Methods

The design, major inclusion and exclusion criteria, end points, and definitions of the PROSPECT study have been described in detail. In brief, 697 patients with ACS underwent grayscale and VH-IVUS examination of the proximal 6 to 8 cm of the all 3 major epicardial coronary vessels after successful percutaneous coronary intervention of all lesions responsible for ACS events and any other planned interventions. Imaging was performed with a synthetic aperture array, 20-MHz, 3.2 Fr catheter (Eagle Eye; Volcano Corporation, Rancho Cordova, California) and motorized catheter pullback (0.5 mm/s). The study was approved by the institutional review board at each participating center, and all patients gave written informed consent.

All baseline angiograms and IVUS images were prospectively analyzed at independent core laboratories (Cardiovascular Research Foundation, New York, New York) without knowledge of future events.

Angiographic quantitative and qualitative coronary angiography measures were performed using proprietary methodology modified from standard CMS software (version 7.0; Medis, Leiden, The Netherlands). Analyses included the major epicardial coronary arteries and all side branches >1.5 mm in diameter.

As described previously, IVUS and VH-IVUS analyses were conducted using QCU-CMS software (Medis) for contouring, pcVH 2.1 software (Volcano Corporation) for contouring and data output, and proprietary software (qVH; Cardiovascular Research Foundation) for segmental qualitative and quantitative output. An IVUS nonculprit lesion was defined as plaque burden (PB) ≥40% involving ≥3 consecutive frames. Lesions were considered separate if there was a ≥5-mm-long segment with <40% PB between them. For every nonculprit lesion, the external elastic membrane (EEM) and lumen borders were detected at ∼0.4-mm intervals and used to determine the EEM, lumen, and plaque + media (EEM minus lumen) cross-sectional area (CSA) and volumes. The slice with the minimal lumen area (MLA) within each nonculprit lesion was identified and assessed. All nonculprit lesions were summed to generate the patient-level IVUS calculation of percent atheroma volume (PAV) :

A plaque rupture was defined as an intraplaque cavity that communicated with the lumen with an overlying residual fibrous cap fragment. Echolucent plaque contained an intraplaque zone of absent or low echogenicity surrounded by tissue of greater echodensity.

VH-IVUS plaque components were color coded as dense calcium (white), necrotic core (red), fibrofatty (light green), or fibrous tissue (dark green) and reported as percentages of total plaque volumes. Each lesion was further classified by VH-IVUS phenotype as previously reported. A fibroatheroma had >10% confluent necrotic core. If >30° of the necrotic core abutted the lumen in ≥3 consecutive frames, the fibroatheroma was classified as thin-cap fibroatheroma (VH-TCFA). All volumes were calculated using Simpson’s rule.

The primary end point of the PROSPECT study was nonculprit lesion-related major adverse cardiac events (MACE): the composite of death from cardiac causes, cardiac arrest, myocardial infarction (MI), or rehospitalization because of unstable or progressive angina according to the Braunwald Unstable Angina Classification and the Canadian Cardiovascular Society Angina Classification. Cardiac death was defined as death due to immediate cardiac cause and included unwitnessed death and death of unknown cause. An independent clinical events committee adjudicated all clinical events occurring during follow-up as because of recurrence at the original treated segments (“culprit” lesion), at a previously untreated coronary segments (“nonculprit” lesions), or at an undetermined segment location (“indeterminate” lesion) if follow-up angiography was not performed.

Categorical variables were presented as number (%) and compared by the chi-square statistics or Fisher’s exact test (if there was an expected cell value <5). Continuous variables were reported as median with interquartile range and compared by Wilcoxon rank-sum tests. A multivariable linear regression analysis was conducted to identify independent predictors for PAV. Univariable predictors of PAV with p values <0.2 were entered into the multivariable model. Independent predictors and their regression coefficients were calculated. Outcomes were summarized as Kaplan-Meier percentages and numbers of events and compared using the log-rank tests. Multivariable Cox regression models were used to determine the independent predictor of MACE. The following variables were considered for the multivariable model using stepwise selection: age, male gender, total nonculprit lesion length, history of cardiac intervention, insulin-dependent diabetes, PAV, necrotic core volume, patients with ≥1 lesions with MLA ≤4 mm ² , and those with ≥1 VH-TCFAs. The discriminatory capability of the PAV to identify patients who had cumulative 3-year events was assessed using the area under the receiver-operating characteristics curve. All statistical analyses were performed using SAS, version 9.2 (SAS Institute Inc., Cary, North Carolina). A p value <0.05 was considered to indicate statistical significance.

Results

Overall, 660 patients and 3,229 nonculprit lesions with complete grayscale IVUS data were identified and included in this study. Of these, 609 patients with 2,874 lesions had complete 3-vessel VH-IVUS data. The median PAV of the total cohort of 660 patients was 49.2% (interquartile range 46.7% to 52.1%).

We divided the study patients into tertiles according to their baseline PAV: low tertile, PAV <47.7% (n = 220); intermediate tertile 47.7% to <50.9% (n = 220); and high tertile ≥50.9% (n = 220). The baseline characteristics of the subjects are listed in Table 1 . The highest PAV tertile group patients were likely to be older (56.9 years [50.2, 65.2] vs 57.7 years [50.0, 67.5] vs 60.4 years [52.5, 67.9], low vs intermediate vs high tertiles, p = 0.052) and more likely to have had previous cardiac intervention (7.7% vs 9.1% vs 15.5%, p = 0.02). The profiles of plasma glucose and lipids and the prevalence of cardiovascular risk factors, such as diabetes mellitus, hypertension, hypercholesterolemia, and current smoking, did not differ among these tertiles. Clinical presentations and Framingham risk scores were also similar. As listed in Table 2 , by multivariable linear analysis, male gender (p = 0.046), patient age (p = 0.0006), and a history of previous cardiac intervention (p = 0.004) were independently associated with baseline PAV.

Table 2

Univariable and multivariable linear regression analysis for predictors of percent atheroma volume

Variable	Univariable		Multivariable
	β Coefficient (95% Confidence Interval)	p Value	β Coefficient (95% Confidence Interval)	p Value
Men	0.52 (-0.25–1.28)	0.19	0.79 (0.01–1.56)	0.046
Age	0.05 (0.02–0.08)	0.0007	0.05 (0.02–0.08)	0.0006
Prior cardiac intervention	1.74 (0.71–2.77)	0.001	1.51 (0.48–2.54)	0.004
Insulin-dependent diabetes	0.81 (-1.17–2.78)	0.43
Hypercholesterolemia	0.73 (0.05–1.41)	0.04
Hypertension	0.43 (-0.23–1.08)	0.20
High density lipoprotein	0.01 (-0.02–0.03)	0.63
Body mass index	-0.06 (-0.12–0.003)	0.04
Metabolic syndrome	0.51 (-0.15–1.17)	0.13

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