Artificial intelligence-quantified total hemorrhagic burden on susceptibility-weighted imaging in acute ischemic stroke: a multicenter cohort analysis

Background: Susceptibility-weighted imaging (SWI) reveals three forms of cerebral hemorrhagic burden: cerebral microbleeds (CMB), chronic parenchymal hemorrhage, and cortical superficial siderosis (cSS). Prior work has focused on CMB counts, whereas the other two are rarely quantified at scale; their prognostic value in ischemic stroke is thus uncertain. An artificial intelligence (AI) tool to quantify all three at registry scale was developed and tested to determine whether the resulting total hemorrhagic burden (THB) score stratifies risk.Methods: The tool was applied to the Clinical Research Collaboration for Stroke in Korea registry (16 sites). After restricting to first-ever ischemic stroke without intravenous thrombolysis or thrombectomy and pre-stroke modified Rankin Scale (mRS) ≤1, 6,124 patients were included in the analysis. THB summed the z-transformed logged values of the three components.Results: CMB, parenchymal hemorrhage, and cSS were positive in 45.8%, 17.1%, and 3.4% of patients, respectively, with distinct clinical determinants. THB was associated with 3-month poor outcome (mRS ≥3): adjusted odds ratio (OR) per standard deviation 1.19 (95% CI, 1.11–1.27; P<0.001). The ordinal mRS shift was driven by parenchymal hemorrhage volume (joint-model OR, 1.23 per log unit) and CMB count (OR, 1.19); cSS was directionally consistent but non-significant. Poor-outcome rates rose monotonically across THB tiers, from 18.6% in the lowest to 36.8% in the highest tier.Conclusion: An AI tool feasibly quantified all three SWI hemorrhagic findings at the registry scale. The resulting THB composite stratified patients by 3-month functional outcome with a tier-based gradient, thus supporting its use for risk stratification.

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Journal
Journal of Neurocritical Care
Published
2026-06-30
DOI
https://doi.org/10.18700/jnc.260038
Primary Topic
Intracerebral and Subarachnoid Hemorrhage Research
Type
article
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article

Artificial intelligence-quantified total hemorrhagic burden on susceptibility-weighted imaging in acute ischemic stroke: a multicenter cohort analysis

Jun Yup Kim, Jihoon Kang, Hae-Bong Jeong, Chan-Young Park et al.
Journal of Neurocritical Care
Intracerebral and Subarachnoid Hemorrhage Research
article

Artificial intelligence-quantified total hemorrhagic burden on susceptibility-weighted imaging in acute ischemic stroke: a multicenter cohort analysis

Jun Yup Kim, Jihoon Kang, Hae-Bong Jeong, Chan-Young Park, Wi‐Sun Ryu, Soo Joo Lee, Jae Guk Kim, Chi Kyung Kim, Joong‐Goo Kim, Jae‐Kwan Cha, Kyu Sun Yum, Hee‐Joon Bae, Jay Chol Choi, Dong-Seok Gwak, Doo Hyuk Kwon, Min-Surk Kye, Chulho Kim, Minwoo Lee, Sang Hwa Lee, Beom Joon Kim, Do Yeon Kim, Jonguk Kim, Kyungbok Lee, Jee Hyun Kwon, Baik Kyun Kim, Myung Jae Lee, Kwang-Yeol Park, Yong-Jin Cho, Jeong-Yoon Lee, Kyusik Kang, Joon-Tae Kim, Jeong-Ho Hong, Hong-Kyun Park, Wook-Joo Kim, Sung-Il Sohn, Nakhoon Kim, Hyunsoo Kim, Jun Lee, Mi Sun Oh, Keun-Sik Hong, Tai Hwan Park, Chulho Kim, Dong-Ick Shin, Kyung-Ho Yu
article en

Abstract

Background: Susceptibility-weighted imaging (SWI) reveals three forms of cerebral hemorrhagic burden: cerebral microbleeds (CMB), chronic parenchymal hemorrhage, and cortical superficial siderosis (cSS). Prior work has focused on CMB counts, whereas the other two are rarely quantified at scale; their prognostic value in ischemic stroke is thus uncertain. An artificial intelligence (AI) tool to quantify all three at registry scale was developed and tested to determine whether the resulting total hemorrhagic burden (THB) score stratifies risk.Methods: The tool was applied to the Clinical Research Collaboration for Stroke in Korea registry (16 sites). After restricting to first-ever ischemic stroke without intravenous thrombolysis or thrombectomy and pre-stroke modified Rankin Scale (mRS) ≤1, 6,124 patients were included in the analysis. THB summed the z-transformed logged values of the three components.Results: CMB, parenchymal hemorrhage, and cSS were positive in 45.8%, 17.1%, and 3.4% of patients, respectively, with distinct clinical determinants. THB was associated with 3-month poor outcome (mRS ≥3): adjusted odds ratio (OR) per standard deviation 1.19 (95% CI, 1.11–1.27; P<0.001). The ordinal mRS shift was driven by parenchymal hemorrhage volume (joint-model OR, 1.23 per log unit) and CMB count (OR, 1.19); cSS was directionally consistent but non-significant. Poor-outcome rates rose monotonically across THB tiers, from 18.6% in the lowest to 36.8% in the highest tier.Conclusion: An AI tool feasibly quantified all three SWI hemorrhagic findings at the registry scale. The resulting THB composite stratified patients by 3-month functional outcome with a tier-based gradient, thus supporting its use for risk stratification.

Journal of Neurocritical CareVol. 19(1)
Ulsan College (KR), Hallym University (KR), Eulji University (KR), Korea University Medical Center (KR), Dong-A University Hospital (KR), Soonchunhyang University Hospital Seoul (KR), Seoul National University Bundang Hospital (KR), University of Ulsan (KR), Seoul Medical Center (KR), Chonnam National University Hospital (KR), Dongguk University Ilsan Hospital (KR), Inje University Ilsan Paik Hospital (KR), Ulsan University Hospital (KR), Yeungnam University Medical Center (KR), Chung-Ang University Hospital (KR), Hallym University Sacred Heart Hospital (KR), Chungbuk National University Hospital (KR), Hallym University Chuncheon Sacred Heart Hospital (KR), Jeju National University Hospital (KR), Keimyung University (KR)
Korea Health Industry Development Institute, Ministry of Science and ICT, South Korea
Openalex Percentile: Top 8%
Intracerebral and Subarachnoid Hemorrhage Research
DOIOpen Access PDFOpenAlex
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