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J Cardiovasc Comput Tomogr. 2016 Mar-Apr;10(2);121-7.

J Cardiovasc Comput Tomogr. 2016 Mar-Apr;10(2);121-7.
J Cardiovasc Comput Tomogr. 2016 Mar-Apr;10(2);121-7.

Research paper

Total coronary atherosclerotic plaque burden assessment by CT angiography for detecting obstructive coronary artery disease associated with myocardial perfusion abnormalities

Satoru Kishi a ,1,Tiago A.Magalh ~a

es b ,1,Rodrigo J.Cerci a ,Matthew B.Matheson c ,Andrea Vavere a ,Yutaka Tanami d ,Pieter H.Kitslaar e ,Richard T.George a ,

Jeffrey Brinker a ,Julie https://www.doczj.com/doc/e78866600.html,ler a ,Melvin E.Clouse f ,Pedro A.Lemos g ,Hiroyuki Niinuma h ,Johan H.C.Reiber e ,Carlos E.Rochitte g ,Frank J.Rybicki i ,Marcelo F.Di Carli j ,Christopher Cox c ,Joao A.C.Lima a ,Armin Arbab-Zadeh a ,*

a

Department of Medicine,Division of Cardiology,Johns Hopkins University School of Medicine,Baltimore,MD,USA

b

Department of Medicine,Division of Cardiology,Catholic University of Paran a

(PUC-PR),Brazil.c

Johns Hopkins University Bloomberg School of Public Health,Baltimore,MD,USA d

Department of Radiology,Keio University,Tokyo,Japan e

Division of Image Processing,Department of Radiology,Leiden University Medical Center /Medis Medical Imaging Systems,Leiden,The Netherlands f

Beth Israel Deaconess Medical Center,Harvard University,Boston,MA,USA g Heart Institute (InCor),University of Sao Paulo Medical School,S ~a o Paulo,Brazil h

Division of Cardiology,St.Luke's International Hospital,Tokyo,Japan i

The Ottawa Hospital Research Institute and the Department of Radiology,The University of Ottawa Faculty of Medicine,Ottawa,Canada j

Department of Radiology,Brigham and Women's Hospital,Harvard University,Boston,MA,USA

a r t i c l e i n f o

Article history:

Received 19November 2014Received in revised form 8December 2015

Accepted 11January 2016

Available online 14January 2016Keywords:

Coronary artery disease Coronary heart disease CT angiography

Myocardial perfusion Atherosclerotic plaque

a b s t r a c t

Background:Total atherosclerotic plaque burden assessment by CT angiography (CTA)is a promising tool for diagnosis and prognosis of coronary artery disease (CAD)but its validation is restricted to small clinical studies.We tested the feasibility of semi-automatically derived coronary atheroma burden assessment for identifying patients with hemodynamically signi ?cant CAD in a large cohort of patients with heterogenous characteristics.

Methods:This study focused on the CTA component of the CORE320study population.A semi-automated contour detection algorithm quanti ?ed total coronary atheroma volume de ?ned as the dif-ference between vessel and lumen volume.Percent atheroma volume (PAV ?[total atheroma volume/total vessel volume]?100)was the primary metric for assessment (n ?374).The area under the receiver operating characteristic curve (AUC)determined the diagnostic accuracy for identifying patients with hemodynamically signi ?cant CAD de ?ned as !50%stenosis by quantitative coronary angiography and associated myocardial perfusion abnormality by SPECT.

Results:Of 374patients,139(37%)had hemodynamically signi ?cant CAD.The AUC for PAV was 0.78(95%con ?dence interval [CI]0.73e 0.83)compared with 0.84[0.79e 0.88]by standard expert CTA interpre-tation (p ?0.02).Accuracy for both CTA (0.91[0.87,0.96])and PAV (0.86[0.81e 0.91])increased after excluding patients with history of CAD (p <0.01for both).Bland-Altman analysis revealed good agreement between two observers (bias of 280.2mm 3[161.8,398.7]).

Abbreviations:AUC,area under the receiver operating characteristic curve;CI,con ?dence interval;CTA,computed tomography angiography;ROC,receiver operating characteristic;SPECT,single photon emission tomography;PAV,percent atheroma volume;NTAV,normalized total atheroma volume.

*Corresponding author.Johns Hopkins University School of Medicine,Division of Cardiology,600N.Wolfe Street,Halsted 559,Baltimore,MD 21287-0025,USA.E-mail address:azadeh1@https://www.doczj.com/doc/e78866600.html, (A.Arbab-Zadeh).1

Authors contributed equally to this

study Contents lists available at ScienceDirect

Journal of Cardiovascular Computed Tomography

jo urnal homepag e:www.JournalofCard

https://www.doczj.com/doc/e78866600.html,

https://www.doczj.com/doc/e78866600.html,/10.1016/j.jcct.2016.01.005

1934-5925/?2016Society of Cardiovascular Computed Tomography.Published by Elsevier Inc.All rights reserved.

Journal of Cardiovascular Computed Tomography 10(2016)121e 127

Conclusions:A semi-automatically derived index of total coronary atheroma volume yields good accu-racy for identifying patients with hemodynamically signi?cant CAD,though marginally inferior to CTA expert reading.These results convey promise for rapid,reliable evaluation of clinically relevant CAD.?2016Society of Cardiovascular Computed Tomography.Published by Elsevier Inc.All rights reserved.

1.Introduction

Semi-automated contour detection algorithms based on CT coronary angiography(CTA)have shown promise for assessment of total coronary atherosclerotic plaque burden which may provide fast,reliable assessment of coronary artery disease(CAD).1,2How-ever,results are available only from relatively small clinical studies which focused on the main coronary arteries sparing side branches. In a recent study,evaluation of total atheroma burden by CTA performed better than standard lumen assessment for identifying coronary arteries with hemodynamically signi?cant coronary arterial stenosis as determined by fractional?ow reserve(FFR).3 These results emphasize the importance of atherosclerotic burden for determining coronary blood?ow restriction.Indeed,lower grade stenoses may cause critical reduction in coronary blood?ow in the presence of diffuse atherosclerotic disease.4On the other hand,FFR results may not correspond to myocardial perfusion data, which are more commonly used in clinical practice to guide med-ical management.5The purpose of this study was to test the feasibility and the diagnostic accuracy of total coronary atheroma assessment obtained by a semi-automated contour detection al-gorithm for identifying coronary artery disease associated with myocardial perfusion abnormalities in a large clinical cohort.

2.Methods

2.1.Study design and study population

The study design of the CORE320multicenter study has been previously detailed.6The CORE320study d Coronary Artery Evalu-ation using320-row Multidetector Computed Tomography Angi-ography and Myocardial Perfusion d is a prospective,multicenter, multinational,diagnostic study designed to compare the accuracy of combined CTA and myocardial computed tomography perfusion imaging(CTP)against the combination of invasive coronary angi-ography(ICA)and Single-Photon Emission Computed Tomography Myocardial Perfusion Imaging(SPECT-MPI).7Patients45to85years of age who were referred for clinically indicated ICA for suspected or known CAD were enrolled.

2.2.CT acquisition,image reconstruction,transfer,and analysis

A detailed description of CORE320-image acquisition and interpretation methods has been published.8In brief,all CT images were acquired before invasive angiography using a single protocol developed for a320?0.5mm-detector row CT system(Aquilion ONE,Toshiba Medical Systems,Otawara,Japan).Patient prepara-tion included oral(75e150mg)or IV(up to15mg)metoprolol and sublingual,fast-acting nitrates.Fifty to70mL of iodinated contrast (Iopamidol370mg iodine/mL)was injected intravenously at 4.0e5.0mL/sec for each of the separate,axial,prospectively ECG-triggered acquisitions.For all CTA acquisitions,de-identi?ed sino-grams were reconstructed,processed,and interpreted by inde-pendent core laboratories.CT data were reconstructed to generate 0.5-mm slice thickness images with a0.25-mm increment using both a standard(FC43)and a sharp(FC05)convolution kernel.Two level III certi?ed investigators evaluated each CTA study for the presence and severity of CAD;disagreements were resolved by consensus.Readers examined all coronary artery segments of 1.0mm in diameter or more for the presence of CAD using a19-segment coronary artery model.All coronary lesions with a sub-jective diameter stenosis of!30%underwent quantitative evalua-tion on a continuous scale(0e100%)using software tools(Vitrea?FX version3.0workstation,Vital Images,Minnetonka,MN,USA)at the discretion of the reader.Typical analysis time for each study was35e45minutes(range15e90minutes).The analysis was shorter in patients without known CAD(on average, 25e35minutes).

2.3.Coronary atheroma volume analysis

All reconstructed datasets were transferred to an of?ine work-station for quantitative coronary atheroma volume analysis using dedicated software with a semi-automated3-dimensional(3D) contour detection algorithm(QAngio CT Research Edition version 2.0RC4,Medical imaging systems(MEDIS),Leiden,the Netherlands).2,9,10The software was selected for our purposes based on its validation record and its user friendly interface. Quantitative atheroma analysis was performed by two indepen-dent,experienced observers who were blinded to initial CTA, quantitative coronary angiography(QCA),and clinical data.The reconstructed images were displayed at a window width of700and a window level of200to standardize quantitative coronary artery assessment.On the basis of longitudinal contours,cross-sectional images at0.5-mm intervals were obtained to create transversal lumen and vessel wall contours,using automated contour detec-tion techniques applied to the intensity gradients in the cross sections and guided by the longitudinal contours.These cross-sectional contours were examined and,if necessary,corrected by the observer(Fig.1).All coronary vessels were assessed using a19-coronary segment model,including each epicardial vessel and side branches with at least1.5mm in diameter.Therefore,we included smaller segments than in previous studies given the advancements in CT technology in recent years.Segments containing stents and those with poor image quality were excluded from analysis.The following parameters were derived per segment:vessel length, vessel volume,lumen volume,mean plaque burden,minimum and maximum plaque thickness,and mean lumen and plaque intensity. The plaque volume was calculated by subtracting the lumen vol-ume from the vessel volume.For each patient,the vessel,lumen, atheroma,and length values were calculated by adding all the analyzed segments.Required time for analysis(including editing) was typically20e30minutes per patient(range10e60minutes). Mean analysis time was shorter in patients without history of CAD, typically15e25minutes.

Based on prior investigations of plaque assessment,we de?ned three quantitative atheroma volume indices11:

1.Percent atheroma volume(PAV),%:(total atheroma volume/to-

tal vessel volume)?100.

2.Length normalized total atheroma volume(length normTAV),

mm3/m:total atheroma volume/total segment length.

S.Kishi et al./Journal of Cardiovascular Computed Tomography10(2016)121e127 122

3.Normalized total atheroma volume (normTAV),mm 3:(total atheroma volume/total segment length)?mean total vessel length;mean total vessel length ?average length of total vessel in the sample.Total lumen volume was also indexed to total segment length and LV mass.

2.4.Invasive coronary angiography acquisition and analysis Invasive angiography was performed using standard techniques within 60days following SPECT and CTA acquisition.Quantitative coronary angiography (QCA)was performed using standard,vali-dated analysis software (CAAS II QCA Research version 2.0.1,PIE Medical Imaging,Maastricht,The Netherlands).Coronary segments were de ?ned using a 19-coronary segment model,and all coronary segments 1.5mm or more in diameter were analyzed quantita-tively.Signi ?cant coronary artery stenosis (obstructive CAD)was de ?ned as !50%diameter stenosis by QCA.2.5.SPECT acquisition and analysis

Myocardial territories were analyzed by SPECT for rest and stress myocardial perfusion abnormalities with a severity and reversibility-scored,4-point scoring model using a 13-territory model.12The summed stress score (SSS)was de ?ned as the sum of abnormal myocardial segments at stress phase.7,8In the analysis,artifacts did not contribute to the summed stress score (SSS)and therefore a SSS !1de ?ned an abnormal SPECT study according to established methods of multi-center core SPECT laboratories.132.6.De ?nition of outcome

Study outcome was the presence of at least one !50%stenosis by QCA with an associated perfusion abnormality SPECT (SSS !1).7,12Ambiguities in regards to associations were resolved by a dedicated consensus committee compromised of the respec-tive core lab leaders.

2.7.Statistical analysis

Patients'data were summarized by using median and inter-quartile range for continuous variables and percent for categorical variables.Receiver operating characteristic (ROC)curves were used to determine the diagnostic performance of CTA stenosis and total coronary atheroma volume indices to predict ?ow-limiting coro-nary stenosis as de ?ned by the combination of QCA and SPECT.We compared the area under the ROC curve (AUC)for total coronary atheroma volume indices with standard expert CTA stenosis assessment for identifying patients with signi ?cant CAD and associated perfusion abnormality,using standard signi ?cance tests for paired data.In addition,95%con ?dence intervals were computed for differences between AUC values using the bootstrap with 2000samples.AUC values were computed using standard methods.Pre-speci ?ed sub-analyses included patients without history of coronary artery disease and restriction of plaque volume analysis to “core ”coronary segments,i.e.,proximal coronary seg-ments of the three coronary arteries (proximal and mid right cor-onary artery,left main,proximal and mid left anterior descending coronary artery,and proximal left circum ?ex coronary artery.All data were reported with 95%con ?dence intervals (CI).The 381CT studies were analyzed for coronary atheroma indices by two ob-servers who read 198and 183studies,respectively.The inter-observer agreement for total coronary atheroma volume was determined for 50randomly selected patients which were read by both observers;Bland-Altman plots were conducted to assess bias and inter-observer variability.Statistical signi ?cance was deter-mined at p values <0.05.All analyses were conducted using the statistical software packages SAS (version 9.3for Windows,SAS Institute Inc.,Cary,NC,USA)and Stata (version 12for Windows,StataCorp,College Station,TX,USA).3.Results

3.1.Clinical characteristics

Of 381patients included in the ?nal CORE320study sample,seven patients were excluded from this analysis because of poor overall image quality,resulting in a ?nal study population of 374patients.A total of 6,032coronary arterial segments were evalu-ated.Of these,189(3.1%)were excluded for analysis because they were uninterpretable by CT because of motion and/or poor contrast to noise ratio.Coronary calcium was not a reason for exclusion.Table 1displays the clinical data and baseline characteristics for the entire study population and according to the presence of at least one !50%stenosis by QCA and associated myocardial perfusion abnormality.The median age of all patients was 62years (range 56to 68years):67%were male,33%were Asian,11%were African-American,and 56%were Caucasian.Patients had a high preva-lence of risk factors (hypertension 78%,diabetes 34%,dyslipidemia 68%,current smoker 18%,and previous percutaneous coronary intervention 29%).The proportion of stable angina was 97%vs.3%unstable angina.Median calcium score was 161Interquartile Range [IQR 9,509]for all patients,251(68,579)in patients with known CAD and 111[1,404]in patients without prior history of CAD.3.2.Observer Variability for Plaque Volume Assessment by CTA

Bland-Altman analysis in 49patients (one study result out of 50was not available for technical reasons)revealed good agreement as shown in Fig.2.A bias was found of 280.2mm 3(95%CI:161.8,398.7)with a ratio of standard deviations of 1.17(95%CI:1.01,1.35).Based on the bias found,the ?nal results (vessel and lumen volume measurements)were adjusted using linear calibration curves

with Figure 1.Plaque Assessment by CT Angiography Using a Semi-Automated Contour Detection Algorithm (Panels A-D).(A)A CT image of the left anterior descending artery is shown using a curved multi-planar reformatted (cMPR)volume.(B)The same vessel as in A is shown after lumen and vessel wall contour tracking by the software.The dotted line indicates the site of cross-sectional image display in panels C and D.(C)A Cross-sectional image at the in B speci ?ed site is shown.Noncalci ?ed atherosclerotic plaque is noted resulting in moderate lumen encroachment.(D)The same image as in C is shown after contour tracing of the vessel and lumen borders which de ?ne the plaque area (vessel area minus lumen area).

S.Kishi et al./Journal of Cardiovascular Computed Tomography 10(2016)121e 127123

the more senior observer as the reference standard.3.3.Coronary artery disease evaluation

The measures of atheroma burden in subjects strati ?ed ac-cording to the reference standard incidence of coronary stenoses with myocardial perfusion abnormalities are shown in Table 2.Of 374patients,139patients (37.2%)had ?ow-limiting CAD.The me-dian CTA stenosis,length normTAV,PAV,and normTAV were 62%,6.0m 3/m,55.0%,and 2962.0mm 3,respectively (Table 2).

Diagnostic performance of CTA stenosis and quantitative total coronary atheroma volume indices for pre-detection of ?ow-limiting coronary stenosis.

Table 3and Fig.3show the diagnostic accuracies for CTA and atheroma indices.The AUC for predicting ?ow-limiting coronary stenosis for standard CTA stenosis assessment was 0.84(95%CI,0.79e 0.88)compared with 0.78(0.73e 0.83)for PAV (p ?0.02).The difference for AUC between CTA and PAV was 0.057(95%bootstrap CI:0.008,0.104).After excluding patients with stents AUC rose to 0.83for PAV (0.78e 0.88).The AUC for normTAV (0.72[0.67e 0.78])

was lower than that by PAV and CTA (p <0.001).When only the proximal coronary segments were considered in a subanalysis,the results were similar to that reported above for the entire coronary tree (Fig.3B).Accuracies were also similar when a perfusion defect by SPECT was not informed by the location of a stenoses by QCA,i.e.,and endpoint of any 50%QCA stenosis in the presence of any perfusion defect by SPECT in the same patient regardless of their location:AUC 0.85(0.81e 0.89)for CTA and 0.79for PAV ((0.75e 0.84),p ?0.03).The difference for AUC between CTA and PAV was 0.051(95%bootstrap CI:à0.005,0.105).Information by PAV or normTAV did not signi ?cantly improve AUC for CTA (Fig.3C and D).When separating the combined endpoint,AUC was greater for PAV vs.QCA alone ((0.85[0.81e 0.88])than PAV vs.SPECT alone (0.67[0.62e 0.67],p <0.001).Of note,in 85patients SPECT ?ndings were normal despite !50%stenosis by QCA while only 44patients with abnormal SPECT ?ndings had <50%stenosis by QCA.3.4.Accuracy for patients without previous coronary artery disease In patients without prior history of CAD,the diagnostic accuracy

Table 1

Baseline Patients Characteristics.Characteristic

All n ?374Stenosis y n ?139No stenosis n ?235p-value Age,in years

62.1(55.7e 68.4)62.0(55.6e 68.4)62.1(55.7e 68.5)0.62Male Gender,n (%)249(67)112(81)137(58)<0.0001Asian,n (%)

122(33)47(34)75(32)0.78

African American,n (%)43(11)14(10)29(12)Caucasian,n (%)209(56)78(56)131(56)Weight,Kg 74(65e 86)72(64e 86)74(65e 85)0.61Height,cm 167(160e 173)168(161e 174)166(158e 172)0.06BMI,kg/m 2

26.6(24.1e 30.1)26.2(24.0e 28.7)26.7(24.2e 30.8)0.08Hypertension,n (%)290(78)114(83)176(75)0.10Diabetes,n (%)

126(34)55(40)71(30)0.06Dyslipidemia,n (%)248(68)102(76)146(63)0.01Previous MI,n (%)

99(26)61(44)38(16)<0.0001Prior percutaneous coronary intervention,n (%)111(30)59(42)52(22)<0.0001Currently Smokes,n (%)63(18)19(15)44(19)0.15

Past Smoker,n (%)131(37)56(43)75(33)Never Smokes,n (%)

163(46)55(42)108(48)Family history of CAD,n (%)157(44)61(47)96(43)0.54Previous heart failure,n (%)NYHA class I 8(16)3(14)5(18)0.63

NYHA class II 40(82)18(86)22(79)NYHA class III 1(2)0(0)1(4)NYHA class IV

(0)

(0)

(0)

Angina at presentation Unstable angina,n (%)9(3)3(3)6(4)0.63

Stable angina,n (%)

251(97)104(97)147(96)Angina (within 30days),Canadian Class,n (%)061(22)15(13)46(27)0.005

1110(39)39(35)71(42)297(34)51(45)46(27)312(4)6(5)6(4)4

3

(1)

2

(2)

1

(1)

Prior Stress Testing (30days),n (%)ECG only 15(4)7(5)8(3)0.44Echo

8(2)5(4)3(1)0.13Prior Stress Testing Result,n (%)Positive

11(50)5(42)6(60)0.39Negative/equivocal 11(50)

7(58)

4(40)

LV mass*,g

148(128e 175)166(134e 186)144(126e 162)0.0001LV mass index*,g/m 2.7

36.7(32.6e 43.2)38.7(33.6e 46.7)36.1(32.0e 41.4)0.003Coronary artery stenosis (CTA !50%),n (%)246(66)129(93)117(50)<0.0001Coronary artery stenosis (QCA !50%),n (%)

223(60)132(95)91(39)<0.0001Myocardial hypo-perfusion (SPECT:SSS >0),n (%)187(50)139(100)48(20)<0.0001Myocardial ischemia (SPECT:SDS >0),n (%)

148

(40)

109

(78)

39

(17)

<0.0001

Continuous variable data are presented as median (interquartile range).

BMI ?body mass index;CAD ?coronary artery disease;CTA ?computed tomography angiography;LV ?left ventricular;MI ?myocardial infarction;QCA ?quantitative coronary angiography;SPECT ?single-photon emission computed tomography;SSS ?summed stress score;SDS ?summed difference score.*Incomplete data for LV mass:n ?332for all,n ?122for stenosis,and n ?210for no stenosis.y Stenosis refers to at least one !50%stenosis by QCA with related perfusion de ?cit by SPECT.

S.Kishi et al./Journal of Cardiovascular Computed Tomography 10(2016)121e 127

124

among the tested atheroma indices as well as the standard CTA assessment by expert readers was higher than for the entire cohort (Table 3).The AUC for PAV (0.86;CI,0.81e 0.91)was non-signi ?cantly lower than that from the expert-determined CTA ste-nosis evaluation (0.91;95%CI,0.87e 0.96,p ?0.08).AUCs of normTAV and length normTAV (0.80;95%CI,0.74e 0.86)were smaller than for expert-determined CTA stenosis (Table 3).In pa-tients with history of CAD,the AUCs of all parameters were less than 0.70,indicating modest performance.4.Discussion

A semi-automated derived index of percent atheroma volume (PAV)obtained by CTA identi ?ed patients with hemodynamically signi ?cant CAD with good diagnostic accuracy.Results were slightly inferior,however,compared with expert readers who assessed the CTA data sets by conventional methods.Reader

experience has been shown to in ?uence the results of standard CTA assessment.14High inter-observer agreement for the semi-auto-mated PAV evaluation raises hope for achieving consistent results among readers with a broad range of experiences even though the small reported bias among observers suggests some degree of experience may be indicated.15The software required little contour editing to achieve the reported performance,which resulted in shorter analysis times compared with standard CTA stenosis assessment.Our analysis was not restricted to proximal coronary segments but included the entire coronary tree.Thus,our results reveal promising diagnostic capabilities for plaque volume assess-ment by CTA which can be achieved in a rapid,reliable fashion.

While diagnostic accuracies of PAV -as well those by standard CTA -were solid for the entire study population,performance increased to good levels when only patients without prior CAD were considered.Since patients without prior CAD are the current target population for CTA assessment,clinical application of PAV may facilitate practical,reliable assessment for hemodynamically signi ?cant CAD similar to what has been achieved with noninvasive fractional ?ow reserve assessment by CT.16Furthermore,given the evidence for total plaque volume as an important risk factor for adverse coronary events,17it is conceivable that the prognostic information of such assessment will further enhance the clinical value of PAV evaluation.

Several recent studies addressed the diagnostic value of auto-mated contour detection algorithms by CTA.In comparison to intravascular ultrasound (IVUS),quantitative coronary atheroma assessment by CTA yielded good agreement 1,18Using percent aggregate plaque volume e which is comparable to PAV in the current study e a recent clinical study found superior diagnostic accuracy compared with standard lumen assessment by CTA for identifying hemodynamically signi ?cant coronary lesions.3Our results principally con ?rm the promising performance of plaque volume assessment by CTA,but extend its signi ?cance by assessing the entire coronary tree instead of studying individual lesions and by using myocardial perfusion imaging instead of FFR for hemo-dynamic assessment.While the reference standard for optimal CAD assessment remains controversial,19comprehensive myocardial blood ?ow assessment in addition to anatomic information carries some advantages over lesion speci ?c evaluation.5

Because

Figure 2.Variability of Atheroma Volume Assessment among Observers.Shown are Bland-Altman plots on the difference of total atheroma volume between observer 1and observer 2in 49patients.Bias was 280.20mm 3(95%CI:161.8,398.7with a ratio of standard deviations of 1.17(95%CI:1.01,1.35)).

Table 2

Quanti ?ed Coronary Artery Characteristics.Characteristic

All n ?374Stenosis z n ?139No Stenosis n ?235p-value Vessel length,mm 505.0(420.0e 570.6)463.5(385.3e 552.9)525.0(451.5e 582.4)<0.0001Vessel volume,mm 35388.4(4187.1e 6665.0)5282.9(4034.9e 6493.2)5458.9(4327.6e 6742.0)0.22Lumen volume,mm 32373.4(1799.8e 3002.0)2083.0(1583.0e 2752.7)2574.1(1964.4e 3154.7)<0.0001Plaque volume,mm 3

2946.4(2317.8e 3615.0)3099.5(2407.8e 3745.4)2864.4(2223.8e 3535.2)0.02Percent atheroma volume,%55.0(50.4e 60.0)

59.2(55.6e 63.5)

52.4(48.3e 57.5)

<0.0001Normalized TAV,mm 3

2962.0

(2520.4e 3409.6)3321.6

(2902.7e 3765.5)2804.2

(2355.4e 3186.4)<0.0001Length normalized TAV,mm 3/m 6.0(5.1e 6.9)

6.7(5.9e

7.6)

5.7(4.8e

6.5)

<0.0001Core Vessel length*,mm 139.1(115.5e 162.0)129.5(103.0e 150.0)148.0(124.5e 167.5)<0.0001Core Vessel volume*,mm 32388.9(1906.4e 3049.4)2212.8(1808.2e 2927.4)2480.3(1950.1e 3101.2)0.02Core Lumen volume*,mm 31025.9(785.0e 1432.0)856.6(714.4e 1172.8)1145.3(889.0e 1497.1)<0.0001Core Plaque volume*,mm 3

1341.9(1030.6e 1611.0)1343.4(1067.4e 1654.3)1332.1(1022.1e 1590.8)0.35Core Percent atheroma volume y ,%54.5(49.9e 60.4)

59.4(53.9e 64.8)

52.5(47.6e 57.2)

<0.0001Core Normalized TAV*,mm 3

1356.9

(1141.9e 1570.3)1493.7(1296.4e 1756.9)1266.8

(1094.9e 1465.2)<0.0001Core Length normalized TAV*,mm 3/m 9.8(8.3e 11.4)10.8(9.4e 12.7)9.2(7.9e 10.6)<0.0001Lumen volume/length,mm 3/m

4.8(4.1e

5.7)

4.5(3.8e

5.1)

5.0(4.2e 5.8)

0.0004Lumen volume/length/LV mass y ,mm 3/m/g 0.032(0.026e 0.041)0.028(0.023e 0.035)0.035(0.028e 0.042)<0.0001Coronary artery stenosis by CTA,%62(41e 89)91(69e 100)48(36e 67)<0.0001Coronary artery stenosis by QCA,%60(28e 91)95(76e 100)43(15e 63)<0.0001Calcium Score,Agatston score

161

(9e 509)

373

(143e 936)

64

(0e 300)

<0.0001

Continuous variable data are presented as median (interquartile range).*Core segments are proximal and mid right coronary artery,left main,proximal and left anterior descending coronary artery,and proximal left circum ?ex coronary artery.y Incomplete data for LV mass:n ?332for all,n ?67for revascularization,and n ?265for no revascularization.z Stenosis refers to at least one !50%stenosis by QCA with related perfusion de ?cit by SPECT;CTA ?computed tomography angiography;LV ?left ven-tricular;TAV ?total atheroma volume;QCA ?quantitative coronary angiography.

S.Kishi et al./Journal of Cardiovascular Computed Tomography 10(2016)121e 127125

atherosclerotic plaque burden in ?uences coronary blood ?ow in regard to its quantity and distribution,it may be better positioned to address the hemodynamic impact of CAD.20Future in-vestigations will de ?ne the role of coronary atheroma quanti ?ca-tion for clinical management,particularly,in comparison to the many emerging tools available with cardiac CT,e.g,myocardial perfusion imaging,CT-FFR,or transluminal attenuation gradient assessment.21

4.1.Limitations

Our study has limitations.First,the CORE320study was not designed to address the present research question and thus a po-wer calculation for this analysis was not performed.As power calculations would not be appropriate as a post hoc measure,we provide 95%con ?dence intervals for our analyses supporting the robustness of our ?ndings.It should also be noted that the CORE320

Table 3

Diagnostic Accuracy According to History of Coronary Artery Disease.

Overall

No history of CAD History of CAD Effect

AUC 95%CI AUC 95%CI AUC 95%CI p Percent atheroma volume,%0.780.73,0.830.860.81,0.910.600.51,0.69<.001Normalized TAV,mm 3

0.720.67,0.780.800.74,0.860.600.50,0.69<.001Length normalized TAV,mm 3/m 0.720.67,0.780.800.74,0.860.600.50,0.69<.001CTA stenosis,%

0.840.79,0.880.910.87,0.960.680.59,0.77<.001Core percent atheroma volume*,%0.750.69,0.800.830.77,0.890.600.51,0.69<.001Core normalized TAV*,mm 3

0.710.65,0.760.750.68,0.820.630.54,0.720.036Core length normalized TAV*,mm 3/m 0.710.65,0.760.750.68,0.820.630.54,0.720.036Lumen volume/length,mm 3/m

0.610.55,0.670.630.54,0.710.540.44,0.630.174Lumen volume/length/LV mass y ,mm 3/m/g 0.670.60,0.730.680.59,0.770.590.49,0.690.181Core Lumen volume*,mm 3

0.67

0.61,

0.73

0.66

0.58,

0.75

0.59

0.49,

0.69

0.276

*Core segments de ?nition is the same as in Table 2.y Incomplete data for LV mass:n ?332for all,n ?67for revascularization,and n ?265for no revascularization.AUC ?area under the receiver operating characteristic curve;CAD ?coronary artery disease;CI ?con ?dence interval;CTA ?computed tomography angiography;LV ?left ventricular;TAV ?total atheroma

volume.

Figure 3.Diagnostic Performance of Total Coronary Atheroma Volume Evaluation Compared with Standard CTA Assessment.Panel A shows the ROC curves for percent atheroma volume (AUC,0.78;95%CI,0.73e 0.83),normalized total atheroma volume (AUC,0.73;95%CI,0.67e 0.78),and CTA stenosis (AUC,0.84;95%CI,0.79e 0.88)for identifying a patient with !50%stenosis by quantitative coronary angiography and associated myocardial perfusion abnormality by SPECT.There was a signi ?cant difference in AUC between the percent atheroma volume curve and the CTA stenosis curve (p ?0.02)and normalized total atheroma volume (p ?0.04).There was also a signi ?cant difference in AUC between normalized total atheroma volume curve and CTA stenosis curve (p ?0.001).Panel B shows the same analysis as in Panel A but restricted to proximal coronary arterial segments (left main coronary artery,proximal and mid left anterior descending artery,proximal and mid right coronary artery,and proximal left circum ?ex coronary artery).There was a signi ?cant difference in AUC between core normalized total atheroma volume curve and CTA stenosis curve (p <0.001)and between core CTA stenosis and core percent atheroma volume curve (p ?.0007),however a signi ?cant difference was not found between core percent atheroma volume and core normalized total atheroma volume (p ?0.23).Panel C shows the diagnostic accuracy when information from CTA is combined with percent atheroma volume or normalized total atheroma volume,respectively.There is no statistically signi ?cant increase in diagnostic accuracy for either index over standard CTA evaluation.Panel D shows the same analysis as in Panel C but restricted to proximal coronary segments.There is no statistically signi ?cant increase in diagnostic accuracy for either index over standard CTA evaluation.

S.Kishi et al./Journal of Cardiovascular Computed Tomography 10(2016)121e 127

126

study population contains patients who are at higher risk than typically seen with the application of CTA.Thus,results may not be applicable to low risk populations.Second,prospectively total atheroma assessment was limited to non-stented segments.Third, we excluded coronary artery segments of less than1.5mm diam-eter for plaque assessment because of CT's modest spatial resolu-tion in comparison with ICA.Fourth,we recognize that this study does not assess the incremental value of plaque volume analyses when combined with CTA,or with CTA plus CT myocardial perfu-sion imaging.However,the purpose of this study was to establish the diagnostic accuracy of a rapid,practical tool for CAD assessment e without the need for additional imaging.Fifth,the contour detection algorithm undergoes frequent upgrades and improve-ments,some of them not included in our version.For example,we noted that the software computed substantial“plaque”volumes even in patients without visually apparent CAD,indicating that these data had high residual noise levels.Further improvements in software performance may allow trimming such noise for the bene?t of better diagnostic performance.Similarly,there is hope that further software upgrades may allow including smaller seg-ments,stented lesions,and perform better with poor image quality or extensive calci?https://www.doczj.com/doc/e78866600.html,stly,it should be noted that the soft-ware is for research purposes only at this time and not yet validated for clinical use.

5.Conclusions

In patients without history of coronary artery disease,a semi-automatically derived index of percent atheroma volume by CTA yields good accuracy for identifying obstructive coronary artery disease that is associated with myocardial perfusion abnormalities. These results,while slightly inferior to expert evaluation,convey promise for a rapid,reliable assessment of clinically relevant cor-onary artery disease.Future software developments are likely to expand the performance and the role of automated assessments of CAD by CTA for clinical practice.

Funding Sources

The sponsor of the CORE320study,Toshiba Medical Systems Corporation,was not involved during any stage of the planning, design,data acquisition,data analysis,or manuscript preparation of this study.

Disclosures

Dr.J.H.C.Reiber has a part-time appointment as Prof of Medical Imaging at the Leiden University Medical Center(LUMC)and is the CEO of Medis medical imaging systems,Leiden,the Netherlands.

P.Kitslaar has a research appointment at the LUMC,Division of Image Processing(LKEB),Dept of Radiology and is an employee of Medis,Leiden,the Netherlands.

Drs Rybicki and Arbab-Zadeh disclose their membership of the CORE320steering committee.The CORE320study was sponsored by Toshiba Medical Systems.

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