Journal
IEEE TRANSACTIONS ON MEDICAL IMAGING
Volume 32, Issue 11, Pages 1989-1996Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMI.2013.2269275
Keywords
Arteriosclerosis; biomechanics; cardiology; catheterization; image co-registration; image processing
Categories
Funding
- American Heart Association Postdoctoral Fellowship
- Graduate Research Fellowship from the National Science Foundation
- Pfizer Pharmaceuticals
- Volcano Corp.
- Wallace H. Coulter Translation Grant Program
- Toshiba America Medical Systems
- Toshiba America Medical Systems, Inc.
- Georgia Research Alliance
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Considerable efforts have been directed at identifying prognostic markers for rapidly progressing coronary atherosclerotic lesions that may advance into a high-risk (vulnerable) state. Intravascular ultrasound (IVUS) has become a valuable clinical tool to study the natural history of coronary artery disease (CAD). While prospectively IVUS studies have provided tremendous insight on CAD progression, and its association with independent markers (e. g., wall shear stress), they are limited by the inability to examine the focal association between spatially heterogeneous variables (in both circumferential and axial directions). Herein, we present a framework to automatically co-register longitudinal (in-time) virtual histology-intravascular ultrasound (VH-IVUS) imaging data in the circumferential direction (i.e., rotate follow-up image so circumferential basis coincides with corresponding baseline image). Multivariate normalized cross correlation was performed on paired images (n = 636) from five patients using three independent VH-IVUS defined parameters: artery thickness, VH-IVUS defined plaque constituents, and VH-IVUS perivascular imaging data. Results exhibited high correlation between co-registration rotation angles determined automatically versus manually by an expert reader (r(2) = 0.90). Furthermore, no significant difference between automatic and manual co-registration angles was observed (91.31 +/- 1.04 degrees and 91.07 +/- 1.04 degrees, respectively;) p = 0.48 and Bland-Altman analysis yielded excellent agreement (bias = 0.24 degrees, 95% CI +/ - 16.33 degrees). In conclusion, we have developed, verified, and validated an algorithm that automatically co-registers VH-IVUS imaging data that will allow for the focal examination of CAD progression.
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