We sought to assess the incremental prognostic value of quantitative plaque characterization beyond established CT risk scores.Several plaque characteristics detectable by coronary computed tomographic angiography (coronary CTA) are thought to be indicative of vulnerable plaques and subsequent cardiac events, particularly low attenuation plaque volume (LAPV), positive remodeling and the napkin-ring sign which is high density vascular adhesion with a small center of low density. It is unknown how quantitative plaque assessment can contribute to the long-term prediction of cardiovascular events in relation to established CT risk scores such as the calcium score or Segment Stenosis Score (SSS).In 1168 consecutive patients with suspected coronary artery disease (CAD), calcium score measurement and coronary plaque characterization was performed comprising the presence of calcified, non-calcified, and partially calcified plaques on a per-segment basis. In all non-calcified or partially calcified plaques, semi-automated plaque analysis was performed to quantify low attenuation plaque volume (density <30 HU), total non-calcified plaque volume (<150 HU, TNCPV) and remodeling index. The presence of the napkin-ring sign was assessed visually. The study endpoint was the occurrence of major adverse cardiac events (MACE), a composite of cardiac death, myocardial infarction and coronary revascularization more than 90 days after coronary CTA.During a clinical follow up of 5.7 years, MACE was observed in 46 patients (3.9%). All plaque characteristics were associated with MACE. The strongest association was observed for LAPV (HR 1.12, p < 0.0001). LAPV showed incremental prognostic value in a stepwise multivariable model including the Morise Score for clinical risk, calcium score and SSS (p = 0.036).LAPV, TPV, PR and presence of the napkin-ring sign are predictors of MACE independently of clinical risk presentation. LAPV carries slight additional prognostic information beyond the calcium score and conventional coronary CTA analysis. It may therefore improve risk prediction after CT imaging.