Received March 25, 2009; accepted August 4, 2009. This review updates the role of various intravascular imaging techniques (1) in the detection of vulnerable plaque and (2) during percutaneous coronary intervention (PCI), especially drug-eluting stent (DES) implantation and follow-up—including intravascular ultrasound (IVUS), virtual histology (VH-IVUS) and integrated backscatter (IB-IVUS), optical coherent tomography (OCT), near-infrared (NIR) spectroscopy, angioscopy, and MRI. ### IVUS, IB-IVUS, and VH-IVUS The current intracoronary ultrasound imaging frequency range of 20 to 45 MHz provides 70 to 200 μm axial resolution with >5 mm penetration.1,2 Grayscale IVUS allows robust quantitative measurements including lumen, vessel, and plaque area; qualitative assessment of lesions preintervention; and quantitative assessment and complications of lesions postintervention; however, it has poor sensitivity for detecting lipid-rich plaque (67%).3 High-frequency IVUS transducers can produce better resolution that should also improve plaque characterization but at the trade off of greater ultrasound reflection from blood. Blood speckle with >40 MHz ultrasound can cause confusion when identifying the lumen-tissue border, detecting in-stent neointimal tissue, etc; but it is easily solved by saline (negative contrast) injection through the guiding catheter.4 Standard grayscale IVUS is limited, in part, because it uses only reflected ultrasound amplitude to formulate the image and requires significant postprocessing. In an effort to improve on the qualitative assessment of the reflected ultrasound signal, Kawasaki et al developed a plaque characterization algorithm called IB-IVUS using time domain information directly from the radiofrequency signal. This process has resulted in improved plaque characterization with a reported in vitro sensitivity of 90% and specificity or 92% for lipid-rich plaque.5,6 In a similar effort to improve plaque characterization, spectral analysis (VH-IVUS) combined frequency and amplitude analysis and used an algorithm developed from known tissue types to detect fibrous plaque, fibrofatty plaque, necrotic core (NC), and dense calcium (Figure 1A′, 1B′). Reported sensitivity and …