AJNR. American journal of neuroradiology · 2024
Lesion-Filling Index from Quantitative DSA Correlates with Hemorrhage of Cerebral AVM.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Li Ruinan, Chen Yu, Chen Pingting, Ma Li, Han Heze, Li Zhipeng, Zhou Wanting, Chen Xiaolin, Zhao Yuanli
Аннотация
BACKGROUND AND PURPOSE: Rupture is the most life-threatening manifestation of cerebral AVMs. This study aimed to explore the hemodynamic mechanism of AVM rupture. We introduced a new quantitative DSA parameter that can reflect the degree of intranidal blood stasis, called the lesion-filling index.
MATERIALS AND METHODS: This study examined patients with AVMs who had undergone both DSA and MR imaging between 2013 and 2014. Clinical presentations, angioarchitecture, and hemodynamic parameters generated from quantitative DSA were analyzed using univariate and multivariable logistic regression. The lesion-filling index was defined as the arterial diagnostic window divided by the volume of the AVM. To assess the correlation between the lesion-filling index and rupture, we incorporated the lesion-filling index into 2 published prediction models widely recognized for predicting AVM rupture risk, R2eD and VALE. The DeLong test was used to examine whether the addition of the lesion-filling index improved predictive efficacy.
RESULTS: A total of 180 patients with AVMs were included. The mean lesion-filling index values in the ruptured group were higher compared with the unruptured group (390.27 [SD, 919.81] versus 49.40 [SD, 98.25]), P < .001). A higher lesion-filling index was significantly correlated with AVM rupture in 3 different multivariable logistic models, adjusting for angioarchitecture factors (OR = 1.004, P = .02); hemodynamic factors (OR = 1.005, P = .009); and combined factors (OR = 1.004, P = .03). Both R2eD (area under the curve, 0.601 versus 0.624; P = .15) and VALE (area under the curve, 0.603 versus 0.706; P < .001) predictive models showed improved predictive performance after incorporating the lesion-filling index and conducting 10-fold cross-validation.
CONCLUSIONS: The lesion-filling index showed a strong correlation with AVM rupture, suggesting that overperfusion is the hemodynamic mechanism leading to AVM rupture.
MATERIALS AND METHODS: This study examined patients with AVMs who had undergone both DSA and MR imaging between 2013 and 2014. Clinical presentations, angioarchitecture, and hemodynamic parameters generated from quantitative DSA were analyzed using univariate and multivariable logistic regression. The lesion-filling index was defined as the arterial diagnostic window divided by the volume of the AVM. To assess the correlation between the lesion-filling index and rupture, we incorporated the lesion-filling index into 2 published prediction models widely recognized for predicting AVM rupture risk, R2eD and VALE. The DeLong test was used to examine whether the addition of the lesion-filling index improved predictive efficacy.
RESULTS: A total of 180 patients with AVMs were included. The mean lesion-filling index values in the ruptured group were higher compared with the unruptured group (390.27 [SD, 919.81] versus 49.40 [SD, 98.25]), P < .001). A higher lesion-filling index was significantly correlated with AVM rupture in 3 different multivariable logistic models, adjusting for angioarchitecture factors (OR = 1.004, P = .02); hemodynamic factors (OR = 1.005, P = .009); and combined factors (OR = 1.004, P = .03). Both R2eD (area under the curve, 0.601 versus 0.624; P = .15) and VALE (area under the curve, 0.603 versus 0.706; P < .001) predictive models showed improved predictive performance after incorporating the lesion-filling index and conducting 10-fold cross-validation.
CONCLUSIONS: The lesion-filling index showed a strong correlation with AVM rupture, suggesting that overperfusion is the hemodynamic mechanism leading to AVM rupture.