Stroke is the number one cause of disability in the United States. In order to reduce the burden of disability caused by stroke there is a need for better stroke treatments that are available to more stroke victims. Endovascular therapies are increasingly being used and may fill this need as they have high rates of recanalization. It is, however, not known which patients benefit clinically. Previous studies suggest that stroke patients with a small volume of irreversible ischemic injury (infarct core) and a large volume of reversible ischemic injury (penumbra) are most likely to benefit from restoration of blood flow. MRI shows promise for identification of the ischemic core and penumbra but it has very limited availability in US emergency rooms. Computed Tomography Perfusion (CTP) imaging is a potential solution as it is widely available and can easily be added to a non-contrast head CT, already routinely obtained to evaluate stroke patients in the emergency room. However, methods for processing of CTP images and criteria for interpretation of the images are still immature. Therefore, patient selection based on CTP images is not ready for implementation in clinical trials or clinical practice. The overall goal of the CTP to predict Response to recanalization in Ischemic Stroke Project (CRISP) is to develop a practical tool to identify acute stroke patients who are likely to benefit from endovascular therapy. The project has two main parts. During the first part (year 1), we propose to develop a fully automated system (RAPID) for processing of CT Perfusion (CTP) images that will generate brain maps of the ischemic core and penumbra. We will also define criteria, based on these CTP maps, which predict if a patient is likely to benefit from restoration of blood flow. These criteria will be based on data from a retrospective cohort of 95 patients treated at St Luke's hospital. During the second part (years 2-5), we aim to demonstrate that physicians in the emergency setting, with the aid of a fully automated CTP analysis program (RAPID), can accurately predict response to recanalization in stroke patients undergoing revascularization. To achieve this aim we will conduct a prospective cohort study of 100 consecutive stroke patients who will undergo a CTP scan prior to endovascular therapy. The study will be conducted at two sites (Stanford University and St Luke's Hospital). Patients will have an early follow-up scan within 6 hours to assess reperfusion and a late follow-up scan at day 5 to determine the final infarct. The successful execution of this research will provide physicians with an easy, automated method to select patients who are likely to benefit from restoration of blood flow. Such a method, thanks to easy accessibility to CT technology, would be of great value for patient selection in multi-center clinical acute stroke trials and, eventually, in routine clinical practice.

Public Health Relevance

The key objective of the CTP to predict Response to recanalization in Ischemic Stroke Project (CRISP) is to obtain sufficient preliminary data to optimally design a definitive study to assess the risks and benefits of new stroke treatments aimed at restoration of blood flow. We believe that CRISP will clarify that specific CT perfusion findings can identify patients who are likely to benefit from restoration of blood flow to the brain. These findings will eventually lead to effective therapies for a large population of stroke patients who are currently ineligible for treatment and substantially reduce stroke-related disability.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS075209-04
Application #
8623151
Study Section
Acute Neural Injury and Epilepsy Study Section (ANIE)
Program Officer
Moy, Claudia S
Project Start
2011-09-01
Project End
2016-02-29
Budget Start
2014-03-01
Budget End
2015-02-28
Support Year
4
Fiscal Year
2014
Total Cost
$560,538
Indirect Cost
$160,658
Name
Stanford University
Department
Neurology
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
Mishra, Nishant K; Albers, Gregory W; Christensen, Søren et al. (2014) Comparison of magnetic resonance imaging mismatch criteria to select patients for endovascular stroke therapy. Stroke 45:1369-74