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The early identification of susceptibility to adverse cardiovascular outcomes and risk stratification amongst asymptomatic individuals, as well as amongst those with overt disease continues to be one of the major priorities of clinically-orientated research in the field of atherothrombosis (Dotsenko et al., 2008). Conventional cardiovascular risk assessment is based on traditional risk factors such as serum cholesterol concentrations, blood pressure levels, smoking, and diabetes mellitus. However, available data from epidemiological studies indicate that these classic risk factors do not fully explain the distribution of risk in the general population. On the other hand, classic risk scores may provide variable results in different people groups (Blankenberg et al., 2010). Besides, coronary artery disease often occurs in the absence of traditional risk factors (Yilmaz et al., 2007). Therefore, it is becoming increasingly clear that the newer laboratory measures may be useful to refine risk estimates in the general population. The pressing need for the development and clinical implementation of new markers of atherothrombotic disease has fuelled rapidly expanding research into cardiac biomarkers (Dotsenko et al., 2008; Le & Wilson, 2010) . Cardiovascular biomarkers have the potential to augment clinical risk stratification by aiding in screening, diagnosis and assessment of prognosis. However, most current biomarkers have only modest predictive value, and there is a need to identify additional biomarkers from new biological pathways (May & Wang, 2008). Biomarker research is actively developing new testing strategies trying to improve upon current approaches, but it is often unclear how to assess the incremental prognostic information that a new test provides (Wood & Greenland, 2009). Some individual biomarkers such as C-reactive protein (CRP) have demonstrated consistent associations with incident cardiovascular events across multiple studies, but the magnitude of these associations is modest, and only small improvements in discrimination and reclassification are seen. One attractive solution to the limitations of individual biomarkers is to combine nonredundant biomarkers into panels to enhance risk assessment. However, results of studies testing multiple biomarkers for risk prediction in primary prevention populations have not provided a clear picture, with some studies showing qualified promise and others suggesting limited value (de Lemos & Rohatgi, 2010). This chapter provides an overview of the way of biomarker

New Noninvasive Modalities in Coronary Angiography - Diagnostic Values of New Biomarkers for Cardiovascular Disease