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Increased Left Atrial Appendage Density on Computerized Tomography is Associated with Cardioembolic Stroke
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Increased Left Atrial Appendage Density on Computerized Tomography is Associated with Cardioembolic Stroke Andrew D. Chang, MS,* Gian C. Ignacio, BS,* Ronald Akiki, BS,* Brian Mac Grory, MD,* Shawna S. Cutting, MD,* Tina Burton, MD,* Mahesh Jayaraman, MD,*,†,‡ Alexander Merkler, MD,{ Christopher Song, MD,§ Athena Poppas, MD,§ Hooman Kamel, MD,{ Mitchell S.V. Elkind, MD,║,$ Karen Furie, MD,* Michael Atalay, MD,‡ and Shadi Yaghi, MD# Background and purpose: While studies have stratified cardioembolic (CE) stroke risk by qualitative left atrial appendage (LAA) morphology and biomarkers of atrial dysfunction, the quantitative properties that underlie these observations are not well established. Accordingly, we hypothesized that LAA volume and contrast density (attenuation) on computerized tomography (CT) may capture the structural and hemodynamic processes that underlie CE stroke risk. Methods: Data were collected from a single center prospective ischemic stroke database over 18 months and included all patients with ischemic stroke who previously underwent routine, nongated, contrast enhanced thin-slice (2.5 mm) chest CT. Stroke subtype was determined based on the inpatient diagnostic evaluation. LAA volume and attenuation were determined from CT studies performed for various clinically appropriate indications. Univariate and multivariable analyses were performed to determine factors associated with ischemic stroke subtype, including known risk factors and biomarkers, as well as LAA density and morphologic measures. Results: We identified 311 patients with a qualifying chest CT (119 CE subtype, 109 Embolic Stroke of Undetermined Source (ESUS), and 83 non-CE). In unadjusted models, there was an association between CE (versus non-CE) stroke subtype and LAA volume (OR per mL increase 1.15, 95% CI 1.07-1.24, P < .001) and LAA density (4th quartile versus 1st quartile; OR 2.95, 95% CI 1.28-6.80, P = .011), but not with ESUS (versus non-CE) subtype. In adjusted models, only the association between LAA density and CE stroke subtype persisted (adjusted OR 3.71, 95% CI 1.37-10.08, P = .010). Conclusion: The LAA volume and density values on chest CT are associated with CE stroke subtype but not ESUS subtype. Patients with ESUS and increased LAA volume or attenuation may be a subgroup where the mechanism is CE and anticoagulation can be tested for secondary stroke prevention.
From the *The Warren Alpert Medical School of Brown University, Department of Neurology, Providence, Rhode Island; †The Warren Alpert Medical School of Brown University, Department of Neurosurgery, Providence, Rhode Island; ‡The Warren Alpert Medical School of Brown University, Department of Radiology, Providence, Rhode Island; {Departments of Neurology and Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York, New York; §The Warren Alpert Medical School of Brown University, Department of Internal Medicine, Division of Cardiovascular Medicine, Providence, Rhode Island; ║Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, New York; $Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York; and # New York Langone Hospital, Department of Neurology, Brooklyn, New York. Received September 9, 2019; revision received December 9, 2019; accepted December 13, 2019. Sources of funding: This study was funded by the American Heart Association AHA Award #17MCPRP33670965. Disclosures: Dr. Elkind discloses receiving personal compensation for consulting for Abbott; receiving personal compensation for writing chapters on stroke for UpToDate; and research funding from the BMS-Pfizer Alliance for Eliquis and from Roche for a federally-funded clinical trial of atrial cardiopathy and stroke prevention. Address correspondence to Shadi Yaghi, MD, Department of Neurology, New York Langone Hospital, 150 55th St., Brooklyn, NY 11220. E-mail: [email protected]. 1052-3057/$ - see front matter © 2019 Elsevier Inc. All rights reserved. https://doi.org/10.1016/j.jstrokecerebrovasdis.2019.104604
Journal of Stroke and Cerebrovascular Diseases, Vol. &&, No. && (&&), 2019: 104604
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2 Key Words: Left atrial appendage—stroke—atrial tomography © 2019 Elsevier Inc. All rights reserved.
Introduction Ischemic stroke is a significant cause of mortality in the United States, accounting for 87% of all stroke cases and 113,000 deaths annually.1 Effective stroke treatment and secondary prevention strategies rely on timely identification of stroke mechanism, particularly when it pertains to cardioembolic (CE) subtypes that respond to anticoagulant therapy.2 Previous studies have demonstrated that the left atrial appendage (LAA) is the most common source of thrombus formation in patients with nonvalvular atrial fibrillation, and therefore a primary site of interest in assessing CE stroke risk.3 Moreover, quantitative volumetric and hemodynamic analyses of the LAA have shown increasing promise in predicting ischemic stroke risk. One study suggests that LAA size and structural complexity are valuable indicators of stroke risk.4-6 Computational fluid dynamic analyses further demonstrate the exact mechanisms by which complex LAA morphologies promote stasis and thrombus formation.7 While transesophageal echocardiogram (TEE) is the gold standard modality to assess LAA dysfunction, its use is limited by potential procedural complications such as esophageal perforation, upper gastrointestinal bleeding, and laryngospasm.8 In fact, most ischemic stroke patients do not obtain such a study for work-up of stroke etiology9 but rather have a 2-dimensional transthoracic echocardiogram as part of their diagnostic evaluation, a test that offers limited assessment of LAA structure and function.10 Nevertheless, since hemodynamic status and cardiovascular architecture dictate the speed and distribution of the intravenous contrast agent throughout the body, contrast-enhanced chest computerized tomography (CT) may be capable of not only evaluating underlying cardiac disease,11 but also predicting CE stroke risk by capturing certain variables linked to stagnant flow in the LAA. Namely, hemodynamics underlying thrombus formation in the LAA may be reflected by significant differences in LAA volume or contrast density and these may be indirect markers of stagnant flow. To our knowledge, there is very limited if any data on the association between these measures and CE stroke subtypes in patients with ischemic stroke. This study aims to investigate the association between LAA volume and attenuation acquired through chest CT and embolic stroke subtypes (CE and Embolic Stroke of Undetermined Source (ESUS)) as opposed to nonCE etiologies.
Methods Patient Population The institutional review board at lifespan approved this study. Data were collected from a prospective inpatient
fibrillation—computed
database and included consecutive patients admitted to our facility with a discharge diagnosis of ischemic stroke over an 18-month period. Demographic data and clinical risk factors were retrieved from electronic medical records at the time of discharge. In general, patients admitted with a diagnosis of ischemic stroke underwent a standard diagnostic evaluation that included laboratory testing, brain imaging, intracranial, and extracranial vascular imaging, 12-lead electrocardiogram, cardiac telemetry throughout their inpatient hospital stay, and transthoracic echocardiography.
Study Variables a) Clinical demographic and outcome variables: age, sex, hypertension, diabetes, hyperlipidemia, coronary heart disease, AF, prior transient ischemic attack or stroke, congestive heart failure, current smoking, and National Institute of Health Stroke Scale on admission.
CT Chest With Contrast Protocol Qualifying imaging included thin-slice (2.5 mm) non ECG-gated contrast enhanced CT or CT angiography (CTA) of the chest performed for clinical indications within 5 years from the stroke. Anonymized, thin-slice images were analyzed using commercially available software (iNtuitionTM, TeraRecon, Foster City, CA) for detailed multiplanar reconstruction.
Primary Predictors 1) LAA volume: The LAA was identified on coronal plane inferior to the confluence of left pulmonary veins. Viewing planes were then aligned according to the origin of the LAA as it emerges from the remaining left atrium, demarcated by a sharp change in surface contour readily identified on CT. LAA orifice crosssectional area was measured along this plane. Total LAA volume was measured by serial segmentation and summation of cross-sectional areas starting from the orifice. The LA volume was measured in a similar manner using boundary conditions of the mitral valve and interatrial septum (Fig 1). Due to concerns of accuracy using nongated chest CT for volumetric measurements, we compared CT-based measurements of LA volume with those obtained by standard echocardiography. CT and echocardiogram-based measurements showed a moderate positive correlation (r = .423, n = 133, P < .001).
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Figure 1. Measurement of LAA volume and orifice cross-sectional area. Multiplanar rotation was used to identify the plane of the LAA orifice for measurement of cross-sectional area and volume segmentation. A. First, the LAA was identified on traditional coronal section (highlighted structure), and sections were realigned along the apparent plane of the LAA orifice (dashed line). B. In the modified “sagittal” plane, sections were once again re-aligned to the LAA orifice plane. C. The final, modified “axial” plane provided the true orientation of the LAA orifice without skew.
2) LAA attenuation: Multiplanar reconstruction of chest CTA was used to visualize the long-axis of the LAA. A 2-cm linear region of interest was drawn along the central cavity of the LAA. Serial Hounsfield unit (HU) values were obtained at every 0.5-mm increment along this region of interest, for a total of 40 measurements. The cumulative mean of collected attenuation values were then calculated for each patient and used as the final LAA attenuation value (Fig 2).
Primary Outcome: Stroke subtype The primary outcome was stroke subtype divided into 3 categories: CE, ESUS, and non-CE stroke. All stroke etiologies were determined prospectively by the treating vascular neurology attending using criteria previously described.12
Statistical Analysis Patients were divided into 3 groups: CE subtype, ESUS subtype, and defined nonCE subtype which included large vessel disease, small vessel disease, or other defined mechanism. We compared clinical characteristics between the 3 groups. We used t tests and 1-way ANOVA for continuous variables and Fisher’s test for categorical variables. We used multivariate ANOVA to determine main and interaction effects between stroke subtype and LAA morphology on continuous volumetric measures. We then performed prespecified multivariable regression analyses to determine the associations between stroke subtype and LAA attenuation values. Covariate adjustments were included in regressions according to four prespecified models: model 1, which adjusted for age and sex; model 2, which adjusted for CHADS2-Vasc and National Institute of Health Stroke Scale; model 3, which included covariates in model 2 plus CT LA volume; model 4, which included covariates in model 3 plus CT LAA volume. Analyses were performed using SPSS version 20.0 (Chicago, IL) and P < .05 was considered statistically significant.
Results Baseline Characteristics of the Study Sample
Figure 2. Measurement of LAA attenuation. Multiplanar rotation was used to identify a reconstructed sagittal view of the LAA for measurement of attenuation. A. We created a 2-cm linear ROI was used to trace the central cavity of the LAA, with serial measurements of Hounsfield unit (HU) density at 0.5-mm increments. B. Total mean (represented by dotted black line) and standard deviation (represented by region shaded red) of HU densities along the linear ROI were calculated and used for subsequent analyses.
We identified 311 patients (25.3%) with a qualifying chest CT performed [119 CE subtype, 109 ESUS, and 83 NCE]. Baseline characteristics of patients with and without a qualifying CT were similar. The mean age of all patients in our cohort was 72.5 § 13.8 years, and 55.6% were men. Baseline characteristics of the study sample are shown in Table 1. Of note, while our data consisted of a variety of contrast-enhanced chest CT modalities, imaging techniques did not significantly vary by stroke subtype. Specifically, there were no differences in the proportion of chest CTA modalities obtained, the interval of time from chest CTA to stroke, the type of IV contrast agent used, or the volume and rate of contrast injection (Table 2).
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Table 1. Univariate analysis of baseline characteristics based on stroke subtype Stroke subtype
Age (mean SD) Sex (% female) Hypertension, n Diabetes, n Hyperlipidemia, n Coronary heart disease, n Prior stroke, n Congestive heart failure, n Atrial fibrillation, n Active smoker, n Wall-motion abnormality, n Ejection fraction (mean SD) LA diameter (mean SD) LA volume (mean SD) NIHSS (median, IQR)
CE n = 119 (38.3%)
ESUS n = 109 (35.0%)
NCE n = 83 (26.7%)
P
76.9 § 11.8 61 (51.3%) 102 (85.7%) 29 (24.4%) 61 (51.3%) 38 (31.9%) 28 (23.5%) 31 (26.1%) 97 (81.5%) 15 (12.6%) 17 (24.3%) 57 § 15 42.9 § 7.3 80.4 § 33.8 9.5 (4-22)
69.2 § 15.1 52 (47.7%) 88 (80.7%) 36 (33%) 64 (58.7%) 26 (23.9%) 19 (17.4%) 13 (12%) 1 (0.9%) 22 (20.4%) 4 (6.7%) 62 § 15 35.5 § 6.1 55.8 § 21.9 6 (3-15)
70.6 § 13.2 25 (30.1%) 69 (83.1%) 24 (28.9%) 41 (49.4%) 20 (24.1%) 23 (27.7%) 7 (8.5%) 6 (7.2%) 14 (16.9%) 4 (8.5%) 60 § 10 36.4 § 6.7 56.2 § 23.9 4 (2-12)
<.001 .008 .602 .351 .370 .306 .226 .001 <.001 .287 .007 .046 <.001 <.001 <.001
Table 2. Univariate analysis of chest CTA technique and left atrial measurements based on stroke subtype Stroke subtype
Chest CTA modality, n CTA chest only* CTA chest/abdomen/pelvis IV-contrast agent, n Omnipaque Isovue Visipaque IV-contrast administration Injection volume (median IQR) Injection rate (median IQR) Slice thickness (median IQR) Time interval stroke to chest CTA (median IQR) LA volume (mean SD) LAA volume (mean SD) LAA orifice area (mean SD) LAA morphology Chicken-wing Cauliflower Cactus Windsock LAA attenuation (mean SD)
CE n = 119 (38.3%)
ESUS n = 109 (35.0%)
NCE n = 83 (26.7%)
101 (84.9%) 18 (15.1%)
95 (87.2%) 14 (12.8%)
65 (78.3%) 18 (21.7%)
78 (65.5%) 18 (19.3%) 0 (0.0%)
64 (58.7%) 21 (19.3%) 1 (.9%)
53 (63.9%) 13 (15.7%) 1 (1.2%)
100 (80-130) 4 (3.75-4) 2.5 (.7-2.5) 0.41 (.01-1.64) 93.8 § 30.9 11.0 § 4.6 4.1 § 1.7
100 (80-130) 4 (3-4) 2.5 (.8-2.5) 1.72 (.21-4.04) 66.9 § 19.0 7.9 § 3.8 2.9 § 1.3
100 (100-130) 4 (3-4) 2.5 (.7-2.5) 1.50 (.04-2.64) 71.5 § 22.2 8.5 § 3.8 5.0 § 13.8
33 (27.7%) 13 (10.9%) 21 (17.6%) 52 (43.7%) 270 § 130
19 (17.4%) 15 (13.8%) 15 (13.8%) 60 (55.0%) 237 § 107
37 (44.6%) 9 (10.8%) 7 (8.4%) 30 (36.1%) 216 § 113
P value .239
.889
.112 .379 .672 .214 <.001 <.001 .144 .003
.005
*Includes CTA Chest, CTA Pulmonary Embolism, CTA Aortic Dissection, CTA Coronary, CTA Thoracic.
Association Between LAA Volume and Stroke Subtype Compared to NCE stroke subtypes, patients with CE stroke subtype exhibited larger LAA volumes (11.0 § 4.6 cc versus 8.5 § 3.8 cc, P < .001). On the other hand, there was no significant difference in LAA volume between patients with ESUS and NCE subtypes (7.9 § 3.8 cc versus 8.5 § 3.8 cc, P = .303).
Association Between LAA Attenuation and Stroke Subtype In univariate analyses, when compared to patients with NCE, LAA attenuation values were greater in CE (270 § 130 HU versus 216 § 113 HU, P = .002). LAA attenuation was numerically higher in patients with ESUS compared to NCE stroke but this difference did not achieve
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statistical significance (237 § 107 HU versus 216 § 113 HU, P = .218).
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this association was not significant after adjusting for potential confounders (Table 4). To provide practical thresholds for clinical utility, we repeated our multivariable models using stratified LAA attenuation based on quartiles (n = 78 per group): (1) Minimal LAA attenuation: less than 168 HU; (2) Mild LAA attenuation: 168-240 HU; (3) Moderate LAA attenuation: 241-318 HU; (4) Severe LAA attenuation: greater than 318 HU. Using minimal LAA attenuation as a baseline for comparison, there was a significant association between CE subtype and maximal LAA attenuation exceeding 318 HU (unadjusted OR, 2.95; 95% CI, 1.28-6.80; P = .011), but not for the mild and moderate LAA attenuation quartiles. This pattern of association remained significant in the fully adjusted model (Model 4: adjusted OR for maximal LAA attenuation, 3.71; 95% CI, 1.37-10.08; P = .010; Table 5). On the other hand, using minimal LAA attenuation as a baseline for comparison, there was increased odds of having ESUS stroke subtypes compared to NCE with increasing LAA attenuation, but this difference did not achieve statistical significance (Table 5).
Multivariable Models of the Association Between LAA Volume With Stroke Subtype In unadjusted models, LAA volume was associated with CE compared to NCE stroke subtypes (odds ratio [OR] per mL increase, 1.154; 95% confidence interval [CI], 1.07-1.24; P < .001). This relationship persisted in fully adjusted models (adjusted OR per unit increase, 1.10; 95% CI, 1.01-1.20; P = .038). In contrast, there was no association between LAA volume and ESUS subtypes, when compared to NCE stroke subtypes (OR .95, 95% CI 0.871.04, P = .291; Table 3).
Multivariable Models on the Association Between Stroke Subtype and LAA Attenuation In unadjusted models, there was an association between CE subtype and LAA attenuation (OR per HU increase, 1.004; 95% CI, 1.001-1.006; P = .003), with high sensitivity (.88) and specificity (.61). This association persisted after adjusting for potential confounders (Model 2: adjusted OR per HU increase, 1.004; 95% CI, 1.001-1.007; P = .007), CT-based measurements of LA volume (Model 3: adjusted OR per unit increase, 1.004; 95% CI, 1.0011.007; P = .005), and LAA volume (Model 4: adjusted OR per unit increase, 1.004; 95% CI, 1.001-1.007; P = .004). On the other hand, there was a trend for association between LAA attenuation and ESUS in unadjusted models (OR per unit increase, 1.002; 95% CI, 0.999-1.004; P = .1). However,
Sensitivity Analyses Sensitivity analyses were performed adjusting for AF. When AF was added to the fully adjusted model, we found no association between LAA volume and CE stroke subtype. On the other hand, the association between LAA attenuation and CE stroke subtype persisted after adjusting for AF (adjusted OR per unit increase, 1.007; 95% CI, 1.002-1.012; P = .003). Indeed, 2-way ANOVA analyses redemonstrated these findings, with a significant main
Table 3. Multivariate analyses showing association between LAA volume and stroke subtype CE
Unadjusted Model 1 Model 2 Model 3
ESUS
P value
OR
95% CI
P value
OR
95% CI
<.001 .001 .016 .038
1.15 1.14 1.10 1.10
1.07-1.24 1.06-1.23 1.02-1.10 1.01-1.20
.268 .485 .141 .290
.96 .97 .94 .95
.89-1.03 .90-1.05 .87-1.02 .87-1.04
Model 1 adjusted for age and sex; model 2 adjusted for CHADS2-Vasc score and NIHSS; model 3 adjusted for CHADS2-Vasc, NIHSS and left atrial volume index (LAVI).
Table 4. Multivariate analyses showing association between LAA attenuation and stroke subtype CE
Unadjusted Model 1 Model 2 Model 3 Model 4
ESUS
P value
OR
95% CI
.003 .049 .007 .005 .004
1.004 1.003 1.004 1.004 1.004
1.001-1.006 1.000-1.005 1.001-1.007 1.001-1.007 1.001-1.007
P value .187 .399 .208 0.278 0.317
OR
95% CI
1.002 1.001 1.002 1.002 1.001
.999-1.004 .998-1.004 .999-1.005 .999-1.004 .999-1.004
Adjusted covariates in model 1: age, sex; model 2: chads2-vasc and NIHSS; model 3: chads2-vasc, NIHSS, and CT-LAV; model 4: chads2-vasc, NIHSS, CT-LAV, and CT-LAAV.
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Table 5. Multivariate analyses showing association between LAA attenuation quartiles and stroke subtype CE
Unadjusted
Model 1
Model 2
Model 3
Model 4
ESUS
LAA attenuation
P value
OR
95% CI
P value
OR
95% CI
Mild Moderate Maximal Mild Moderate Maximal Mild Moderate Maximal Mild Moderate Maximal Mild Moderate Maximal
.622 .189 .011 .867 .596 .099 .827 .193 .027 .837 .328 .014 .705 .281 .01
1.217 1.716 2.95 1.072 1.258 2.104 1.103 1.83 2.792 1.104 1.642 3.431 1.204 1.737 3.71
.557-2.661 .766-3.846 1.281-6.796 .476-2.413 .539-2.938 .868-5.098 .459-2.653 .736-4.546 1.122-6.953 .429-2.844 .608-4.439 1.283-9.179 .460-3.150 .637-4.739 1.366-10.076
.641 .548 .355 .386 .724 .662 .447 .334 .380 .416 .390 .447 .300 .499 .537
.833 1.272 1.488 .703 1.156 1.217 .719 1.527 1.503 .701 1.460 1.427 .628 1.354 1.339
.387-1.795 .580-2.789 .641-3.455 .317-1.559 .517-2.582 .504-2.938 .308-1.680 .647-3.602 .605-3.734 .299-1.648 .616-3.460 .570-3.572 .260-1.515 .562-3.259 .529-3.388
Adjusted covariates in model 1: age, sex; model 2: chads2-vasc and NIHSS; model 3: chads2-vasc, NIHSS, and CT-LAV; model 4: chads2-vasc, NIHSS, CT-LAV, and CT-LAAV.
effect of stroke subtype on LAA density (P = .002), but not for AF status (P = .343). In addition, there were no significant differences in LAA attenuation among patients with CE stroke subtypes based on AF status (273 § 133 HU [n = 97] versus 256 § 113 HU [n = 22], P = .573).
Discussion This study demonstrates increased LAA volume and LAA attenuation are independently associated with CE stroke subtype compared to NCE subtypes, and these associations persisted after adjusting for potential confounders.
Mechanisms of Association The association between CT contrast density and CE stroke subtype is not surprising, as increased contrast density in the LAA may indicate stasis which is one of the prerequisites for thrombus formation and embolic stroke. This was shown in TEE studies where spontaneous echocardiographic contrast (SEC) has been shown to be associated with increased stroke risk in patients with AF.13 Moreover, 1 study demonstrated patients with SEC had significantly greater variability in LAA attenuation measured on contrast enhanced multi-detector CT.14 Interestingly, the association between LAA density and CE stroke subtype persisted after adjusting for LAA volume and for AF. This suggests that, in addition to LAA volume, certain structural and functional elements of LAA may contribute to stagnant blood flow. In fact, studies have shown a correlation between the LAA morphology and low LAA peak flow-velocity that lead to stasis of blood in the LAA.15 In our study, the association between LAA volume and CE stroke subtype was not present after adjusting for AF. This is consistent with previous studies showing that
dilation of the left atrium and perhaps the LAA are associated with AF, particularly the nonparoxysmal types.16-18 On the other hand, it is possible that increased LAA attenuation may be a reflection of other biomarkers of atrial dysfunction or cardiopathy such as fibrosis19, reduced contractility, or increased P-wave terminal force in lead V1 on ECG20 which have been shown to correlate with cryptogenic and CE stroke subtypes. In our study, the association between LAA attenuation and ESUS did not achieve statistical significance, which could partly be related to being underpowered. This could also be due to the fact that ESUS is a heterogeneous group where some are possibly related to embolism from the LAA, while others are related to atherosclerosis, hypercoagulability, or cardiac shunt (PFO).2 Therefore, markers of LAA dysfunction may not be specific to ESUS, and larger studies are needed to further assess this association. Furthermore, the association between LAA attenuation and CE stroke persisted after adjusting for AF and LAA volume. While this finding could be by chance, the LAA may be a source of clots in patients with CE stroke subtypes other than AF. For instance, patients with recent myocardial infarction or reduced ejection fraction could have undiagnosed paroxysmal AF where the LAA serves as the source of thrombus. In addition, factors other than LAA volume may be implicated in causing stagnant flow in the LAA. For instance, studies have shown structural and functional characteristics of the LAA that are associated with stagnant flow and stroke risk. Therefore, increased LAA size is not the only factor leading to stagnant flow within the LAA appendage.4
Therapeutic Implications This study has several therapeutic implications. As opposed to TEE, contrast enhanced CT chest is a
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noninvasive modality with minimal risk and may be a simple tool to evaluate functional and structural aspects of the LAA that predict stroke risk. Furthermore, LAA volume and attenuation may be studied to improve identification of patients at risk for CE stroke, particularly those with AF and a CHADS-VASc score of less than 2 where the treatment is currently controversial. In addition, patients with ESUS and evidence of increased LAA volume or IV-contrast attenuation may constitute a subgroup where the mechanism is CE, and anticoagulation may be tested for secondary stroke prevention. This has been suggested in patients with cryptogenic stroke and evidence of biomarkers of atrial dysfunction or cardiopathy, and the AtRial Cardiopathy and Antithrombotic Drugs In prevention After cryptogenic stroke (ARCADIA) trial is currently testing apixaban versus aspirin in such patients.21
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Our study has several strengths, however. First, chest CT biomarkers were determined by 2 trained investigators with excellent inter-rater agreement who were blinded to stroke subtype. Stroke subtype was prospectively adjudicated before any LAA assessments were performed, limiting any incurred bias. Third, the CT scans performed were of excellent quality and allowed for good visualization of the LAA.
Conclusion LAA attenuation and volume on contrast enhanced chest CT are associated with cardioembolic stroke. Larger multicenter studies are needed to confirm our findings and to investigate the utility of these biomarkers in estimating embolic stroke risk and response to anticoagulation therapy.
Conflict of Interest Strengths and Limitations This study has several major limitations. The chest CT studies obtained were nongated studies, which may have led to variability in measuring LAA volume and density. We found that chest CT type was similar between the 3 categories, but this does not eliminate the implicated bias. Second, this is a small single center study and therefore results lack generalizability and should be considered hypothesisgenerating at this time. Third, not all patients had a CT chest, which is a source of selection bias. Fourth, we lack data on other markers of atrial dysfunction [P wave terminal force in V1 and N-terminal pro b-type natriuretic peptide (NT proBNP)] in addition to TEE-measured LAA biomarkers such as LAA flow velocity. Despite the correlation between LA volume and chest CT and LA volume on TTE in our study, studies are needed to correlate between our CT-measured biomarkers and TEE measurements which are considered a gold standard way to quantify LAA dysfunction. Fifth, our LAA volume and density measurements were done by one rater and thus studies showing inter-rater reliability are needed. In our studies, however, there was a significant correlation between LA volume on TTE and CT chest which implies that highlights the accuracy of our CTbased volumetric assessments. Sixth, while time intervals from chest CTA to stroke were not different between each stroke subtype, we may have been underpowered to detect a difference and therefore future studies should examine this association using chest imaging performed at the time of the stroke. Seventh, a contrast enhanced CT chest may carry a risk of anaphylaxis due to contrast allergy, nephrotoxicity, and radiation exposure which may limit its widespread use. In addition, it adds cost to the healthcare system and may not change management in a large proportion of patients. Therefore, studies are needed to test the cost-effectiveness of CT chest in patients with ischemic stroke and to identify a subgroup where contrast enhanced CT evaluation of the LAA will likely lead to a change in clinical management and prove to be cost-effective.
The authors have no relevant conflict of interest.
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stratification in patients with nonvalvular atrial fibrillation. Scient Rep 2016;6:27650. Hsieh BP, Jha O, Chandra R, et al. Novel computed tomography indexes of left atrial appendage stasis. Int J Cardiovasc Imaging 2013;29:237-244. Fukushima K, Fukushima N, Kato K, et al. Correlation between left atrial appendage morphology and flow velocity in patients with paroxysmal atrial fibrillation. Eur Heart J Cardiovasc Imaging 2016;17:59-66. Seko Y, Kato T, Haruna T, et al. Association between atrial fibrillation, atrial enlargement, and left ventricular geometric remodeling. Scient Rep 2018;8:6366. Andersen JS, Egeblad H, Abildgaard U, et al. Atrial fibrillation and left atrial enlargement: Cause or effect? J Int Med 1991;229:253-256.
18. Rostagno C, Olivo G, Comeglio M, et al. Left atrial size changes in patients with paroxysmal lone atrial fibrillation. An echocardiographic follow-up. Angiology 1996;47: 797-801. 19. Fonseca AC, Alves P, Inacio N, et al. Patients with undetermined stroke have increased atrial fibrosis: a cardiac magnetic resonance imaging study. Stroke 2018;49: 734-737. 20. Kamel H, Hunter M, Moon YP, et al. Electrocardiographic left atrial abnormality and risk of stroke: Northern manhattan study. Stroke 2015;46:3208-3212. 21. Kamel H, Longstreth Jr. WT, Tirschwell DL, et al. The atrial cardiopathy and antithrombotic drugs in prevention after cryptogenic stroke randomized trial: rationale and methods. Int J Stroke 2019;14:207-214.
Increased Left Atrial Appendage Density on Computerized Tomography is Associated with Cardioembolic Stroke Andrew D. Chang, MS,* Gian C. Ignacio, BS,* Ronald Akiki, BS,* Brian Mac Grory, MD,* Shawna S. Cutting, MD,* Tina Burton, MD,* Mahesh Jayaraman, MD,*,†,‡ Alexander Merkler, MD,{ Christopher Song, MD,§ Athena Poppas, MD,§ Hooman Kamel, MD,{ Mitchell S.V. Elkind, MD,║,$ Karen Furie, MD,* Michael Atalay, MD,‡ and Shadi Yaghi, MD# Background and purpose: While studies have stratified cardioembolic (CE) stroke risk by qualitative left atrial appendage (LAA) morphology and biomarkers of atrial dysfunction, the quantitative properties that underlie these observations are not well established. Accordingly, we hypothesized that LAA volume and contrast density (attenuation) on computerized tomography (CT) may capture the structural and hemodynamic processes that underlie CE stroke risk. Methods: Data were collected from a single center prospective ischemic stroke database over 18 months and included all patients with ischemic stroke who previously underwent routine, nongated, contrast enhanced thin-slice (2.5 mm) chest CT. Stroke subtype was determined based on the inpatient diagnostic evaluation. LAA volume and attenuation were determined from CT studies performed for various clinically appropriate indications. Univariate and multivariable analyses were performed to determine factors associated with ischemic stroke subtype, including known risk factors and biomarkers, as well as LAA density and morphologic measures. Results: We identified 311 patients with a qualifying chest CT (119 CE subtype, 109 Embolic Stroke of Undetermined Source (ESUS), and 83 non-CE). In unadjusted models, there was an association between CE (versus non-CE) stroke subtype and LAA volume (OR per mL increase 1.15, 95% CI 1.07-1.24, P < .001) and LAA density (4th quartile versus 1st quartile; OR 2.95, 95% CI 1.28-6.80, P = .011), but not with ESUS (versus non-CE) subtype. In adjusted models, only the association between LAA density and CE stroke subtype persisted (adjusted OR 3.71, 95% CI 1.37-10.08, P = .010). Conclusion: The LAA volume and density values on chest CT are associated with CE stroke subtype but not ESUS subtype. Patients with ESUS and increased LAA volume or attenuation may be a subgroup where the mechanism is CE and anticoagulation can be tested for secondary stroke prevention.
From the *The Warren Alpert Medical School of Brown University, Department of Neurology, Providence, Rhode Island; †The Warren Alpert Medical School of Brown University, Department of Neurosurgery, Providence, Rhode Island; ‡The Warren Alpert Medical School of Brown University, Department of Radiology, Providence, Rhode Island; {Departments of Neurology and Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York, New York; §The Warren Alpert Medical School of Brown University, Department of Internal Medicine, Division of Cardiovascular Medicine, Providence, Rhode Island; ║Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, New York; $Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York; and # New York Langone Hospital, Department of Neurology, Brooklyn, New York. Received September 9, 2019; revision received December 9, 2019; accepted December 13, 2019. Sources of funding: This study was funded by the American Heart Association AHA Award #17MCPRP33670965. Disclosures: Dr. Elkind discloses receiving personal compensation for consulting for Abbott; receiving personal compensation for writing chapters on stroke for UpToDate; and research funding from the BMS-Pfizer Alliance for Eliquis and from Roche for a federally-funded clinical trial of atrial cardiopathy and stroke prevention. Address correspondence to Shadi Yaghi, MD, Department of Neurology, New York Langone Hospital, 150 55th St., Brooklyn, NY 11220. E-mail: [email protected]. 1052-3057/$ - see front matter © 2019 Elsevier Inc. All rights reserved. https://doi.org/10.1016/j.jstrokecerebrovasdis.2019.104604
Journal of Stroke and Cerebrovascular Diseases, Vol. &&, No. && (&&), 2019: 104604
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2 Key Words: Left atrial appendage—stroke—atrial tomography © 2019 Elsevier Inc. All rights reserved.
Introduction Ischemic stroke is a significant cause of mortality in the United States, accounting for 87% of all stroke cases and 113,000 deaths annually.1 Effective stroke treatment and secondary prevention strategies rely on timely identification of stroke mechanism, particularly when it pertains to cardioembolic (CE) subtypes that respond to anticoagulant therapy.2 Previous studies have demonstrated that the left atrial appendage (LAA) is the most common source of thrombus formation in patients with nonvalvular atrial fibrillation, and therefore a primary site of interest in assessing CE stroke risk.3 Moreover, quantitative volumetric and hemodynamic analyses of the LAA have shown increasing promise in predicting ischemic stroke risk. One study suggests that LAA size and structural complexity are valuable indicators of stroke risk.4-6 Computational fluid dynamic analyses further demonstrate the exact mechanisms by which complex LAA morphologies promote stasis and thrombus formation.7 While transesophageal echocardiogram (TEE) is the gold standard modality to assess LAA dysfunction, its use is limited by potential procedural complications such as esophageal perforation, upper gastrointestinal bleeding, and laryngospasm.8 In fact, most ischemic stroke patients do not obtain such a study for work-up of stroke etiology9 but rather have a 2-dimensional transthoracic echocardiogram as part of their diagnostic evaluation, a test that offers limited assessment of LAA structure and function.10 Nevertheless, since hemodynamic status and cardiovascular architecture dictate the speed and distribution of the intravenous contrast agent throughout the body, contrast-enhanced chest computerized tomography (CT) may be capable of not only evaluating underlying cardiac disease,11 but also predicting CE stroke risk by capturing certain variables linked to stagnant flow in the LAA. Namely, hemodynamics underlying thrombus formation in the LAA may be reflected by significant differences in LAA volume or contrast density and these may be indirect markers of stagnant flow. To our knowledge, there is very limited if any data on the association between these measures and CE stroke subtypes in patients with ischemic stroke. This study aims to investigate the association between LAA volume and attenuation acquired through chest CT and embolic stroke subtypes (CE and Embolic Stroke of Undetermined Source (ESUS)) as opposed to nonCE etiologies.
Methods Patient Population The institutional review board at lifespan approved this study. Data were collected from a prospective inpatient
fibrillation—computed
database and included consecutive patients admitted to our facility with a discharge diagnosis of ischemic stroke over an 18-month period. Demographic data and clinical risk factors were retrieved from electronic medical records at the time of discharge. In general, patients admitted with a diagnosis of ischemic stroke underwent a standard diagnostic evaluation that included laboratory testing, brain imaging, intracranial, and extracranial vascular imaging, 12-lead electrocardiogram, cardiac telemetry throughout their inpatient hospital stay, and transthoracic echocardiography.
Study Variables a) Clinical demographic and outcome variables: age, sex, hypertension, diabetes, hyperlipidemia, coronary heart disease, AF, prior transient ischemic attack or stroke, congestive heart failure, current smoking, and National Institute of Health Stroke Scale on admission.
CT Chest With Contrast Protocol Qualifying imaging included thin-slice (2.5 mm) non ECG-gated contrast enhanced CT or CT angiography (CTA) of the chest performed for clinical indications within 5 years from the stroke. Anonymized, thin-slice images were analyzed using commercially available software (iNtuitionTM, TeraRecon, Foster City, CA) for detailed multiplanar reconstruction.
Primary Predictors 1) LAA volume: The LAA was identified on coronal plane inferior to the confluence of left pulmonary veins. Viewing planes were then aligned according to the origin of the LAA as it emerges from the remaining left atrium, demarcated by a sharp change in surface contour readily identified on CT. LAA orifice crosssectional area was measured along this plane. Total LAA volume was measured by serial segmentation and summation of cross-sectional areas starting from the orifice. The LA volume was measured in a similar manner using boundary conditions of the mitral valve and interatrial septum (Fig 1). Due to concerns of accuracy using nongated chest CT for volumetric measurements, we compared CT-based measurements of LA volume with those obtained by standard echocardiography. CT and echocardiogram-based measurements showed a moderate positive correlation (r = .423, n = 133, P < .001).
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Figure 1. Measurement of LAA volume and orifice cross-sectional area. Multiplanar rotation was used to identify the plane of the LAA orifice for measurement of cross-sectional area and volume segmentation. A. First, the LAA was identified on traditional coronal section (highlighted structure), and sections were realigned along the apparent plane of the LAA orifice (dashed line). B. In the modified “sagittal” plane, sections were once again re-aligned to the LAA orifice plane. C. The final, modified “axial” plane provided the true orientation of the LAA orifice without skew.
2) LAA attenuation: Multiplanar reconstruction of chest CTA was used to visualize the long-axis of the LAA. A 2-cm linear region of interest was drawn along the central cavity of the LAA. Serial Hounsfield unit (HU) values were obtained at every 0.5-mm increment along this region of interest, for a total of 40 measurements. The cumulative mean of collected attenuation values were then calculated for each patient and used as the final LAA attenuation value (Fig 2).
Primary Outcome: Stroke subtype The primary outcome was stroke subtype divided into 3 categories: CE, ESUS, and non-CE stroke. All stroke etiologies were determined prospectively by the treating vascular neurology attending using criteria previously described.12
Statistical Analysis Patients were divided into 3 groups: CE subtype, ESUS subtype, and defined nonCE subtype which included large vessel disease, small vessel disease, or other defined mechanism. We compared clinical characteristics between the 3 groups. We used t tests and 1-way ANOVA for continuous variables and Fisher’s test for categorical variables. We used multivariate ANOVA to determine main and interaction effects between stroke subtype and LAA morphology on continuous volumetric measures. We then performed prespecified multivariable regression analyses to determine the associations between stroke subtype and LAA attenuation values. Covariate adjustments were included in regressions according to four prespecified models: model 1, which adjusted for age and sex; model 2, which adjusted for CHADS2-Vasc and National Institute of Health Stroke Scale; model 3, which included covariates in model 2 plus CT LA volume; model 4, which included covariates in model 3 plus CT LAA volume. Analyses were performed using SPSS version 20.0 (Chicago, IL) and P < .05 was considered statistically significant.
Results Baseline Characteristics of the Study Sample
Figure 2. Measurement of LAA attenuation. Multiplanar rotation was used to identify a reconstructed sagittal view of the LAA for measurement of attenuation. A. We created a 2-cm linear ROI was used to trace the central cavity of the LAA, with serial measurements of Hounsfield unit (HU) density at 0.5-mm increments. B. Total mean (represented by dotted black line) and standard deviation (represented by region shaded red) of HU densities along the linear ROI were calculated and used for subsequent analyses.
We identified 311 patients (25.3%) with a qualifying chest CT performed [119 CE subtype, 109 ESUS, and 83 NCE]. Baseline characteristics of patients with and without a qualifying CT were similar. The mean age of all patients in our cohort was 72.5 § 13.8 years, and 55.6% were men. Baseline characteristics of the study sample are shown in Table 1. Of note, while our data consisted of a variety of contrast-enhanced chest CT modalities, imaging techniques did not significantly vary by stroke subtype. Specifically, there were no differences in the proportion of chest CTA modalities obtained, the interval of time from chest CTA to stroke, the type of IV contrast agent used, or the volume and rate of contrast injection (Table 2).
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Table 1. Univariate analysis of baseline characteristics based on stroke subtype Stroke subtype
Age (mean SD) Sex (% female) Hypertension, n Diabetes, n Hyperlipidemia, n Coronary heart disease, n Prior stroke, n Congestive heart failure, n Atrial fibrillation, n Active smoker, n Wall-motion abnormality, n Ejection fraction (mean SD) LA diameter (mean SD) LA volume (mean SD) NIHSS (median, IQR)
CE n = 119 (38.3%)
ESUS n = 109 (35.0%)
NCE n = 83 (26.7%)
P
76.9 § 11.8 61 (51.3%) 102 (85.7%) 29 (24.4%) 61 (51.3%) 38 (31.9%) 28 (23.5%) 31 (26.1%) 97 (81.5%) 15 (12.6%) 17 (24.3%) 57 § 15 42.9 § 7.3 80.4 § 33.8 9.5 (4-22)
69.2 § 15.1 52 (47.7%) 88 (80.7%) 36 (33%) 64 (58.7%) 26 (23.9%) 19 (17.4%) 13 (12%) 1 (0.9%) 22 (20.4%) 4 (6.7%) 62 § 15 35.5 § 6.1 55.8 § 21.9 6 (3-15)
70.6 § 13.2 25 (30.1%) 69 (83.1%) 24 (28.9%) 41 (49.4%) 20 (24.1%) 23 (27.7%) 7 (8.5%) 6 (7.2%) 14 (16.9%) 4 (8.5%) 60 § 10 36.4 § 6.7 56.2 § 23.9 4 (2-12)
<.001 .008 .602 .351 .370 .306 .226 .001 <.001 .287 .007 .046 <.001 <.001 <.001
Table 2. Univariate analysis of chest CTA technique and left atrial measurements based on stroke subtype Stroke subtype
Chest CTA modality, n CTA chest only* CTA chest/abdomen/pelvis IV-contrast agent, n Omnipaque Isovue Visipaque IV-contrast administration Injection volume (median IQR) Injection rate (median IQR) Slice thickness (median IQR) Time interval stroke to chest CTA (median IQR) LA volume (mean SD) LAA volume (mean SD) LAA orifice area (mean SD) LAA morphology Chicken-wing Cauliflower Cactus Windsock LAA attenuation (mean SD)
CE n = 119 (38.3%)
ESUS n = 109 (35.0%)
NCE n = 83 (26.7%)
101 (84.9%) 18 (15.1%)
95 (87.2%) 14 (12.8%)
65 (78.3%) 18 (21.7%)
78 (65.5%) 18 (19.3%) 0 (0.0%)
64 (58.7%) 21 (19.3%) 1 (.9%)
53 (63.9%) 13 (15.7%) 1 (1.2%)
100 (80-130) 4 (3.75-4) 2.5 (.7-2.5) 0.41 (.01-1.64) 93.8 § 30.9 11.0 § 4.6 4.1 § 1.7
100 (80-130) 4 (3-4) 2.5 (.8-2.5) 1.72 (.21-4.04) 66.9 § 19.0 7.9 § 3.8 2.9 § 1.3
100 (100-130) 4 (3-4) 2.5 (.7-2.5) 1.50 (.04-2.64) 71.5 § 22.2 8.5 § 3.8 5.0 § 13.8
33 (27.7%) 13 (10.9%) 21 (17.6%) 52 (43.7%) 270 § 130
19 (17.4%) 15 (13.8%) 15 (13.8%) 60 (55.0%) 237 § 107
37 (44.6%) 9 (10.8%) 7 (8.4%) 30 (36.1%) 216 § 113
P value .239
.889
.112 .379 .672 .214 <.001 <.001 .144 .003
.005
*Includes CTA Chest, CTA Pulmonary Embolism, CTA Aortic Dissection, CTA Coronary, CTA Thoracic.
Association Between LAA Volume and Stroke Subtype Compared to NCE stroke subtypes, patients with CE stroke subtype exhibited larger LAA volumes (11.0 § 4.6 cc versus 8.5 § 3.8 cc, P < .001). On the other hand, there was no significant difference in LAA volume between patients with ESUS and NCE subtypes (7.9 § 3.8 cc versus 8.5 § 3.8 cc, P = .303).
Association Between LAA Attenuation and Stroke Subtype In univariate analyses, when compared to patients with NCE, LAA attenuation values were greater in CE (270 § 130 HU versus 216 § 113 HU, P = .002). LAA attenuation was numerically higher in patients with ESUS compared to NCE stroke but this difference did not achieve
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statistical significance (237 § 107 HU versus 216 § 113 HU, P = .218).
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this association was not significant after adjusting for potential confounders (Table 4). To provide practical thresholds for clinical utility, we repeated our multivariable models using stratified LAA attenuation based on quartiles (n = 78 per group): (1) Minimal LAA attenuation: less than 168 HU; (2) Mild LAA attenuation: 168-240 HU; (3) Moderate LAA attenuation: 241-318 HU; (4) Severe LAA attenuation: greater than 318 HU. Using minimal LAA attenuation as a baseline for comparison, there was a significant association between CE subtype and maximal LAA attenuation exceeding 318 HU (unadjusted OR, 2.95; 95% CI, 1.28-6.80; P = .011), but not for the mild and moderate LAA attenuation quartiles. This pattern of association remained significant in the fully adjusted model (Model 4: adjusted OR for maximal LAA attenuation, 3.71; 95% CI, 1.37-10.08; P = .010; Table 5). On the other hand, using minimal LAA attenuation as a baseline for comparison, there was increased odds of having ESUS stroke subtypes compared to NCE with increasing LAA attenuation, but this difference did not achieve statistical significance (Table 5).
Multivariable Models of the Association Between LAA Volume With Stroke Subtype In unadjusted models, LAA volume was associated with CE compared to NCE stroke subtypes (odds ratio [OR] per mL increase, 1.154; 95% confidence interval [CI], 1.07-1.24; P < .001). This relationship persisted in fully adjusted models (adjusted OR per unit increase, 1.10; 95% CI, 1.01-1.20; P = .038). In contrast, there was no association between LAA volume and ESUS subtypes, when compared to NCE stroke subtypes (OR .95, 95% CI 0.871.04, P = .291; Table 3).
Multivariable Models on the Association Between Stroke Subtype and LAA Attenuation In unadjusted models, there was an association between CE subtype and LAA attenuation (OR per HU increase, 1.004; 95% CI, 1.001-1.006; P = .003), with high sensitivity (.88) and specificity (.61). This association persisted after adjusting for potential confounders (Model 2: adjusted OR per HU increase, 1.004; 95% CI, 1.001-1.007; P = .007), CT-based measurements of LA volume (Model 3: adjusted OR per unit increase, 1.004; 95% CI, 1.0011.007; P = .005), and LAA volume (Model 4: adjusted OR per unit increase, 1.004; 95% CI, 1.001-1.007; P = .004). On the other hand, there was a trend for association between LAA attenuation and ESUS in unadjusted models (OR per unit increase, 1.002; 95% CI, 0.999-1.004; P = .1). However,
Sensitivity Analyses Sensitivity analyses were performed adjusting for AF. When AF was added to the fully adjusted model, we found no association between LAA volume and CE stroke subtype. On the other hand, the association between LAA attenuation and CE stroke subtype persisted after adjusting for AF (adjusted OR per unit increase, 1.007; 95% CI, 1.002-1.012; P = .003). Indeed, 2-way ANOVA analyses redemonstrated these findings, with a significant main
Table 3. Multivariate analyses showing association between LAA volume and stroke subtype CE
Unadjusted Model 1 Model 2 Model 3
ESUS
P value
OR
95% CI
P value
OR
95% CI
<.001 .001 .016 .038
1.15 1.14 1.10 1.10
1.07-1.24 1.06-1.23 1.02-1.10 1.01-1.20
.268 .485 .141 .290
.96 .97 .94 .95
.89-1.03 .90-1.05 .87-1.02 .87-1.04
Model 1 adjusted for age and sex; model 2 adjusted for CHADS2-Vasc score and NIHSS; model 3 adjusted for CHADS2-Vasc, NIHSS and left atrial volume index (LAVI).
Table 4. Multivariate analyses showing association between LAA attenuation and stroke subtype CE
Unadjusted Model 1 Model 2 Model 3 Model 4
ESUS
P value
OR
95% CI
.003 .049 .007 .005 .004
1.004 1.003 1.004 1.004 1.004
1.001-1.006 1.000-1.005 1.001-1.007 1.001-1.007 1.001-1.007
P value .187 .399 .208 0.278 0.317
OR
95% CI
1.002 1.001 1.002 1.002 1.001
.999-1.004 .998-1.004 .999-1.005 .999-1.004 .999-1.004
Adjusted covariates in model 1: age, sex; model 2: chads2-vasc and NIHSS; model 3: chads2-vasc, NIHSS, and CT-LAV; model 4: chads2-vasc, NIHSS, CT-LAV, and CT-LAAV.
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Table 5. Multivariate analyses showing association between LAA attenuation quartiles and stroke subtype CE
Unadjusted
Model 1
Model 2
Model 3
Model 4
ESUS
LAA attenuation
P value
OR
95% CI
P value
OR
95% CI
Mild Moderate Maximal Mild Moderate Maximal Mild Moderate Maximal Mild Moderate Maximal Mild Moderate Maximal
.622 .189 .011 .867 .596 .099 .827 .193 .027 .837 .328 .014 .705 .281 .01
1.217 1.716 2.95 1.072 1.258 2.104 1.103 1.83 2.792 1.104 1.642 3.431 1.204 1.737 3.71
.557-2.661 .766-3.846 1.281-6.796 .476-2.413 .539-2.938 .868-5.098 .459-2.653 .736-4.546 1.122-6.953 .429-2.844 .608-4.439 1.283-9.179 .460-3.150 .637-4.739 1.366-10.076
.641 .548 .355 .386 .724 .662 .447 .334 .380 .416 .390 .447 .300 .499 .537
.833 1.272 1.488 .703 1.156 1.217 .719 1.527 1.503 .701 1.460 1.427 .628 1.354 1.339
.387-1.795 .580-2.789 .641-3.455 .317-1.559 .517-2.582 .504-2.938 .308-1.680 .647-3.602 .605-3.734 .299-1.648 .616-3.460 .570-3.572 .260-1.515 .562-3.259 .529-3.388
Adjusted covariates in model 1: age, sex; model 2: chads2-vasc and NIHSS; model 3: chads2-vasc, NIHSS, and CT-LAV; model 4: chads2-vasc, NIHSS, CT-LAV, and CT-LAAV.
effect of stroke subtype on LAA density (P = .002), but not for AF status (P = .343). In addition, there were no significant differences in LAA attenuation among patients with CE stroke subtypes based on AF status (273 § 133 HU [n = 97] versus 256 § 113 HU [n = 22], P = .573).
Discussion This study demonstrates increased LAA volume and LAA attenuation are independently associated with CE stroke subtype compared to NCE subtypes, and these associations persisted after adjusting for potential confounders.
Mechanisms of Association The association between CT contrast density and CE stroke subtype is not surprising, as increased contrast density in the LAA may indicate stasis which is one of the prerequisites for thrombus formation and embolic stroke. This was shown in TEE studies where spontaneous echocardiographic contrast (SEC) has been shown to be associated with increased stroke risk in patients with AF.13 Moreover, 1 study demonstrated patients with SEC had significantly greater variability in LAA attenuation measured on contrast enhanced multi-detector CT.14 Interestingly, the association between LAA density and CE stroke subtype persisted after adjusting for LAA volume and for AF. This suggests that, in addition to LAA volume, certain structural and functional elements of LAA may contribute to stagnant blood flow. In fact, studies have shown a correlation between the LAA morphology and low LAA peak flow-velocity that lead to stasis of blood in the LAA.15 In our study, the association between LAA volume and CE stroke subtype was not present after adjusting for AF. This is consistent with previous studies showing that
dilation of the left atrium and perhaps the LAA are associated with AF, particularly the nonparoxysmal types.16-18 On the other hand, it is possible that increased LAA attenuation may be a reflection of other biomarkers of atrial dysfunction or cardiopathy such as fibrosis19, reduced contractility, or increased P-wave terminal force in lead V1 on ECG20 which have been shown to correlate with cryptogenic and CE stroke subtypes. In our study, the association between LAA attenuation and ESUS did not achieve statistical significance, which could partly be related to being underpowered. This could also be due to the fact that ESUS is a heterogeneous group where some are possibly related to embolism from the LAA, while others are related to atherosclerosis, hypercoagulability, or cardiac shunt (PFO).2 Therefore, markers of LAA dysfunction may not be specific to ESUS, and larger studies are needed to further assess this association. Furthermore, the association between LAA attenuation and CE stroke persisted after adjusting for AF and LAA volume. While this finding could be by chance, the LAA may be a source of clots in patients with CE stroke subtypes other than AF. For instance, patients with recent myocardial infarction or reduced ejection fraction could have undiagnosed paroxysmal AF where the LAA serves as the source of thrombus. In addition, factors other than LAA volume may be implicated in causing stagnant flow in the LAA. For instance, studies have shown structural and functional characteristics of the LAA that are associated with stagnant flow and stroke risk. Therefore, increased LAA size is not the only factor leading to stagnant flow within the LAA appendage.4
Therapeutic Implications This study has several therapeutic implications. As opposed to TEE, contrast enhanced CT chest is a
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noninvasive modality with minimal risk and may be a simple tool to evaluate functional and structural aspects of the LAA that predict stroke risk. Furthermore, LAA volume and attenuation may be studied to improve identification of patients at risk for CE stroke, particularly those with AF and a CHADS-VASc score of less than 2 where the treatment is currently controversial. In addition, patients with ESUS and evidence of increased LAA volume or IV-contrast attenuation may constitute a subgroup where the mechanism is CE, and anticoagulation may be tested for secondary stroke prevention. This has been suggested in patients with cryptogenic stroke and evidence of biomarkers of atrial dysfunction or cardiopathy, and the AtRial Cardiopathy and Antithrombotic Drugs In prevention After cryptogenic stroke (ARCADIA) trial is currently testing apixaban versus aspirin in such patients.21
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Our study has several strengths, however. First, chest CT biomarkers were determined by 2 trained investigators with excellent inter-rater agreement who were blinded to stroke subtype. Stroke subtype was prospectively adjudicated before any LAA assessments were performed, limiting any incurred bias. Third, the CT scans performed were of excellent quality and allowed for good visualization of the LAA.
Conclusion LAA attenuation and volume on contrast enhanced chest CT are associated with cardioembolic stroke. Larger multicenter studies are needed to confirm our findings and to investigate the utility of these biomarkers in estimating embolic stroke risk and response to anticoagulation therapy.
Conflict of Interest Strengths and Limitations This study has several major limitations. The chest CT studies obtained were nongated studies, which may have led to variability in measuring LAA volume and density. We found that chest CT type was similar between the 3 categories, but this does not eliminate the implicated bias. Second, this is a small single center study and therefore results lack generalizability and should be considered hypothesisgenerating at this time. Third, not all patients had a CT chest, which is a source of selection bias. Fourth, we lack data on other markers of atrial dysfunction [P wave terminal force in V1 and N-terminal pro b-type natriuretic peptide (NT proBNP)] in addition to TEE-measured LAA biomarkers such as LAA flow velocity. Despite the correlation between LA volume and chest CT and LA volume on TTE in our study, studies are needed to correlate between our CT-measured biomarkers and TEE measurements which are considered a gold standard way to quantify LAA dysfunction. Fifth, our LAA volume and density measurements were done by one rater and thus studies showing inter-rater reliability are needed. In our studies, however, there was a significant correlation between LA volume on TTE and CT chest which implies that highlights the accuracy of our CTbased volumetric assessments. Sixth, while time intervals from chest CTA to stroke were not different between each stroke subtype, we may have been underpowered to detect a difference and therefore future studies should examine this association using chest imaging performed at the time of the stroke. Seventh, a contrast enhanced CT chest may carry a risk of anaphylaxis due to contrast allergy, nephrotoxicity, and radiation exposure which may limit its widespread use. In addition, it adds cost to the healthcare system and may not change management in a large proportion of patients. Therefore, studies are needed to test the cost-effectiveness of CT chest in patients with ischemic stroke and to identify a subgroup where contrast enhanced CT evaluation of the LAA will likely lead to a change in clinical management and prove to be cost-effective.
The authors have no relevant conflict of interest.
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