qTICI: Quantitative assessment of brain tissue reperfusion on digital subtraction angiograms of acute ischemic stroke patients

Abstract

Background The Thrombolysis in Cerebral Infarction (TICI) scale is an important outcome measure to evaluate the quality of endovascular stroke therapy. The TICI scale is ordinal and observer-dependent, which may result in suboptimal prediction of patient outcome and inconsistent reperfusion grading. Aims We present a semi-automated quantitative reperfusion measure (quantified TICI (qTICI)) using image processing techniques based on the TICI methodology. Methods We included patients with an intracranial proximal large vessel occlusion with complete, good quality runs of anteroposterior and lateral digital subtraction angiography from the MR CLEAN Registry. For each vessel occlusion, we identified the target downstream territory and automatically segmented the reperfused area in the target downstream territory on final digital subtraction angiography. qTICI was defined as the percentage of reperfused area in target downstream territory. The value of qTICI and extended TICI (eTICI) in predicting favorable functional outcome (modified Rankin Scale 0–2) was compared using area under receiver operating characteristics curve and binary logistic regression analysis unadjusted and adjusted for known prognostic factors. Results In total, 408 patients with M1 or internal carotid artery occlusion were included. The median qTICI was 78 (interquartile range 58–88) and 215 patients (53%) had an eTICI of 2C or higher. qTICI was comparable to eTICI in predicting favorable outcome with area under receiver operating characteristics curve of 0.63 vs. 0.62 (P = 0.8) and 0.87 vs. 0.86 (P = 0.87), for the unadjusted and adjusted analysis, respectively. In the adjusted regression analyses, both qTICI and eTICI were independently associated with functional outcome. Conclusion qTICI provides a quantitative measure of reperfusion with similar prognostic value for functional outcome to eTICI score.

Clinical Effect of Digital Subtraction Angiography Combined with Neurointerventional Thrombolysis for Acute Ischemic Cerebrovascular Disease and Its Influence on Vascular Endothelial Function and Oxidative Stress

“…Among all kinds of thrombolytic therapy, neurointerventional therapy is minimally invasive, which uses guidewires, balloon dilatation, and other related materials to explore and treat the diseased blood vessels through intravascular catheters [ 31 ], while DSA can obtain clear and pure vascular images through subtraction, enhancement, and reimaging to achieve vascular visualization. The application of DSA in the process of implementing neurointerventional thrombolytic therapy can better relieve the stenosis and obstruction of diseased blood vessels, restore the blood perfusion of brain tissue, control the development of patients' condition, and effectively improve patient prognosis [ 32 ].…”

Deep Learning–Based Automated Thrombolysis in Cerebral Infarction Scoring: A Timely Proof-of-Principle Study

“…Focusing on the methodical contributions, the main advantages of the proposed end-to-end DL-based approach to automated mTICI scoring in comparison to semiautomatic methods that aim at the assessment of the antegrade reperfusion in brain tissue (and with that on an indirect TICI score assessment using perfusion values) like the recently described qTICI approach 23 are as follows: • The mTICI score definition is learned implicitly. That is, the evidence of vessel revascularization, slow distal blood flow and antegrade perfusion are inherently taken into account.…”

Eloquence-based reperfusion scoring and its ability to predict post-thrombectomy disability and functional status

“…30 In terms of clinical application, our findings could help the operator to determine when it is appropriate to pursue additional thrombectomy attempts or abort the procedure depending on the anatomical location of the nonreperfused region considering its "risk-benefit" ratio versus a strictly volume-based perfusion assessment. As automated assessment of TICI and similar reperfusion scales are becoming more widely investigated, 31,32 defining the clinical effect of distinct anatomical regions could be used to further refine such predictive scores before they enter clinical practice.…”