지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
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초록· 키워드
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Background and Purpose Multiphase computed tomographic angiography (mCTA) provides time variant images of pial vasculature supplying brain in patients with acute ischemic stroke (AIS). To develop a machine learning (ML) technique to predict tissue perfusion and infarction from mCTA source images. Methods 284 patients with AIS were included from the Precise and Rapid assessment of collaterals using multi-phase CTA in the triage of patients with acute ischemic stroke for Intra-artery Therapy (Prove-IT) study. All patients had non-contrast computed tomography, mCTA, and computed tomographic perfusion (CTP) at baseline and follow-up magnetic resonance imaging/noncontrast- enhanced computed tomography. Of the 284 patient images, 140 patient images were randomly selected to train and validate three ML models to predict a pre-defined Tmax thresholded perfusion abnormality, core and penumbra on CTP. The remaining 144 patient images were used to test the ML models. The predicted perfusion, core and penumbra lesions from ML models were compared to CTP perfusion lesion and to follow-up infarct using Bland-Altman plots, concordance correlation coefficient (CCC), intra-class correlation coefficient (ICC), and Dice similarity coefficient. Results Mean difference between the mCTA predicted perfusion volume and CTP perfusion volume was 4.6 mL (limit of agreement [LoA], ?53 to 62.1 mL; P=0.56; CCC 0.63 [95% confidence interval [CI], 0.53 to 0.71; P<0.01], ICC 0.68 [95% CI, 0.58 to 0.78; P<0.001]). Mean difference between the mCTA predicted infarct and follow-up infarct in the 100 patients with acute reperfusion (modified thrombolysis in cerebral infarction [mTICI] 2b/2c/3) was 21.7 mL, while it was 3.4 mL in the 44 patients not achieving reperfusion (mTICI 0/1). Amongst reperfused subjects, CCC was 0.4 (95% CI, 0.15 to 0.55; P<0.01) and ICC was 0.42 (95% CI, 0.18 to 0.50; P<0.01); in non-reperfused subjects CCC was 0.52 (95% CI, 0.20 to 0.60; P<0.001) and ICC was 0.60 (95% CI, 0.37 to 0.76; P<0.001). No difference was observed between the mCTA and CTP predicted infarct volume in the test cohort (P=0.67). Conclusions A ML based mCTA model is able to predict brain tissue perfusion abnormality and follow-up infarction, comparable to CTP.
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등록된 정보가 없습니다.
참고문헌 (33)
참고문헌 신청
Albers GW / 2018 / Thrombectomy for stroke at 6 to 16 hours with selection by perfusion imaging / N Engl J Med 378:708~718
Mokin M / 2017 / Predictive value of RAPID assessed perfusion thresholds on final infarct volume in SWIFT PRIME(Solitaire With the Intention for Thrombectomy as Primary Endovascular Treatment) / Stroke 48:932~938
Nogueira RG / 2018 / Thrombectomy 6 to 24 hours after stroke with a mismatch between deficit and infarct / N Engl J Med 378:11~21
Campbell BC / 2015 / Endovascular therapy for ischemic stroke with perfusion-imaging selection / N Engl J Med 372:1009~1018
Campbell BC / 2011 / Cerebral blood flow is the optimal CT perfusion parameter for assessing infarct core / Stroke 42:3435~3440
Mokin M / 2017 / Predictive value of RAPID assessed perfusion thresholds on final infarct volume in SWIFT PRIME(Solitaire With the Intention for Thrombectomy as Primary Endovascular Treatment) / Stroke 48:932~938
Nogueira RG / 2018 / Thrombectomy 6 to 24 hours after stroke with a mismatch between deficit and infarct / N Engl J Med 378:11~21
Campbell BC / 2015 / Endovascular therapy for ischemic stroke with perfusion-imaging selection / N Engl J Med 372:1009~1018
Campbell BC / 2011 / Cerebral blood flow is the optimal CT perfusion parameter for assessing infarct core / Stroke 42:3435~3440
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