Precranial artery calcification burden: a potential indicator of the clinical outcome of reperfusion in patients with acute large artery occlusion

Abstract

Objective

With mechanical thrombectomy (MT), we investigated the prognostic importance of aortic arch calcification (AoAC) and carotid sinus calcification (CaSC) for symptomatic intracerebral hemorrhage (sICH) and poor outcome in acute large artery occlusion (LAO).

Methods

In this retrospective observational study, we calculated pre-cranial artery calcification burden (PACB) scores (burden score of AoAC and CaSC) using the AoAC grading scale score plus Woodcock visual score. The outcome measure was sICH per the European Cooperative Acute Stroke Study III definition. A 3-month modified Rankin scale score 3–6 was designated as poor outcome.

Results

Compared with patients who had PACB <3, those with PACB ≥3 showed substantially higher risks of sICH (odds ratio [OR] = 2.567, 95% confidence interval [CI] = 1.187–5.550) and poor outcome (OR = 4.777, 95% CI = 1.659–13.756). According to receiver operating characteristic (ROC) curves, adding PACB to the regression model enhanced the predictive value for poor outcome (area under the ROC curve [AUC]: 0.718 vs. 0.519, Z = 2.340) and in patients receiving MT (AUC: 0.714 vs. 0.584, Z = 2.021), independently.

Conclusions

Factors related to PACB were consistent with common risk factors of systemic atherosclerosis. Low PACB scores indicated better prognosis. In patients with LAO following MT, PACB was useful in predicting sICH and poor clinical outcome.

Keywords

Aortic arch calcification carotid sinus calcification large artery occlusion symptomatic intracerebral hemorrhage reperfusion treatment retrospective study

Introduction

Acute ischemic stroke is a major cause of morbidity and mortality worldwide. In the setting of large artery occlusion (LAO), reperfusion treatment including intravenous thrombolysis (IV) and mechanical thrombectomy (MT) have considerably helped to improve patient outcomes. As the most serious complication of reperfusion treatment for LAO, the risk of symptomatic intracerebral hemorrhage (sICH) was 4.4% in an EVT arm vs. 4.3% in the control arm, according to one report.¹

Arterial calcification has long been associated with advanced atherosclerosis.^2,3 Previous studies have explored the correlation between systemic arterial calcification and hemorrhagic transformation (HT) or poor prognosis after thrombolysis, but the conclusions are inconsistent.^4–7 These studies, however, have mainly focused on intracranial arterial calcification, which is rarely present at the pre-treatment stage. Moreover, the relationship between systemic arterial calcification, sICH, and long-term stroke prognosis remains unclear, especially in patients with LAO who receive reperfusion therapy.

Calcification in the pre-cranial arteries, which include aortic arch calcification (AoAC) and carotid siphon calcification (CaSC), is associated with the burden of systemic calcification.⁸ Kim et al. found that calcifications of the internal carotid artery (ICA) can reflect the degree of cerebral atherosclerosis.⁹ Because the aortic arch to the carotid artery is the only way for intravenous recombinant tissue plasminogen activator (rt-PA) or thrombectomy devices to enter the brain, we hypothesized that assessment of the calcification burden of AoAC and CaSC may be a factor in predicting the outcomes of reperfusion therapy. Two visual calcification grading systems, the AoAC grading scale¹⁰ and CaSC Woodcock visual score,¹¹ have been used to accurately assess the degree of calcification on non-contrast computed tomography (NCCT). Therefore, we aimed to investigate the associations between pretreatment pre-cranial artery calcification burden (PACB; AoAC plus CaSC score) and outcomes for patients with LAO stroke who receive reperfusion treatment.

Methods

Patients

This was a retrospective observational study. We used data from our site within the International Stroke Perfusion Imaging Registry (INSPIRE). The registry received central ethics board approval from the Hunter New England Health District ethics committee (2023, no. 11/08/17/4.01) and institutional ethics board approval. Written informed consent was obtained for each patient for the collection of their clinical and demographic data. From the INSPIRE database, patients with anterior circulation ischemic stroke from March 2018 to March 2022 were consecutively included in the study if they fulfilled the following criteria: (i) underwent pre-treatment multimodal CT including NCCT and CT perfusion (CTP); (ii) had middle cerebral artery (MCA), anterior cerebral artery (ACA), or ICA occlusion on pretreatment 4D CT angiography (CTA) reconstructed from CTP; (iii) pre-stroke modified Rankin Scale score (mRS) ≤2. Patients were excluded if they (i) had poor image quality owing to motion artifact, and (ii) could not tolerate clinical and imaging follow-up before discharge.

Imaging acquisition and analysis

Imaging protocol

All CT imaging was acquired on a 320-detector row 640-slice cone beam multidetector CT scanner (Aquilion One, Toshiba Medical Systems). Whole-brain NCCT was performed in one rotation (detector width, 16 cm). Subsequent to NCCT, a CTP was acquired after administering 50 mL of contrast agent (Ultravist 370; Bayer HealthCare, Berlin, Germany) injected intravenously at a rate of 6 mL/s followed by 50 mL of saline (acquisition parameters: 120 kV, 128 mAs; scanning coverage 240 mm, scanning width 5 mm). Starting 7 s after contrast injection, a pulsed full rotation scan with 18 time points acquired over 60 s with a total pulse image acquisition time of 9.5 s was used. The scanning protocol of follow-up NCCT performed within 24 hours after intervention was the same as that of the baseline NCCT.

All patients also underwent magnetic resonance imaging (MRI) examination using a 3.0-Tesla scanner (Discovery MR 750; GE Healthcare, Waukesha, WI, USA) during hospitalization. The protocol included axial T2-weighted, fluid-attenuated inversion recovery (FLAIR) and diffusion weighted imaging (DWI). The parameters of MRI sequences were: 1) T2-FLAIR: repetition time (TR) = 9000 ms, echo time (TE) = 120 ms, field of view (FOV) = 220 cm, matrix = 256 × 256, flip angle = 160, echo train length = 18, bandwidth = 50, slice thickness = 5 mm, and interslice gap =1.5 mm; 2) DWI: TR = 3071 ms, TE =120 ms, FOV = 220 × 220 cm, matrix = 160 ×192, slice thickness = 5 mm, interslice gap = 1.5 mm, and b-value = 0, 1000.

Pre-cranial artery calcification burden (PACB) assessment

The PACB score, comprising the burden score of AoAC and CaSC, was calculated as the AoAC grading scale (AGS) score plus Woodcock visual score. According to the AGS, the AoAC on baseline chest CT was divided into no visible calcification (0 points), spotty calcification (1 point), lamellar calcification (2 points), and circular calcification (3 points) (Figure 1(a)).¹⁰ According to the Woodcock visual score, CaSC on baseline non-contrast cranial CT was divided into no visible calcification (0 points), thin discontinuous calcification (1 point), thin continuous or thick discontinuous calcification (2 points), and thick continuous calcification (3 points) (Figure 1(b)).¹¹

Figure 1.

(a) Aortic arch calcification (AoAC) grading scale (AGS). According to the AGS, the degree of AoAC detected by chest computed tomography (CT) was divided into four grades (the white arrow points to the calcification area): no visible calcification (0 points), spotty calcification of the aortic arch ≤1 mm in diameter (1 point), lamellar calcification >1 mm in diameter (2 points), circular calcification (3 points) and (b) carotid siphon calcification (CaSC) score. According to the Woodcock visual score, CaSC on baseline non-contrast cranial CT was divided into four grades: no visible calcification (0 points), thin discontinuous calcification (1 point), thin continuous or thick discontinuous calcification (2 points), and thick continuous calcification (3 points) (Figure 1(b)). Severe pre-cranial artery calcification burden (PACB) was defined as PACB score (AoAC plus CaSC score) ≥3 points.

According to our observational assumption, patients with PACB scores 3 to 6 were assigned to the severe calcification group, and those with PACB scores 0 to 2 were assigned to the non-severe calcification group.

Assessment of hypoperfusion and ischemic core volume

All pre-treatment brain CTPs were post-processed with MIStar (Apollo Medical Imaging Technology, Melbourne, Australia). The software automatically performs motion correction and selects an arterial input function from an unaffected artery (most often the ACA). A threshold delay time >3 s was used for volumetric measurement of the hypoperfusion area and relative cerebral blood flow <30% was used for calculating ischemic core volume.¹²

Intracranial CT angiography clot burden score (CBS)

A 10-point score is normal, implying the absence of a thrombus. Two points (as indicated) were subtracted for a thrombus found on CTA in the supraclinoid ICA and each of the proximal and distal halves of the MCA trunk.¹³

Cerebral small vessel disease (CSVD) burden score

All four MRI markers of CSVD (lacunes, white matter hyperintensities [WMHs], perivascular spaces [PVSs], and cerebral microbleeds [CMBs]) were identified according to the previously reported neuroimaging standards.¹⁴ Briefly, the deep white matter and periventricular white matter were graded separately according to the Fazekas scale. We graded the number of PVSs in the basal ganglia using a three-category ordinal scale, as follows: 0–10 (category 1); 11–25 (category 2); >25 (category 3). The number of lacunes and CMBs was also recorded. CMBs strictly located in lobes were not recorded. For each patient, an overall CSVD burden score was calculated by adding 1 point with the presence of any of the four CSVD markers. The overall CSVD score ranged from 0 to 4 points. The CSVD burden scores were assessed on the contralateral hemispheres.

Two raters (XFC and SZ), blinded to the clinical data and patient course and outcomes, jointly evaluated the AoAC and CaSC scores, CSVD burden score, CBS, and HT. One rater (XFC) measured the above parameters in all patients twice, with the two raters reviewing the sessions at a 1-month interval. The other observer (SZ) independently performed the same evaluation.

Outcomes

The primary outcomes were sICH and 3-month mRS score of 3 to 6. HT was classified as hemorrhagic infarction or parenchymal hemorrhage, according to the European Cooperative Acute Stroke Study definition. sICH was defined as any intracranial hemorrhage associated with an increase of ≥3 points on the National Institutes of Health Stroke Scale (NIHSS) or death in 7 days.¹⁵

The NIHSS score was evaluated at three time points: baseline, 24 to 72 hours after admission, and at discharge. The mRS score was used to identify the clinical outcome at 3 months after discharge. An mRS score of 0 to 2 was designated a good outcome; an mRS score of 3 to 6 was designated a poor outcome.

Statistical analysis

Statistical analyses were performed using IBM SPSS version 24.0 (IBM Corp., Armonk, NY, USA). The kappa statistic and intraclass correlation coefficient (ICC) were used to test inter- and intra-observer reliability for evaluating the AoAC and CaSC scores, CBS, CSVD burden score, and HT.

Demographic and baseline characteristics and imaging features were reported using descriptive statistics. Numeric and nominal variables are expressed as the mean ± standard deviation or median (interquartile range [IQR]) and frequency (percentage), respectively. A t-test was used to compare normally distributed data between groups, and the rank-sum test was used to compare non-normally distributed data. Counting data are expressed as frequency and percentage, and chi-square analysis was used for comparisons between groups. A correlation heat map was drawn to visualize the correlations between PACB score and other baseline characteristics after stroke using corrplot package (R version 3.6.1; www.r-project.org). Binary logistic regression analysis was performed to identify risk factors for sICH and poor patient outcome. Pooled data are presented with 95% confidence intervals (CIs) and displayed in a forest plot using R version 3.6.1. After univariate analysis of all clinically relevant covariates, those with p < 0.05 were included in the multivariable logistic model. Statistical significance was set at p < 0.05.

Ethics approval and consent to participate

The protocols of this study were approved by the local ethics committee. Our study was conducted in accordance with the Helsinki Declaration of 1975, as revised in 2013. The authors declare that all supporting data are available within the article and its Data Supplement. We de-identified all patient details. The reporting of this study conforms to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.¹⁶

Results

Inter- and intra-observer agreement

Excellent inter- and intra-observer reliabilities were achieved for the AoAC score (κ = 0.959 and 0.868, respectively), CaSC score (κ = 0.908 and 0.8567, respectively), HT (κ = 0.925 and 0.915, respectively), CBS (ICC = 0.913, p < 0.05), and CSVD burden score (ICC = 0.872, p < 0.05).

Patient characteristics

Of 189 patients who met the inclusion criteria, 186 were finally enrolled; three patients were excluded owing to poor image quality. Among the total, 70 (37.6%) were men. The median (range) age was 71 (58–80) years and the median (IQR) NIHSS score at baseline was 15 (11–19). In total, 153 patients (74.6%) were identified as having AoAC and 142 (69.3%) as having CaSC. The PACB score (i.e., the AoAC plus CaSC score) showed a median (IQR) of 3 (1–4), and 74 (39.9%) patients had PACB scores ≥3. All 186 patients received reperfusion therapy, including 16.8% (31/186) who were treated with IV rt-PA, 59.7% (111/186) with direct MT, and 23.7% (44/186) with bridging therapy. After reperfusion therapy, of 83 patients (44.6%) who had HT based on follow-up CT, 32 (17.2%) had sICH. Patients’ median (IQR) NIHSS score at discharge was 8 (3–16), and 60.2% (112/186) had a poor 3-month outcome.

Factors associated with PACB

A Spearman correlation test revealed a significant relationship between the AoAC and CaSC score (ρ = 0.474, p < 0.001) (Figure 2). AoAC was associated with CSVD. In all patients (n = 186), binary logistic regression analysis showed that, compared with patients who had a PACB score of 6, those with PACB scores 0 to 2 were less likely to have sICH; patients with PACB scores 3 to 5 showed no significant difference in risk of sICH (Figure 3(a)). Among patients who received MT (n = 155), compared with patients who had a PACB score of 6, those with scores 0 to 2 were also less likely to have sICH (Figure 3(b)). AoAC was associated with SVD score, age, smoking, hypertension, atrial fibrillation (AF), baseline glucose, white blood cells (WBC), C-reactive protein, cholesterol, warfarin use, and baseline NIHSS score. CaSC was associated with CSVD score, age, hypertension, systolic blood pressure (SBP), and baseline NIHSS score.

Figure 2.

Pairwise comparisons of baseline factors are shown with a color gradient denoting Spearman’s rank correlation coefficient. Edge width corresponds to the Mantel’s statistic, and edge color denotes the statistical significance based on 999 permutations. The color gradient indicates Spearman’s rank correlation coefficients, with more positive values (dark blue) indicating stronger positive correlations and more negative values (dark red) indicating stronger negative correlations. CaSC, carotid sinus calcification; AoAC, aortic arch calcification; PACB, pe-cranial artery calcification burden; LS, lacunar stroke; PVS, perivascular space; SVD, small vascular disease; WMH, white matter hyperintensities; DBP, diastolic blood pressure; SBP, systolic blood pressure; CBS, clot burden score; TIA, transient ischemic attack; CHO, cholesterol; LDL, low density lipoprotein; WBC, white blood cell; CRP, c-reactive protein; CMB, cerebral microbleed; IHD, ischemic heart disease; AF, atrial fibrillation; TOAST, Trial of Org 10172 in Acute Stroke Treatment; NIHSS, National Institutes of Health stroke scale.

Figure 3.

Binary logistic regression analysis for the relationship of pre-cranial artery calcification burden (PACB) score with symptomatic intracerebral hemorrhage (sICH). (a) In all patients (n = 186), forest plot of risk factors (p ≥ 0.05) for sICH in stroke patients with reperfusion therapy in univariate logistic regression analysis. Four potential risk factors (age, ischemic core volume, PACB score, and clot burden score [CBS]) were analyzed using univariate regression analysis. Forest plots showed that compared with patients who had a PACB score of 6, patients with PACB scores 0–2 were less likely to have sICH and (b) in patients who received mechanical thrombectomy (n = 155), compared with patients who had a PACB score of 6, those with scores 0–2 were also less likely to have sICH. OR, odds ratio; CI, confidence interval.

PACB was associated with CSVD score, age, smoking, hypertension, SBP, AF, glucose, WBC, and baseline NIHSS score. AoAC, CaSC, and PACB scores were not associated with ischemic hypoperfusion and core volumes.

Association between PACB score and clinical outcome

The results of univariate analysis for factors associating with sICH and 3-month poor outcome are described in Supplementary Tables 1 and 2. Spearman’s correlation analysis showed that PACB scores were not associated with HT but were associated with sICH, NIHSS score, and mRS score at discharge, as well as the occurrence of poor outcome (all p < 0.05).

The distribution of each PACB score according to the occurrence of sICH and poor outcome is shown in Supplementary Figure 1. In all patients (n = 186), binary logistic regression analysis showed that, compared with patients who had a PACB score of 6, those with PACB scores 0 to 2 were less likely to have sICH; patients with PACB scores 3 to 5 showed no significant associated with the risk of sICH (Figure 3(a)). In patients who received MT (n = 155), compared with patients with a PACB score of 6, those with scores 0 to 2 were also less likely to have sICH (Figure 3(b)). Receiver operating characteristic (ROC) curve analysis showed that the PACB score had good predictive value for sICH in all patients (n = 186), with an area under the ROC curve (AUC) of 0.719 (95% CI = 0.631–0.806, p < 0.001; sensitivity: 68.8%, specificity: 66.2%) and a cutoff value at 3. Patients with PACB score ≥3 had an approximately 2.6-fold higher risk of sICH when compared with patients who scored less than 3 (odds ratio [OR] = 2.567, 95% CI = 1.187–5.550, p = 0.017).

As for poor 3-month outcome, binary logistic regression analysis also showed that patients with PACB scores 0 to 2 were less likely to have poor outcomes in comparison with patients who had a PACB score of 6. In subgroup analysis of patients who received MT, a similar result was found in patients with PACB scores 0 to 2 (Figure 4). In all populations (n = 186), ROC analysis showed that PACB score had a good predictive value for poor outcome, with an AUC of 0.646 (95% CI = 0.588–0.762, p < 0.001; sensitivity: 67%, specificity: 59.5%) and a cutoff score of 3. Patients with PACB scores ≥3 had an approximately 4.8-fold risk of poor outcomes when compared with patients who scored less than 3 (OR = 4.777, 95% CI = 1.659–13.756, p = 0.004).

Figure 4.

Binary logistic regression analysis for the relationship of pre-cranial artery calcification burden (PACB) score with poor outcome. (a) In all patients (n = 186), forest plot of risk factors (p < 0.05) for poor outcome in patients with stroke who received reperfusion therapy in univariate logistic regression analysis. Four potential risk factors (age, ischemic core volume, atrial fibrillation [AF] and PACB score) were analyzed using univariate regression analysis. Forest plots showed that compared with patients who had a PACB score of 6, those with PACB scores 0–2 were less likely to have poor outcomes and (b) in patients who received mechanical thrombectomy (n = 155), compared with patients with a PACB score of 6, those with scores 0–2 were also less likely to have poor outcomes. CBS, clot burden score; OR, odds ratio; CI, confidence interval.

ROC analysis also showed that, compared with the regression model that did not include PACB score, inclusion of the PACB score in the model provided a higher predictive value for 3-month poor outcome in all patients (AUC: 0.718 vs. 0.519, Z = 2.340, p = 0.019) and in patients who received MT (AUC: 0.714 vs. 0.584, Z = 2.021, p = 0.043) (Figure 5(b), (d)). However, this extra benefit of the PACB score was not found in predicting sICH (Figure 5(a), (c)). In addition, in all 154 patients with MT, only nine were not recanalized. We did not find that PACB had a similar impact in recanalized versus non-recanalized patients. Further investigation with a larger number of patients is needed.

Figure 5.

ROC comparison analysis in all patients and patients with mechanical thrombectomy. ROC, receiver operating curve; AF, atrial fibrillation; PACB, pre-cranial artery calcification burden; AUC, area under the ROC curve; CBS, blot burden score.

Discussion

In this study, we found that the factors related to PACB are consistent with common risk factors of systemic atherosclerosis. The lower the PACB score, especially when <3 points, the less likelihood of having sICH or long-term poor outcome; this result was still valid in patients who received MT. A low PACB score indicated a better prognosis than a high PACB score (≥3 points).

Our correlation analysis results suggested that age, CSVD score, past disease history, and certain inflammatory mechanisms may jointly affect the degree of PACB. Most of these factors are classic risk factors for atherosclerosis. However, it is worth noting that CSVD score was the factor most closely related to the PACB score in this study, except for age. Previous studies have reported the relationship between a degree of intracranial and extracranial calcification and CSVD components (e.g., WMH, PVS, CMB);^7,17–19 however, this study adds evidence regarding the comorbidity of PACB and CSVD in patients with acute LAO.

Previous studies have investigated the relationship between the arterial calcification burden and risk of stroke recurrence. In recent years, however, researchers have begun to focus on the mechanism of arterial calcification burden affecting the prognosis of stroke.²⁰ We found that the lower the PACB score, the lower the risk of sICH and poor outcome. Especially when the score was less than 3, the risk of sICH and poor prognosis was significantly lower than that of patients with a PACB score of 6. However, with a PACB score ≥3, the risk of sICH and poor prognosis was approximately 2.6 and 4.8 times that of patients with a PACB score of 0 to 2, respectively. The underlying mechanism may be that, when the burden of pre-cranial calcification is increased, the degree of arterial stiffness or lumen stenosis is high. This might hinder the thrombolytic efficiency or advance of the thrombus removal stent, thereby hindering complete removal of the thrombus, affecting the recanalization degree and even leading to symptomatic HT owing to vascular wall damage.²¹

Our research serves to improve the evaluation the arterial calcification burden from the aortic arch to the skull before reperfusion treatment with the combination of chest and brain CT scans, and our findings can have a role in promoting investigation of the mechanism related to systematic calcification in the prognosis of stroke. As a routine examination, assessment using NCCT is suitable for clinical practice in most hospitals. Although some studies have improved evaluation of the degree of intracranial calcification with the aid of enhanced CT, owing to increased intracranial bone structures, it is necessary to distinguish the high density of blood vessels and bones to determine whether vascular wall calcification is present, agreement about which is challenging between readers. In addition, Kim et al.⁹ found that calcification of the ICA can reflect the degree of intracranial atherosclerosis. Therefore, in this study, we selected the aortic arch and ICA for evaluation of calcification, which can reflect the degree of calcification in key areas with systemic calcification after the blood leaves the heart. Our results also showed that considering that the PACB score before reperfusion treatment will improve the predictive ability of long-term prognosis. In the future, we will further evaluate and verify the effectiveness of the PACB score using a larger prospective dataset.

This study has several limitations. First, the study design was retrospective and selection bias cannot be ruled out. Second, the data in the current study were derived from a single center and the number of patients with LAO was small. Third, although sICH was independently related to severe systemic calcification in our study, we could not conclude that severe systemic calcification is a strict contraindication for reperfusion treatment in LAO.

Conclusion

Our findings indicated the possibility of increased sICH and poor outcome incidence in patients with LAO and severe systemic calcification. PACB was effective in predicting sICH and 3-month poor outcome in patients with LAO after reperfusion treatment. Taking the PACB score into consideration may yield more precise prediction of poor outcomes; however, this should be confirmed using a larger prospective clinical dataset in the future.

Supplemental Material

sj-pdf-1-imr-10.1177_03000605241260364 - Supplemental material for Precranial artery calcification burden: a potential indicator of the clinical outcome of reperfusion in patients with acute large artery occlusion

Supplemental material, sj-pdf-1-imr-10.1177_03000605241260364 for Precranial artery calcification burden: a potential indicator of the clinical outcome of reperfusion in patients with acute large artery occlusion by Xiaofeng Cai, Dengfeng Zhou, Peng Wang, Zheyu Zhang, Yongmei Fan, Longting Lin, Yu Geng, Mahmud Mossa-Basha, Chengcheng Zhu and Sheng Zhang in Journal of International Medical Research

Footnotes

Authors’ contributions

XC, SZ, and YG contributed to the conception and design of this study. XC, DZ, and YF contributed to acquisition and analysis of the data and figure preparation. PW, ZZ, and LL contributed to the data analysis. XC, SZ, CZ, and MM contributed to drafting the manuscript. All authors contributed to the article and approved the submitted version.

Date availability statement

The data are openly available in a public repository ().

Declaration of conflicting interest

The authors declare that there is no conflict of interest.

Funding

This work was supported by Zhejiang Traditional Chinese Medicine Science and Technology Program (grant no. 2023ZL259), the Medical Science and Technology Project of Zhejiang Province (grant no. 2022KY600 and 2024KY019), the Zhejiang Provincial Natural Science Foundation of China (grant no. LGF22H090020), the Medical Health Science and Technology Project of the Zhejiang Provincial Health Commission (grant no. 2024KY637), and Key Project of the Department of Science and Technology of Zhejiang Province (2018C03008). The perfusion analysis software (MIStar) was provided to the site as part of their involvement in INSPIRE (), a study funded by the National Health and Medical Research Council of Australia.

ORCID iDs

Xiaofeng Cai

Peng Wang

Supplementary material

Supplemental material for this article is available online.

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Supplementary Material

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