417 Predicting Hematoma Expansion after Spontaneous Intracerebral Hemorrhage Through a Noncontrast Computed Tomography Based Model. (1st April 2022)

• Record Type: Journal Article
• Authors: Seymour, Samantha; Rava, Ryan; Ionita, Ciprian; Snyder, Kenneth V.; Waqas, Muhammad; Davies, Jason; Levy, Elad I.; Siddiqui, Adnan H.
• Is Part Of: Neurosurgery. Volume 68(2022)Supplement 1
• Page Start: 97
• Page End: 98
• Publication Date: 2022-04-01
• Subjects: Nervous system -- Surgery -- Periodicals; 617.48005
• DOI: 10.1227/NEU.0000000000001880_417
• Languages: English
• ISSNs: 0148-396X

Abstract

Abstract : INTRODUCTION: Spontaneous Intracerebral Hemorrhage (ICH) accounts for 15% of all acute strokes and is the deadliest stroke subtype with a 40% mortality rate after one month. More than 75% of all ICH patients are severely disabled or deceased after the first year. 30% of patients continue to bleed and demonstrate significant hematoma expansion (HE). Once HE occurs in ICH patients, treatment options are limited and the patient prognosis is significantly decreased. METHODS: NCCT scans for 200 ICH patients (70 expansion, 130 non-expansion) who presented with stroke-like symptoms between August 2016 and December 2019 were collected for this study. The patients had at least one of the following hemorrhages: intraparenchymal (n = 181), intraventricular (n = 45), subdural (n = 13), or subarachnoid (n = 19). Data augmentation and skull-stripping was conducted. A deep neural network was used to identify and segment the hemorrhagic region. Two networks were trained using two-dimensional images created by taking the standard deviation and mean of the voxel intensities over the entire volume to classify hematoma expansion using a training:testing split of 80:20 and 20 iterations of Monte Carlo cross validation. RESULTS: Hematoma expansion metrics using st.dev images are seen with a 95% confidence interval as: accuracy = 0.65 ± 0.04, sensitivity = 0.79 ± 0.06, specificity = 0.58 ± 0.06, precision = 0.51 ± 0.04, negative predictive value (NPV) = 0.84 ± 0.03. Metrics using mean images are: accuracy = 0.64 ± 0.03, sensitivity = 0.68 ± 0.08, specificity = 0.63 ± 0.07, precision = 0.49 ± 0.02, NPV = 0.78 ± 0.03. CONCLUSION: CNNs have the ability to predict hematoma expansion by utilizing two-dimensional images created from flattening NCCT volumes. Taking the st.dev over the NCCT volume within the hemorrhagic region is a better predictor of HE due to its more cautious approach indicated by a higher sensitivity metric.