Introduction Cerebral angiographic revascularization grading is the primary method for measuring the angiographic success of acute ischemic stroke (AIS) endovascular therapy and is one of the strongest predictors for clinical outcome. Of the many reported scales, the modified Treatment in Cerebral Ischemia (mTICI) scale is the preferred grading scale for assessment of revascularization. Currently, mTICI grading is based on visual crude estimations by the operator, which may introduce error and bias in to the evaluation. Here, we present an update on our on-going study to automatize mTICI and provide a more accurate and precise grading tool: Quantified TICI (qTICI).
Methods Phase one of the project is to develop a database of 15–30 patients with an aplastic/hypoplastic anterior cerebral artery (ACA) in order to establish the standard average and predicted 100% qTICI for the isolated middle cerebral artery (MCA) territory. To map the MCA territory, a retrospective review of patients between the ages of 18–85 was performed from our Digital Subtraction Angiography (DSA) database at the Medical College of Wisconsin. All consecutive cases with aplastic/hypoplastic ACA (to minimise contaminating blood flow from the ACA territory) are included in this study. Existing Siemens software is currently in use to estimate the territory of normal capillary blush and establish normal blood flow values in this database.
Results We have identified 19 consecutive patients with aplastic/hypoplastic ACA between the ages of 18–85, from our DSA database of over 3000 cases. Nine patients had aplastic A1 and 10 had hypoplastic A1 segments of the ACA. Once normal capillary blush of the MCA territory has been established and automatized, we will use those normalised values per age to compare the capillary blush and blood flow of the pathological cases- a cohort of 20–25 patients who have stroke secondary to MCA occlusion. Values of qTICI will be compared and validated using standard visual estimation of mTICI. Clinical correlation of qTICI with outcome will also be performed. The goal is to establish software that will accurately grade mTICI on a continuous scale rather than using the current crude visual estimation with wide range 4 strata, which will eliminate the operator dependent bias and increase the precision and accuracy of the revascularization grading.
Conclusion The qTICI Grading Software once developed will have the potential to revolutionise the way clinicians and interventionalists grade revascularization post AIS endovascular therapy. The clinical implications of establishing automatized and quantified revascularization scale is critical in improving treatment safety and efficacy.
Disclosures A. Sattar: None. K. Asif: None. M. Teleb: None. A. Castonguay: None. M. Issa: None. O. Zaidat: None.
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