What Is the “Optimal” Target Mismatch Criteria for Acute Ischemic Stroke?

So at the end of this there is still NO PROTOCOL. You can be thankful your doctor is completely guessing on what needs to be done.  Do you trust your doctor to GUESS CORRECTLY?

What Is the “Optimal” Target Mismatch Criteria for Acute Ischemic Stroke?

Chushuang Chen^1*, Mark W. Parsons², Christopher R. Levi^3,4, Neil J. Spratt^3,4, Longting Lin², Timothy Kleinig⁵, Kenneth Butcher⁶, Xin Cheng⁷, Qiang Dong⁷, Billy O'Brien⁸, Richard I. Avivi⁹, Martin Krause¹⁰, P. N. Sylaja¹¹, Philip Choi¹², Sandeep Bhuta¹³, Congguo Yin¹⁴, Jianhong Yang¹⁵, Peng Wang¹⁶, Weiwen Qiu¹⁷ and Andrew Bivard¹

• ¹Melbourne Brain Centre, University of Melbourne, Parkville, VIC, Australia
• ²Department of Neurology, Liverpool Hospital, University of New South Wales, Sydney, NSW, Australia
• ³Department of Neurology, John Hunter Hospital, University of Newcastle, Callaghan, NSW, Australia
• ⁴Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
• ⁵Department of Neurology, Royal Adelaide Hospital, Adelaide, SA, Australia
• ⁶Prince of Wales Medical School, University of New South Wales, Sydney, NSW, Australia
• ⁷Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
• ⁸Department of Neurology, Gosford Hospital, Gosford, NSW, Australia
• ⁹Division of Neuroradiology, Department of Medical Imaging, University of Toronto and Sunnybrook Health Sciences Centre, Toronto, ON, Canada
• ¹⁰Department of Neurology, Kolling Institute, Royal North Shore Hospital, University of Sydney, Sydney, NSW, Australia
• ¹¹Department of Neurology, Sri Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India
• ¹²Department of Neurology, Box Hill Hospital, Melbourne, VIC, Australia
• ¹³Department of Medical Imaging, Gold Coast University Hospital, Southport, QLD, Australia
• ¹⁴Department of Neurology, Hangzhou First Hospital, Zhejiang, China
• ¹⁵Department of Neurology, Ningbo First Hospital, Zhejiang, China
• ¹⁶Department of Neurology, Taizhou First People's Hospital, Zhejiang, China
• ¹⁷Department of Neurology, Lishui People's Hospital, Zhejiang, China

We aimed to compare Perfusion Imaging Mismatch (PIM) and Clinical Core Mismatch (CCM) criteria in ischemic stroke patients to identify the effect of these criteria on selected patient population characteristics and clinical outcomes. Patients from the INternational Stroke Perfusion Imaging REgistry (INSPIRE) who received reperfusion therapy, had pre-treatment multimodal CT, 24-h imaging, and 3 month outcomes were analyzed. Patients were divided into 3 cohorts: endovascular thrombectomy (EVT), intravenous thrombolysis alone with large vessel occlusion (IVT-LVO), and intravenous thrombolysis alone without LVO (IVT-nonLVO). Patients were classified using 6 separate mismatch criteria: PIM-using 3 different measures to define the perfusion deficit (Delay Time, Tmax, or Mean Transit Time); or CCM-mismatch between age-adjusted National Institutes of Health Stroke Scale and CT Perfusion core, defined as relative cerebral blood flow <30% within the perfusion deficit defined in three ways (as above). We assessed the eligibility rate for each mismatch criterion and its ability to identify patients likely to respond to treatment. There were 994 patients eligible for this study. PIM with delay time (PIM-DT) had the highest inclusion rate for both EVT (82.7%) and IVT-LVO (79.5%) cohorts. In PIM positive patients who received EVT, recanalization was strongly associated with achieving an excellent outcome at 90-days (e.g., PIM-DT: mRS 0-1, adjusted OR 4.27, P = 0.005), whereas there was no such association between reperfusion and an excellent outcome with any of the CCM criteria (all p > 0.05). Notably, in IVT-LVO cohort, 58.2% of the PIM-DT positive patients achieved an excellent outcome compared with 31.0% in non-mismatch patients following successful recanalization (P = 0.006).

Conclusion: PIM-DT was the optimal mismatch criterion in large vessel occlusion patients, combining a high eligibility rate with better clinical response to reperfusion. No mismatch criterion was useful to identify patients who are most likely response to reperfusion in non-large vessel occlusion patients.

Introduction

Selection of patients using target mismatch can identify acute ischemic stroke patients who are most likely to benefit from intravenous thrombolysis (IVT) or endovascular thrombectomy (EVT) in an extended time window (1–3). However, the exact patient selection criteria remain a controversial topic. The DEFUSE3 (3) and EXTEND IA (4) using Perfusion Imaging Mismatch (PIM), which preferentially enroll patients with a largely treatable penumbra and small ischemic core. The DAWN trial (1) applied a Clinical-Core Mismatch (CCM) where an age-adjusted National Institutes of Health Stroke Scale (NIHSS) score was used as a surrogate for the total perfusion deficit, in combination with a small age-adjusted ischemic core define mismatch. However, various thresholds calculated by different post-processing algorithms, defining penumbra and core, has been reported. The most common set of thresholds defining penumbra and core are time to peak of the residual function (Tmax) > 6 s and relative cerebral blood flow (rCBF) <30%, or delay time (DT) >3 s and rCBF <30% (5). When calculating Mean Transit Time (MTT), Tmax and CBF by singular value deconvolution (sSVD), the algorithm assumes no delay in blood flow from proximal arteries to the ischemic region, as, almost invariably in ischemic stroke, there is delay and dispersion of the contrast between the more proximal arterial input function (AIF) and the ischemic region (6). The sSVD is a delay-sensitive algorithm, resulting in underestimation of CBF and overestimation of MTT (6–8). This is highly clinically relevant as different definitions of the perfusion deficit may affect reperfusion treatment eligibility. It is a challenge to determine which mismatch criteria are superior to others in term of optimally identifying excellent reperfusion responders and excluding those who are either likely to be harmed or who have a good natural history regardless of treatment, in routine clinical practice.

Therefore, in this study we aimed to: (i) to compare the various PIM and CCM criteria using different definitions of perfusion deficit; and (ii) assess the ability of each criterion to identify acute stroke patients who are most likely to respond to reperfusion treatment in different subgroups of acute ischemic stroke patients. We hypothesized: (i) that there would be considerable differences in the proportion of patients selected with each mismatch criterion; and (ii) that the presence of PIM or CCM positivity may not uniformly predict response to reperfusion treatment in different sub-groups of acute ischemic stroke patients.