Quick search in Citations
This JournalAnywhereCitation
Advanced Search
Research Article
Originally Published 3 February 2012
Free Access

Comparison of Exercise Treadmill Testing With Cardiac Computed Tomography Angiography Among Patients Presenting to the Emergency Room With Chest Pain: The Rule Out Myocardial Infarction Using Computer-Assisted Tomography (ROMICAT) Study

Ron Blankstein, MD, Waleed Ahmed, MD, Fabian Bamberg, MD, MPH, Ian S. Rogers, MD, MBA, MPH, Christopher Lothar Schlett, MD, Khurram Nasir, MD, MPH, Joao Fontes, MD, Ahmed Tawakol, MD, Thomas J. Brady, MD, John T. Nagurney, MD, MPH, Udo Hoffmann, MD, MPH, and Quynh A. Truong, MD, MPHAuthor Info & Affiliations
Circulation: Cardiovascular Imaging
Volume 5, Number 2
https://doi.org/10.1161/CIRCIMAGING.111.969568
Track CitationsAdd to favorites
PDF/EPUB

Abstract

Background—

The aims of our study were to (1) examine how data from exercise treadmill testing (ETT) can identify patients who have coronary plaque or stenosis, using CT angiography (CTA) as the reference standard, and (2) identify patient characteristics that may be used in selecting ETT versus CTA.

Methods and Results—

The Rule Out Myocardial Infarction Using Computer-Assisted Tomography (ROMICAT) trial was an observational cohort study of acute chest pain patients presenting to the emergency department with normal initial troponin and a nonischemic ECG. Univariate and multivariable analyses were performed to assess the relationship of baseline clinical data and ETT parameters with coronary plaque and stenosis on CTA. Of the 220 patients who had ETT (mean age, 51 years; 63% men), 21 (10%) had positive results. A positive ETT had a sensitivity of 30% and specificity of 93% to detect >50% stenosis. The sensitivity increased to 83% after excluding uninterpretable segments and evaluating the ability to detect a >70% stenosis. Predictors of plaque included older age, male sex, diabetes, hypertension, hyperlipidemia, lower functional capacity, and a lower Duke Treadmill Score. Both a positive ETT and a low Duke Treadmill Score were significant univariate and multivariable predictors of stenosis >50% on CTA Whereas the prevalence of stenosis by CTA was greater among patients with more risk factors, coronary stenosis was not present among men <40 years old or women <50 years old or individuals who achieved at least 13 metabolic equivalents on ETT.

Conclusions—

Among low- to intermediate-risk patients with acute chest pain, a positive ETT has a limited sensitivity but high specificity for the detection of >50% stenosis by CTA. Although patients with a high number of clinical risk factors are more likely to have obstructive coronary artery disease, those who are young or who would be expected to have a very high exercise capacity are unlikely to have coronary stenosis and therefore may benefit from initial ETT testing instead of CTA.

Introduction

Exercise treadmill testing (ETT) is a well-validated, inexpensive test that can be used for the evaluation of patients with suspected coronary artery diseases (CAD).1 In addition to identifying patients who have exercise-induced ECG changes suggestive of ischemia, ETT also provides important data on exercise capacity, blood pressure, and heart rate response to exercise, symptoms, and the presence of exercise-induced arrhythmias. In patients who are able to exercise, this information can then be used to establish short- and long-term risk of mortality and cardiovascular events.2,3 Nevertheless, ETT has an imperfect sensitivity and specificity for the identification of obstructive CAD and does not reliably identify whether CAD is present or absent.4,5
Clinical Perspective on p 242
Coronary CT angiography (CTA) allows for the noninvasive visualization of coronary atherosclerosis and can detect the presence of obstructive coronary artery disease. Recently, it has been shown that an effective clinical use of this test may be among low- to intermediate-risk patients presenting to the emergency department with acute chest pain.6–10 In this population, the absence of any coronary plaque can effectively rule out the presence of an acute coronary syndrome and identify patients with excellent prognosis. Nevertheless, the use of CTA in this setting is limited as it exposes patients to radiation, requires iodinated contrast, and cannot provide information on functional capacity.11
Although both CTA and ETT can be used to evaluate low- to intermediate-risk patients presenting to the emergency department, there is a paucity of studies that directly compare these tests in patients with acute chest pain. Therefore, we sought to (1) examine how data from ETT can identify patients who have coronary plaque or stenosis, using CTA as the reference standard, and (2) identify patient characteristics which could be used in selecting between ETT and CTA.

Methods

Study Population

Details of the Rule Out Myocardial Infarction Using Computer-Assisted Tomography (ROMICAT) study have been previously reported.7 Briefly, ROMICAT was a double-blinded, single-center, prospective, observational cohort study of 368 consecutive adult patients at low to intermediate likelihood of acute coronary syndrome who presented to the emergency department of Massachusetts General Hospital with acute chest pain whose initial ECG and biomarkers were inconclusive. The intake period was a cumulative period of 18 months, ending in May 2007. Exclusion criteria were notable for patients with atrial fibrillation and serum creatinine >1.3 mg/dL. All eligible patients who consented underwent ECG-gated contrast-enhanced 64-slice multidetector CT. All patients and caregivers were blinded to the findings of the CT. Patients received standard of care to rule out acute coronary syndrome during index hospitalization, including serial ECGs, biomarkers, and cardiac testing as clinically requested by the patient's caring physicians. The institutional review board approved the study protocol and all patients provided written informed consent.
The current study population included 220 patients referred for an ETT as part of their standard clinical care, including 117 patients who had an ETT without imaging and 103 patients who had an ETT as part of a stress myocardial perfusion imaging (MPI) study. None of the patients had a pacemaker, Wolf-Parkinson-White pattern on their ECG, or were taking digoxin. Two patients who were referred for MPI had an uninterpretable ECG due to baseline ST-segment depressions and were excluded from the study.

CTA Acquisition

CTA was performed using a standard 64-slice multidetector CT coronary angiography (Sensation 64, Siemens Medical Solutions, Forchheim, Germany) protocol that was acquired at end inspiration and included the administration of sublingual nitroglycerin (0.6 mg) and intravenous β-blocker (metoprolol 5–20 mg) for those with the baseline heart rate >60 beats per minute and no other contraindications. A test bolus protocol was used to determine the optimal timing of contrast injection (20 mL contrast agent followed by 40 mL saline, flow rate of 5 mL/s). CTA acquisition used 80–100 mL of contrast (Iodixanol 320 mg/mL, General Electrics Healthcare, Princeton, NJ) followed by 40 mL saline at a rate of 5 mL/s.
CT images were acquired in spiral mode, gantry rotation time of 330 ms, 64×0.6 mm slice collimation, tube voltage of 120 kV, effective tube current of 850–950 mA, with ECG tube current modulation when appropriate. For coronary artery assessment, axial images were reconstructed with the use of a medium sharp convolution kernel with a slice thickness of 0.75 mm and increment of 0.4 mm.

CTA Interpretation

For the detection of CAD, the 17-segment model based on the American Heart Association classification with the addition of the posterior left ventricular branch as segment 16 and the ramus intermedius as segment 17 was used.12 For each of the 17 segments, coronary atherosclerotic plaque, plaque composition (calcified, mixed, or noncalcified), and stenosis was visually classified as either present or absent as determined by two reader consensus using Leonardo workstation (Siemens Medical Solutions, Forchheim, Germany).13 Readers were blind to all clinical data, including ETT and MPI test results. For each lesion causing luminal obstruction, stenosis severity was categorized as >50% or >70% by diameter. The extent of coronary plaque burden was scored from 0–17 and treated as a continuous variable.

Exercise Treadmill Testing

The majority of ETTs (218 of 220) used a symptom-limiting Bruce protocol according to established guidelines1 as part of routine clinical care. For 2 patients, a manual exercise protocol was used. During each examination, continuous 12-lead ECG monitoring was obtained. The target heart rate was determined as 85% of the maximum predicted heart rate (MPHR=220 minus age). The ETT study was considered diagnostic if the patient reached target heart rate, achieved a peak pressure product >25 000, or developed typical angina symptoms during the test. A positive ETT was defined as upsloping ST depressions ≥1.5 mm or downsloping/horizontal depressions ≥1.0 mm in at least 2 leads. All ST-segment measurements were performed 80 ms after the J point. The maximum ST-segment depression from all leads was used to represent the overall magnitude of ST-segment depression for the study. The Duke Treadmill Score (DTS) was calculated for each patient who completed the Bruce protocol as exercise time (minutes) minus (5× maximal ST-segment depression in millimeters) minus (4× angina index; 0, no angina; 1, angina; 2, angina as reason for stopping test).
Among the subgroup of patients who had single-photon emission computed tomography (SPECT) MPI as part of their ETT test, we performed an exploratory analysis to examine the SPECT MPI results when ETT and CTA findings were discrepant. A positive SPECT MPI was defined as a summed stress score ≥3.

Covariates of Interest

Cardiovascular risk factors and medical history were assessed at the time of subject enrollment, based on self-report as well as the medical records during the index hospitalization. Body mass index was defined as weight (kilograms) divided by the height squared (meters). Hypertension was defined as systolic blood pressure of at least 140 mm Hg or diastolic blood pressure of at least 90 mm Hg or current antihypertensive treatment. Diabetes mellitus was defined as a fasting plasma glucose ≥126 mg/dL or treatment with a hypoglycemic agent. Hyperlipidemia was defined as total cholesterol of ≥200 mg/dL or treatment with a lipid-lowering medication. Family history of CAD was defined as having a first-degree female (<65 years) or male (<55 years) relative with a documented history of myocardial infarction or sudden cardiac death. Subjects were classified as smokers if they had smoked at least 1 cigarette per day in the year before the study.

Statistical Analysis

Continuous variables were expressed as mean±SD or medians (interquartile range), where appropriate; categorical variables were described by frequency. The differences in means between 2 groups were determined using Student t test for continuous variables and differences in proportions were determined by Fisher exact or χ2 test, as appropriate.
When determining the diagnostic accuracy of a positive ETT to detect stenosis on CTA, lesions for which stenosis by CTA could not be excluded (ie, uninterpretable segments) were counted as positive. However, because there is often a lack of certainty about whether such patients truly have obstructive disease, we also recalculated the diagnostic accuracy when these segments were excluded.
We used logistic regression to identify clinical and ETT predictors of coronary plaque and coronary artery stenosis ≥50%. The clinical (ie, before including ETT parameters) multivariable models included variables that were clinically relevant and demonstrated a univariate association with the dependent variable of interest. To avoid model overfitting and given the strong correlation between many of the ETT parameters evaluated (eg, exercise time, metabolic equivalents [METS] achieved, DTS), each ETT parameter was added separately to the baseline multivariable model, which included only clinical variables.
In addition, we examined the distribution of patient characteristics (eg, age and sex) and traditional clinical risk factors in order to identify cut-points that can be used to exclude the presence of coronary artery stenosis. A 2-tailed probability value of <0.05 was considered to indicate statistical significance. All analyses were performed using SAS (Version 9.2, SAS Institute Inc, Cary, NC) and Stata (IC, Version 11.0, College Station, TX).

Results

Baseline Characteristics

Table 1 depicts the baseline characteristics of the study population. In comparison to patients referred for ETT without imaging, those referred for ETT with SPECT were older, more likely to have hypertension, and had a higher Thrombolysis In Myocardial Infarction risk score. Consequently, patients referred for SPECT were significantly more likely to be diagnosed with unstable angina during the index hospitalization [10 (10%) versus 2 (2%), P=0.01].
Table 1. Baseline Characteristics and 6-Month Follow-Up of Patients Stratified by Type of Treadmill Testing Performed
 All Patients (n=220)ETT Only (n=117, 53%)ETT With SPECT (n=103, 47%)P Value
Age, y, mean±SD51±1050±953±110.04
Male sex, n (%)139 (63%)80 (68%)59 (57%)0.09
Race   0.15
    White188 (85%)104 (89%)84 (82%) 
    African American18 (18%)9 (8%)9 (9%) 
    Other14 (6%)4 (3%)10 (10%) 
Body mass index, kg/m2, mean±SD29±629±630±60.30
Diabetes, n (%)18 (8%)8 (7%)10 (10%)0.44
Hypertension, n (%)71 (32%)31 (27%)40 (39%)0.05
Hyperlipidemia, n (%)78 (35%)36 (31%)42 (41%)0.12
Family history, n (%)56 (25%)27 (23%)29 (28%)0.38
Smoking, n (%)   0.55
    Never smoked113 (51%)64 (55%)49 (48%) 
    Current smoker58 (26%)28 (24%)30 (29%) 
    Former smoker49 (22%)25 (21%)24 (23%) 
TIMI risk score, n (%)   0.0009
    Low211 (96%)117 (100%)94 (91%) 
    Intermediate8 (4%)08 (8%) 
    High1 (<1%)01 (1%) 
Acute coronary syndrome during index hospitalization, n (%)   0.01
    Myocardial infarction0 (0%)0 (0%)0 (0%) 
    Unstable angina pectoris12 (5%)2 (2%)10 (19%) 
Six-month follow-up   0.058
    Major adverse cardiovascular events000 
    Outpatient visit without testing18 (8%)7 (6%)11 (11%) 
    Outpatient visit with testing4 (2%)1 (1%)3 (3%) 
    Readmission without testing1 (<1%)1 (1%)0 
    Readmission with testing5 (2%)5 (4%)0 
ETT indicates exercise stress testing; SPECT, single-photon emission computed tomography; TIMI, Thrombolysis In Myocardial Infarction.

ETT Results

A total of 21 (10%) of 220 treadmill tests were considered positive by ECG criteria. When considering the exercise parameters (Table 2), 180 (82%) of the patients achieved their target heart rate. Of the 40 patients who did not achieve an adequate target heart rate, 10 had a peak pressure product >25 000 and 30 had typical angina during the test. When combining these criteria, 214 (97%) patients were considered to have diagnostic studies. Of the 6 patients with nondiagnostic studies, only 1 was found to have an acute coronary syndrome (and was also the only patient in this group that had stenosis on CTA).
Table 2. Exercise Parameters of Patients Undergoing ETT
 All Patients (n=220)ETT Only (n=117, 53%)ETT With SPECT (n=103, 47%)P Value
Positive ETT test21 (10%)9 (8%)12 (12%)0.36
Patients achieving target heart rate, n (%)180 (82%)101 (86%)79 (77%)0.08
Diagnostic study214 (97%)116 (99%)98 (95%)0.10
Exercise time, min9.3±310±39±30.006
METS achieved10.9±311.5±310.3±30.04
Duke Treadmill Score8±48.5±47.3±40.026
Resting SBP, mm Hg120±16118±15123±170.03
Resting DBP, mm Hg75±1075±975±110.69
Baseline HR, bpm70±1171±1269±110.51
Peak HR, bpm153±19156±18149±200.015
Percentage of maximum heart rate achieved, %90±991±989±100.36
Peak SBP, bpm163±23162±22164±240.71
Double product, ×100024.9±4.825.3±4.724.4±4.90.17
Patients with angina during stress test, n (%)74 (21%)28 (24%)19 (18%)0.32
Duration of angina, min8±38±48±30.50
ETT indicates exercise stress testing; SPECT, single-photon emission computed tomography; METS, metabolic equivalents; SBP, systolic blood pressure; DBP, diastolic blood pressure; HR, heart rate.
The mean exercise time for all patients in the study was 9.3 minutes, and on average 10.9 METS were achieved. Patients referred for ETT with SPECT imaging had a lower exercise capacity and a lower DTS; however, the proportion of positive ETT tests in each of these subgroups was similar (12% versus 8%, P=0.36).

CTA Results

By CTA, 68 (31%) of patients had plaque without stenosis, whereas 33 (15%) had stenosis. Among them, 6 patients had stenosis >70%. The remaining 119 (54%) patients had no plaque or stenosis. Among the 101 patients with CAD, the average number of segments with plaque was 4±3; a positive ETT was associated with a higher number of segments with calcified plaque (Figure 1).
Figure 1. Extent and type of plaque among patients with coronary artery disease, stratified by positive and negative exercise treadmill testing (ETT) results.
In comparison to patients with no plaque or stenosis, those with disease (Table 3) were older and had lower exercise time, work load, and DTS. The presence of angina during testing was not related to the presence of plaque or stenosis.
Table 3. ETT Characteristics of Patients With and Without Coronary Plaque on CTA
 Any Plaque by CTA (n=101, 46%)No CAD by CTA (n=119, 54%)P Value
Age, y, mean±SD55±1048±9<0.001
Exercise time, min8.7±2.89.8±2.60.001
METS achieved10.1±3.211.6±2.9<0.001
Duke Treadmill Score6.9±4.38.9±3.5<0.001
Percentage of maximum predicted heart rate89%±9.8%91%±9.5%0.04
Positive ETT, n (%)13 (13%)8 (7%)0.09
No. of patients with any horizontal ST depression6 (6%)2 (2%)0.09
No. of patients with upsloping ST depression0 (0%)5 (4%)0.045
No. of patients with downsloping ST depression7 (7%)1 (1%)0.019
Angina during stress test, n (%)25 (25%)22 (18%)0.259
Significant atrial or ventricular ectopy, n (%)58 (57%)55 (46%)0.097
ETT done with SPECT, n (%)57 (56%)46 (39%)0.008
ETT indicates exercise stress testing; CTA, CT angiography; CAD, coronary artery disease; SPECT, single-photon emission computed tomography.

Diagnostic Accuracy of ETT for Detection of Stenosis by CTA

Positive ETT had a sensitivity of 0.30 and specificity of 0.94 for detection of stenosis ≥50% by CTA (Table 4). When confining this analysis to the 180 patients who achieved ≥85% of their MPHR, the sensitivity increased to 0.41, whereas the specificity was unchanged. Accordingly, the sensitivity of ETT among patients with submaximal heart rate was low (9%), as only 1 of 11 patients in this group who had stenosis had a positive ETT by ECG criteria (see Figure 2 for examples of CTA and ETT correlations).
Table 4. Diagnostic Accuracy of a Positive ETT to Detect Plaque/Stenosis on CTA
Reference CriteriaPrevalence of (+) ETTPrevalence of (+) CTASensitivitySpecificityPPVNPV
CTA with any plaque or stenosis21/220101/2200.13 (0.07–0.21)0.93 (0.87–0.97)0.62 (0.38–0.82)0.56 (0.49–0.63)
CTA 50% threshold criteria      
    >50% Threshold or CTA uninterpretable      
    All patients21/22033/2200.30 (0.16–0.49)0.94 (0.90–0.97)0.48 (0.26–0.70)0.88 (0.83–0.93)
    Patients achieving ≥85% MPHR19/18022/1800.41 (0.21–0.63)0.94 (0.89–0.97)0.47 (0.24–0.71)0.92 (0.87–0.96)
    >50% Threshold (excluding patients with uninterpretable segments)      
    All patients18/20215/2020.47 (0.21–0.73)0.94 (0.90–0.97)0.39 (0.17–0.64)0.96 (0.92–0.98)
    Patients achieving ≥85% MPHR16/16810/1680.60 (0.26–0.88)0.94 (0.89–0.97)0.38 (0.15–0.65)0.97 (0.93–0.99)
CTA 70% threshold criteria      
    >70% Threshold or CTA uninterpretable      
    All patients21/22024/2200.33 (0.16–0.55)0.93 (0.89–0.96)0.38 (0.18–0.62)0.92 (0.87–0.95)
    Patients achieving ≥85% MPHR19/18018/1800.44 (0.22–0.69)0.93 (0.88–0.97)0.42 (0.20–0.67)0.94 (0.89–0.97)
    >70% Threshold (excluding patients with uninterpretable segments)      
    All patients18/2026/2020.83 (0.36–1.00)0.93 (0.89–0.96)0.28 (0.10–0.54)1.00 (0.97–1.00)
    Patients achieving ≥85% MPHR16/1686/1680.83 (0.36–1.00)0.93 (0.88–0.97)0.31 (0.11–0.59)0.99 (0.96–1.00)
Sensitivity, specificity, PPV, and NPV were calculated in all patients (n=220) and in a subgroup of patients who achieved ≥85% of the MPHR.
ETT indicates exercise stress testing; CTA, CT angiography; PPV, positive predictive value; NPV, negative predictive value; MPHR, maximum predicted heart rate.
Figure 2. Examples of CT angiography (CTA) findings from patients with positive and negative exercise treadmill testing (ETT). A, Forty-year-old man presenting with acute chest pain. CTA identified the presence of mostly calcified plaque in the mid left anterior descending artery (LAD), resulting in significant stenosis. ETT was positive due to 1-mm horizontal ST depressions in leads V3-V6. B, Fifty-one–year-old man with chest pain. CTA identified large amount of plaque in the mid LAD, resulting in significant stenosis. On ETT testing, the patient exercised for 9 minutes on the Bruce protocol (10 metabolic equivalents) and had no significant ECG changes.
When patients with uninterpretable segments were excluded, the sensitivity of ETT to identify stenosis >50% increased to 0.47 (and 0.60 when the analysis was confined to the 180 patients who achieved ≥85% of their MPHR), whereas the high specificity was unchanged. When stenosis on CTA >70% was used as the reference standard, the sensitivity to detect stenosis increased from 0.33 and 0.44 (among patients achieving ≥85% of MPHR) to 0.83, whereas the specificity remained unchanged (Table 4).

Exploratory Analysis of Discrepant ETT and CTA Results

Among the 103 patients who had SPECT MPI performed as part of their ETT test, 14 (14%) individuals had a perfusion defect. Of 4 patients who had positive ETT results but no stenosis on CTA, none had a perfusion defect on SPECT imaging. On the other hand, 3 of 5 (60%) patients that had a negative ETT but stenosis on CTA had a positive SPECT MPI. Of 6 patients who had both stenosis on CTA and a positive ETT, 4 (66%) had a perfusion defect on SPECT imaging. Only a small proportion (5 of 76; 7%) of individuals who had both a negative ETT and no stenosis on CTA had a perfusion defect on SPECT MPI.

Predictors of Coronary Plaque and Stenosis

Tables 5 and 6 show univariate and multivariable predictors for plaque or stenosis on CTA. Older age, male sex, diabetes, and hypertension all had a significant univariate association with plaque and stenosis. The presence of hyperlipidemia had a significant association with the presence of plaque but not for stenosis, whereas having a family history of CAD was only associated with stenosis.
Table 5. Clinical and ETT Parameters Predicting the Presence of Plaque on Univariate and Multivariable Analysis
Clinical PredictorsAt Least 1 Segment With Any Plaque
Univariate AnalysisMultivariable Analysis
ORP ValueORP Value
For every decile of age2.41<0.0013.00<0.001
Male sex2.280.0055.91<0.001
Diabetes4.630.0093.440.061
Hypertension3.14<0.0012.360.021
Hyperlipidemia2.92<0.0011.830.08
Family history1.250.47  
Smoking1.130.67  
ETT parameters    
    Positive ETT2.050.131.54*0.44
    Exercise time, per minute change0.850.0020.88*0.058
    METS achieved0.850.0010.87*0.018
    Duke Treadmill Score0.88<0.0010.91*0.044
    Angina with stress2.050.1281.16*0.71
ETT indicates exercise stress testing; OR, odds ratio; METS, metabolic equivalents.
*
ETT parameters were each added individually to multivariable model, which included age, sex, diabetes, hypertension, and hyperlipidemia.
Table 6. Clinical and ETT Parameters Predicting the Presence of Stenosis of >50% in at Least 1 Segment on Univariate and Multivariable Analysis
Clinical PredictorsAt Least 1 Segment With Stenosis >50%
Univariate AnalysisMultivariable Analysis
ORP ValueORP Value
For every decile of age2.53<0.0013.55<0.001
Male sex2.430.056.210.001
Diabetes5.670.0015.270.012
Hypertension4.10<0.0012.890.026
Hyperlipidemia1.900.09  
Family history2.180.052.660.05
Smoking1.490.33  
ETT parameters    
    Positive ETT6.96<0.0017.31*0.001
    Exercise time, per minute change0.830.0070.89*0.23
    METS achieved0.830.0030.87*0.11
    Duke Treadmill Score0.81<0.0010.84*0.006
    Angina with stress1.470.37  
ETT indicates exercise stress testing; OR, odds ratio; METS, metabolic equivalents.
*
ETT parameters were each added individually to multivariable model, which included age, sex, diabetes, hypertension, and family history.
In a multivariable model that included all significant clinical risk factors, exercise time, workload achieved (METS), and the DTS were all significant predictors for the presence of plaque (Table 5). Importantly, a positive ETT and angina during stress were not significant predictors of plaque in any model. On the other hand, after accounting for all significant clinical predictors, the only ETT parameters that remained significant predictors of stenosis were a positive ETT and a low DTS (Table 6).

Evaluation of Possible Criteria for Selecting ETT Versus CTA

Among the 44 patients who exercised more than 13 METS, none had any stenosis on CTA, although 25% (11 of 44) had plaque. None of the 17 male patients with age <40 or 26 female patients with age <50 had stenosis. However, 12 of these 43 patients (12%) had plaque. When combining these criteria, 72 patients (33%) had age <40 for males or <50 for females or achieved >13 METS. None of these patients had stenosis, although 15 (21%) of them had plaque.
An analysis to identify whether the presence or number of risk factors can be used to identify subgroups of patients who have a lower or higher diagnostic accuracy from ETT did not identify any consistent groups of patients who derive greater accuracy from ETT. As can be seen in Figure 3, whereas the prevalence of stenosis increased with patients who had more risk factors, ETT had a low sensitivity to detect disease regardless of the number of risk factors.
Figure 3. Prevalence of stenosis on CT angiography (CTA) across increasing number of risk factors. There is a higher prevalence of stenosis by CTA among patients with a higher number of risk factors (P<0.001). For each patient, the number of risk factors represents how many of the following comorbidities exist: hypertension, diabetes, hyperlipidemia, and family history. Regardless of the number of risk factors, 50% or fewer of the patients with stenosis in each category had a positive ETT, reflecting the fact that the limited sensitivity of exercise treadmill testing (ETT) to detect stenosis is similar in patients with or without risk factors. Negative ETT is indicated in blue; positive ETT is indicated in red; percentages on top of each bar represent the sensitivity of ETT to detect stenosis on CTA.

Discussion

Our study supports the fact that ETT is a useful yet imperfect test for evaluating low-risk patients presenting to the emergency room with acute chest pain. Even after accounting for all baseline clinical risk factors, a positive ETT (odds ratio=7.3, P=0.001) and a lower DTT were significant predictors of the presence of stenosis, whereas a lower exercise capacity (eg, METS achieved) was an independent predictor for the presence of plaque.
The ROMICAT study design provides us with the unique opportunity to directly compare the data provided by ETT against the anatomic information provided by CTA. Notably, in the cohort of patients included in the present study, all patients had ETT and CTA by protocol and thus test selection was not influenced by examination results. We found that ST depressions during ETT exhibited reduced sensitivity (ranging from 30–60%) but a high specificity (94%) for the detection of a 50% lesion by CTA. It is noteworthy that whereas the presence of stenosis by CTA is associated with adverse prognosis,14 this finding does not reliably identify the presence of ischemia. Therefore, the limited sensitivity of ischemic ECG changes in identifying 50% stenosis by CTA is not unexpected. On the other hand, the sensitivity to detect 70% stenosis is higher, particularly if uninterpretable segments are excluded. Notably, the excellent specificity of ST depressions for identifying stenosis is higher than was observed in other studies,5 in part reflecting the absence of post test referral bias in our cohort.15
Our findings suggest that in patients with clinical concern for obstructive disease, further testing with imaging after an equivocal ETT may be reasonable. Thus, when the pretest probability of disease is high enough that even after a negative ETT, clinical concern remains, initial testing with imaging—either CTA or perfusion imaging—may represent a reasonable testing option. Supporting the complementary role of these tests, Nieman et al5 compared the diagnostic performance of ETT and CTA among ambulatory patients with stable chest pain. Among 98 of 471 patients who had invasive angiography, they found that CTA had a better sensitivity whereas ETT had a better specificity for detecting angiographic stenosis. However, their study is limited by referral bias because the decision for coronary angiography was clinically driven.
Given that both ETT and CTA may both be suitable testing option for low- to intermediate-risk patients presenting with acute chest pain,16–18 we sought to identify potential patient characteristics that may be used in deciding which patients could be tested with ETT only and which patients could potentially benefit from CTA. Importantly, we found that (1) younger patients (eg, men <40 years of age or women <50 years of age) did not have any stenosis; (2) patients who achieved >13 METS did not have any stenosis; and (3) patients with more clinical risk factors were more likely to have stenosis.
These finding suggest that ideal patients for ETT include those who are young, are expected to have a good exercise capacity, and have no or limited number of risk factors. On the other hand, testing with CTA first or MPI may be considered for patients who are older or who have multiple risk factors.19 Our findings are consistent with those of Bourque et al,20 who found that patients who can achieve ≥10 METS on ETT are extremely unlikely to have any ischemia.
Although both ETT and CTA are suitable testing option for low- to intermediate-risk patients presenting with acute chest pain,17,18 as per the aforementioned introduction, there are advantages and disadvantages for either strategy. Advantages of ETT include the absence of ionizing radiation, wide availability, and lower test cost. However, unlike CTA, before performing exercise testing, exclusion of active ischemia (ie, with serial cardiac biomarkers) is often needed.
Recently, it has been demonstrated that cardiac CT can be used to acquire simultaneous data on both coronary anatomy and vasodilator-induced stress MPI.21,22 Although such a test could potentially be used to evaluate for the presence of stenosis and ischemia in patients with acute chest pain, further studies are needed to establish the diagnostic accuracy of this technique. Even if such an approach will be ready for clinical care, most low- to intermediate-risk patients with acute chest pain would only require a rest CTA study. Subsequently, and only after a myocardial infarction has been ruled out, a stress CT could then be considered for patients who have coronary lesions of uncertain hemodynamic significance or in patients with prior CAD who have extensive calcifications or stents.
In keeping with other studies23 and guidelines,24 our study supports the fact that ETT cannot detect coronary atherosclerosis (eg, even among patients who achieved 13 METS, 21% had plaque) and thus should not be used in identifying patients who need more aggressive primary prevention measures. In contrast, CTA can identify coronary atherosclerosis, which in patients without previously recognized risk factors may be used for intensification of lifestyle and/or pharmacological preventive therapies.25 Nevertheless, it is unknown whether the identification of nonobstructive coronary atherosclerosis among patients presenting to the emergency department leads to any changes in subsequent therapies (which often require implementation in the outpatient setting) or outcomes. Short-term follow-up data from the ROMICAT data showed that in comparison to individuals who had no plaque, those with nonobstructive plaque had a higher rate of adverse events over 2 years (4.6% versus 0%), although it is noteworthy that most of the events in this group occurred during the first 30 days.26
CTA can also be used to identify other potential explanation for a given patient's chest pain, such as pulmonary embolus, dissection, or hiatal hernia. However, CTA also identifies “incidental” findings (eg, pulmonary nodule), which at times have questionable clinical significance but lead to increased cost and contributes to patient anxiety. Future studies are needed to identify whether the added information provided by CTA leads to differences in patient treatment and outcomes.

Limitations

Although the reference standard used in our study is stenosis on CTA, it is well known that anatomic measures of stenosis—whether by CTA or invasive angiography—are poor predictors of the hemodynamic significance of CAD. For instance, a 50% lesion on CTA has a positive predictive value ranging from 40–60% for identifying ischemia.27 Nevertheless, the use of CTA as the reference offers the advantage of detecting subclinical plaque and also offers an opportunity to examine the diagnostic accuracy of ETT in a population that is free from posttest referral bias. In our study, the diagnosis of an acute coronary syndrome was in part made using data from ETT and thus we were not able to determine the diagnostic accuracy of ETT for identifying whether or not acute coronary syndrome was present.
Because the CTA results were made blind to the providers and patients, we are unable to examine the downstream resource utilization and cost associated with ETT versus CTA. In the online-only Data Supplement Appendix, we compare the observed in-hospital downstream resource utilization testing after ETT with the projected resource utilization that would be anticipated if the CTA results were available.
Our study included patients who had ETT only as well as patients who had ETT with SPECT. The inclusion of a wide range of patients allowed us to better characterize the relationship between ETT testing and CTA results. Notably, our main findings—including the limited sensitivity of ETT—persisted even when the analysis was restricted to patients who had ETT without SPECT imaging.

Clinical Perspective

Although both coronary CT angiography (CTA) and exercise treadmill testing (ETT) can be used to evaluate low- to intermediate-risk patients, there is a paucity of studies that directly compare these tests in patients with acute chest pain. The goal of our study was to examine how data from ETT can identify patients who have coronary plaque or stenosis, using CTA as the reference standard. In addition, we were interested in identifying patient characteristics that could be used in selecting between ETT and CTA. In keeping with prior work and supporting the poor correlation of coronary anatomy and myocardial ischemia, we observed that the ETT results had a low sensitivity to identify the presence of coronary artery stenosis. However, interestingly, the specificity was high, in part reflecting the absence of posttest referral bias in this cohort. We also observed that the ETT results were not useful for excluding the presence of coronary atherosclerosis as even among individuals who achieved 13 metabolic equivalents, 21% had plaque. In our study, coronary stenosis was not present among men <40 years old or women <50 years old or individuals who achieved at least 13 metabolic equivalents on ETT. Therefore, younger individuals or those who would be expected to have a high exercise capacity may benefit from initial ETT testing instead of CTA. On the other hand, testing with CTA or myocardial perfusion imaging may be considered for patients who are older or who have multiple risk factors.

Sources of Funding

This work was supported by the National Institutes of Health (NIH) (R01 HL080053). Drs Blankstein, Ahmed, Rogers, and Truong received support from NIH grant T32HL076136. Dr Truong also received support from NIH grants K23HL098370 and L30HL093896.

References

1.
Gibbons RJ, Balady GJ, Bricker JT, Chaitman BR, Fletcher GF, Froelicher VF, Mark DB, McCallister BD, Mooss AN, O'Reilly MG, Winters WL, Antman EM, Alpert JS, Faxon DP, Fuster V, Gregoratos G, Hiratzka LF, Jacobs AK, Russell RO, Smith SC. ACC/AHA 2002 guideline update for exercise testing: summary article: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (committee to update the 1997 exercise testing guidelines). J Am Coll Cardiol. 2002;40:1531–1540.
Crossref
PubMed
Google Scholar
2.
Lauer MS, Pothier CE, Magid DJ, Smith SS, Kattan MW. An externally validated model for predicting long-term survival after exercise treadmill testing in patients with suspected coronary artery disease and a normal electrocardiogram. Ann Intern Med. 2007;147:821–828.
Crossref
PubMed
Google Scholar
3.
Mark DB, Shaw L, Harrell FE, Hlatky MA, Lee KL, Bengtson JR, McCants CB, Califf RM, Pryor DB. Prognostic value of a treadmill exercise score in outpatients with suspected coronary artery disease. N Engl J Med. 1991;325:849–853.
Crossref
PubMed
Google Scholar
4.
Goldschlager N. Use of the treadmill test in the diagnosis of coronary artery disease in patients with chest pain. Ann Intern Med. 1982;97:383–388.
Crossref
PubMed
Google Scholar
5.
Nieman K, Galema T, Weustink A, Neefjes L, Moelker A, Musters P, de Visser R, Mollet N, Boersma H, de Feijter PJ. Computed tomography versus exercise electrocardiography in patients with stable chest complaints: real-world experiences from a fast-track chest pain clinic. Heart. 2009;95:1669–1675.
Crossref
PubMed
Google Scholar
6.
Rubinshtein R, Halon DA, Gaspar T, Jaffe R, Karkabi B, Flugelman MY, Kogan A, Shapira R, Peled N, Lewis BS. Usefulness of 64-slice cardiac computed tomographic angiography for diagnosing acute coronary syndromes and predicting clinical outcome in emergency department patients with chest pain of uncertain origin. Circulation. 2007;115:1762–1768.
Crossref
PubMed
Google Scholar
7.
Hoffmann U, Bamberg F, Chae CU, Nichols JH, Rogers IS, Seneviratne SK, Truong QA, Cury RC, Abbara S, Shapiro MD, Moloo J, Butler J, Ferencik M, Lee H, Jang IK, Parry BA, Brown DF, Udelson JE, Achenbach S, Brady TJ, Nagurney JT. Coronary computed tomography angiography for early triage of patients with acute chest pain: the ROMICAT (Rule Out Myocardial Infarction Using Computer Assisted Tomography) trial. J Am Coll Cardiol. 2009;53:1642–1650.
Crossref
PubMed
Google Scholar
8.
Goldstein JA, Gallagher MJ, O'Neill WW, Ross MA, O'Neil BJ, Raff GL. A randomized controlled trial of multi-slice coronary computed tomography for evaluation of acute chest pain. J Am Coll Cardiol. 2007;49:863–871.
Crossref
PubMed
Google Scholar
9.
Hollander JE, Litt HI, Chase M, Brown AM, Kim W, Baxt WG. Computed tomography coronary angiography for rapid disposition of low-risk emergency department patients with chest pain syndromes. Acad Emerg Med. 2007;14:112–116.
Crossref
PubMed
Google Scholar
10.
Taylor AJ, Cerqueira M, Hodgson JM, Mark D, Min J, O'Gara P, Rubin GD, Kramer CM, Wolk MJ. ACCF/SCCT/ACR/AHA/ASE/ASNC/NASCI/SCAI/SCMR 2010 appropriate use criteria for cardiac computed tomography: a report of the American College Of Cardiology Foundation Appropriate Use Criteria Task Force, the Society of Cardiovascular Computed Tomography, the American College of Radiology, the American Heart Association, the American Society of Echocardiography, the American Society of Nuclear Cardiology, the North American Society for Cardiovascular Imaging, the Society for Cardiovascular Angiography and Interventions, and the Society for Cardiovascular Magnetic Resonance. Circulation. 2010;122:e525–e555.
Crossref
PubMed
Google Scholar
11.
Hendel RC. Is computed tomography coronary angiography the most accurate and effective noninvasive imaging tool to evaluate patients with acute chest pain in the emergency department? CT coronary angiography is the most accurate and effective noninvasive imaging tool for evaluating patients presenting with chest pain to the emergency department: antagonist viewpoint. Circ Cardiovasc Imaging. 2009;2:264–275.
Crossref
PubMed
Google Scholar
12.
Austen WG, Edwards JE, Frye RL, Gensini GG, Gott VL, Griffith LS, McGoon DC, Murphy ML, Roe BB. A reporting system on patients evaluated for coronary artery disease: report of the ad hoc committee for grading of coronary artery disease, council on cardiovascular surgery, American Heart Association. Circulation. 1975;51:5–40.
Crossref
PubMed
Google Scholar
13.
Bamberg F, Dannemann N, Shapiro MD, Seneviratne SK, Ferencik M, Butler J, Koenig W, Nasir K, Cury RC, Tawakol A, Achenbach S, Brady TJ, Hoffmann U. Association between cardiovascular risk profiles and the presence and extent of different types of coronary atherosclerotic plaque as detected by multidetector computed tomography. Arterioscler Thromb Vasc Biol. 2008;28:568–574.
Crossref
PubMed
Google Scholar
14.
Min JK, Shaw LJ, Berman DS. The present state of coronary computed tomography angiography a process in evolution. J Am Coll Cardiol. 2010;55:957–965.
Crossref
PubMed
Google Scholar
15.
Hachamovitch R, Di Carli MF. Methods and limitations of assessing new noninvasive tests, part I: anatomy-based validation of noninvasive testing. Circulation. 2008;117:2684–2690.
Crossref
PubMed
Google Scholar
16.
Taylor AJ, Cerqueira M, Hodgson JM, Mark D, Min J, O'Gara P, Rubin GD. ACCF/SCCT/ACR/AHA/ASE/ASNC/SCAI/SCMR 2010 appropriate use criteria for cardiac computed tomography: a report of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, the Society of Cardiovascular Computed Tomography, the American College of Radiology, the American Heart Association, the American Society of Echocardiography, the American Society of Nuclear Cardiology, the Society for Cardiovascular Angiography and Interventions, and the Society for Cardiovascular Magnetic Resonance. Circulation. 2010;122:e525–e55.
Crossref
PubMed
Google Scholar
17.
Amsterdam EA, Kirk JD, Bluemke DA, Diercks D, Farkouh ME, Garvey JL, Kontos MC, McCord J, Miller TD, Morise A, Newby LK, Ruberg FL, Scordo KA, Thompson PD; American Heart Association Exercise, Cardiac Rehabilitation, Prevention Committee of the Council on Clinical Cardiology, Council on Cardiovascular Nursing, Interdisciplinary Council on Quality of Care and Outcomes Research. Testing of low-risk patients presenting to the emergency department with chest pain: a scientific statement from the American Heart Association. Circulation. 2010;122:1756–1776.
Crossref
PubMed
Google Scholar
18.
Gibbons RJ, Balady GJ, Timothy Bricker J, Chaitman BR, Fletcher GF, Froelicher VF, Mark DB, McCallister BD, Mooss AN, O'Reilly MG, Winters WL, Antman EM, Alpert JS, Faxon DP, Fuster V, Gregoratos G, Hiratzka LF, Jacobs AK, Russell RO, Smith SC, Committee Members, Task Force Members. ACC/AHA 2002 guideline update for exercise testing: summary article: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (committee to update the 1997 exercise testing guidelines). Circulation. 2002;106:1883–1892.
Crossref
PubMed
Google Scholar
19.
Blankstein R, Devore AD. Selecting a noninvasive imaging study after an inconclusive exercise test. Circulation. 2010;122:1514–1518.
Crossref
PubMed
Google Scholar
20.
Bourque JM, Holland BH, Watson DD, Beller GA. Achieving an exercise workload of ≥10 metabolic equivalents predicts a very low risk of inducible ischemia: does myocardial perfusion imaging have a role? J Am Coll Cardiol. 2009;54:538–545.
Crossref
PubMed
Google Scholar
21.
Blankstein R, Shturman LD, Rogers IS, Rocha-Filho JA, Okada DR, Sarwar A, Soni AV, Bezerra H, Ghoshhajra BB, Petranovic M, Loureiro R, Feuchtner G, Gewirtz H, Hoffmann U, Mamuya WS, Brady TJ, Cury RC. Adenosine-induced stress myocardial perfusion imaging using dual-source cardiac computed tomography. J Am Coll Cardiol. 2009;54:1072–1084.
Crossref
PubMed
Google Scholar
22.
George RT, Arbab-Zadeh A, Miller JM, Kitagawa K, Chang HJ, Bluemke DA, Becker L, Yousuf O, Texter J, Lardo AC, Lima JA. Adenosine stress 64- and 256-row detector computed tomography angiography and perfusion imaging: a pilot study evaluating the transmural extent of perfusion abnormalities to predict atherosclerosis causing myocardial ischemia. Circ Cardiovasc Imaging. 2009;2:174–182.
Crossref
PubMed
Google Scholar
23.
Lin FY, Saba S, Weinsaft JW, Wong FJ, Szulc M, Kligfeld P, Okin PM, Berman DS, Shaw LJ, Min JK. Relation of plaque characteristics defined by coronary computed tomographic angiography to ST-segment depression and impaired functional capacity during exercise treadmill testing in patients suspected of having coronary heart disease. Am J Cardiol. 2009;103:50–58.
Crossref
PubMed
Google Scholar
24.
Greenland P, Alpert JS, Beller GA, Benjamin EJ, Budoff MJ, Fayad ZA, Foster E, Hlatky MA, Hodgson JM, Kushner FG, Lauer MS, Shaw LJ, Smith SC, Taylor AJ, Weintraub WS, Wenger NK, Jacobs AK, Anderson JL, Albert N, Buller CE, Creager MA, Ettinger SM, Guyton RA, Halperin JL, Hochman JS, Nishimura R, Ohman EM, Page RL, Stevenson WG, Tarkington LG, Yancy CW. 2010 ACCF/AHA guideline for assessment of cardiovascular risk in asymptomatic adults: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2010;56:e50–e103.
Crossref
PubMed
Google Scholar
25.
Blankstein R, Murphy MK, Nasir K, Gazelle GS, Batlle JC, Al-Mallah M, Shturman L, Hoffmann U, Cury RC, Abbara S, Brady TJ, Lee TH. Perceived usefulness of cardiac computed tomography as assessed by referring physicians and its effect on patient management. Am J Cardiol. 2010;105:1246–1253.
Crossref
PubMed
Google Scholar
26.
Schlett CL, Banerji D, Siegel E, Bamberg F, Lehman SJ, Ferencik M, Brady TJ, Nagurney JT, Hoffmann U, Truong QA. Prognostic value of ct angiography for major adverse cardiac events in patients with acute chest pain from the emergency department: 2-year outcomes of the ROMICAT trial. J Am Coll Cardiol Cardiovasc Imaging. 2011;4:481–491.
Crossref
PubMed
Google Scholar
27.
Blankstein R, Di Carli MF. Integration of coronary anatomy and myocardial perfusion imaging. Nat Rev Cardiol. 2010;7:226–236.
Crossref
PubMed
Google Scholar

Information & Authors

Information

Published In

Go to Circulation: Cardiovascular Imaging
Go to Circulation: Cardiovascular Imaging
Circulation: Cardiovascular Imaging
Volume 5 • Number 2 • March 2012
Pages: 233 - 242
PubMed: 22308274

Copyright

© 2012 American Heart Association, Inc.

Versions

You are viewing the most recent version of this article.

History

Received: 20 June 2011
Accepted: 25 January 2012
Published online: 3 February 2012
Published in print: March 2012

Permissions

Request permissions for this article.

Keywords

  1. cardiovascular CT
  2. exercise testing
  3. coronary artery disease
  4. stress testing

Subjects

  1. Acute Coronary Syndromes
  2. Computerized Tomography (CT)
  3. Exercise Testing
  4. Rehabilitation

Authors

Affiliations

Ron Blankstein, MD
From the Department of Medicine (Cardiovascular Division) and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (R.B.); the Section of Cardiovascular Medicine, Yale University, New Haven, CT (K.N.); the National Heart, Lung, and Blood Institute and Boston University Framingham Heart Study, Framingham, MA (J.F.); and the Cardiac MR PET CT Program (W.A., F.B., I.S.R., C.L.S., A.T., T.J.B., U.H., Q.A.T.), the Division of Cardiology (Q.A.T.), the Department of Radiology (A.T., T.J.B., Q.A.T.), and the Department of Emergency Medicine (J.T.N., U.H.), Massachusetts General Hospital, Harvard Medical School, Boston, MA.
View all articles by this author
Waleed Ahmed, MD
From the Department of Medicine (Cardiovascular Division) and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (R.B.); the Section of Cardiovascular Medicine, Yale University, New Haven, CT (K.N.); the National Heart, Lung, and Blood Institute and Boston University Framingham Heart Study, Framingham, MA (J.F.); and the Cardiac MR PET CT Program (W.A., F.B., I.S.R., C.L.S., A.T., T.J.B., U.H., Q.A.T.), the Division of Cardiology (Q.A.T.), the Department of Radiology (A.T., T.J.B., Q.A.T.), and the Department of Emergency Medicine (J.T.N., U.H.), Massachusetts General Hospital, Harvard Medical School, Boston, MA.
View all articles by this author
Fabian Bamberg, MD, MPH
From the Department of Medicine (Cardiovascular Division) and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (R.B.); the Section of Cardiovascular Medicine, Yale University, New Haven, CT (K.N.); the National Heart, Lung, and Blood Institute and Boston University Framingham Heart Study, Framingham, MA (J.F.); and the Cardiac MR PET CT Program (W.A., F.B., I.S.R., C.L.S., A.T., T.J.B., U.H., Q.A.T.), the Division of Cardiology (Q.A.T.), the Department of Radiology (A.T., T.J.B., Q.A.T.), and the Department of Emergency Medicine (J.T.N., U.H.), Massachusetts General Hospital, Harvard Medical School, Boston, MA.
View all articles by this author
Ian S. Rogers, MD, MBA, MPH
From the Department of Medicine (Cardiovascular Division) and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (R.B.); the Section of Cardiovascular Medicine, Yale University, New Haven, CT (K.N.); the National Heart, Lung, and Blood Institute and Boston University Framingham Heart Study, Framingham, MA (J.F.); and the Cardiac MR PET CT Program (W.A., F.B., I.S.R., C.L.S., A.T., T.J.B., U.H., Q.A.T.), the Division of Cardiology (Q.A.T.), the Department of Radiology (A.T., T.J.B., Q.A.T.), and the Department of Emergency Medicine (J.T.N., U.H.), Massachusetts General Hospital, Harvard Medical School, Boston, MA.
View all articles by this author
Christopher Lothar Schlett, MD
From the Department of Medicine (Cardiovascular Division) and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (R.B.); the Section of Cardiovascular Medicine, Yale University, New Haven, CT (K.N.); the National Heart, Lung, and Blood Institute and Boston University Framingham Heart Study, Framingham, MA (J.F.); and the Cardiac MR PET CT Program (W.A., F.B., I.S.R., C.L.S., A.T., T.J.B., U.H., Q.A.T.), the Division of Cardiology (Q.A.T.), the Department of Radiology (A.T., T.J.B., Q.A.T.), and the Department of Emergency Medicine (J.T.N., U.H.), Massachusetts General Hospital, Harvard Medical School, Boston, MA.
View all articles by this author
Khurram Nasir, MD, MPH
From the Department of Medicine (Cardiovascular Division) and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (R.B.); the Section of Cardiovascular Medicine, Yale University, New Haven, CT (K.N.); the National Heart, Lung, and Blood Institute and Boston University Framingham Heart Study, Framingham, MA (J.F.); and the Cardiac MR PET CT Program (W.A., F.B., I.S.R., C.L.S., A.T., T.J.B., U.H., Q.A.T.), the Division of Cardiology (Q.A.T.), the Department of Radiology (A.T., T.J.B., Q.A.T.), and the Department of Emergency Medicine (J.T.N., U.H.), Massachusetts General Hospital, Harvard Medical School, Boston, MA.
View all articles by this author
Joao Fontes, MD
From the Department of Medicine (Cardiovascular Division) and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (R.B.); the Section of Cardiovascular Medicine, Yale University, New Haven, CT (K.N.); the National Heart, Lung, and Blood Institute and Boston University Framingham Heart Study, Framingham, MA (J.F.); and the Cardiac MR PET CT Program (W.A., F.B., I.S.R., C.L.S., A.T., T.J.B., U.H., Q.A.T.), the Division of Cardiology (Q.A.T.), the Department of Radiology (A.T., T.J.B., Q.A.T.), and the Department of Emergency Medicine (J.T.N., U.H.), Massachusetts General Hospital, Harvard Medical School, Boston, MA.
View all articles by this author
Ahmed Tawakol, MD
From the Department of Medicine (Cardiovascular Division) and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (R.B.); the Section of Cardiovascular Medicine, Yale University, New Haven, CT (K.N.); the National Heart, Lung, and Blood Institute and Boston University Framingham Heart Study, Framingham, MA (J.F.); and the Cardiac MR PET CT Program (W.A., F.B., I.S.R., C.L.S., A.T., T.J.B., U.H., Q.A.T.), the Division of Cardiology (Q.A.T.), the Department of Radiology (A.T., T.J.B., Q.A.T.), and the Department of Emergency Medicine (J.T.N., U.H.), Massachusetts General Hospital, Harvard Medical School, Boston, MA.
View all articles by this author
Thomas J. Brady, MD
From the Department of Medicine (Cardiovascular Division) and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (R.B.); the Section of Cardiovascular Medicine, Yale University, New Haven, CT (K.N.); the National Heart, Lung, and Blood Institute and Boston University Framingham Heart Study, Framingham, MA (J.F.); and the Cardiac MR PET CT Program (W.A., F.B., I.S.R., C.L.S., A.T., T.J.B., U.H., Q.A.T.), the Division of Cardiology (Q.A.T.), the Department of Radiology (A.T., T.J.B., Q.A.T.), and the Department of Emergency Medicine (J.T.N., U.H.), Massachusetts General Hospital, Harvard Medical School, Boston, MA.
View all articles by this author
John T. Nagurney, MD, MPH
From the Department of Medicine (Cardiovascular Division) and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (R.B.); the Section of Cardiovascular Medicine, Yale University, New Haven, CT (K.N.); the National Heart, Lung, and Blood Institute and Boston University Framingham Heart Study, Framingham, MA (J.F.); and the Cardiac MR PET CT Program (W.A., F.B., I.S.R., C.L.S., A.T., T.J.B., U.H., Q.A.T.), the Division of Cardiology (Q.A.T.), the Department of Radiology (A.T., T.J.B., Q.A.T.), and the Department of Emergency Medicine (J.T.N., U.H.), Massachusetts General Hospital, Harvard Medical School, Boston, MA.
View all articles by this author
Udo Hoffmann, MD, MPH
From the Department of Medicine (Cardiovascular Division) and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (R.B.); the Section of Cardiovascular Medicine, Yale University, New Haven, CT (K.N.); the National Heart, Lung, and Blood Institute and Boston University Framingham Heart Study, Framingham, MA (J.F.); and the Cardiac MR PET CT Program (W.A., F.B., I.S.R., C.L.S., A.T., T.J.B., U.H., Q.A.T.), the Division of Cardiology (Q.A.T.), the Department of Radiology (A.T., T.J.B., Q.A.T.), and the Department of Emergency Medicine (J.T.N., U.H.), Massachusetts General Hospital, Harvard Medical School, Boston, MA.
View all articles by this author
Quynh A. Truong, MD, MPH
From the Department of Medicine (Cardiovascular Division) and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (R.B.); the Section of Cardiovascular Medicine, Yale University, New Haven, CT (K.N.); the National Heart, Lung, and Blood Institute and Boston University Framingham Heart Study, Framingham, MA (J.F.); and the Cardiac MR PET CT Program (W.A., F.B., I.S.R., C.L.S., A.T., T.J.B., U.H., Q.A.T.), the Division of Cardiology (Q.A.T.), the Department of Radiology (A.T., T.J.B., Q.A.T.), and the Department of Emergency Medicine (J.T.N., U.H.), Massachusetts General Hospital, Harvard Medical School, Boston, MA.
View all articles by this author

Notes

Guest Editor for this article was João A. Lima, MD.
Correspondence to Ron Blankstein, MD, Cardiovascular Division and Department of Radiology, Brigham and Women's Hospital, 75 Francis St, Room Shapiro 5096, Boston, MA 02115. E-mail [email protected]

Disclosures

None.

Metrics & Citations

Metrics

Citations

Download Citations

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Select your manager software from the list below and click Download.

    • Florentina A. Simader,
    • Rasha K. Al-Lamee,
    To Test or Not to Test? The Utility of Noninvasive Cardiac Testing for Chest Pain Without Myocardial Infarction, Circulation: Cardiovascular Quality and Outcomes, 17, 6, (e011017), (2024)./doi/10.1161/CIRCOUTCOMES.124.011017
    Abstract
    • Christopher W. Baugh,
    • Margarita E. Pena,
    • Robert B. Takla,
    • Ahmad O. Hadri,
    • Sharon E. Mace,
    National cost savings, operational and safety benefits from use of magnetocardiography in the assessment of emergency department chest pain patients, American Heart Journal Plus: Cardiology Research and Practice, 45, (100434), (2024).https://doi.org/10.1016/j.ahjo.2024.100434
    Crossref
    • Peng-Chong Zhu,
    • Jiayi Shen,
    • Ren-Yi Qian,
    • Jian Xu,
    • Chong Liu,
    • Wu-Ming Hu,
    • Ying Zhang,
    • Ling-Chun Lv,
    Effect of tanshinone IIA for myocardial ischemia/reperfusion injury in animal model: preclinical evidence and possible mechanisms, Frontiers in Pharmacology, 14, (2023).https://doi.org/10.3389/fphar.2023.1165212
    Crossref
    • Tianli Li,
    • Jialin Jin,
    • Fenglan Pu,
    • Ying Bai,
    • Yajun Chen,
    • Yan Li,
    • Xian Wang,
    Cardioprotective effects of curcumin against myocardial I/R injury: A systematic review and meta-analysis of preclinical and clinical studies, Frontiers in Pharmacology, 14, (2023).https://doi.org/10.3389/fphar.2023.1111459
    Crossref
    • Sean Paul Gaine,
    • Garima Sharma,
    • Albree Tower-Rader,
    • Mina Botros,
    • Lara Kovell,
    • Anushri Parakh,
    • Malissa J. Wood,
    • Colleen M. Harrington,
    Multimodality Imaging in the Detection of Ischemic Heart Disease in Women, Journal of Cardiovascular Development and Disease, 9, 10, (350), (2022).https://doi.org/10.3390/jcdd9100350
    Crossref
    • Pieter van der Bijl,
    • Jan Stassen,
    • Jeroen J Bax,
    Guideline-based use of cardiac imaging for chronic coronary syndromes, European Heart Journal, 44, 2, (159-161), (2022).https://doi.org/10.1093/eurheartj/ehac630
    Crossref
    • Martha Gulati,
    • Phillip D. Levy,
    • Debabrata Mukherjee,
    • Ezra Amsterdam,
    • Deepak L. Bhatt,
    • Kim K. Birtcher,
    • Ron Blankstein,
    • Jack Boyd,
    • Renee P. Bullock-Palmer,
    • Theresa Conejo,
    • Deborah B. Diercks,
    • Federico Gentile,
    • John P. Greenwood,
    • Erik P. Hess,
    • Steven M. Hollenberg,
    • Wael A. Jaber,
    • Hani Jneid,
    • José A. Joglar,
    • David A. Morrow,
    • Robert E. O’Connor,
    • Michael A. Ross,
    • Leslee J. Shaw,
    2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain, Journal of Cardiovascular Computed Tomography, 16, 1, (54-122), (2022).https://doi.org/10.1016/j.jcct.2021.11.009
    Crossref
    • Alexandre de Matos Soeiro,
    • Bruno Biselli,
    • Tatiana C.A.T Leal,
    • Aline Siqueira Bossa,
    • Maria Cristina César,
    • Sérgio Jallad,
    • Priscila Gherardi Goldstein,
    • Patrícia Oliveira Guimarães,
    • Carlos Vicente Serrano,
    • Cesar Higa Nomura,
    • Débora Nakamura,
    • Carlos Eduardo Rochitte,
    • Paulo Rogério Soares,
    • Múcio Tavares de Oliveira,
    Desempenho Diagnóstico da Angiotomografia Computadorizada e da Avaliação Seriada de Troponina Cardíaca Sensível em Pacientes com Dor Torácica e Risco Intermediário para Eventos Cardiovasculares, Arquivos Brasileiros de Cardiologia, (2021).https://doi.org/10.36660/abc.20210006
    Crossref
    • Martha Gulati,
    • Phillip D. Levy,
    • Debabrata Mukherjee,
    • Ezra Amsterdam,
    • Deepak L. Bhatt,
    • Kim K. Birtcher,
    • Ron Blankstein,
    • Jack Boyd,
    • Renee P. Bullock-Palmer,
    • Theresa Conejo,
    • Deborah B. Diercks,
    • Federico Gentile,
    • John P. Greenwood,
    • Erik P. Hess,
    • Steven M. Hollenberg,
    • Wael A. Jaber,
    • Hani Jneid,
    • José A. Joglar,
    • David A. Morrow,
    • Robert E. O’Connor,
    • Michael A. Ross,
    • Leslee J. Shaw,
    2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain: Executive Summary: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines, Circulation, 144, 22, (e336-e367), (2021)./doi/10.1161/CIR.0000000000001030
    Abstract
    • Martha Gulati,
    • Phillip D. Levy,
    • Debabrata Mukherjee,
    • Ezra Amsterdam,
    • Deepak L. Bhatt,
    • Kim K. Birtcher,
    • Ron Blankstein,
    • Jack Boyd,
    • Renee P. Bullock-Palmer,
    • Theresa Conejo,
    • Deborah B. Diercks,
    • Federico Gentile,
    • John P. Greenwood,
    • Erik P. Hess,
    • Steven M. Hollenberg,
    • Wael A. Jaber,
    • Hani Jneid,
    • José A. Joglar,
    • David A. Morrow,
    • Robert E. O’Connor,
    • Michael A. Ross,
    • Leslee J. Shaw,
    2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines, Circulation, 144, 22, (e368-e454), (2021)./doi/10.1161/CIR.0000000000001029
    Abstract
  11. See more

View Options

View options

PDF and All Supplements

Download PDF and All Supplements

PDF/EPUB

View PDF/EPUB
Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Personal login Institutional Login
Save for later Item saved, go to cart
Purchase Options

Purchase this article to access the full text.

Purchase access to this article for 24 hours

Comparison of Exercise Treadmill Testing With Cardiac Computed Tomography Angiography Among Patients Presenting to the Emergency Room With Chest Pain
Circulation: Cardiovascular Imaging
  • Vol. 5
  • No. 2

Purchase access to this journal for 24 hours

Circulation: Cardiovascular Imaging
  • Vol. 5
  • No. 2
Restore your content access

Enter your email address to restore your content access:

Note: This functionality works only for purchases done as a guest. If you already have an account, log in to access the content to which you are entitled.

Media

Figures

Other

Tables

Share

Share

Share article link

Share

View full text|Download PDF

Comment Response