computed tomography angiography and perfusion to assess coronary artery stenosis causing perfusion...

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CLINICAL RESEARCH

Computed tomography angiography andperfusiontoassesscoronaryarterystenosiscausingperfusion defects by single photon emissioncomputed tomography: the CORE320 studyCarlos E. Rochitte4†, Richard T. George1†, Marcus Y. Chen5, Armin Arbab-Zadeh1,Marc Dewey6, Julie M. Miller1, Hiroyuki Niinuma7,8, Kunihiro Yoshioka7,Kakuya Kitagawa9, Shiro Nakamori9, Roger Laham10, Andrea L. Vavere1,Rodrigo J. Cerci1, Vishal C. Mehra1, Cesar Nomura11, Klaus F. Kofoed12,Masahiro Jinzaki13, Sachio Kuribayashi13, Albert de Roos14, Michael Laule6,Swee Yaw Tan15, John Hoe16, Narinder Paul17, Frank J. Rybicki3, Jeffery A. Brinker1,Andrew E. Arai5, Christopher Cox2, Melvin E. Clouse10, Marcelo F. Di Carli3, andJoao A.C. Lima1*

1Division of Cardiology, Department of Medicine, Johns Hopkins Hospital and School of Medicine, 600 N. Wolfe St., Blalock 524, Baltimore, MD 21287, USA; 2Johns Hopkins BloombergSchool of Public Health, Baltimore, MD, USA; 3Brigham and Women’s Hospital, Boston, MA, USA; 4Heart Institute, InCor, University of Sao Paulo Medical School, Sao Paulo, Brazil;5National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA; 6Charite Medical School, Humboldt, Berlin, Germany; 7Iwate Medical University, Morioka,Japan; 8St Luke’s InternationalHospital, Tokyo, Japan; 9Mie UniversityHospital, Tsu, Japan; 10Beth IsraelDeaconess Medical Center,Harvard University, Boston,MA, USA; 11Albert EinsteinHospital, Sao Paulo, Brazil; 12Universityof Copenhagen, Denmark; 13Keio University, Tokyo, Japan; 14Leiden University Medical Center, Leiden, the Netherlands; 15National Heart Center,Singapore, Singapore; 16Mount Elizabeth Hospital, Singapore, Singapore; and 17Toronto General Hospital, Toronto, Canada

Received 5 August 2013; revised 21 October 2013; accepted 1 November 2013

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

Methodsand results

Weconducted amulticentre study toevaluate the accuracyof integrated CTA–CTP for the identification ofpatientswithflow-limiting CAD defined by ≥50% stenosis by invasive coronary angiography (ICA) with a corresponding perfusiondeficit on stress single photon emission computed tomography (SPECT/MPI). Sixteen centres enroled 381 patientswho underwent combined CTA–CTP and SPECT/MPI prior to conventional coronary angiography. All four image mo-dalities were analysed in blinded independent core laboratories. The prevalence of obstructive CAD defined by com-bined ICA–SPECT/MPI and ICA alone was 38 and 59%, respectively. The patient-based diagnostic accuracy definedby the area under the receiver operating characteristic curve (AUC) of integrated CTA–CTP for detecting or excludingflow-limitingCADwas0.87 [95% confidence interval (CI): 0.84–0.91]. In patients withoutpriormyocardial infarction, theAUC 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, spe-cificity, positive predictive, and negative predicative values (95% CI) were 80% (72–86), 74% (68–80), 65% (58–72), and86% (80–90), respectively. For flow-limiting disease defined by ICA-SPECT/MPI, the accuracy of CTA was significantlyincreased 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 byICA causing a perfusion defect by SPECT/MPI.

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* Corresponding author. Tel: +1 410-614-1284, Fax: +1 410-614-8222, Email: jlima@jhmi.edu

European Heart Journaldoi:10.1093/eurheartj/eht488

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Keywords Imaging † Atherosclerosis † Ischemia † Perfusion † Multislice computed tomography

IntroductionCoronary artery disease (CAD) is the leading cause of morbidity andmortality worldwide.1 The treatment of CAD has changed signifi-cantly in the last two decades. The development of drug-elutingstents2 initially increased the numberof revascularizationproceduresand fostered a relative overreliance on coronary stenosis. However,recent trials3,4 havedemonstrated thatboth anatomical and function-al significance are crucial to clinical outcomes for symptomatic CADpatients considered for revascularization. Coronary computed tom-ography angiography (CTA) has high sensitivity and excellent nega-tive predictive value (NPV) to exclude significant coronary stenosisin patients with chest pain and suspected CAD.5 –7 Appropriatenesscriteria have thus recommended CTA for symptomatic patients withintermediate and low pretest probability of CAD.8

Both invasive coronary angiography (ICA) and CTA provide mor-phologic data but inherently lack the physiologic information neededto determine haemodynamic significance, provided either bycatheter-based fractional flow reserve (FFR),4 or non-invasivemethods such as single photon emission tomography/myocardialperfusion imaging (SPECT/MPI), positron emission tomography(PET), or magnetic resonance imaging (MRI).3,9– 11 The rationalefor the use of a single modality test combining anatomy and physi-ology also includes the need to conserve resources and reduce vari-ation in clinical imaging algorithms.12,13

In this regard, results from experimental and single centre clinicalmyocardial CT perfusion (CTP) studies14– 17 have stimulated enthu-siasm for a multicentre, international study using centralized, blindedanalyses to determine the diagnostic accuracy of combined CTA andCTP in comparison with other non-invasive methods in current clin-ical use. Therefore, the purpose of this study was to test the hypoth-esis that a combined, non-invasive CTA/CTP strategy could reliablyidentify or exclude flow limiting coronary stenoses in patients withsuspected CAD using the composite reference standard of ICAplus SPECT/MPI.

Methods

Patient populationThe Coronary Artery Evaluation using 320-row Multidetector Com-puted Tomography Angiography and Myocardial Perfusion (CORE320)study is a prospective, diagnostic studyperformed at 16centres in8 coun-tries (www.clinicaltrials.gov, NCT00934037). Adverse events weretracked, reported, and reviewed by an independent data safety and mon-itoring board. All centres received study approval by their local institu-tional review board, and all patients gave written informed consent.

The CORE320 study design has been previously published.18 Patientsbetween 45 and 85 years of age with suspected or known CAD and clin-ically referred for ICA were eligible for enrolment. Exclusion criteriawere: known allergy to iodinated contrast media, elevated serum creatin-ine (.1.5 mg/dL) or calculated creatinine clearance of ,60 mL/min,atrial fibrillation, second or third degree atrio-ventricular block, previouscardiac surgery, coronary intervention within the past 6 months,

evidence of acute coronary syndrome with thrombolysis, myocardial in-farction risk score ≥5 or elevated cardiac enzymes in the past 72 h, highradiation exposure (≥5.0 rems) in the 18 months before consent, andbody mass index .40 m/kg2 among others.18 Women of child-bearingpotential had a negative pregnancy test within 24 h preceding CT. Thestudy enrolled and analysed all patients regardless of calcium score andpresence of stents.

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

All non-invasive imaging (SPECT/MPI, CTA, and CTP) was performedprior to ICA in all patients within 60 days of the ICA and in a CORE320validated laboratory.18 Single photon emission tomography/myocardialperfusion imaging could be via exercise or pharmacologic stress andwas performed for clinical purposes or as part of the research protocol.

Multidetector computed tomographyangiographyand perfusion acquisition and dataanalysisThe CTA and CTP acquisitions have been published in detail.19 In brief, allCT images (including calcium scoring) were acquired before ICA using asingle protocol19 developed for a 320 × 0.5 mm detector row system(Aquilion ONE, Toshiba Medical Systems, Otawara, Japan). Patient prep-aration included oral (75–150 mg) or IV (up to 15 mg) metoprolol andsublingual, fast acting nitrates. Computed tomography angiography(CTA) and CTP acquisitions were performed with 50–70 mL of iodi-nated contrast (Iopamidol 370 mg iodine/mL) injected intravenously at4.0–5.0 mL/s for eachof the separate, axial, prospectively ECG-triggeredacquisitions. Computed tomography myocardial perfusion images wereacquired during a continuous 6 min intravenous infusion of adenosineat a rate of 0.14 mg/kg/min IV. The effective radiation dose was estimatedfrom the dose–length product provided by the scanner.20

For all CTA and CTP acquisitions, de-identified sinograms were recon-structed, processed, and interpreted by independent core laborator-ies.18,19 The function of these two independent, centralized,laboratories have been described in detail previously; importantly, theCTP core lab was blinded from CTA and vice versa.19 Computed tomog-raphy angiography5,19 and CTP19,21 studies were interpreted by two sep-arate and independent and experienced investigators and disagreementswere resolved by consensus. ForCTA, all coronary lesions with a subject-ive stenosis of ≥30% underwent quantitative evaluation using a VitreaTM

fX version 3.0 workstation (Vital Images, Minnetonka, MN, USA). ForCTP, myocardial segments were categorized (0 ¼ normal myocardialperfusion, 1 ¼ mild, perfusion deficit, 2 ¼ moderate, and 3 ¼ severe)semi-quantitatively using visual assessment with additional support ofcustomized software (Myocardial Perfusion, Toshiba MedicalSystems).5,14,19,21 A summed stress score (SSS) was then calculated forall segments.21 Blinded adjudication22 was performed to meticulouslyverify co-registration of CTP defined perfusion defects with culpritvessels as defined by CTA.

Invasive coronary angiography (ICA) andsingle photon emission computed tomographydata acquisition and analysisClinically indicated ICA was performed using standard techniques within60 days of the combined CTA–CTP acquisition. Coronary segmentation

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used standard software (PIE Medical Imaging, Maastricht, the Nether-lands), and lesion severity was determined by quantitative coronary angi-ography.5 Single photon emission computed tomography acquisitions

used 99mTc-labelled imaging agents, with approximately 8 mCi for restand 25 mCi for stress MPI studies. Exercise or pharmacologic stresstesting with adenosine or dipyridamole infusion followed standard

Figure1 AcompleteCORE320 imagingdata set fora64-year-old malewithoutpriorhistoryof coronaryartery diseasewith chestpain 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 revealeda 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 ante-roseptal, the basal anteroseptal and apical walls. The left circumflex artery revealed an 87% diameter stenosis by CTA, a 79% diameter stenosis byICA, mild defects in the distal inferoseptal and distal inferolateral walls, and moderate defects in the distal anterolateral and distal anterior walls byCTP, and a moderate defect in the distal anterior wall by SPECT. The right coronaryartery revealed a 60% diameter stenosis by CTA, a 77% diameterstenosis by ICA, a mild defect in the distal inferoseptal wall by CTP, and no myocardial perfusion defects by SPECT.

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protocols.23 The procedures of the independent SPECT core laboratoryhave been described previously.18,19,22

Statistical analysisAll data from core laboratories and clinical database were analysed in thestatistical core laboratory at the Bloomberg School of Public Health. Theprimary analysis estimated the diagnostic accuracy, at the patient level, ofthe combination of quantitative CTA with visual semiquantitative CTPmeasurements, and using the Leaman score24 to adjust for lesion loca-tion, in comparison with the combination of quantitative ICA and visualSPECT/MPI measurements.

The analysis was based on the area under the receiver operating char-acteristic (ROC) curve (AUC). For the reference standard, each patientand vessel was classified as normal or having CAD, defined as ≥ 50% byICA with an associated perfusion defect by SPECT/MPI. The ROC curvewas based on a logistic regression analysis with CTA, CTP, and Leamanscore as predictor variables. The risk score (the linear predictor) fromthe logistic regression was used to construct the ROC curve. The AUCwas estimated non-parametrically using standard methods.25 The stand-ard error of the AUC was estimated using the bootstrap26 with resam-pling at the patient level, primarily to account for the prior estimationof 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, withthe patient being the unit of analysis. A sample size of 400 (including 10%dropout rate, i.e. 360)wasestimatedas necessary todetect a difference inthe AUCof fivepoints between the null and alternative hypothesis using aone-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%. Second-ary analyses based on a three vessel-territory (LAD, LCX, and RCA)model were adjusted for the effects of within patient clustering, alsousing the bootstrap.28 All data are reported with 95% CIs. The thresholdof significance was P , 0.05. Statistical analyses were performed usingSAS 9.1, Stata 11, and SPlus 8.0.

ResultsAmong 436 eligible patients recruited (November 2009–July 2011),55 wereexcluded (Figure 2) because the imaging was inadequate (n ¼16) or incomplete (n ¼ 39). In 10 of the 39 patients with incompleteimaging, the CTP component was uninterpretable. Table 1 sum-marizes the characteristics of 381 patients with all imaging plus the10 patients with uninterpretable CTP data due to protocol violations(n ¼ 391). The remaining 381 patients with complete imaging studieswere included in the primary diagnostic analysis. All imaging studieswere 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 temporaryatrioventricular block during adenosine infusion (Table 2).Thirty-eight percent of patients included in the primary analysis hada prior history of CAD [prior MI (27%), previous CAD documentedby invasive angiography or percutaneous coronary intervention(30%), with overlap between the two groups (19%)]. The medianestimated total body effective radiation doses for combined CTA–

CTP, SPECT, and ICA were 9.32, 9.75, and 12.0 mSv, respectively(Table 1).

Patient-based diagnostic performance ofcombined computed tomographyangiography–computed tomographymyocardial perfusion for detection of ahaemodynamically significant lesionFor the primary study endpoint, the AUC for combined CTA–CTPwas 0.87 [95% confidence interval (CI): 0.84–0.91] for the predictionof a 50% or greater stenosis by ICA with a corresponding perfusiondefect by SPECT (Figure 3). There was no difference in the primarystudy endpoint if the 10 patients with uninterpretable CTP studieswere considered positive [AUC: 87.3 (95% CI: 84–91)] or negative[87.6 (95% CI: 84–91)]. In patients without prior myocardial infarc-tion (n ¼ 278), the AUC for combined CTA–CTP was 0.90 (95%CI: 0.87–0.94) and in patients without prior CAD (n ¼ 236) theAUC for combined CTA–CTP was 0.93 (95% CI: 0.89–0.97)(Figure 3). Furthermore, we computed the AUC for patients withreversible defects only (i.e. excluding patients with fixed defects).The AUC for this subgroup of patients (n ¼ 344) was 0.89 (95%CI: 0.85–0.92), which was not different from the subgroup withoutprior myocardial infarction. There was no difference in AUC forpatients 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 ¼ 0.781].

The presence of stents, expressed as a history of previous PCI,likely influenced the findings of the CORE320 study. For all patientsenrolled in the study, the diagnostic power of CTA–CTP to identifya flow limiting stenosis defined by ICA–SPECT was AUC ¼ 0.87(95% CI: 0.84–0.91). However, when patients with a history of pre-vious PCI (stents) were excluded, the diagnostic power expressed inthe AUC increased to 0.93 (95% CI: 0.89–96).

When CTA alone (i.e. without perfusion CT) was used to predictICA–SPECT, the AUC was 0.84 (95% CI: 0.79–0.88), significantly(P ¼ 0.02) less than the 0.87 AUC for the combined CTA–CTP ap-proach. The sensitivity, specificity, positive predictive value (PPV),and NPV for the combination of a ≥50% stenosis on CTA with in-creasing thresholds of SSS on CTP to predict the primary endpoint(50% or greater stenosis by ICA with a corresponding perfusiondefect by SPECT) are shown in Table 3. For example, using a SSS of4 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 NPVwere 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 knownCAD, 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), thedegree of CAD was underestimated in 29 patients (false negative)and overestimated in 61 patients (false positive) compared with thecombined outcome of ICA–SPECT.

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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 coronaryangiography.

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Table 1 Baseline characteristics (n 5 391)

Characteristic Value

Age, year 62 (56–68)

Male sex 258 (66)

Ethnicity, number (%)

Hispanic 34 (9)

Non-hispanic 333 (85)

Other 24 (6)

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 suggestiveof CAD

120 (31)

Chest pain symptoms 44 (11)

Heart failure symptoms or shortness ofbreath

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)

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Table 1 Continued

Characteristic Value

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 YorkHeart Association classification; ACS, acute coronary syndrome; ECG,electrocardiogram; SD, standard deviation; CT, computed tomography; ICA,invasive coronary angiography; SPECT, single photon emission computedtomography; CTA, computed tomography angiography; mL, millilitre; mg,milligrams; mSv, millisieverts; bpm, beats per minute; CTP, computed tomographymyocardial perfusion.

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Vessel-based diagnostic performance ofcombined computed tomographyangiography–computed tomographymyocardial perfusion for detection of ahaemodynamically significant lesionIn a vessel-based analysis, the AUC for combined CTA–CTP topredict ICA + SPECT was 0.87 (95% CI: 0.84–0.89). When CTAalone (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 arteryand corresponding perfusion territory, the combined CTA–CTPAUC was 0.89 (95% CI: 0.86–0.93), and the CTA alone AUC was0.84 (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), signifi-cantly less (P ¼ 0.002) (Figure 4C). Finally for the right coronaryartery(RCA) and corresponding territory, the combined CTA–CTP AUCwas 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 ¼ 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, andin patients without known CAD are shown in Table 4. The sensitivity,specificity, PPV, and NPV for the LAD, LCx, and RCA are shown inSupplementary material online, 1.

DiscussionA single CT examination that includes angiography and perfusion candetect haemodynamically significant coronary stenoses defined as.50% by ICA with an associated SPECT/MPI perfusion defect inthe corresponding territory. The performance of the combinedtest improves for patients without known CAD, where the AUCreaches 0.93. CORE320 provides prospective multicentre, multi-national, comprehensive analyses to define the contribution ofCTP imaging over and above the established role of CTA.

Non-invasive myocardial perfusion has been the cornerstone ofclinical evaluation to detect CAD with established diagnostic andprognostic value.10,13,23,29 On the other hand, the presence andlocation of coronary lesions by catheterization is essential for a com-prehensive diagnosis, to evaluate prognosis, and to guide revascular-ization.5 –7 The current reference standard to assemble these datarequires serial imaging with more than one modality.10,11

CORE320 establishes CT as a single imaging platform to gatherboth morphologic and functional information with high accuracy.

Competing single modality image strategies has limitations. Mag-netic resonance imaging angiographyandperfusioncanbeperformedin a single examination, but the tradeoffs related to MRI dramatically

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Table 2 Serious adverse events and adverse events

Number ofpatients

CT associated serious adverse events

Renal failure 0

Reaction to contrast dye 3

Transient heart block 2

Hypotension 1

Extravasation of contrast agent in theantecubital fossa

Pulmonary edemaa 1

Vagal episode 1

Cardiovascular events

Death 0

Myocardial infarctionb 2

Stroke 0

Hospitalization for CV event 4

Coronary dissectionc 2

Chest paind 2

Femoral artery pseudo-aneurism(vascular event)e

Intracerebral bleeding/infarctf 1

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 duringdiagnostic 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.

Figure3 Receiveroperating characteristic (ROC)curveand cor-responding area under the curve (AUC) describing the diagnosticperformance of combined computed tomography angiography(CTA) and computed tomography myocardial perfusion (CTP) toidentify a ≥50% coronary stenosis and a corresponding myocardialperfusion using the reference standard of invasive coronary angiog-raphy (ICA) and single photon emission computed tomographymyocardial perfusion imaging (SPECT/MPI) at a patient level.

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limit the ability to obtain routine high quality coronary angiograms inclinically required scan times.30 While there are also theoretical pos-sibilities to estimate the pressure drop12 or transluminal attenuationgradients across specific coronary stenosis,31 these encouragingmethods are exploratory at this time and if proven useful, could becombined with data obtained at rest and/or during stress perfusionin a comprehensive CT examination.

The advantages and disadvantages of static vs. dynamic CTPimaging32 relate not only to the CT mode of imaging (volumevs. helical) but also to system capabilities of reducing radiation infirst, second, and third generation scanners, which allow for safeimplementation of dynamic CTP. Dynamic imaging enables theconstruction of a time-signal intensity relationship containing a

greater number of points than static imaging at peak stress andrest, which facilitates the identification of perfusion defects vs.artefacts. This is true not only for CT but also for MR perfusionimaging33 but implies greater radiation when CT is used and amore complex tradeoff between dose, spatial resolution, and arte-facts. On the other hand, volume CT has the advantages of arte-fact reduction and straightforward comparison between rest andstress studies with less radiation, greater spatial resolution, andless delineation of contrast dynamics as it traverses different myo-cardial regions during bolus administration. Further advances inCT technology should enhance the ability to obtain diagnosticCTP studies at lower radiation doses in combination with CTA.The results of this study should represent a template for the

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Table 3 Sensitivity, specificity, positive predictive value, and negative predictive value for computed tomographyangiography (CTA) (50% or greater) alone and CTA (50% or greater) with increasing levels of computed tomographymyocardial perfusion sum stress score to predict invasive coronary angiography stenosis ≥ 50% and a single photonemission tomography/myocardial perfusion imaging perfusion deficit

All patients (n 5 381)

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 ¼ 278)

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 ¼ 236)

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 predictivevalue.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.

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incorporation of such advances in the evaluation of patients withsuspected CAD.

Clinical implications, safety, and radiationexposureThe CORE320 protocol acquired rest CTA images before CTP to fa-cilitate 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 wouldthen proceed to having a stress CTP for clinical decision-making

within 1 h of the initial CT diagnosis. The clinical applicability of theproposed stress testing model is the subject of future clinical studies.

Radiation values reported in this study for both the gold-standardand CT protocols reflect the performance of these tests in the spe-cified research context. In this regard, normal CT angiograms orSPECT studies may prevent the performance of CT perfusion and in-vasive angiograms in a large percentage of patients with suspectedCAD, particularly in those with no history of previous CAD. There-fore, the values presented here should be used as guiding posts to aidthe treating physician in decision making about the risk/benefits offurther testing as data are accumulated for each patient.

Figure4 Receiveroperating characteristic (ROC) curve and corresponding area under the curve (AUC) describing the diagnosticperformance ofcombined 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 singlephoton emission tomography/myocardial perfusion imaging (SPECT/MPI) at a vessel level. (A) All vessels, (B) LAD, (C) LCX, and (D) RCA.

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Methodological considerationsWhile b-blockers used to lower patients’ heart rates may produce‘hidden’ ischaemia during adenosine infusion, the accuracy of thecombined approach argues that this theoretical limitation wasminimal because CTP when combined with CTA and comparedwith ICA–SPECT identified more false positive than false negativestudies. Like all modalities, CT has technical limitations, and bothmotion and beam-hardening artefacts can be mistaken formyocardialperfusion 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 con-tributed to false positive results in some patients. We acknowledgeinherent selection bias; specifically, a clinically positive SPECT study

may have influenced the decision to perform invasive angiographyand therefore made the patient eligible for study entry. However,there were no statistical differences in findings among those patientswho had aclinical vs. a researchSPECT, strongly suggesting that selec-tion bias had little or no influence on the study results. Single photonemission tomography/myocardial perfusion imaging is limited in sen-sitivity when compared with other imaging modalities, such as MRI,PET, and invasive FFR. The choice of SPECT/MPI as the perfusionmethod in the definition of a perfusion defect could have led to agreater number of false positive vessels/patients in the CORE320study. Conversely, SPECT/MPI may be more specific particularly insingle vessel CAD and was chosen because it is the most commonmethod of assessing myocardial perfusion non-invasively.

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Table 4 Vessel sensitivity, specificity, positive predictive value, and negative predictive value for computed tomographyangiography (CTA) (50% or greater) alone and CTA (50% or greater) with increasing levels of computed tomographymyocardial perfusion sum stress score to predict invasive coronary angiography stenosis ≥ 50% and a single photonemission tomography/myocardial perfusion imaging perfusion deficit

All vessels (n 5 1143)

Sensitivity Specificity PPV NPV

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 ¼ 834)

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 ¼ 708)

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 logisticmodel 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.

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ConclusionsThe combination of CTA and perfusion correctly identifies patientswith flow limiting CADdefinedas ≥ 50 stenosisby ICAcausing aper-fusion defect by SPECT/MPI. The exclusion of patients with previousmyocardial infarction or known CAD increased the diagnostic powerof combined CTA–CTP in the non-invasive detection of flow limitingCAD defined by ICA-SPECT/MPI.

Supplementary materialSupplementary material is available at European Heart Journal online.

FundingThe study sponsor, Toshiba Medical Systems Corporation, was notinvolved 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 fromToshiba Medical System. M.D., S.Y.T., N.P., and J.H. are on the speaker’sbureau 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 formPhilips Electronics, Bayer, Gerber, and Eisai. M.D. and J.A.C.L. grantsupport fromBracco Diagnostics. S.K. grant support fromDaiichi-SankyoPharmatheutical. M.J. grant support from AZE and Ziosoft. M.D. grantsupport from: European Regional Development Fund, German HeartFoundation, Guerbet, German Science Foundation, and GermanFederal Ministry of Education and Research. M.D. is on the speaker’sbureau for Guerbet, and Bayer-Schering. M.L. is a member of Speakersbureaus for Medtronic Inc, and Eesculap Akademie. M.D. consults forGuerbet and Richard George for ICON Medical Imaging. R.G. reportspaid board membership for GE Healthcare and Astellas Pharma.

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