Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: 3D Fusion between Fluoroscopy Angiograms and SPECT Myocardial Perfusion
  Images to Guide Percutaneous Coronary Intervention   Background. Percutaneous coronary intervention(PCI) in stable coronary artery
disease(CAD) is commonly triggered by abnormal myocardial perfusion
imaging(MPI). However, due to the possibilities of multivessel disease and
variability of coronary artery perfusion distribution, opportunity exists to
better align anatomic stenosis with perfusion abnormalities to improve
revascularization decisions. This study aims to develop a 3D multi-modality
fusion approach to assist decision-making for PCI. Methods. Coronary arteries
from fluoroscopic angiography(FA) were reconstructed into 3D artery anatomy.
Left ventricular(LV) epicardial surface was extracted from SPECT. The 3D artery
anatomy was non-rigidly fused with the LV epicardial surface. The accuracy of
the 3D fusion was evaluated via both computer simulation and real patient data.
For technical validation, simulated FA and MPI were integrated and then
compared with the ground truth from a digital phantom. For clinical validation,
FA and SPECT images were integrated and then compared with the ground truth
from CT angiograms. Results. In the technical evaluation, the distance-based
mismatch error between simulated fluoroscopy and phantom arteries is
1.86(SD:1.43)mm for left coronary arteries(LCA) and 2.21(SD:2.50)mm for right
coronary arteries(RCA). In the clinical validation, the distance-based mismatch
errors between the fluoroscopy and CT arteries were 3.84(SD:3.15)mm for LCA and
5.55(SD:3.64)mm for RCA. The presence of the corresponding fluoroscopy and CT
arteries in the AHA 17-segment model agreed well with a Kappa value of 0.91(95%
CI: 0.89-0.93) for LCA and 0.80(CI: 0.67-0.92) for RCA. Conclusions. Our fusion
approach is technically accurate to assist PCI decision-making and is
clinically feasible to be used in the catheterization laboratory. There is an
opportunity to improve the decision-making and outcomes of PCI in stable CAD.

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The categories of this paper are: q-bio
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The categories of this paper are: chem-ph
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The categories of this paper are: hep-ex
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The categories of this paper are: adap-org
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The categories of this paper are: astro-ph
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The categories of this paper are: stat
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The categories of this paper are: bayes-an
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The categories of this paper are: quant-ph
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The categories of this paper are: alg-geom
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The categories of this paper are: q-alg
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The categories of this paper are: dg-ga
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The categories of this paper are: nucl-ex
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The categories of this paper are: funct-an
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The categories of this paper are: chao-dyn
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The categories of this paper are: q-fin
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The categories of this paper are: cs