Intravascular Optical Coherence Tomography Data Research Articles

Human Coronary Plaque Optical Coherence Tomography Image Repairing, Multilayer Segmentation and Impact on Plaque Stress/Strain Calculations.

Coronary vessel layer structure may have a considerable impact on plaque stress/strain calculations. Most current plaque models use single-layer vessel structures due to the lack of available multilayer segmentation techniques. In this paper, an automatic multilayer segmentation and repair method was developed to segment coronary optical coherence tomography (OCT) images to obtain multilayer vessel geometries for biomechanical model construction. Intravascular OCT data were acquired from six patients (one male; mean age: 70.0) using a protocol approved by the local institutional review board with informed consent obtained. A total of 436 OCT slices were selected in this study. Manually segmented data were used as the gold standard for method development and validation. The edge detection method and cubic spline surface fitting were applied to detect and repair the internal elastic membrane (IEM), external elastic membrane (EEM) and adventitia-periadventitia interface (ADV). The mean errors of automatic contours compared to manually segmented contours were 1.40%, 4.34% and 6.97%, respectively. The single-layer mean plaque stress value from lumen was 117.91 kPa, 10.79% lower than that from three-layer models (132.33 kPa). On the adventitia, the single-layer mean plaque stress value was 50.46 kPa, 156.28% higher than that from three-layer models (19.74 kPa). The proposed segmentation technique may have wide applications in vulnerable plaque research.

Automatic classification of atherosclerotic plaques imaged with intravascular OCT.

Intravascular optical coherence tomography (IV-OCT) allows evaluation of atherosclerotic plaques; however, plaque characterization is performed by visual assessment and requires a trained expert for interpretation of the large data sets. Here, we present a novel computational method for automated IV-OCT plaque characterization. This method is based on the modeling of each A-line of an IV-OCT data set as a linear combination of a number of depth profiles. After estimating these depth profiles by means of an alternating least square optimization strategy, they are automatically classified to predefined tissue types based on their morphological characteristics. The performance of our proposed method was evaluated with IV-OCT scans of cadaveric human coronary arteries and corresponding tissue histopathology. Our results suggest that this methodology allows automated identification of fibrotic and lipid-containing plaques. Moreover, this novel computational method has the potential to enable high throughput atherosclerotic plaque characterization.

Heartbeat OCT: in vivo intravascular megahertz-optical coherence tomography.

Cardiac motion artifacts, non-uniform rotational distortion and undersampling affect the image quality and the diagnostic impact of intravascular optical coherence tomography (IV-OCT). In this study we demonstrate how these limitations of IV-OCT can be addressed by using an imaging system that we called "Heartbeat OCT", combining a fast Fourier Domain Mode Locked laser, fast pullback, and a micromotor actuated catheter, designed to examine a coronary vessel in less than one cardiac cycle. We acquired in vivo data sets of two coronary arteries in a porcine heart with both Heartbeat OCT, working at 2.88 MHz A-line rate, 4000 frames/s and 100 mm/s pullback speed, and with a commercial system. The in vivo results show that Heartbeat OCT provides faithfully rendered, motion-artifact free, fully sampled vessel wall architecture, unlike the conventional IV-OCT data. We present the Heartbeat OCT system in full technical detail and discuss the steps needed for clinical translation of the technology.

Automated tissue characterization of in vivo atherosclerotic plaques by intravascular optical coherence tomography images

Intravascular optical coherence tomography (IVOCT) is rapidly becoming the method of choice for the in vivo investigation of coronary artery disease. While IVOCT visualizes atherosclerotic plaques with a resolution <20µm, image analysis in terms of tissue composition is currently performed by a time-consuming manual procedure based on the qualitative interpretation of image features. We illustrate an algorithm for the automated and systematic characterization of IVOCT atherosclerotic tissue. The proposed method consists in a supervised classification of image pixels according to textural features combined with the estimated value of the optical attenuation coefficient. IVOCT images of 64 plaques, from 49 in vivo IVOCT data sets, constituted the algorithm’s training and testing data sets. Validation was obtained by comparing automated analysis results to the manual assessment of atherosclerotic plaques. An overall pixel-wise accuracy of 81.5% with a classification feasibility of 76.5% and per-class accuracy of 89.5%, 72.1% and 79.5% for fibrotic, calcified and lipid-rich tissue respectively, was found. Moreover, measured optical properties were in agreement with previous results reported in literature. As such, an algorithm for automated tissue characterization was developed and validated using in vivo human data, suggesting that it can be applied to clinical IVOCT data. This might be an important step towards the integration of IVOCT in cardiovascular research and routine clinical practice.

Consensus Standards for Acquisition, Measurement, and Reporting of Intravascular Optical Coherence Tomography Studies: A Report From the International Working Group for Intravascular Optical Coherence Tomography Standardization and Validation

The purpose of this document is to make the output of the International Working Group for Intravascular Optical Coherence Tomography (IWG-IVOCT) Standardization and Validation available to medical and scientific communities, through a peer-reviewed publication, in the interest of improving the diagnosis and treatment of patients with atherosclerosis, including coronary artery disease. Intravascular optical coherence tomography (IVOCT) is a catheter-based modality that acquires images at a resolution of ~10 μm, enabling visualization of blood vessel wall microstructure in vivo at an unprecedented level of detail. IVOCT devices are now commercially available worldwide, there is an active user base, and the interest in using this technology is growing. Incorporation of IVOCT in research and daily clinical practice can be facilitated by the development of uniform terminology and consensus-based standards on use of the technology, interpretation of the images, and reporting of IVOCT results. The IWG-IVOCT, comprising more than 260 academic and industry members from Asia, Europe, and the United States, formed in 2008 and convened on the topic of IVOCT standardization through a series of 9 national and international meetings. Knowledge and recommendations from this group on key areas within the IVOCT field were assembled to generate this consensus document, authored by the Writing Committee, composed of academicians who have participated in meetings and/or writing of the text. This document may be broadly used as a standard reference regarding the current state of the IVOCT imaging modality, intended for researchers and clinicians who use IVOCT and analyze IVOCT data.