Using Standard First-Pass Perfusion Computed Tomographic Data to Evaluate Collateral Flow in Acute Ischemic Stroke
Background and Purpose—The study aims to determine whether volume transfer constant (Ktrans) maps calculated from first-pass perfusion computed tomographic data are a biomarker of cerebral collateral circulation and predict the clinical outcome in acute ischemic stroke caused by proximal arterial occlusion.
Methods—Consecutive patients with acute occlusion of the middle cerebral artery who received endovascular treatment were enrolled. Digital subtraction angiography, computed tomographic angiography with maximum intensity projection, and Ktrans maps were used to assess their collateral circulation. Agreement between different methods was evaluated using the χ2 tests. The correlations of various radiological and clinical outcomes with the collateral flow score, as determined from Ktrans maps, were calculated.
Results—Seventy-five patients were included, comprising 39 women and 36 men, with a mean age of 65.3±14.6 years. Collateral flow score on Ktrans maps had the highest correlation with digital subtraction angiography (κ=0.8101; P=0.9796). Twenty-five patients had poor collateral circulation on Ktrans maps, 25 had intermediate collateral flow, 20 had good collateral flow, and 5 had excellent collateral flow. Better collateral circulation was associated with better clinical outcome (P<0.0001).
Conclusions—Ktrans maps extracted from standard first-pass perfusion computed tomography are correlated with collateral circulation status after acute proximal arterial occlusion and predictive of outcome.
Collateral blood vessels can provide alternate routes for cerebral circulation, both acutely and chronically, when an artery becomes severely stenotic or occluded. They can preserve perfusion and stabilize cerebral blood flow, thus representing an important determinant of tissue fate. As such, they may represent a potential therapeutic target.1 Good collateral circulation has been shown to correlate with a reduced rate of hemorrhagic transformation, an improved reperfusion rate, smaller infarct cores, and improved clinical outcome.2
Digital subtraction angiography (DSA) is the reference standard for imaging of the Willisian and leptomeningeal collateral vessels. However, DSA is time consuming and invasive and requires expert interventionists to perform. Recent studies have focused on other noninvasive imaging methods for assessment of collateral circulation, including computed tomographic angiography (CTA), perfusion computed tomography (PCT), and arterial spin labeling, among others. Of these techniques, CTA is the most widely used and has good image quality. Maximum intensity projection (MIP) and source imaging are the most studied methods of rendering CTA images.3 Dynamic CTA can be time-resolved and provides data on cerebral vessels in 4 dimensions; it may be a promising way to evaluate collateral flow in the future.4 Kim et al used source data from another novel MRI technique, dynamic susceptibility contrast MRI, to visualize leptomeningeal collaterals in acute ischemic stroke patients with proximal artery occlusion.5 Kim et al also used multiphasic PCT to visualize the leptomeningeal collaterals according to the same principle.6 However, postprocessing and interpretation were still time consuming, and the collateral circulation was still difficult to quantify.5
PCT is a useful tool for assessing tissue at risk in patients with acute ischemic stroke. It can also be used to quantify blood–brain barrier permeability using models such as the Patlak model.7,8 Several studies have used this approach to predict hemorrhagic transformation.9,10
In this study, we test volume transfer constant (Ktrans) maps as a possible surrogate for the collateral flow score (CFS) in acute ischemic stroke by comparing them with CFS values obtained by CTA-MIP and DSA. In addition, we evaluate whether the CFS as determined from PCT permeability can be used to predict clinical or radiological outcomes in patients with acute ischemic stroke who received endovascular treatment.
Materials and Methods
The clinical and imaging data presented in this study were obtained from a repository of data collected as part of standard stroke care at 3 participating institutions: the Military General Hospital of Beijing PLA, Beijing; Southwest Hospital, Chongqing; and Changhai Hospital, Shanghai. Only completely anonymized data were contributed to the repository. Collection and analysis of data from the repository were approved by the respective institutional review boards of the contributing institutions.
We retrospectively identified all consecutive patients admitted to these institutions from January 2011 to January 2014 with signs and symptoms suggesting hemispheric stroke. Inclusion criteria were the following: (1) acute ischemic stroke with occlusion of the M1 segment of the middle cerebral artery, the internal carotid, or both, combined with an admission National Institutes of Health Stroke Scale score between 4 and 22; (2) completion of a computed tomographic (CT) imaging work-up for stroke, including noncontrast-CT, CTA, and PCT, at admission; (3) treatment with intra-arterial thrombolysis with <12 hours from onset to the end of intra-arterial thrombolysis; (4) availability of MRIs or CT scans taken at 2 weeks postictus from which to assess final infarct volume (FIV). Patients were excluded if (1) intravenous tissue-type plasminogen activator treatment was administered before angiography or (2) they received reperfusion treatment using mechanical thrombolytic devices. A flow chart outlining patient selection is shown in Figure 1.
The following demographic and clinical variables were recorded: age, sex, medical history, vascular risk factors, routine blood tests, time from onset to imaging, time from symptom onset to treatment, National Institutes of Health Stroke Scale score on admission, and modified Rankin Score (mRS) at 90 days. Ninetieth-day outcomes were assessed in the outpatient clinic or over the telephone. Death was coded as 6 on the mRS. Stroke mechanisms were subtyped using the TOAST (Trial of Org 10172 in Acute Stroke Treatment) classification and were diagnosed by consensus of 2 stroke neurologists (J.H. and Y.Z.).11
PCT Image Acquisition
PCT studies were obtained on 64-slice CT scanners. Each PCT study involved successive gantry rotations performed in cine mode during intravenous administration of 2 boluses of 40 to 50 mL of iodinated contrast material at an injection rate of 4 to 5 mL/s. Total PCT coverage was 20 mm. Acquisition parameters were 80 kVp and 100 mA·s.
CTA Imaging Protocol
CTA studies of the cervical and intracranial arteries were obtained on 64-slice CT scanners using the following parameters: helical mode, 0.5 to 0.8 s gantry rotation; pitch: 1 to 1.375:1; slice thickness: 0.625 to 1.25 mm; reconstruction interval: 0.5 to 1 mm; acquisition parameters: 120 kVp, 200 to 300 mA·s. A caudocranial scanning direction was selected, ranging from the midchest to the vertex of the brain. CTA scans were performed with 50 mL iohexol (Omnipaque 350, GE Healthcare, Little Chalfont, UK) administered via power injector at 5 mL/s.
DSA Imaging Protocol
DSA was performed using a dedicated biplane cerebral angiographic system (Axiom Artis d BA Twin; Siemens Medical Systems, Erlangen, Germany). Images were acquired during injection of the internal and external carotid arteries and ≥1 vertebral artery. Imaging was performed through the entire arterial and venous phases to evaluate the collateral circulation. All patients underwent endovascular treatment including intra-arterial thrombolysis, with or without mechanical embolectomy at the discretion of the attending neurologist (G.Z., Y.Z, or J.H).
Image Processing and Interpretation
The PCT data were analyzed using the dedicated MIStar software (Apollo Medical Imaging, Melbourne, Australia). This software relies on the central volume principle. The software applies singular value decomposition with delay- and dispersion-correction to produce perfusion maps. The volumes of infarct and penumbra, automatically measured by the software as the areas with delay time >3 s and cerebral blood flow <30%,12 respectively, were recorded.
The permeability parameter–Ktrans maps, interpreted as the indicator of local blood–brain barrier breakdown, were drawn from PCT data using a prototype software program (OmniKinetics, GE Healthcare China, Beijing, China) that can analyze data according to various kinetics models mentioned in the review by Sourbron and Buckley.13 We used the Patlak model7,8 for its simplicity and reputation of robustness. Patlak modeling involves fitting a regression line to observed time-concentration curves for each PCT pixel and to an intravascular reference time-concentration curve. Only first-pass data were considered for the Patlak analysis. The slope of the relative regression line in each pixel was plotted into Ktrans maps. Output images were further analyzed with ImageJ 1.47 for Mac OS (developed by Wayne Rasband of the National Institutes of Health, Bethesda, MD).
A neurologist (H.C.) with 12 years of experience reviewed all noncontrast-CT, PCT, and CTA data. She assessed (1) the infarct core and penumbra volumes on PCT; (2) Alberta Stroke Program Early CT Score and hyperdense middle cerebral artery sign on noncontrast-CT; and (3) CFS, along with the degree of cervical carotid stenosis based on North American Symptomatic Carotid Endarterectomy Trial (NASCET) criteria, on CTA-MIP. A neurologist (N.L.) with 13 years of experience reviewed the follow-up images to measure the FIV. Both reviewers were blinded to the initial clinical interpretation of these studies and provided only with descriptions of the signs and symptoms.
A neuroradiologist (B.W.) and neurologist (G.Z.), both with 14 years of experience, reviewed the DSA images to evaluate pretreatment CFS and reperfusion status. Vascular reperfusion was graded based on the Thrombolysis in Cerebral Infarction classification: 0, no perfusion; 1, penetration with minimal perfusion; 2a, less than 67% perfusion; 2b, more than 67% perfusion; and 3, complete perfusion of the affected vascular territory. Reperfusion status was classified as ER+ (positive for early reperfusion; Thrombolysis in Cerebral Infarction score 2b to 3 within 12 hours of symptom onset) or ER−. Thrombolysis in Cerebral Infarction scores were rated by consensus of a neurologist (G.Z.) and a neuroradiologist (B.W.).
Ktrans maps, generated by a medical imaging scientist (Z.S.), were loaded into ImageJ, and the Polygons tool was used to draw regions of interest corresponding to the ischemic region suggested by PCT. The regions of interest tool was then used to calculate the mean values of the Ktrans maps in these regions of interest. The values of Ktrans maps were calculated twice and independently by each neurologist (H.C. and Y.L.), and intra- and interobserver agreements were analyzed.
Because Malik et al14 found that the various systems for grading collateral circulation based on CTA are highly correlated with one another, we only used the grading system based on CTA-MIP described by Tan et al.15 Collateral circulation on CTA-MIP was graded as follows: 0, negligible coverage of the ischemic region by pial vessels; 1, >0% but no more than 50% of the ischemic region filled by these vessels; 2, >50% but <100% of the ischemic region filled; 3, 100% of the ischemic region filled.
CFS on pretreatment DSA was evaluated using the American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology16 Collateral Flow Grading System, where 0 indicates no visible collateral flow to the ischemic site; 1, slow collateral flow to the periphery of the ischemic site with partial persistence of the defect; 2, rapid collateral flow to the periphery of the ischemic site but in only part of the ischemic territory, with partial persistence of the defect; 3, slow but complete collateral blood flow to the ischemic bed by the late venous phase, 4, complete and rapid collateral blood flow to the vascular bed in the entire ischemic territory by retrograde perfusion. In our study, scores of 0 and 1 were designated together as 1 for consistency with the scale used for CTA-MIP.
Values for CFS on Ktrans maps were based on the mean values in the ischemic cerebral area. CFS was graded as 1 if its mean value was <0.5 mL. Grade 2 indicated a mean value from 0.5 to 1.0 mL. Grade 3 indicated a mean value from 1.0 to 1.5 mL, and grade 4 indicated a value >1.5 mL. Examples of CFS on Ktrans maps and DSA are illustrated in Figure 2.
Good clinical outcome was defined as mRS ≤2 at day 90. Symptomatic intracranial hemorrhage was defined as any hemorrhage associated with an increase of 4 points or more on the National Institutes of Health Stroke Scale or leading to death that was identified as the predominant cause of deterioration.
All data are presented as mean, median with interquartile range, or number with percentages. To analyze the patient characteristics with reference to CFS on Ktrans maps, the Kruskal–Wallis test was used to compare continuous variables, and the Wilcoxon test was used to compare categorical variables between groups. Chi-square tests were used to quantify the level of agreement between CFS and other methods, as were κ values with 95% confidence intervals. Spearman tests were used to analyze the correlation between mRS at 90 days and CFS on Ktrans maps. All statistical analyses were conducted using SAS version 9.3 (SAS Institute, Cary, NC). A P<0.05 was considered to be statistically significant.
Of the 97 patients who met the inclusion criteria during the study period, 11 patients were excluded because of poor quality of PCT owing to motion artifacts. Six patients had an incomplete DSA that prevented the collateral flow from being assessed correctly. Three patients did not have CTA images, and 2 patients could not be contacted during follow-up. In the end, 75 patients were included in this study (Figure 1).
Patient Population and Correlation With CFS on Ktrans Maps
The 75 patients in the final sample comprised 39 women and 36 men with a mean age of 65.3±14.6 years (range 26–89 years). On Ktrans maps, 25 patients (33.3%) had poor collateral circulation (CFS 1), 25 (33%) had intermediate collateral circulation (CFS 2), 20 (26.7%) had good collateral circulation (CFS 3), and 5 (6.7%) had excellent collateral circulation (CFS 4). Clinical and imaging characteristics and outcomes in relation to CFS on Ktrans maps are presented in Table 1. Current smokers and patients with a history of hypertension were more likely to have poor collateral circulation (P=0.0028 and 0.0363, respectively). Infarct core volumes on PCT were much larger in patients with poor collateral flow (CFS 1) compared with others (P=0.0335). The FIVs in patients with poor collateral flow were also larger (P=0.0082). Better collateral circulation always indicated a better clinical outcome, with more patients having an mRS ≤2 (P<0.0001). The other risk factors and imaging variables did not show significant differences among patients with different CFSs.
Correlation Among CFS on Ktrans Maps, CTA-MIP, and DSA
All 3 CFS assessment systems were strongly correlated with one another (Table 2). Ktrans maps had the strongest correlation with DSA. The κ value between them was 0.8101 (95% confidence interval=0.6998–0.9205, P=0.9796). Although the correlations between CTA-MIP and Ktrans maps and between DSA and CTA-MIP were also significant, their κ values were only 0.5599 and 0.5006, respectively, lower than that between Ktrans maps and DSA.
The distributions of CFS values obtained by the different methods are illustrated in Figure 3. CFS values obtained using Ktrans maps were highly consistent with those obtained by DSA. All patients with excellent collateral circulation (CFS=4) on DSA also showed high CFS on Ktrans maps.
Interobserver (weighted κ=0.905, P<0.001) and intraobserver (weighted κ=0.934, P<0.001) agreement were good with regard to CFS assessment on Ktrans maps.
Prediction of Outcomes After Acute Stroke
There were 30 patients with good clinical outcomes (mRS ≤2) and 45 with bad outcome (mRS >2). Several variables, including time from onset to end of endovascular treatment (P=0.381), National Institutes of Health Stroke Scale score at admission (P=0.0191), Alberta Stroke Program Early CT Score on noncontrast-CT (P=0.0183), infarct core on PCT (P=0.0437), successful reperfusion (P=0.0127), FIV (P<0.0001), and CFS on Ktrans maps (P<0.0001), showed significant differences between the 2 groups (Table I in the online-only Data Supplement).
There was a negative correlation between the distribution of mRS at 90 days and CFS on Ktrans maps (rs=−0.5412, P<0.0001). Figure 4A illustrates the distribution of mRS at 90 days according to CFS on Ktrans maps, showing that patients with good or excellent collateral circulation (CFS 3 or 4) were more likely to have a good clinical outcome (mRS ≤2). When we integrated reperfusion status into our analysis of the correlations between CFS on Ktrans maps and outcomes, there was a trend for patients with higher CFS to have better clinical outcome and a higher probability of reperfusion (Figure 4B–4D).
Collateral circulation plays a key role in the pathophysiology of acute ischemic stroke. More robust collateral circulation is associated with better recanalization, better reperfusion, and better clinical outcomes.17 Advanced imaging has shown that better pretreatment collateral circulation can lead to a more favorable mismatch between the penumbra and infarct core and can also keep the penumbra from irreversible infarction for a longer time, leading to smaller FIV after thrombolysis.18
Judging from our results, Ktrans maps based on first-pass PCT data can evaluate the collateral circulation in a more quantitative fashion, with better agreement with DSA, compared with CTA-MIP. To the best of our knowledge, this is the first study to use this method to evaluate collateral circulation in acute ischemic stroke. CFS on Ktrans maps is a good predictor of clinical outcome in patients who have experienced an acute ischemic stroke with proximal arterial occlusion. A patient with higher CFS values on Ktrans maps, indicating better collateral circulation, is likely to have better clinical outcome. In our study, only one patient with excellent collateral circulation died. The poor outcome in this patient was likely related to a lack of recanalization and to symptomatic intracranial hemorrhage. FIV was larger in patients with poor collateral flow, although this factor was not significant on multiple linear regression analysis. Considering the high reperfusion rate in our patients, we did not evaluate the interaction between collateral circulation and reperfusion. However, patients with better collateral circulation were more likely to show reperfusion. In our study, CFS on Ktrans maps did not show any correlation with symptomatic intracranial hemorrhage or FIV. A reasonable explanation might be that all the patients received endovascular treatment, with a significant reperfusion rate, which might have offset the effect of the collateral circulation.
We acknowledge several limitations to our study. First of all, this study was a retrospective analysis with a limited number of cases. The high reperfusion rate may have influenced the natural effect of the collateral circulation on clinical or radiological outcome. Because most of the patients did not undergo MRI at admission, we could not analyze the relationship between CFS and infarct growth. Finally, only patients with middle cerebral artery occlusion were included in this study, which may limit the generalizability of our results.
In conclusion, we found that Ktrans maps based on standard first-pass perfusion CT could be used to assess collateral circulation after acute proximal arterial occlusion accurately and quantitatively. CFS values obtained from Ktrans maps were highly consistent with those obtained from DSA. Better collateral circulation was associated with a better clinical outcome. Further studies are needed to determine the appropriate use of CFS on Ktrans maps in treatment decisions for patients with acute ischemic stroke.
We thank Editage (http://www.editage.cn) for English language editing.
Sources of Funding
This study was supported by the National Natural Science Foundation of China (grant no. 81371286).
The online-only Data Supplement is available with this article at http://stroke.ahajournals.org/lookup/suppl/doi:10.1161/STROKEAHA.114.008015/-/DC1.
- Received November 6, 2014.
- Revision received December 27, 2014.
- Accepted January 15, 2015.
- © 2015 American Heart Association, Inc.
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