Myocardial perfusion imaging is great for assessing the consequence of disrupted blood supply, since it shows how much blood is actually being delievered to different parts of the heart muscle rather than simply looking at the large vessel lesions. Magnetic resonance perfusion imaging (MRPI) is particularly promising due to its superior resolution and a lack of radiation exposure, compared to nuclear imaging.
On the other hand, because MRPI doesn't show individual blood vessels, clinicians face a practical problem when reduced blood flow is detected -- which vessel should be treated?
Previous work on matching the vessels to perfusion territory has shown that the standard 17-segment cannot always be reliably identified with the culprit artery. Below diagram (from Ortiz-Perez et al. 2008) shows the specificity of MR-derived segmental association with the infarct-related artery. Most of the segments could be uniquely attributed.
Other investigators attempted to estimate the perfused mycardial territories directly from detailed vascular images. The example below (Le et al. 2008) used an ex vivo imaging data to divide the myocardium into territories based on their nearness to the neighbouring vessel.
In order to extend these efforts to clinical practice, more work is necessary. In addition, the coronary network used in the second study is more detailed than the typical resolution achievable in patients (note the picture above does not show the full detail of the vasculature), introducing further challenges to clinical translation.
"What is the project plan?"
With the type of data used in the second study, one could design and test an algorithm to define 3D perfusion territories with high accuracy. A key question currently is whether the clinical angiographic images offer enough details to determine the territories reliably -- these objectives will be tackled in the current project, using a high-resolution reconstruction of pig hearts. The project will aim to
i) develop a 'forward' algorithm for assigning each point in myocardium with the feeding vessel. Unlike previous work, this method will use more information than the mere distance, possibly incorporating hemodynamic principles, and
ii) an 'inverse' method will be investigated that, given a perfusion image, will identify the supplying vessel
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