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01.06.2015 | Original Article | Ausgabe 6/2015 Open Access

International Journal of Computer Assisted Radiology and Surgery 6/2015

PCA-derived respiratory motion surrogates from X-ray angiograms for percutaneous coronary interventions

Zeitschrift:
International Journal of Computer Assisted Radiology and Surgery > Ausgabe 6/2015
Autoren:
Hua Ma, Gerardo Dibildox, Carl Schultz, Evelyn Regar, Theo van Walsum
Wichtige Hinweise

Conflict of Interest

Hua Ma, Gerardo Dibildox, Carl Schultz, Evelyn Regar and Theo van Walsum declare that they have no conflict of interest.

Ethical standards

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

Informed consent

For a retrospective study of anonymized image data, informed consent is not required.

Abstract

Purpose

Intraoperative coronary motion modeling with motion surrogates enables prospective motion prediction in X-ray angiograms (XA) for percutaneous coronary interventions. The motion of coronary arteries is mainly affected by patients breathing and heartbeat. Purpose of our work is therefore to extract coronary motion surrogates that are related to respiratory and cardiac motion. In particular, we focus on respiratory motion surrogates extraction in this paper.

Methods

We propose a fast automatic method for extracting patient-specific respiratory motion surrogate from cardiac XA. The method starts with an image preprocessing step to remove all tubular and curvilinear structures from XA images, such as vessels and guiding catheters, followed by principal component analysis on pixel intensities. The respiratory motion surrogate of an XA image is then obtained by projecting its vessel-removed image onto the first principal component.

Results

This breathing motion surrogate was demonstrated to get high correlation with ground truth diaphragm motion (correlation coefficient over 0.9 on average). In comparison with other related methods, the method we developed did not show significant difference (\(p>0.05\)), but did improve robustness and run faster on monoplane and biplane data in retrospective and prospective scenarios.

Conclusions

we developed and evaluated a method in extraction of respiratory motion surrogate from interventional X-ray images that is easy to implement and runs in real time and thus allows extracting respiratory motion surrogates during interventions.

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