Abstract

Aims

To evaluate the diagnostic power of integrating the results of computed tomography angiography (CTA) and CT myocardial perfusion (CTP) to identify coronary artery disease (CAD) defined as a flow limiting coronary artery stenosis causing a perfusion defect by single photon emission computed tomography (SPECT).

Methods and results

We conducted a multicentre study to evaluate the accuracy of integrated CTA–CTP for the identification of patients with flow-limiting CAD defined by ≥50% stenosis by invasive coronary angiography (ICA) with a corresponding perfusion deficit on stress single photon emission computed tomography (SPECT/MPI). Sixteen centres enroled 381 patients who underwent combined CTA–CTP and SPECT/MPI prior to conventional coronary angiography. All four image modalities were analysed in blinded independent core laboratories. The prevalence of obstructive CAD defined by combined ICA–SPECT/MPI and ICA alone was 38 and 59%, respectively. The patient-based diagnostic accuracy defined by the area under the receiver operating characteristic curve (AUC) of integrated CTA–CTP for detecting or excluding flow-limiting CAD was 0.87 [95% confidence interval (CI): 0.84–0.91]. In patients without prior myocardial infarction, the AUC was 0.90 (95% CI: 0.87–0.94) and in patients without prior CAD the AUC for combined CTA–CTP was 0.93 (95% CI: 0.89–0.97). For the combination of a CTA stenosis ≥50% stenosis and a CTP perfusion deficit, the sensitivity, specificity, positive predictive, and negative predicative values (95% CI) were 80% (72–86), 74% (68–80), 65% (58–72), and 86% (80–90), respectively. For flow-limiting disease defined by ICA-SPECT/MPI, the accuracy of CTA was significantly increased by the addition of CTP at both the patient and vessel levels.

Conclusions

The combination of CTA and perfusion correctly identifies patients with flow limiting CAD defined as ≥50 stenosis by ICA causing a perfusion defect by SPECT/MPI.

Introduction

Coronary artery disease (CAD) is the leading cause of morbidity and mortality worldwide.1 The treatment of CAD has changed significantly in the last two decades. The development of drug-eluting stents2 initially increased the number of revascularization procedures and fostered a relative overreliance on coronary stenosis. However, recent trials3,4 have demonstrated that both anatomical and functional significance are crucial to clinical outcomes for symptomatic CAD patients considered for revascularization. Coronary computed tomography angiography (CTA) has high sensitivity and excellent negative predictive value (NPV) to exclude significant coronary stenosis in patients with chest pain and suspected CAD.5–7 Appropriateness criteria have thus recommended CTA for symptomatic patients with intermediate and low pretest probability of CAD.8

Both invasive coronary angiography (ICA) and CTA provide morphologic data but inherently lack the physiologic information needed to determine haemodynamic significance, provided either by catheter-based fractional flow reserve (FFR),4 or non-invasive methods such as single photon emission tomography/myocardial perfusion imaging (SPECT/MPI), positron emission tomography (PET), or magnetic resonance imaging (MRI).3,9–11 The rationale for the use of a single modality test combining anatomy and physiology also includes the need to conserve resources and reduce variation in clinical imaging algorithms.12,13

In this regard, results from experimental and single centre clinical myocardial CT perfusion (CTP) studies14–17 have stimulated enthusiasm for a multicentre, international study using centralized, blinded analyses to determine the diagnostic accuracy of combined CTA and CTP in comparison with other non-invasive methods in current clinical use. Therefore, the purpose of this study was to test the hypothesis that a combined, non-invasive CTA/CTP strategy could reliably identify or exclude flow limiting coronary stenoses in patients with suspected CAD using the composite reference standard of ICA plus SPECT/MPI.

Methods

Patient population

The Coronary Artery Evaluation using 320-row Multidetector Computed Tomography Angiography and Myocardial Perfusion (CORE320) study is a prospective, diagnostic study performed at 16 centres in 8 countries (www.clinicaltrials.gov, NCT00934037). Adverse events were tracked, reported, and reviewed by an independent data safety and monitoring board. All centres received study approval by their local institutional review board, and all patients gave written informed consent.

The CORE320 study design has been previously published.18 Patients between 45 and 85 years of age with suspected or known CAD and clinically referred for ICA were eligible for enrolment. Exclusion criteria were: known allergy to iodinated contrast media, elevated serum creatinine (>1.5 mg/dL) or calculated creatinine clearance of <60 mL/min, atrial fibrillation, second or third degree atrio-ventricular block, previous cardiac surgery, coronary intervention within the past 6 months, evidence of acute coronary syndrome with thrombolysis, myocardial infarction risk score ≥5 or elevated cardiac enzymes in the past 72 h, high radiation exposure (≥5.0 rems) in the 18 months before consent, and body mass index >40 m/kg2 among others.18 Women of child-bearing potential had a negative pregnancy test within 24 h preceding CT. The study enrolled and analysed all patients regardless of calcium score and presence of stents.

The study design included coronary CTA, adenosine stress CTP, SPECT/MPI, and ICA (Figure 1), complete clinical history, and physical examination.

Figure 1

A complete CORE320 imaging data set for a 64-year-old male without prior history of coronary artery disease with chest pain symptoms. The left anterior descending coronary artery revealed a 96% diameter stenosis by computed tomography angiography (CTA) (Row A) and an 85% diameter stenosis by invasive coronary angiography (ICA) (Row B). The computed tomography myocardial perfusion (CTP) (Row C) study revealed a mild defect in the distal anteroseptal wall, and moderate defects in the basal anteroseptal, the basal anterior, the distal anterior, and apical walls, while the single photon emission computed tomography (SPECT) (Row D) study revealed moderate defects in the distal anterior, the distal anteroseptal, the basal anteroseptal and apical walls. The left circumflex artery revealed an 87% diameter stenosis by CTA, a 79% diameter stenosis by ICA, mild defects in the distal inferoseptal and distal inferolateral walls, and moderate defects in the distal anterolateral and distal anterior walls by CTP, and a moderate defect in the distal anterior wall by SPECT. The right coronary artery revealed a 60% diameter stenosis by CTA, a 77% diameter stenosis by ICA, a mild defect in the distal inferoseptal wall by CTP, and no myocardial perfusion defects by SPECT.

Figure 1

A complete CORE320 imaging data set for a 64-year-old male without prior history of coronary artery disease with chest pain symptoms. The left anterior descending coronary artery revealed a 96% diameter stenosis by computed tomography angiography (CTA) (Row A) and an 85% diameter stenosis by invasive coronary angiography (ICA) (Row B). The computed tomography myocardial perfusion (CTP) (Row C) study revealed a mild defect in the distal anteroseptal wall, and moderate defects in the basal anteroseptal, the basal anterior, the distal anterior, and apical walls, while the single photon emission computed tomography (SPECT) (Row D) study revealed moderate defects in the distal anterior, the distal anteroseptal, the basal anteroseptal and apical walls. The left circumflex artery revealed an 87% diameter stenosis by CTA, a 79% diameter stenosis by ICA, mild defects in the distal inferoseptal and distal inferolateral walls, and moderate defects in the distal anterolateral and distal anterior walls by CTP, and a moderate defect in the distal anterior wall by SPECT. The right coronary artery revealed a 60% diameter stenosis by CTA, a 77% diameter stenosis by ICA, a mild defect in the distal inferoseptal wall by CTP, and no myocardial perfusion defects by SPECT.

All non-invasive imaging (SPECT/MPI, CTA, and CTP) was performed prior to ICA in all patients within 60 days of the ICA and in a CORE320 validated laboratory.18 Single photon emission tomography/myocardial perfusion imaging could be via exercise or pharmacologic stress and was performed for clinical purposes or as part of the research protocol.

Multidetector computed tomography angiography and perfusion acquisition and data analysis

The CTA and CTP acquisitions have been published in detail.19 In brief, all CT images (including calcium scoring) were acquired before ICA using a single protocol19 developed for a 320 × 0.5 mm detector row system (Aquilion ONE, Toshiba Medical Systems, Otawara, Japan). Patient preparation included oral (75–150 mg) or IV (up to 15 mg) metoprolol and sublingual, fast acting nitrates. Computed tomography angiography (CTA) and CTP acquisitions were performed with 50–70 mL of iodinated contrast (Iopamidol 370 mg iodine/mL) injected intravenously at 4.0–5.0 mL/s for each of the separate, axial, prospectively ECG-triggered acquisitions. Computed tomography myocardial perfusion images were acquired during a continuous 6 min intravenous infusion of adenosine at a rate of 0.14 mg/kg/min IV. The effective radiation dose was estimated from the dose–length product provided by the scanner.20

For all CTA and CTP acquisitions, de-identified sinograms were reconstructed, processed, and interpreted by independent core laboratories.18,19 The function of these two independent, centralized, laboratories have been described in detail previously; importantly, the CTP core lab was blinded from CTA and vice versa.19 Computed tomography angiography5,19 and CTP19,21 studies were interpreted by two separate and independent and experienced investigators and disagreements were resolved by consensus. For CTA, all coronary lesions with a subjective stenosis of ≥30% underwent quantitative evaluation using a Vitrea™ fX version 3.0 workstation (Vital Images, Minnetonka, MN, USA). For CTP, myocardial segments were categorized (0 = normal myocardial perfusion, 1 = mild, perfusion deficit, 2 = moderate, and 3 = severe) semi-quantitatively using visual assessment with additional support of customized software (Myocardial Perfusion, Toshiba Medical Systems).5,14,19,21 A summed stress score (SSS) was then calculated for all segments.21 Blinded adjudication22 was performed to meticulously verify co-registration of CTP defined perfusion defects with culprit vessels as defined by CTA.

Invasive coronary angiography (ICA) and single photon emission computed tomography data acquisition and analysis

Clinically indicated ICA was performed using standard techniques within 60 days of the combined CTA–CTP acquisition. Coronary segmentation used standard software (PIE Medical Imaging, Maastricht, the Netherlands), and lesion severity was determined by quantitative coronary angiography.5 Single photon emission computed tomography acquisitions used 99mTc-labelled imaging agents, with approximately 8 mCi for rest and 25 mCi for stress MPI studies. Exercise or pharmacologic stress testing with adenosine or dipyridamole infusion followed standard protocols.23 The procedures of the independent SPECT core laboratory have been described previously.18,19,22

Statistical analysis

All data from core laboratories and clinical database were analysed in the statistical core laboratory at the Bloomberg School of Public Health. The primary analysis estimated the diagnostic accuracy, at the patient level, of the combination of quantitative CTA with visual semiquantitative CTP measurements, and using the Leaman score24 to adjust for lesion location, in comparison with the combination of quantitative ICA and visual SPECT/MPI measurements.

The analysis was based on the area under the receiver operating characteristic (ROC) curve (AUC). For the reference standard, each patient and vessel was classified as normal or having CAD, defined as ≥ 50% by ICA with an associated perfusion defect by SPECT/MPI. The ROC curve was based on a logistic regression analysis with CTA, CTP, and Leaman score as predictor variables. The risk score (the linear predictor) from the logistic regression was used to construct the ROC curve. The AUC was estimated non-parametrically using standard methods.25 The standard error of the AUC was estimated using the bootstrap26 with resampling at the patient level, primarily to account for the prior estimation of the regression coefficients in the logistic regression model. Sensitivity, specificity, and predictive values were calculated using a cutoff of ≥50% stenosis on CTA and CTP sum stress scores as demonstrated in Table 3. The sample size determination was based on the primary objective, with the patient being the unit of analysis. A sample size of 400 (including 10% dropout rate, i.e. 360) was estimated as necessary to detect a difference in the AUC of five points between the null and alternative hypothesis using a one-sided test with a significance level of 5% and at least 80% power,26,27 assuming a prevalence of at least 25% and a dropout rate of 10%. Secondary analyses based on a three vessel-territory (LAD, LCX, and RCA) model were adjusted for the effects of within patient clustering, also using the bootstrap.28 All data are reported with 95% CIs. The threshold of significance was P < 0.05. Statistical analyses were performed using SAS 9.1, Stata 11, and SPlus 8.0.

Results

Among 436 eligible patients recruited (November 2009–July 2011), 55 were excluded (Figure 2) because the imaging was inadequate (n = 16) or incomplete (n = 39). In 10 of the 39 patients with incomplete imaging, the CTP component was uninterpretable. Table 1 summarizes the characteristics of 381 patients with all imaging plus the 10 patients with uninterpretable CTP data due to protocol violations (n = 391). The remaining 381 patients with complete imaging studies were included in the primary diagnostic analysis. All imaging studies were completed within the protocol-mandated period before ICA. Within 30 days following ICA, 2 patients had myocardial infarction, 3 had contrast reactions following CT, and 2 developed temporary atrioventricular block during adenosine infusion (Table 2). Thirty-eight percent of patients included in the primary analysis had a prior history of CAD [prior MI (27%), previous CAD documented by invasive angiography or percutaneous coronary intervention (30%), with overlap between the two groups (19%)]. The median estimated total body effective radiation doses for combined CTA–CTP, SPECT, and ICA were 9.32, 9.75, and 12.0 mSv, respectively (Table 1).

Table 1

Baseline characteristics (n = 391)

Characteristic Value 
Age, year 62 (56–68) 
Male sex 258 (66) 
Ethnicity, number (%) 
 Hispanic 34 (9) 
 Non-hispanic 333 (85) 
 Other 24 (6) 
Race 
 White 219 (56) 
 Black 44 (11) 
 Asian 123 (32) 
 Other 5 (1) 
Body mass index 27 (24–30) 
Hypertension 302 (78) 
Diabetes 132 (34) 
Dyslipidaemia 261 (68) 
Previous myocardial infarction 104 (27) 
Smoking 
 Current 66 (18) 
 Past 136 (36) 
 Never 172 (46) 
Family history of CAD 167 (45) 
Prior percutaneous coronary intervention 113 (30) 
 Stents 109 (28) 
History of unstable angina 27 (7) 
Creatinine (mg/dL) 0.9 (0.7–1.0) 
Previous congestive heart failure 
 NYHA class I 9 (17) 
 NYHA class II 42 (81) 
 NYHA class III 1 (2) 
 NYHA class IV 0 (0) 
Previous cerebrovascular accident 12 (3) 
Previous transient ischaemic attack 11 (3) 
Angina at presentation 
 Unstable angina 9 (2) 
 Stable angina 262 (67) 
 Atypical chest pain or other signs/symptoms suggestive of CAD 120 (31) 
  Chest pain symptoms 44 (11) 
  Heart failure symptoms or shortness of breath 36 (9) 
  Abnormal ECG 21 (5) 
  Abnormal stress test 17 (4) 
  Prior CAD and undefined symptoms 2 (1) 
Cardiovascular medications, number (%) 161 (41) 
 ACE/ARB 179 (46) 
 Beta-blocker 178 (46) 
 Salicylates 50 (13) 
 Nitrates 75 (19) 
 Other anti-hypertensive medication 
Grace risk score 97 (82–116) 
Diamond/Forrester score  
 Low risk 8(2) 
 Intermediate risk 263 (67) 
 High risk 120 (31) 
Prior stress testing, non-nuclear (30 days) 
 ECG only 17 (4) 
 Echo 9 (2) 
Prior stress testing result, non-nuclear  
 Positive 13 (52) 
 Negative/equivocal 12 (48) 
Agatston calcium score 162 (9–584) 
Calcium score radiation exposure (mSv) 0.85 (0.82–0.93) 
CTA characteristics 
Contrast Amount in mL, number (%)  
 50 53 (14) 
 60 318 (81) 
 70 20 (5) 
Beta-blocker (oral) in mg, number (%) 
 75 133 (34) 
 150 194 (50) 
 None 64 (16) 
Nitroglycerine during CTA 337 (86) 
CTA radiation exposure (mSv) 3.16 (2.82–3.63) 
CTA heart rate during CT scan (bpm) 54 (49–59) 
CTP characteristics  
Contrast amount in mL, number (%) 
 50 54 (14) 
 60 317 (81) 
 70 20 (5) 
CTP radiation exposure (mSv) 5.31 (3.81–6.04) 
CTP heart rate during CT scan (bpm) 69 (60–78) 
SPECT characteristics 
 Pharmacological 265 (68) 
 Exercise 126 (32) 
 Clinically driven 160 (41) 
 Research driven 231 (59) 
 Radiation exposure (mSv) 9.75 (9.10–13.00) 
ICA characteristics 
 Nitroglycerine during ICA 362 (93) 
 Contrast amount (mL) 100 (75–133) 
 Radiation exposure (mSv) 12.0 (7.6–18.0) 
Characteristic Value 
Age, year 62 (56–68) 
Male sex 258 (66) 
Ethnicity, number (%) 
 Hispanic 34 (9) 
 Non-hispanic 333 (85) 
 Other 24 (6) 
Race 
 White 219 (56) 
 Black 44 (11) 
 Asian 123 (32) 
 Other 5 (1) 
Body mass index 27 (24–30) 
Hypertension 302 (78) 
Diabetes 132 (34) 
Dyslipidaemia 261 (68) 
Previous myocardial infarction 104 (27) 
Smoking 
 Current 66 (18) 
 Past 136 (36) 
 Never 172 (46) 
Family history of CAD 167 (45) 
Prior percutaneous coronary intervention 113 (30) 
 Stents 109 (28) 
History of unstable angina 27 (7) 
Creatinine (mg/dL) 0.9 (0.7–1.0) 
Previous congestive heart failure 
 NYHA class I 9 (17) 
 NYHA class II 42 (81) 
 NYHA class III 1 (2) 
 NYHA class IV 0 (0) 
Previous cerebrovascular accident 12 (3) 
Previous transient ischaemic attack 11 (3) 
Angina at presentation 
 Unstable angina 9 (2) 
 Stable angina 262 (67) 
 Atypical chest pain or other signs/symptoms suggestive of CAD 120 (31) 
  Chest pain symptoms 44 (11) 
  Heart failure symptoms or shortness of breath 36 (9) 
  Abnormal ECG 21 (5) 
  Abnormal stress test 17 (4) 
  Prior CAD and undefined symptoms 2 (1) 
Cardiovascular medications, number (%) 161 (41) 
 ACE/ARB 179 (46) 
 Beta-blocker 178 (46) 
 Salicylates 50 (13) 
 Nitrates 75 (19) 
 Other anti-hypertensive medication 
Grace risk score 97 (82–116) 
Diamond/Forrester score  
 Low risk 8(2) 
 Intermediate risk 263 (67) 
 High risk 120 (31) 
Prior stress testing, non-nuclear (30 days) 
 ECG only 17 (4) 
 Echo 9 (2) 
Prior stress testing result, non-nuclear  
 Positive 13 (52) 
 Negative/equivocal 12 (48) 
Agatston calcium score 162 (9–584) 
Calcium score radiation exposure (mSv) 0.85 (0.82–0.93) 
CTA characteristics 
Contrast Amount in mL, number (%)  
 50 53 (14) 
 60 318 (81) 
 70 20 (5) 
Beta-blocker (oral) in mg, number (%) 
 75 133 (34) 
 150 194 (50) 
 None 64 (16) 
Nitroglycerine during CTA 337 (86) 
CTA radiation exposure (mSv) 3.16 (2.82–3.63) 
CTA heart rate during CT scan (bpm) 54 (49–59) 
CTP characteristics  
Contrast amount in mL, number (%) 
 50 54 (14) 
 60 317 (81) 
 70 20 (5) 
CTP radiation exposure (mSv) 5.31 (3.81–6.04) 
CTP heart rate during CT scan (bpm) 69 (60–78) 
SPECT characteristics 
 Pharmacological 265 (68) 
 Exercise 126 (32) 
 Clinically driven 160 (41) 
 Research driven 231 (59) 
 Radiation exposure (mSv) 9.75 (9.10–13.00) 
ICA characteristics 
 Nitroglycerine during ICA 362 (93) 
 Contrast amount (mL) 100 (75–133) 
 Radiation exposure (mSv) 12.0 (7.6–18.0) 

Numbers are reported as N (%) or median (interquartile range).

CAD, coronary artery disease; mg/dL, milligrams per decilitre; NYHA, New York Heart Association classification; ACS, acute coronary syndrome; ECG, electrocardiogram; SD, standard deviation; CT, computed tomography; ICA, invasive coronary angiography; SPECT, single photon emission computed tomography; CTA, computed tomography angiography; mL, millilitre; mg, milligrams; mSv, millisieverts; bpm, beats per minute; CTP, computed tomography myocardial perfusion.

Table 2

Serious adverse events and adverse events

 Number of patients 
CT associated serious adverse events 
 Renal failure 
 Reaction to contrast dye 
 Transient heart block 
 Hypotension 
 Extravasation of contrast agent in the antecubital fossa 
 Pulmonary edemaa 
 Vagal episode 
Cardiovascular events 
 Death 
 Myocardial infarctionb 
 Stroke 
 Hospitalization for CV event 
  Coronary dissectionc 
  Chest paind 
 Femoral artery pseudo-aneurism (vascular event)e 
 Intracerebral bleeding/infarctf 
 Number of patients 
CT associated serious adverse events 
 Renal failure 
 Reaction to contrast dye 
 Transient heart block 
 Hypotension 
 Extravasation of contrast agent in the antecubital fossa 
 Pulmonary edemaa 
 Vagal episode 
Cardiovascular events 
 Death 
 Myocardial infarctionb 
 Stroke 
 Hospitalization for CV event 
  Coronary dissectionc 
  Chest paind 
 Femoral artery pseudo-aneurism (vascular event)e 
 Intracerebral bleeding/infarctf 

CT, computed tomography angiography; CV, cardiovascular.

aPulmonary edema: patient had CHF exacerbation after the CT scan.

bMyocardial infarction: one patient had MI after PCI and one 5 months later.

cCoronary dissections were as follows: A 59-year-old female had a dissection during diagnostic catheterization and a 71-year-old male had dissection during PCI.

dChest pain: one non-cardiac and one occurred after the CT examination.

eFemoral artery pseudo-aneurism: vascular access complication.

fIntracerebral bleeding/infarct detected 24 h post-cardiac catheterization.

Figure 2

Patient flow. CT, computed tomography; SPECT, single photon emission computed tomography; ICA, invasive coronary angiography; CTA, computed tomography angiography; CTP, computed tomography myocardial perfusion; LAD, left anterior descending coronary artery; LCX, left circumflex coronary artery; RCA, right coronary artery. All invasive coronary angiography analysis performed using quantitative coronary angiography.

Figure 2

Patient flow. CT, computed tomography; SPECT, single photon emission computed tomography; ICA, invasive coronary angiography; CTA, computed tomography angiography; CTP, computed tomography myocardial perfusion; LAD, left anterior descending coronary artery; LCX, left circumflex coronary artery; RCA, right coronary artery. All invasive coronary angiography analysis performed using quantitative coronary angiography.

Patient-based diagnostic performance of combined computed tomography angiography–computed tomography myocardial perfusion for detection of a haemodynamically significant lesion

For the primary study endpoint, the AUC for combined CTA–CTP was 0.87 [95% confidence interval (CI): 0.84–0.91] for the prediction of a 50% or greater stenosis by ICA with a corresponding perfusion defect by SPECT (Figure 3). There was no difference in the primary study endpoint if the 10 patients with uninterpretable CTP studies were considered positive [AUC: 87.3 (95% CI: 84–91)] or negative [87.6 (95% CI: 84–91)]. In patients without prior myocardial infarction (n = 278), the AUC for combined CTA–CTP was 0.90 (95% CI: 0.87–0.94) and in patients without prior CAD (n = 236) the AUC for combined CTA–CTP was 0.93 (95% CI: 0.89–0.97) (Figure 3). Furthermore, we computed the AUC for patients with reversible defects only (i.e. excluding patients with fixed defects). The AUC for this subgroup of patients (n = 344) was 0.89 (95% CI: 0.85–0.92), which was not different from the subgroup without prior myocardial infarction. There was no difference in AUC for patients undergoing a research SPECT study [0.87 (95% CI: 0.82–0.92)] vs. those from whom the SPECT was performed clinically [0.88 (95% CI: 0.83–0.93), P = 0.781].

Figure 3

Receiver operating characteristic (ROC) curve and corresponding area under the curve (AUC) describing the diagnostic performance of combined computed tomography angiography (CTA) and computed tomography myocardial perfusion (CTP) to identify a ≥50% coronary stenosis and a corresponding myocardial perfusion using the reference standard of invasive coronary angiography (ICA) and single photon emission computed tomography myocardial perfusion imaging (SPECT/MPI) at a patient level.

Figure 3

Receiver operating characteristic (ROC) curve and corresponding area under the curve (AUC) describing the diagnostic performance of combined computed tomography angiography (CTA) and computed tomography myocardial perfusion (CTP) to identify a ≥50% coronary stenosis and a corresponding myocardial perfusion using the reference standard of invasive coronary angiography (ICA) and single photon emission computed tomography myocardial perfusion imaging (SPECT/MPI) at a patient level.

The presence of stents, expressed as a history of previous PCI, likely influenced the findings of the CORE320 study. For all patients enrolled in the study, the diagnostic power of CTA–CTP to identify a flow limiting stenosis defined by ICA–SPECT was AUC = 0.87 (95% CI: 0.84–0.91). However, when patients with a history of previous PCI (stents) were excluded, the diagnostic power expressed in the AUC increased to 0.93 (95% CI: 0.89–96).

When CTA alone (i.e. without perfusion CT) was used to predict ICA–SPECT, the AUC was 0.84 (95% CI: 0.79–0.88), significantly (P = 0.02) less than the 0.87 AUC for the combined CTA–CTP approach. The sensitivity, specificity, positive predictive value (PPV), and NPV for the combination of a ≥50% stenosis on CTA with increasing thresholds of SSS on CTP to predict the primary endpoint (50% or greater stenosis by ICA with a corresponding perfusion defect by SPECT) are shown in Table 3. For example, using a SSS of 4 the sensitivity, specificity, PPV, and NPV were 80% (95% CI: 72–86), 74% (95% CI: 68–80), 65% (95% CI: 58–72), and 86% (95% CI: 80–90), respectively (Table 3). In patients without prior MI, using the same threshold, the sensitivity, specificity, PPV, and NPV were 81% (95% CI: 71–89), 77% (95% CI: 71–83), 60% (95% CI: 50–69), and 91% (95% CI: 85–95) and in patients without known CAD, the specificity, PPV, and NPV were 79% (95% CI: 67–88), 81% (95% CI: 74–86), 61% (95% CI: 49–71), and 91% (95% CI: 85–95), respectively (Table 3). In the combined CTA–CTP analysis (CTA ≥50% stenosis with a corresponding CTP SSS of 4), the degree of CAD was underestimated in 29 patients (false negative) and overestimated in 61 patients (false positive) compared with the combined outcome of ICA–SPECT.

Table 3

Sensitivity, specificity, positive predictive value, and negative predictive value for computed tomography angiography (CTA) (50% or greater) alone and CTA (50% or greater) with increasing levels of computed tomography myocardial perfusion sum stress score to predict invasive coronary angiography stenosis ≥ 50% and a single photon emission tomography/myocardial perfusion imaging perfusion deficit

 All patients (n = 381)
 
 Sensitivity Specificity PPV NPV 
CTA alone ≥ 50% Stenosis (95% CI) 92 (87–96) 51 (44–57) 53 (47–60) 92 (86–96) 
CTP SSS 
 0 96 (91–99) 46a (40–53) 52 (46–58) 95 (89–98) 
 1 92 (86–96) 53 (46–59) 54 (48–61) 91 (85–95) 
 2 90 (83–94) 57a (50–63) 56 (49–62) 90 (84–94) 
 3 84a (77–90) 65a (58–71) 59b (52–66) 87 (81–92) 
 4 80a (72–86) 74a (68–80) 65b (58–72) 86 (80–90) 
 5 65a (56–72) 83a (78–88) 70b (61–78) 79b (74–84) 
 Patients without prior MI (n = 278) 
CTA alone ≥ 50% Stenosis (95% CI) 95 (88–99) 54 (47–61) 47 (39–55) 97 (91–99) 
CTP SSS 
 0 98 (92–100) 51a (44–58) 46 (38–53) 98 (93–100) 
 1 92 (84–97) 58 (51–65) 48 (40–56) 94 (89–98) 
 2 88 (79–94) 62a (55–69) 49 (41–58) 93 (87–96) 
 3 86a (77–93) 69a (62–75) 54b (45–62) 92 (87–96) 
 4 80a (71–89) 77a (71–83) 60b (50–69) 91b (85–95) 
 5 64a (52–74) 86a (81–91) 66b (55–76) 85b (79–90) 
 Patients with known CAD excluded (n = 236) 
CTA alone ≥ 50% Stenosis (95% CI) 94 (84–98) 60 (53–68) 46 (37–55) 96 (91–99) 
CTP SSS 
 0 97 (89–100) 58 (50–66) 45 (37–54) 98 (93–100) 
 1 89 (78–95) 66a (59–73) 48 (39–58) 94 (89–98) 
 2 84 (72–92) 70a (62–76) 50 (40–60) 92 (86–96) 
 3 82 (71–91) 75a (68–81) 54b (43–64) 92 (87–96) 
 4 77a (65–87) 81a (74–87) 59b (48–70) 91 (85–95) 
 5 66a (53–78) 89a (84–93) 68b (55–80) 88b (82–93) 
 All patients (n = 381)
 
 Sensitivity Specificity PPV NPV 
CTA alone ≥ 50% Stenosis (95% CI) 92 (87–96) 51 (44–57) 53 (47–60) 92 (86–96) 
CTP SSS 
 0 96 (91–99) 46a (40–53) 52 (46–58) 95 (89–98) 
 1 92 (86–96) 53 (46–59) 54 (48–61) 91 (85–95) 
 2 90 (83–94) 57a (50–63) 56 (49–62) 90 (84–94) 
 3 84a (77–90) 65a (58–71) 59b (52–66) 87 (81–92) 
 4 80a (72–86) 74a (68–80) 65b (58–72) 86 (80–90) 
 5 65a (56–72) 83a (78–88) 70b (61–78) 79b (74–84) 
 Patients without prior MI (n = 278) 
CTA alone ≥ 50% Stenosis (95% CI) 95 (88–99) 54 (47–61) 47 (39–55) 97 (91–99) 
CTP SSS 
 0 98 (92–100) 51a (44–58) 46 (38–53) 98 (93–100) 
 1 92 (84–97) 58 (51–65) 48 (40–56) 94 (89–98) 
 2 88 (79–94) 62a (55–69) 49 (41–58) 93 (87–96) 
 3 86a (77–93) 69a (62–75) 54b (45–62) 92 (87–96) 
 4 80a (71–89) 77a (71–83) 60b (50–69) 91b (85–95) 
 5 64a (52–74) 86a (81–91) 66b (55–76) 85b (79–90) 
 Patients with known CAD excluded (n = 236) 
CTA alone ≥ 50% Stenosis (95% CI) 94 (84–98) 60 (53–68) 46 (37–55) 96 (91–99) 
CTP SSS 
 0 97 (89–100) 58 (50–66) 45 (37–54) 98 (93–100) 
 1 89 (78–95) 66a (59–73) 48 (39–58) 94 (89–98) 
 2 84 (72–92) 70a (62–76) 50 (40–60) 92 (86–96) 
 3 82 (71–91) 75a (68–81) 54b (43–64) 92 (87–96) 
 4 77a (65–87) 81a (74–87) 59b (48–70) 91 (85–95) 
 5 66a (53–78) 89a (84–93) 68b (55–80) 88b (82–93) 

Confidence limits are exact, based on the binomial distribution.

CTA, computed tomography angiography; ICA, invasive coronary angiography; SPECT/MPI, single positron emission computed tomography myocardial perfusion imaging; CAD, coronary artery disease; CI, confidence interval; CTP, computed tomography myocardial perfusion; SSS, sum stress score; PPV, positive predictive value; NPV, negative predictive value.

aThe indicated sensitivity or specificity is significantly different (P < 0.05) from that for CTA alone by McNemar's test.

bPredictive values were compared using Wald tests from a logistic model with GEE.

Vessel-based diagnostic performance of combined computed tomography angiography–computed tomography myocardial perfusion for detection of a haemodynamically significant lesion

In a vessel-based analysis, the AUC for combined CTA–CTP to predict ICA + SPECT was 0.87 (95% CI: 0.84–0.89). When CTA alone (i.e. without perfusion CT) was used to predict ICA–SPECT, the AUC was 0.82 (95% CI: 0.78–0.85), significantly (P < 0.001) less than the 0.87 AUC for the combined CTA–CTP approach (Figure 4A). For the left anterior descending (LAD) coronary artery and corresponding perfusion territory, the combined CTA–CTP AUC was 0.89 (95% CI: 0.86–0.93), and the CTA alone AUC was 0.84 (95% CI: 0.77–0.88), significantly less (P < 0.001) (Figure 4B). For the left circumflex and corresponding perfusion territory (LCX), the combined CTA–CTP AUC was 0.86 (95% CI: 0.82–0.91), and the CTA alone AUC was 0.81 (95% CI: 0.75–0.86), significantly less (P = 0.002) (Figure 4C). Finally for the right coronary artery (RCA) and corresponding territory, the combined CTA–CTP AUC was 0.86 (95% CI: 0.81–0.90), and the CTA alone AUC was 0.81 (95% CI: 0.76–0.87), also significantly less (P = 0.002) (Figure 4D). The sensitivity, specificity, PPV, and NPV for the vessel based analysis (including all three vessel territories) in patients without prior MI, and in patients without known CAD are shown in Table 4. The sensitivity, specificity, PPV, and NPV for the LAD, LCx, and RCA are shown in Supplementary material online, 1.

Table 4

Vessel sensitivity, specificity, positive predictive value, and negative predictive value for computed tomography angiography (CTA) (50% or greater) alone and CTA (50% or greater) with increasing levels of computed tomography myocardial perfusion sum stress score to predict invasive coronary angiography stenosis ≥ 50% and a single photon emission tomography/myocardial perfusion imaging perfusion deficit

 All vessels (n = 1143)
 
 Sensitivity Specificity PPV NPV 
CTA alone ≥ 50% Stenosis (95% CI) 83 (77–88) 64 (60–69) 41 (36–46) 92 (90–95) 
CTP SSS 
 0 89a (85–93) 61b (57–65) 41 (36–46) 95a (93–97) 
 1 81 (76–86) 70b (66–74) 45a (39–50) 93 (90–95) 
 2 73b (67–78) 76b (73–79) 47a (42–53) 90 (88–93) 
 3 61b (55–67) 83b (80–86) 52a (45–58) 88a (85–90) 
 4 52b (46–58) 88b (86–91) 57a (50–64) 86a (83–89) 
 5 41a (35–47) 93b (91–94) 62a (54–70) 84a (81–87) 
 Vessels in patients without prior MI (n = 834) 
CTA alone ≥ 50% Stenosis (95% CI) 90 (83–96) 69 (64–73) 37 (31–44) 97 (95–99) 
CTP SSS 
 0 94 (89–98) 66a (61–71) 36 (30–43) 98 (97–99) 
 1 85 (79–92) 74a (70–78) 41a (34–48) 96 (94–98) 
 2 73b (65–80) 80b (76–83) 43a (35–50) 93b (91–96) 
 3 61b (53–69) 85b (82–88) 46a (38–55) 91b (89–94) 
 4 51b (44–59) 90b (88–92) 51a (43–60) 90b (87–93) 
 5 40b (32–48) 94b (93–96) 60a (49–70) 88b (85–91) 
 Vessels in patients with known CAD excluded (n = 708) 
CTA alone ≥ 50% Stenosis (95% CI) 88 (81–96) 73 (68–77) 39 (32–47) 97 (95–99) 
CTP SSS 
 0 93 (88–98) 71a (66–76) 39 (32–47) 98 (97–100) 
 1 84 (76–92) 79a (75–84) 45a (37–54) 96 (94–98) 
 2 71b (63–80) 84a (81–88) 47a (38–57) 94b (91–96) 
 3 61b (51–70) 89b (86–91) 52a (42–62) 92b (89–95) 
 4 50b (42–59) 92b (90–94) 56a (46–66) 90b (87–93) 
 5 41b (32–50) 96b (94–97) 66a (55–78) 89b (86–92) 
 All vessels (n = 1143)
 
 Sensitivity Specificity PPV NPV 
CTA alone ≥ 50% Stenosis (95% CI) 83 (77–88) 64 (60–69) 41 (36–46) 92 (90–95) 
CTP SSS 
 0 89a (85–93) 61b (57–65) 41 (36–46) 95a (93–97) 
 1 81 (76–86) 70b (66–74) 45a (39–50) 93 (90–95) 
 2 73b (67–78) 76b (73–79) 47a (42–53) 90 (88–93) 
 3 61b (55–67) 83b (80–86) 52a (45–58) 88a (85–90) 
 4 52b (46–58) 88b (86–91) 57a (50–64) 86a (83–89) 
 5 41a (35–47) 93b (91–94) 62a (54–70) 84a (81–87) 
 Vessels in patients without prior MI (n = 834) 
CTA alone ≥ 50% Stenosis (95% CI) 90 (83–96) 69 (64–73) 37 (31–44) 97 (95–99) 
CTP SSS 
 0 94 (89–98) 66a (61–71) 36 (30–43) 98 (97–99) 
 1 85 (79–92) 74a (70–78) 41a (34–48) 96 (94–98) 
 2 73b (65–80) 80b (76–83) 43a (35–50) 93b (91–96) 
 3 61b (53–69) 85b (82–88) 46a (38–55) 91b (89–94) 
 4 51b (44–59) 90b (88–92) 51a (43–60) 90b (87–93) 
 5 40b (32–48) 94b (93–96) 60a (49–70) 88b (85–91) 
 Vessels in patients with known CAD excluded (n = 708) 
CTA alone ≥ 50% Stenosis (95% CI) 88 (81–96) 73 (68–77) 39 (32–47) 97 (95–99) 
CTP SSS 
 0 93 (88–98) 71a (66–76) 39 (32–47) 98 (97–100) 
 1 84 (76–92) 79a (75–84) 45a (37–54) 96 (94–98) 
 2 71b (63–80) 84a (81–88) 47a (38–57) 94b (91–96) 
 3 61b (51–70) 89b (86–91) 52a (42–62) 92b (89–95) 
 4 50b (42–59) 92b (90–94) 56a (46–66) 90b (87–93) 
 5 41b (32–50) 96b (94–97) 66a (55–78) 89b (86–92) 

Confidence limits are calculated using GEE to account for multiple vessels per patient. Sensitivity, specificity, and predictive values were compared using Wald tests from a logistic model with GEE.

CTA, computed tomography angiography; CAD, coronary artery disease; CI, confidence interval; CTP, computed tomography myocardial perfusion; SSS, sum stress score; PPV, positive predictive value; NPV, negative predictive value.

aStatistic is significantly different (P < 0.05) from that for CTA alone.

bDifference between tests is dependent on vessel.

Figure 4

Receiver operating characteristic (ROC) curve and corresponding area under the curve (AUC) describing the diagnostic performance of combined computed tomography angiography (CTA) and computed tomography myocardial perfusion (CTP) and CTA alone to identify a ≥50% coronary stenosis and a corresponding myocardial perfusion defect using the reference standard of invasive coronary angiography (ICA) and single photon emission tomography/myocardial perfusion imaging (SPECT/MPI) at a vessel level. (A) All vessels, (B) LAD, (C) LCX, and (D) RCA.

Figure 4

Receiver operating characteristic (ROC) curve and corresponding area under the curve (AUC) describing the diagnostic performance of combined computed tomography angiography (CTA) and computed tomography myocardial perfusion (CTP) and CTA alone to identify a ≥50% coronary stenosis and a corresponding myocardial perfusion defect using the reference standard of invasive coronary angiography (ICA) and single photon emission tomography/myocardial perfusion imaging (SPECT/MPI) at a vessel level. (A) All vessels, (B) LAD, (C) LCX, and (D) RCA.

Discussion

A single CT examination that includes angiography and perfusion can detect haemodynamically significant coronary stenoses defined as >50% by ICA with an associated SPECT/MPI perfusion defect in the corresponding territory. The performance of the combined test improves for patients without known CAD, where the AUC reaches 0.93. CORE320 provides prospective multicentre, multinational, comprehensive analyses to define the contribution of CTP imaging over and above the established role of CTA.

Non-invasive myocardial perfusion has been the cornerstone of clinical evaluation to detect CAD with established diagnostic and prognostic value.10,13,23,29 On the other hand, the presence and location of coronary lesions by catheterization is essential for a comprehensive diagnosis, to evaluate prognosis, and to guide revascularization.5–7 The current reference standard to assemble these data requires serial imaging with more than one modality.10,11 CORE320 establishes CT as a single imaging platform to gather both morphologic and functional information with high accuracy.

Competing single modality image strategies has limitations. Magnetic resonance imaging angiography and perfusion can be performed in a single examination, but the tradeoffs related to MRI dramatically limit the ability to obtain routine high quality coronary angiograms in clinically required scan times.30 While there are also theoretical possibilities to estimate the pressure drop12 or transluminal attenuation gradients across specific coronary stenosis,31 these encouraging methods are exploratory at this time and if proven useful, could be combined with data obtained at rest and/or during stress perfusion in a comprehensive CT examination.

The advantages and disadvantages of static vs. dynamic CTP imaging32 relate not only to the CT mode of imaging (volume vs. helical) but also to system capabilities of reducing radiation in first, second, and third generation scanners, which allow for safe implementation of dynamic CTP. Dynamic imaging enables the construction of a time-signal intensity relationship containing a greater number of points than static imaging at peak stress and rest, which facilitates the identification of perfusion defects vs. artefacts. This is true not only for CT but also for MR perfusion imaging33 but implies greater radiation when CT is used and a more complex tradeoff between dose, spatial resolution, and artefacts. On the other hand, volume CT has the advantages of artefact reduction and straightforward comparison between rest and stress studies with less radiation, greater spatial resolution, and less delineation of contrast dynamics as it traverses different myocardial regions during bolus administration. Further advances in CT technology should enhance the ability to obtain diagnostic CTP studies at lower radiation doses in combination with CTA. The results of this study should represent a template for the incorporation of such advances in the evaluation of patients with suspected CAD.

Clinical implications, safety, and radiation exposure

The CORE320 protocol acquired rest CTA images before CTP to facilitate translation to clinical care; patients with normal or near-normal CTA images will not generally need perfusion imaging. Patients with intermediate degrees of coronary stenosis would then proceed to having a stress CTP for clinical decision-making within 1 h of the initial CT diagnosis. The clinical applicability of the proposed stress testing model is the subject of future clinical studies.

Radiation values reported in this study for both the gold-standard and CT protocols reflect the performance of these tests in the specified research context. In this regard, normal CT angiograms or SPECT studies may prevent the performance of CT perfusion and invasive angiograms in a large percentage of patients with suspected CAD, particularly in those with no history of previous CAD. Therefore, the values presented here should be used as guiding posts to aid the treating physician in decision making about the risk/benefits of further testing as data are accumulated for each patient.

Methodological considerations

While β-blockers used to lower patients' heart rates may produce ‘hidden’ ischaemia during adenosine infusion, the accuracy of the combined approach argues that this theoretical limitation was minimal because CTP when combined with CTA and compared with ICA–SPECT identified more false positive than false negative studies. Like all modalities, CT has technical limitations, and both motion and beam-hardening artefacts can be mistaken for myocardial perfusion deficits. The later was minimized using an advanced beam-hardening correction developed and implemented for this study.19 However, beam hardening and other CT artefacts could have contributed to false positive results in some patients. We acknowledge inherent selection bias; specifically, a clinically positive SPECT study may have influenced the decision to perform invasive angiography and therefore made the patient eligible for study entry. However, there were no statistical differences in findings among those patients who had a clinical vs. a research SPECT, strongly suggesting that selection bias had little or no influence on the study results. Single photon emission tomography/myocardial perfusion imaging is limited in sensitivity when compared with other imaging modalities, such as MRI, PET, and invasive FFR. The choice of SPECT/MPI as the perfusion method in the definition of a perfusion defect could have led to a greater number of false positive vessels/patients in the CORE320 study. Conversely, SPECT/MPI may be more specific particularly in single vessel CAD and was chosen because it is the most common method of assessing myocardial perfusion non-invasively.

Conclusions

The combination of CTA and perfusion correctly identifies patients with flow limiting CAD defined as ≥ 50 stenosis by ICA causing a perfusion defect by SPECT/MPI. The exclusion of patients with previous myocardial infarction or known CAD increased the diagnostic power of combined CTA–CTP in the non-invasive detection of flow limiting CAD defined by ICA-SPECT/MPI.

Supplementary material

Supplementary material is available at European Heart Journal online.

Funding

The study sponsor, Toshiba Medical Systems Corporation, was not involved in any stage of the study design, data acquisition, data analysis, or manuscript preparation.

Conflict of interest: M.D., A.deR., K.K., J.B., R.C., C.C., M.F.D.C., R.G., J.H., M.J., K.K., S.K., J. M.M., S.N., S.Y.T., A.V., V.C.M., K.Y., J.A.C.L., C.N., N.P., F.R., and A.A.-Z. report institutions receive grant support from Toshiba Medical System. M.D., S.Y.T., N.P., and J.H. are on the speaker's bureau for Toshiba Medical Systems. M.D., M.J., K.K., S.K., and R.G. report grant support from GE Healthcare. K.K. grant support form Philips Electronics, Bayer, Gerber, and Eisai. M.D. and J.A.C.L. grant support from Bracco Diagnostics. S.K. grant support from Daiichi-Sankyo Pharmatheutical. M.J. grant support from AZE and Ziosoft. M.D. grant support from: European Regional Development Fund, German Heart Foundation, Guerbet, German Science Foundation, and German Federal Ministry of Education and Research. M.D. is on the speaker's bureau for Guerbet, and Bayer-Schering. M.L. is a member of Speakers bureaus for Medtronic Inc, and Eesculap Akademie. M.D. consults for Guerbet and Richard George for ICON Medical Imaging. R.G. reports paid board membership for GE Healthcare and Astellas Pharma.

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Author notes

Authors contributed equally as first author.

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