Real-time plaque characterization and visualization with spectral analysis of intravascular ultrasound data

Coronary artery disease is the number one cause of death in the United States and the Western world, and approximately 250,000 affected people die per year without ever being admitted to a hospital. One of the main reasons of such a high death-rate without any diagnosis is that more than 50 or heart-attacks) occur in patients with no prior history of known heart disease or symptoms. Coronary artery disease leads to the occlusion of arteries that are vital in providing nutrients to the heart muscles. The disease develops by progressive accumulation or formation of "plaque" within an artery. Certain types of plaques could occlude blood flow and yet might be "stable". These plaques usually have a high fibrous content, and are known as hard plaques. On the other hand, "unstable" or "soft" plaques might not cause much occlusion but could be vulnerable to rupture. Rupture of such plaques could lead to total or partial occlusion in arteries resulting in sudden cardiac death or heart-attack. In fact, 68 coronary arteries are less than 50.Intravascular ultrasound (IVUS) is a minimally invasive imaging modality that provides cross-section images of arteries in real-time, allowing visualization of atherosclerotic plaques in vivo. In standard IVUS gray-scale images, calcified regions of plaque and dense fibrous components generally reflect ultrasound energy well and thus appear bright and homogeneous on IVUS images. Conversely, regions of low echo reflectance in IVUS images are usually labeled "soft" or "mixed" plaque. However, this visual interpretation has been demonstrated to be very inconsistent in accurately determining plaque composition and does not allow real-time assessment of quantitative plaque constituents.Spectral analysis of the backscattered radiofrequency (RF) ultrasound signals allows detailed assessment of plaque composition. Advanced mathematical techniques can be employed to extract spectral information from these RF data to determine composition. The spectral content or signature of RF data reflected from tissue depends on density, compressibility, concentration, size, etc. A combination of spectral parameters were used to develop statistical classification schemes for analysis of in vivo IVUS data in real-time. The clinical data acquisition system is ECG gated and the analysis software developed by our group reconstructs IVUS gray-scale images from the acquired RF data. A combination of spectral parameters and active contour models is used for real-time 3D plaque segmentation followed by computation of color-coded tissue maps for each image cross-section and longitudinal views of the entire vessel. The "fly-through" mode allows one to visualize the complete length of the artery internally with the histology components at the lumen surface. In addition, vessel and plaque metrics such as areas and volumes of individual plaque components (collagen, fibro-lipid, calcium, lipid-core) are also available.