Initial investigation of the use of angiographic parametric imaging for early prognosis of delayed cerebral ischemia in patients with subarachnoid hemorrhage

Roman Price; Mohammad Mahdi Shiraz Bhurwani; Kelsey N. Sommer; Andre Monteiro; Ammad A. Baig; Jason M. Davies; Adnan H. Siddiqui; Ciprian N. Ionita

doi:10.1117/12.2612081

4 April 2022 Initial investigation of the use of angiographic parametric imaging for early prognosis of delayed cerebral ischemia in patients with subarachnoid hemorrhage

Roman Price, Mohammad Mahdi Shiraz Bhurwani, Kelsey N. Sommer, Andre Monteiro, Ammad A. Baig, Jason M. Davies, Adnan H. Siddiqui, Ciprian N. Ionita

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Proceedings Volume 12036, Medical Imaging 2022: Biomedical Applications in Molecular, Structural, and Functional Imaging; 120361Q (2022) https://doi.org/10.1117/12.2612081
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Conference Poster

Abstract

Purpose: Subarachnoid Hemorrhage (SAH) is a lethal hemorrhagic stroke that account for 25% of cerebrovascular deaths. As a result of the initial bleed, a chain of physiological events are initiated which may lead to Delayed Cerebral Ischemia (DCI). As of now we have no diagnostic capability to identify patients which may present DCI a few weeks after initial presentation. We propose to investigate whether a data driven approach using angiographic parametric imaging (API) may predict occurrence of the DCI. Materials and Methods: Digital Subtraction Angiographic (DSA) sequences from 125 SAH patients were used retrospectively to perform API assessment of the entire brain hemisphere where the hemorrhage was detected. Four Regions of Interests (ROIs) were placed to extract five average API biomarkers in the lateral and AP DSAs. Data driven analysis using Logistic Regression was performed for various API parameters and ROIs to find the optimal configuration to maximize the prognosis accuracy. Each model performance was evaluated using area under the curve of the receiver operator characteristic (AUROC). Results: Data driven approach with API has a 60% accuracy predicting DCI occurrence. We determined that location of the ROI for extraction of the API parameters is very important for the data driven model performance. Normalizing the values using the inlet velocities for each patient yield higher and more consistent results. Single API biomarkers models had poor prediction accuracies, barely better than chance. Conclusions: This effectiveness exploratory study demonstrates for the first time, that prognosis of the DCI in SAH patients, is feasible and warrants a more in-depth investigation.

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Roman Price, Mohammad Mahdi Shiraz Bhurwani, Kelsey N. Sommer, Andre Monteiro, Ammad A. Baig, Jason M. Davies, Adnan H. Siddiqui, and Ciprian N. Ionita "Initial investigation of the use of angiographic parametric imaging for early prognosis of delayed cerebral ischemia in patients with subarachnoid hemorrhage", Proc. SPIE 12036, Medical Imaging 2022: Biomedical Applications in Molecular, Structural, and Functional Imaging, 120361Q (4 April 2022); https://doi.org/10.1117/12.2612081

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