease (CAD) constitutes the largest category of CVD, and includes diseases caused by plaque formation in the coronary arteries resulting in a range of...
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ndltd-bl.uk-oai-ethos.bl.uk-6771472017-07-25T03:29:48ZMicrosphere flow quantification and bias detection with a porcine coronary modelSinclair, Matthew David MauriceSmith, Nicolas Peter ; Schaeffter, Tobias Richard ; Lee, Chul Joo2015Cardiovascular disease (CVD) is the single largest cause of death in the world, accounting for nearly 30% of mortalities each year. Coronary artery disease (CAD) constitutes the largest category of CVD, and includes diseases caused by plaque formation in the coronary arteries resulting in a range of pathologies including coronary stenosis, ischemia, hibernating myocardium, infarct and heart failure. Clinical dynamic contrast enhanced (DCE) MRI is an emerging non-invasive method for assessing the extent and severity of perfusion defects in the heart. Recently algorithms have been used to quantify myocardial blood flow (MBF) from excised porcine Langendorff hearts under normal flow, low flow, and stress conditions, with validation provided by the microsphere deposition technique. Microspheres of 15 micron diameter deposited within the myocardium were imaged with a fluorescent episcopic cryomicrotome after DCE-MRI acquisition, providing high-resolution images of the heart which were spatially co-registered to the MRI images. Previous validation studies involved physically sectioning hearts into segments for comparison to DCE-MRI. The presented method provided direct correspondence and hence higher accuracy of tissue segments used for the comparative calculation of MBF from DCE-MRI and microspheres. Results of the validation study in 8 pig hearts showed strong correlations at both 1.5T (n = 4) and 3T (n = 4) field strengths, and under all of the experimental flow conditions. A question which has previously arisen regarding the distribution of microspheres in the coronary arterial circulation has been whether they undergo phase separation. Previous to this study geometric information of the coronary arterial structure has not been available for comparison to the distribution of microspheres to determine if this phenomenon plays a role in the observed bias of microspheres relative to a molecular tracer, IDMI. A Poiseuille flow model with an outlet flow boundary condition dependent on perfused tissue mass has been used to simulate flow distribution in a porcine coronary arterial network. The network reconstructed from cryomicrotome imaging data consisted of approximately 105 arterial and arteriolar vessel segments, with a minimum vessel diameter of 0.13mm. A novel analysis using confidence intervals of a binomial distribution at every vascular bifurcation was used to determine the presence of phase separation in the coronary arteries and large arterioles, and to identify the most prevalent locations of phase separation within the network. It is known that phase separation of red blood cells and microspheres occurs in vessels of a diameter similar to that of the particles, namely the small arterioles and capillaries. Results revealed that microsphere phase separation was most prevalent at bifurcations in the conduit coronary arteries, where branching asymmetry was highest. Phase separation prevalence was reduced at arteriolar bifurcations, where branching asymmetry was lower. This is the first study relating coronary arterial geometry with microsphere distributions and serves as an explanation for previously observed microsphere distribution bias in tissue regions of high flow. In future this bias may be corrected using a suitable model, but further work needs to be done to ascertain more accurate terminal vessel boundary conditions.616.1King's College London (University of London)http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.677147http://kclpure.kcl.ac.uk/portal/en/theses/microsphere-flow-quantification-and-bias-detection-with-a-porcine-coronary-model(cd2412bd-3e69-4e70-abc5-ba503fe4af10).htmlElectronic Thesis or Dissertation |
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616.1 Sinclair, Matthew David Maurice Microsphere flow quantification and bias detection with a porcine coronary model |
description |
Cardiovascular disease (CVD) is the single largest cause of death in the world, accounting for nearly 30% of mortalities each year. Coronary artery disease (CAD) constitutes the largest category of CVD, and includes diseases caused by plaque formation in the coronary arteries resulting in a range of pathologies including coronary stenosis, ischemia, hibernating myocardium, infarct and heart failure. Clinical dynamic contrast enhanced (DCE) MRI is an emerging non-invasive method for assessing the extent and severity of perfusion defects in the heart. Recently algorithms have been used to quantify myocardial blood flow (MBF) from excised porcine Langendorff hearts under normal flow, low flow, and stress conditions, with validation provided by the microsphere deposition technique. Microspheres of 15 micron diameter deposited within the myocardium were imaged with a fluorescent episcopic cryomicrotome after DCE-MRI acquisition, providing high-resolution images of the heart which were spatially co-registered to the MRI images. Previous validation studies involved physically sectioning hearts into segments for comparison to DCE-MRI. The presented method provided direct correspondence and hence higher accuracy of tissue segments used for the comparative calculation of MBF from DCE-MRI and microspheres. Results of the validation study in 8 pig hearts showed strong correlations at both 1.5T (n = 4) and 3T (n = 4) field strengths, and under all of the experimental flow conditions. A question which has previously arisen regarding the distribution of microspheres in the coronary arterial circulation has been whether they undergo phase separation. Previous to this study geometric information of the coronary arterial structure has not been available for comparison to the distribution of microspheres to determine if this phenomenon plays a role in the observed bias of microspheres relative to a molecular tracer, IDMI. A Poiseuille flow model with an outlet flow boundary condition dependent on perfused tissue mass has been used to simulate flow distribution in a porcine coronary arterial network. The network reconstructed from cryomicrotome imaging data consisted of approximately 105 arterial and arteriolar vessel segments, with a minimum vessel diameter of 0.13mm. A novel analysis using confidence intervals of a binomial distribution at every vascular bifurcation was used to determine the presence of phase separation in the coronary arteries and large arterioles, and to identify the most prevalent locations of phase separation within the network. It is known that phase separation of red blood cells and microspheres occurs in vessels of a diameter similar to that of the particles, namely the small arterioles and capillaries. Results revealed that microsphere phase separation was most prevalent at bifurcations in the conduit coronary arteries, where branching asymmetry was highest. Phase separation prevalence was reduced at arteriolar bifurcations, where branching asymmetry was lower. This is the first study relating coronary arterial geometry with microsphere distributions and serves as an explanation for previously observed microsphere distribution bias in tissue regions of high flow. In future this bias may be corrected using a suitable model, but further work needs to be done to ascertain more accurate terminal vessel boundary conditions. |
author2 |
Smith, Nicolas Peter ; Schaeffter, Tobias Richard ; Lee, Chul Joo |
author_facet |
Smith, Nicolas Peter ; Schaeffter, Tobias Richard ; Lee, Chul Joo Sinclair, Matthew David Maurice |
author |
Sinclair, Matthew David Maurice |
author_sort |
Sinclair, Matthew David Maurice |
title |
Microsphere flow quantification and bias detection with a porcine coronary model |
title_short |
Microsphere flow quantification and bias detection with a porcine coronary model |
title_full |
Microsphere flow quantification and bias detection with a porcine coronary model |
title_fullStr |
Microsphere flow quantification and bias detection with a porcine coronary model |
title_full_unstemmed |
Microsphere flow quantification and bias detection with a porcine coronary model |
title_sort |
microsphere flow quantification and bias detection with a porcine coronary model |
publisher |
King's College London (University of London) |
publishDate |
2015 |
url |
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.677147 |
work_keys_str_mv |
AT sinclairmatthewdavidmaurice microsphereflowquantificationandbiasdetectionwithaporcinecoronarymodel |
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