No clue how this is going to get you to 100% recovery. Then why the hell was this research done?
Ghost infarct core following endovascular reperfusion: A risk for computed tomography perfusion misguided selection in stroke
Background
Computed tomography perfusion (CTP) has been increasingly used for patient selection in mechanical thrombectomy for stroke. However, previous studies suggested that CTP might overestimate the infarct size. The term ghost infarct core (GIC) has been used to describe an overestimation of the final infarct volumes by pre-treatment CTP of >10 ml.
Aim
We sought to study the frequency and predictors of GIC.
Methods
A prospectively collected mechanical thrombectomy database at a comprehensive stroke center between September 2010 and August 2020 was reviewed. Patients were included if they had a successful reperfusion (mTICI2b-3), a pre-procedure CTP, and final infarct volume measured on follow-up magnetic resonance imaging. Uni- and multivariable analyses were performed to identify predictors of GIC.
Results
Among 923 eligible patients (median [IQR] age, 64 [55–75] years; NIHSS, 16 [11–21]; onset to reperfusion time, 436.5 [286–744.5] min), GIC was identified in 77 (8.3%) of the overall patients and in 14% (47/335) of those reperfused within 6 h of symptom onset. The median overestimation volume was 23.2 [16.4–38.3] mL. GIC was associated with higher NIHSS score, larger areas of infarct core and tissue at risk on CTP, unfavorable collateral scores, and shorter times from onset to image acquisition and to reperfusion as compared to non-GIC. Patients with GIC had smaller median final infarct volumes (10.7 vs. 27.1 ml, p < 0.001), higher chances of functional independence (76.2% vs. 55.5%, adjusted odds ratio (aOR) 3.829, 95% CI [1.505–9.737], p = 0.005), lower disability (one-point-mRS improvement, aOR 1.761, 95% CI [1.044–2.981], p = 0.03), and lower mortality (6.3% vs. 15%, aOR 0.119, 95% CI [0.014–0.984], p = 0.048) at 90 days. On multivariable analysis, time from onset to reperfusion ≤6 h (OR 3.184, 95% CI [1.743–5.815], p < 0.001), poor collaterals (OR 2.688, 95% CI [1.466–4.931], p = 0.001), and higher NIHSS score (OR 1.060, 95% CI [1.010–1.113], p = 0.018) were independent predictors of GIC.
Conclusion
GIC is a relatively common entity, particularly in patients with poor collateral status, higher baseline NIHSS score, and early presentation, and is associated with more favorable outcomes. Patients should not be excluded from reperfusion therapies on the sole basis of CTP findings, especially in the early window.
Keywords
Stroke, thrombectomy, infarct size, CTP, ghost core, collaterals
Marcus Stroke & Neuroscience Center, Grady Memorial Hospital and Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
The first two authors contributed equally to this work.
Corresponding author(s):
Raul G Nogueira, Grady Memorial Hospital, 80 Jesse Hill Drive SE, Room 8D108A, Atlanta, GA 30303, USA. Email: raul.g.nogueira@emory.edu
Introduction
Neuroimaging plays a vital role in determining care in acute ischemic stroke (AIS) patients, with non-contrast computed tomography (NCCT) still remaining the first-line imaging modality for differential diagnosis and eligibility assessment for reperfusion therapies, such as intravenous thrombolysis (IVT) and mechanical thrombectomy (MT).1
Ever since the description of dynamic CT,2,3 the concept of evaluating how the contrast reaches the cerebral vessels and parenchyma over time has evolved through the decades until it reached the era of modern CT perfusion (CTP) and automated processing. CTP has been increasingly used as a screening tool for assessing patients with AIS in order to identify the areas of infarcted brain and potentially salvageable ischemic tissue,4-7 allowing the consideration of acute reperfusion therapies8-10 even in patients in the extended time window.11,12
Besides the good correlation between cerebral blood flow (CBF) and cerebral blood volume (CBV) with final infarct volumes (FIV) calculated by follow-up NCCT or magnetic resonance imaging (MRI),13-16 some other advantages of CTP over other imaging modalities include potentially higher accuracy in detecting and delineating the ischemic core as compared to NCCT alone17,18 as well as broader availability, faster acquisition times,19,20 and lower costs as compared to MRI.21,22
However, the possibility of overestimation of the FIV by CBV and CBF parameters of CTP has been increasingly recognized in face of the continuous improvement in terms of both the quality and speed of reperfusion over the past few years. The term ghost infarct core (GIC) has been specifically used to describe an overestimation of the FIV by pre-treatment CTP of >10 ml (Figure 1).23,24 In this study, we sought to describe the frequency and predictors of GIC in a large cohort of AIS patients that underwent MT.
Figure 1. Example of overestimation of the final infarct volume by the rCBF parameter (purple area) on CT perfusion (top panel) in a fully reperfused stroke patient after mechanical thrombectomy. Note that the hyperintensities are minimal on follow-up DWI (bottom panel). This was a 47 years old African American male presenting with a baseline NIHSS of 17 that was selected for mechanical thrombectomy. Time from onset to reperfusion was 170 min with mTICI2b. Collateral score was 1.
Methods
Patient selection and study variables
This was a post-hoc analysis of a prospectively maintained database for all consecutive cases of AIS patients with large vessel occlusions (LVO) who underwent MT at a comprehensive stroke center between September 2010 and August 2020. Inclusion criteria encompassed patients who (1) underwent pre-procedural CTP, (2) had LVO involving the intracranial internal carotid artery (ICA) and/or proximal middle cerebral artery (MCA, M1- or M2-segments), (3) were successfully reperfused after MT (mTICI 2b-3), and (4) had FIV measured on follow-up MRI.
The GIC was defined as an overestimation greater than 10 mL in the FIV by the rCBF < 30% parameter.23,24 Demographic, clinical, radiological, and procedural variables were obtained from each patient for analysis and comparison between the GIC and non-GIC cohorts. A subgroup analysis was performed for patients who were successfully reperfused (mTICI 2b-3) within 6 h from stroke onset. In addition, the rates of GIC in terms of final reperfusion grades, occlusion location and time from stroke onset to reperfusion were evaluated.
A sensitivity analysis was performed using receiver operating characteristic curves (ROC) to identify the time of symptom onset to reperfusion that best predicts the presence of GIC. For imaging protocol, see Methods section, online data supplement.
Statistical analysis
After normality testing with the Shapiro-Wilk test, continuous variables were reported as median (interquartile range [IQR]) and compared using the Mann–Whitney U test. Categorical variables were reported as proportions and percentages. Categorical variables were compared by χ2 test or Fisher exact test, as appropriate. Multivariable regression analysis was performed to identify the independent predictors of GIC. All variables with p < 0.10 in the univariable analysis were assessed by a step-wise logistic regression analysis. A backward elimination strategy was performed, using p > 0.10 of the likelihood ratio test for exclusion, to identify the covariates that best predict the presence of GIC in a final model. Likewise, the association of GIC with functional independence and mortality at 90 days was performed. An ordinal shift analysis was performed using an ordinal regression to analyze differences in 90-day mRS outcomes across patients with and without GIC. A ROC curve was utilized to determine the most adequate time cutoff point in which GIC was more likely to occur using an unweighted Youden’s index calculation. Significance was set at p < 0.05, and all p values were based on two-tailed tests. The statistical analysis was performed using the software IBM SPSS Statistics 26 (IBM® Armonk, NY, USA).
Results
A total of 2298 patients underwent MT at our center between September 2010 and August 2020. Out of these, 858 patients were excluded from the study for not having undergone CTP prior to treatment, 400 patients for not having a brain MRI for follow-up imaging, 79 for having other types of occlusion, and 38 for having no or suboptimal reperfusion (e.g., mTICI 0-2a), leaving 923 patients for the current analysis (Figure I, online data supplement). The infarct core volume on CTP was larger than FIV on MRI in 137 (14.8%) patients with a median overestimation volume of 13.29 [3.75–26.1] mL. A total of 77 (8.3%) patients were found to have GIC. The median size of the GIC in the overall cohort was 23.2 [16.4–38.3] mL and did not differ between cases with time from onset to reperfusion ≤6 h versus those >6 h or with unknown time (26.1 [16.1–35.4] vs. 19.7 [17.46–42.04] mL, p = 0.65).
The GIC group demonstrated lower proportion of patients with diabetes mellitus (13% vs. 23.9%, p = 0.03), higher median NIHSS (19 [14–22.5] vs. 16 [11–20], p < 0.001), larger baseline infarct cores (41 [26.4–63] vs. 5.8 [0–17.7] mL, p < 0.001), larger areas of tissue at risk in Tmax > 6.0 s (181.5 [146–230] vs. 124.1 [72–184.2] mL, p < 0.001), lower proportion of favorable collateral scores (61.7% vs. 82.9%, p < 0.001), shorter times from onset to image acquisition (209 [118–363] vs. 326 [184–627] min, p < 0.001), and shorter times from onset to reperfusion (307 [224–481] vs. 455 [297–768] min, p < 0.001). The remaining baseline clinical, radiological, and demographic characteristics did not significantly differ between the two groups (Table 1).
As compared to the non-GIC patients, the GIC group had significantly smaller FIVs (10.7 [4.7–26.9] vs. 27.1 [11.8–67.5] mL, p < 0.001) and higher chances of functional independence (76.2% vs. 55.5%, adjusted odds ratio (aOR) 3.829, 95% CI [1.505–9.737], p = 0.005) and lower disability (one-point mRS improvement, aOR 1.761, 95% CI [1.044–2.981], p = 0.03) (Figure 2) as well as lower mortality (6.3% vs. 15%, aOR 0.119, 95% CI [0.014–0.984], p = 0.048) at 90 days.
Figure 2. Distribution of 90-day modified Rankin Scale (mRS) scores. There is a significant difference between patients with ghost infract core and those with ghost infract core (shift analysis by Wilcoxon signed-rank test, p = 0.01). Adjusted odds ratio for one-point mRS improvement, 1.761, 95% CI [1.044–2.981], p = 0.03).
Predictors of GIC
On multivariable analysis, time from onset to reperfusion ≤6 h (OR 3.184, 95% CI [1.743–5.815], p < 0.001), poor collateral scores (OR 2.688, 95% CI [1.466–4.931], p = 0.001), and higher baseline NIHSS score (OR 1.060, 95% CI [1.010–1.113], p = 0.018) were identified as independent predictors of the occurrence of GIC.
Subgroup analysis
A total of 335 patients (36.3% of the overall cohort) were reperfused within the first 6 h from stroke onset, among those 76 (22.7%) patients had overestimation of the baseline infarct volume on CTP (as compared to FIV on MRI), with a median overestimation volume of 15.11 [5.05–27.79] mL. GIC was found in 47/335 (14%) patients with a median overestimation volume of 26.1 [16.1–35.4]. In this early window subgroup, GIC patients similarly demonstrated lower proportion of patients with diabetes mellitus (8.5% vs. 24.3%, p = 0.01) and favorable collateral scores (60% vs. 81.7%, p = 0.003), higher median NIHSS score (19 [15–23] vs. 16 [12–21], p = 0.01), larger baseline infarct cores (43 [27.8–65] vs. 6 [0–19.4] mL, p < 0.001), larger areas of tissue at risk in Tmax >6.0 s (184 [151.5–229.2] vs. 137 [84.2–189] mL, p < 0.001), smaller FIV (9.3 [3.5–27.6] vs. 21.4 [9.5–60] mL, p < 0.001), higher rates of functional independence (86.1% vs. 59.2%, p = 0.002), and lower rates of 90-day mortality (0% vs. 13%, p = 0.02). Times from onset to image acquisition (129 [87–208] vs. 151 [92.5–214], p = 0.53) and to reperfusion (255 [195–300] vs. 260.5 [205.8–313.5] min, p = 0.34) were comparable between both groups (Table I, online data supplement). Additionally, in patients with time from stroke onset to reperfusion > 6 h, overestimation of the baseline infarct volume was identified in 61/580 (10.5%) patients with a median overestimation volume of 9.54 [2.69–19.70] mL. GIC was identified in 30/588 (5.1%) patients with a median overestimation volume of 19.7 [17.46–42.04]. The rates of GIC in terms of final reperfusion grade, occlusion location, and time from stroke onset to reperfusion are illustrated in Table II, online data supplement.
Sensitivity analysis
ROC curve analysis and Youden’s index showed an optimal cutoff point of 359.5 min in time from onset to reperfusion to detect the presence of GIC (sensitivity of 63%, specificity of 63%, AUC of 0.656) (Figure 3). For the purpose of providing a more practical time cutoff, this was approximated to 6 h, with similar test statistics with a sensitivity of 64%, a specificity of 60%, and an AUC of 0.627 (95% CI 0.567–0.687, p < 0.001) for the presence of GIC.
Figure 3. Receiver operating characteristic curves of time from onset to reperfusion for prediction of the presence of ghost infarct core.
Discussion
Our study demonstrated that in reperfused MT patients, rCBF < 30% may overestimate the FIV calculated on follow-up MRI, considered to be the gold standard for infarct volume estimation.25,26 Moreover, we demonstrated that GIC is more common in the early time window (<6 h) and is associated with poor collateral scores but also more favorable outcomes. Notably, the GIC phenomenon occurred in approximately 15% of the patients reperfused within 6 h from stroke onset and the median volume of overestimation was greater than 25 mL with overestimation volumes surpassing 35 mL in a quarter of the GIC patients. These factors raise significant concerns about the accuracy of CTP as a selection tool for reperfusion therapies in AIS patients, especially in the early window.
The observation that the likelihood of occurrence of GIC is time dependent is consistent with the results from previous studies.23,24 One of the reasons that may cause those higher rates of overestimation in patients who were scanned and reperfused early may be the fact that the rCBF <30% parameter, although the most accurately correlated with irreversibly ischemic tissue in general,27 does not represent actual cell death. CBF reduction’s impact on tissue is likely dependent not only on its intensity but also on its duration. Therefore, at least in early presenters, other thresholds or conjunction of perfusion parameters might have to be considered in order to optimize the accuracy of the estimation of the truly infarcted tissue, as it was recently suggested by the work of Bivard et al.28
Previous studies have reported the association between good collateral status and smaller baseline perfusion lesion volumes.29,30 In our study, we found that poor collateral scores were independently associated with the occurrence of rCBF overestimation of the FIV calculated on follow-up scans. This may be explained by the strong interaction between visual collateral scores and contrast peak density. Poor collateral status would lead to lower contrast peak density and, consequently, to larger perfusion and ischemic core lesion volumes on CTP.31 Although this correlation with increased baseline lesion volumes exists, we are led to think by the current findings that these parameters might not be as reliable as previously believed to accurately predict FIV sizes in this specific population of patients.
It is important to remark that in the subgroup analysis of patients reperfused within 6 h, GIC was significantly more frequently observed (14% vs. 5.1% of patients with onset to reperfusion unknown or longer than 6 h, p < 0.001). This suggests that CTP may be less reliable in the early time window. Given the dramatic benefit of MT within the first 6 h along with its highly favorable safety and cost-effective profiles, any selection tool that may potentially be used to exclude patients from treatment must have an extremely high degree of accuracy. Our data adds to the growing body of evidence that supports that the CTP findings must be carefully interpreted and should not be the sole reason to exclude patients from reperfusion treatment.32,33 Notably, the optimal cutoff point in time from onset to reperfusion (359.5 min) to detect the presence of GIC found in our study was longer than what has been reported in some previous studies. This is likely explained by the significant larger sample size and broader time distribution in our study presumably leading to greater statistical power.
One of the strengths of this study over others previously published on this same subject is related to the considerably larger size of our patient cohort as well as to the fact that we used only CBF (the most accurate predictor of FIV)15,27 to determine infarct core in the acute setting and MRI (the most sensitive and accurate method to determine infarcted tissue)25,26 to calculate FIV, which made the data less prone to measuring errors than if we had included less accurate follow-up imaging methods, such as NCCT. Moreover, we also only evaluated successfully reperfused (TICI 2b-3) patients, which reduced interference that the natural evolution of stroke might have had in the imaging outcomes.
Our study is limited by the fact that it represents a sample from a single center and by its retrospective nature. The utilization of only single-phase CTA calculated collateral scores was also a limiting factor, since we were not able to discriminate cases in which CTA scan acquisition was performed too early or too late after the contrast bolus or where contrast enhancement was not optimal. A total of 858 (37.3%) patients were excluded from the analysis not having undergone pre-treatment CTP at our center. In our institution, multimodal imaging is part of the acute stroke protocol thus all consecutive patients are expected to undergo NCCT/CTA/CTP whenever feasible. The typical reasons for not performing CTP include (1) skipping conventional imaging in favor of the “direct to angiography suite protocol” with cone beam CT in the biplane equipment,34 (2) having difficult IV placement where contrast administration would be expected cause significant treatment delays, (3) history of iodine contrast allergy, and (4) renal dysfunction. However, since these factors occur in a random basis, we do not expect that the missed CTP cases would have been a significant source of bias. Finally, the discrepancy between the CTP and MRI acquisitions in terms of slice thickness and brain coverage as well as the inclusion of patients with successful but incomplete reperfusion (mTICI2b) may have resulted in an underestimation of the true occurrence of GIC.
Conclusion
In conclusion, the GIC phenomenon is an under recognized but relatively frequent entity that may inappropriately exclude patients from reperfusion therapy, especially in the early presentation. This finding is of critical importance to raise awareness in the clinical community about the negative impacts that a CTP-centered approach for the selection of endovascular therapy may have on stroke patients. In the presence of a favorable non-contrast CT, CTP should not be used as the only criterion to exclude patients from endovascular reperfusion.
Declaration of conflicting interests
The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: RGN reports consulting fees for advisory roles with Anaconda, Biogen, Cerenovus, Genentech, Imperative Care, Medtronic, Phenox, Prolong Pharmaceuticals, Stryker Neurovascular and stock options for advisory roles with Astrocyte, Brainomix, Cerebrotech, Ceretrieve, Corindus Vascular Robotics, Vesalio, Viz-AI, and Perfuze. DCH is a consultant for Stryker and Vesalio and holds stock options at Viz.AI.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
Keywords
Stroke, thrombectomy, infarct size, CTP, ghost core, collaterals
Marcus Stroke & Neuroscience Center, Grady Memorial Hospital and Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
The first two authors contributed equally to this work.
Corresponding author(s):
Raul G Nogueira, Grady Memorial Hospital, 80 Jesse Hill Drive SE, Room 8D108A, Atlanta, GA 30303, USA. Email: raul.g.nogueira@emory.edu
Introduction
Neuroimaging plays a vital role in determining care in acute ischemic stroke (AIS) patients, with non-contrast computed tomography (NCCT) still remaining the first-line imaging modality for differential diagnosis and eligibility assessment for reperfusion therapies, such as intravenous thrombolysis (IVT) and mechanical thrombectomy (MT).1
Ever since the description of dynamic CT,2,3 the concept of evaluating how the contrast reaches the cerebral vessels and parenchyma over time has evolved through the decades until it reached the era of modern CT perfusion (CTP) and automated processing. CTP has been increasingly used as a screening tool for assessing patients with AIS in order to identify the areas of infarcted brain and potentially salvageable ischemic tissue,4-7 allowing the consideration of acute reperfusion therapies8-10 even in patients in the extended time window.11,12
Besides the good correlation between cerebral blood flow (CBF) and cerebral blood volume (CBV) with final infarct volumes (FIV) calculated by follow-up NCCT or magnetic resonance imaging (MRI),13-16 some other advantages of CTP over other imaging modalities include potentially higher accuracy in detecting and delineating the ischemic core as compared to NCCT alone17,18 as well as broader availability, faster acquisition times,19,20 and lower costs as compared to MRI.21,22
However, the possibility of overestimation of the FIV by CBV and CBF parameters of CTP has been increasingly recognized in face of the continuous improvement in terms of both the quality and speed of reperfusion over the past few years. The term ghost infarct core (GIC) has been specifically used to describe an overestimation of the FIV by pre-treatment CTP of >10 ml (Figure 1).23,24 In this study, we sought to describe the frequency and predictors of GIC in a large cohort of AIS patients that underwent MT.
Figure 1. Example of overestimation of the final infarct volume by the rCBF parameter (purple area) on CT perfusion (top panel) in a fully reperfused stroke patient after mechanical thrombectomy. Note that the hyperintensities are minimal on follow-up DWI (bottom panel). This was a 47 years old African American male presenting with a baseline NIHSS of 17 that was selected for mechanical thrombectomy. Time from onset to reperfusion was 170 min with mTICI2b. Collateral score was 1.
Methods
Patient selection and study variables
This was a post-hoc analysis of a prospectively maintained database for all consecutive cases of AIS patients with large vessel occlusions (LVO) who underwent MT at a comprehensive stroke center between September 2010 and August 2020. Inclusion criteria encompassed patients who (1) underwent pre-procedural CTP, (2) had LVO involving the intracranial internal carotid artery (ICA) and/or proximal middle cerebral artery (MCA, M1- or M2-segments), (3) were successfully reperfused after MT (mTICI 2b-3), and (4) had FIV measured on follow-up MRI.
The GIC was defined as an overestimation greater than 10 mL in the FIV by the rCBF < 30% parameter.23,24 Demographic, clinical, radiological, and procedural variables were obtained from each patient for analysis and comparison between the GIC and non-GIC cohorts. A subgroup analysis was performed for patients who were successfully reperfused (mTICI 2b-3) within 6 h from stroke onset. In addition, the rates of GIC in terms of final reperfusion grades, occlusion location and time from stroke onset to reperfusion were evaluated.
A sensitivity analysis was performed using receiver operating characteristic curves (ROC) to identify the time of symptom onset to reperfusion that best predicts the presence of GIC. For imaging protocol, see Methods section, online data supplement.
Statistical analysis
After normality testing with the Shapiro-Wilk test, continuous variables were reported as median (interquartile range [IQR]) and compared using the Mann–Whitney U test. Categorical variables were reported as proportions and percentages. Categorical variables were compared by χ2 test or Fisher exact test, as appropriate. Multivariable regression analysis was performed to identify the independent predictors of GIC. All variables with p < 0.10 in the univariable analysis were assessed by a step-wise logistic regression analysis. A backward elimination strategy was performed, using p > 0.10 of the likelihood ratio test for exclusion, to identify the covariates that best predict the presence of GIC in a final model. Likewise, the association of GIC with functional independence and mortality at 90 days was performed. An ordinal shift analysis was performed using an ordinal regression to analyze differences in 90-day mRS outcomes across patients with and without GIC. A ROC curve was utilized to determine the most adequate time cutoff point in which GIC was more likely to occur using an unweighted Youden’s index calculation. Significance was set at p < 0.05, and all p values were based on two-tailed tests. The statistical analysis was performed using the software IBM SPSS Statistics 26 (IBM® Armonk, NY, USA).
Results
A total of 2298 patients underwent MT at our center between September 2010 and August 2020. Out of these, 858 patients were excluded from the study for not having undergone CTP prior to treatment, 400 patients for not having a brain MRI for follow-up imaging, 79 for having other types of occlusion, and 38 for having no or suboptimal reperfusion (e.g., mTICI 0-2a), leaving 923 patients for the current analysis (Figure I, online data supplement). The infarct core volume on CTP was larger than FIV on MRI in 137 (14.8%) patients with a median overestimation volume of 13.29 [3.75–26.1] mL. A total of 77 (8.3%) patients were found to have GIC. The median size of the GIC in the overall cohort was 23.2 [16.4–38.3] mL and did not differ between cases with time from onset to reperfusion ≤6 h versus those >6 h or with unknown time (26.1 [16.1–35.4] vs. 19.7 [17.46–42.04] mL, p = 0.65).
The GIC group demonstrated lower proportion of patients with diabetes mellitus (13% vs. 23.9%, p = 0.03), higher median NIHSS (19 [14–22.5] vs. 16 [11–20], p < 0.001), larger baseline infarct cores (41 [26.4–63] vs. 5.8 [0–17.7] mL, p < 0.001), larger areas of tissue at risk in Tmax > 6.0 s (181.5 [146–230] vs. 124.1 [72–184.2] mL, p < 0.001), lower proportion of favorable collateral scores (61.7% vs. 82.9%, p < 0.001), shorter times from onset to image acquisition (209 [118–363] vs. 326 [184–627] min, p < 0.001), and shorter times from onset to reperfusion (307 [224–481] vs. 455 [297–768] min, p < 0.001). The remaining baseline clinical, radiological, and demographic characteristics did not significantly differ between the two groups (Table 1).
As compared to the non-GIC patients, the GIC group had significantly smaller FIVs (10.7 [4.7–26.9] vs. 27.1 [11.8–67.5] mL, p < 0.001) and higher chances of functional independence (76.2% vs. 55.5%, adjusted odds ratio (aOR) 3.829, 95% CI [1.505–9.737], p = 0.005) and lower disability (one-point mRS improvement, aOR 1.761, 95% CI [1.044–2.981], p = 0.03) (Figure 2) as well as lower mortality (6.3% vs. 15%, aOR 0.119, 95% CI [0.014–0.984], p = 0.048) at 90 days.
Figure 2. Distribution of 90-day modified Rankin Scale (mRS) scores. There is a significant difference between patients with ghost infract core and those with ghost infract core (shift analysis by Wilcoxon signed-rank test, p = 0.01). Adjusted odds ratio for one-point mRS improvement, 1.761, 95% CI [1.044–2.981], p = 0.03).
Predictors of GIC
On multivariable analysis, time from onset to reperfusion ≤6 h (OR 3.184, 95% CI [1.743–5.815], p < 0.001), poor collateral scores (OR 2.688, 95% CI [1.466–4.931], p = 0.001), and higher baseline NIHSS score (OR 1.060, 95% CI [1.010–1.113], p = 0.018) were identified as independent predictors of the occurrence of GIC.
Subgroup analysis
A total of 335 patients (36.3% of the overall cohort) were reperfused within the first 6 h from stroke onset, among those 76 (22.7%) patients had overestimation of the baseline infarct volume on CTP (as compared to FIV on MRI), with a median overestimation volume of 15.11 [5.05–27.79] mL. GIC was found in 47/335 (14%) patients with a median overestimation volume of 26.1 [16.1–35.4]. In this early window subgroup, GIC patients similarly demonstrated lower proportion of patients with diabetes mellitus (8.5% vs. 24.3%, p = 0.01) and favorable collateral scores (60% vs. 81.7%, p = 0.003), higher median NIHSS score (19 [15–23] vs. 16 [12–21], p = 0.01), larger baseline infarct cores (43 [27.8–65] vs. 6 [0–19.4] mL, p < 0.001), larger areas of tissue at risk in Tmax >6.0 s (184 [151.5–229.2] vs. 137 [84.2–189] mL, p < 0.001), smaller FIV (9.3 [3.5–27.6] vs. 21.4 [9.5–60] mL, p < 0.001), higher rates of functional independence (86.1% vs. 59.2%, p = 0.002), and lower rates of 90-day mortality (0% vs. 13%, p = 0.02). Times from onset to image acquisition (129 [87–208] vs. 151 [92.5–214], p = 0.53) and to reperfusion (255 [195–300] vs. 260.5 [205.8–313.5] min, p = 0.34) were comparable between both groups (Table I, online data supplement). Additionally, in patients with time from stroke onset to reperfusion > 6 h, overestimation of the baseline infarct volume was identified in 61/580 (10.5%) patients with a median overestimation volume of 9.54 [2.69–19.70] mL. GIC was identified in 30/588 (5.1%) patients with a median overestimation volume of 19.7 [17.46–42.04]. The rates of GIC in terms of final reperfusion grade, occlusion location, and time from stroke onset to reperfusion are illustrated in Table II, online data supplement.
Sensitivity analysis
ROC curve analysis and Youden’s index showed an optimal cutoff point of 359.5 min in time from onset to reperfusion to detect the presence of GIC (sensitivity of 63%, specificity of 63%, AUC of 0.656) (Figure 3). For the purpose of providing a more practical time cutoff, this was approximated to 6 h, with similar test statistics with a sensitivity of 64%, a specificity of 60%, and an AUC of 0.627 (95% CI 0.567–0.687, p < 0.001) for the presence of GIC.
Figure 3. Receiver operating characteristic curves of time from onset to reperfusion for prediction of the presence of ghost infarct core.
Discussion
Our study demonstrated that in reperfused MT patients, rCBF < 30% may overestimate the FIV calculated on follow-up MRI, considered to be the gold standard for infarct volume estimation.25,26 Moreover, we demonstrated that GIC is more common in the early time window (<6 h) and is associated with poor collateral scores but also more favorable outcomes. Notably, the GIC phenomenon occurred in approximately 15% of the patients reperfused within 6 h from stroke onset and the median volume of overestimation was greater than 25 mL with overestimation volumes surpassing 35 mL in a quarter of the GIC patients. These factors raise significant concerns about the accuracy of CTP as a selection tool for reperfusion therapies in AIS patients, especially in the early window.
The observation that the likelihood of occurrence of GIC is time dependent is consistent with the results from previous studies.23,24 One of the reasons that may cause those higher rates of overestimation in patients who were scanned and reperfused early may be the fact that the rCBF <30% parameter, although the most accurately correlated with irreversibly ischemic tissue in general,27 does not represent actual cell death. CBF reduction’s impact on tissue is likely dependent not only on its intensity but also on its duration. Therefore, at least in early presenters, other thresholds or conjunction of perfusion parameters might have to be considered in order to optimize the accuracy of the estimation of the truly infarcted tissue, as it was recently suggested by the work of Bivard et al.28
Previous studies have reported the association between good collateral status and smaller baseline perfusion lesion volumes.29,30 In our study, we found that poor collateral scores were independently associated with the occurrence of rCBF overestimation of the FIV calculated on follow-up scans. This may be explained by the strong interaction between visual collateral scores and contrast peak density. Poor collateral status would lead to lower contrast peak density and, consequently, to larger perfusion and ischemic core lesion volumes on CTP.31 Although this correlation with increased baseline lesion volumes exists, we are led to think by the current findings that these parameters might not be as reliable as previously believed to accurately predict FIV sizes in this specific population of patients.
It is important to remark that in the subgroup analysis of patients reperfused within 6 h, GIC was significantly more frequently observed (14% vs. 5.1% of patients with onset to reperfusion unknown or longer than 6 h, p < 0.001). This suggests that CTP may be less reliable in the early time window. Given the dramatic benefit of MT within the first 6 h along with its highly favorable safety and cost-effective profiles, any selection tool that may potentially be used to exclude patients from treatment must have an extremely high degree of accuracy. Our data adds to the growing body of evidence that supports that the CTP findings must be carefully interpreted and should not be the sole reason to exclude patients from reperfusion treatment.32,33 Notably, the optimal cutoff point in time from onset to reperfusion (359.5 min) to detect the presence of GIC found in our study was longer than what has been reported in some previous studies. This is likely explained by the significant larger sample size and broader time distribution in our study presumably leading to greater statistical power.
One of the strengths of this study over others previously published on this same subject is related to the considerably larger size of our patient cohort as well as to the fact that we used only CBF (the most accurate predictor of FIV)15,27 to determine infarct core in the acute setting and MRI (the most sensitive and accurate method to determine infarcted tissue)25,26 to calculate FIV, which made the data less prone to measuring errors than if we had included less accurate follow-up imaging methods, such as NCCT. Moreover, we also only evaluated successfully reperfused (TICI 2b-3) patients, which reduced interference that the natural evolution of stroke might have had in the imaging outcomes.
Our study is limited by the fact that it represents a sample from a single center and by its retrospective nature. The utilization of only single-phase CTA calculated collateral scores was also a limiting factor, since we were not able to discriminate cases in which CTA scan acquisition was performed too early or too late after the contrast bolus or where contrast enhancement was not optimal. A total of 858 (37.3%) patients were excluded from the analysis not having undergone pre-treatment CTP at our center. In our institution, multimodal imaging is part of the acute stroke protocol thus all consecutive patients are expected to undergo NCCT/CTA/CTP whenever feasible. The typical reasons for not performing CTP include (1) skipping conventional imaging in favor of the “direct to angiography suite protocol” with cone beam CT in the biplane equipment,34 (2) having difficult IV placement where contrast administration would be expected cause significant treatment delays, (3) history of iodine contrast allergy, and (4) renal dysfunction. However, since these factors occur in a random basis, we do not expect that the missed CTP cases would have been a significant source of bias. Finally, the discrepancy between the CTP and MRI acquisitions in terms of slice thickness and brain coverage as well as the inclusion of patients with successful but incomplete reperfusion (mTICI2b) may have resulted in an underestimation of the true occurrence of GIC.
Conclusion
In conclusion, the GIC phenomenon is an under recognized but relatively frequent entity that may inappropriately exclude patients from reperfusion therapy, especially in the early presentation. This finding is of critical importance to raise awareness in the clinical community about the negative impacts that a CTP-centered approach for the selection of endovascular therapy may have on stroke patients. In the presence of a favorable non-contrast CT, CTP should not be used as the only criterion to exclude patients from endovascular reperfusion.
Declaration of conflicting interests
The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: RGN reports consulting fees for advisory roles with Anaconda, Biogen, Cerenovus, Genentech, Imperative Care, Medtronic, Phenox, Prolong Pharmaceuticals, Stryker Neurovascular and stock options for advisory roles with Astrocyte, Brainomix, Cerebrotech, Ceretrieve, Corindus Vascular Robotics, Vesalio, Viz-AI, and Perfuze. DCH is a consultant for Stryker and Vesalio and holds stock options at Viz.AI.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
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