级联VB-Net分割模型用于急性缺血性脑卒中患者扩散加权成像中缺血核心分割的研究

目的:探讨级联VB-Net深度学习网络对扩散加权成像（DWI）中急性缺血性脑卒中缺血核心检出和分割的价值。方法:回顾性分析2016年12月至2018年12月在河南省人民医院就诊的1 500例急性缺血性卒中患者的MRI资料。将1 500例患者的2 456个病灶依据采集时间按8∶1∶1分为训练集、验证集和测试集。首先在脑D...

Segmentation of core infarct in acute ischemic stroke in diffusion weighted imaging using cascaded VB-Net

Objective To explore the detection and segmentation of ischemic core infarct volume of the acute stroke in diffusion weighted imaging(DWI)images using cascaded VB-Net.Methods MRI data of 1500 patients(2456 lesions)with acute ischemic stroke in Henan Provincial People′s Hospital from December 2016 to December 2018 were retrospectively analyzed.Firstly,manual segmentation of ischemic core was performed on DWI images(b=1000 s/mm2),and then all data were divided into training set,validation set and independent test set by 8∶1∶1.Then,the cascaded VB-Net was constructed,and the core infarct was automatically detected and segmented in the test set.Interclass correlation coefficient(ICC)was used to evaluate the consistency of volume size measured by manual segmentation and cascaded VB-Net.The patients were divided into large ischemic core lesion group(ischemic core volume≥10 ml)and small ischemic core lesion group(ischemic core volume<10 ml),and the Dice coefficient difference between the two groups was compared using Mann-Whitney U test.Results In independent test set,cascaded model had the detection rate of 94.6%(243/257)with Dice coefficient of 0.76(0.68,0.84).The agreement of cacade VB-Net segmented[4.19(1.21,14.13)ml]and manual segmented ischemic core infarct volume[4.08(1.19,17.92)ml]was high(ICC=0.97,P<0.001).There was no significant difference in Dice coefficient between large and small lesion groups[0.76(0.69,0.85),0.76(0.67,0.84),Z=-0.44,P=0.657].Conclusions The cascaded VB-Net model provided a tool to realize automatic detection,segmentation,and calculation of ischemic core infarct volume.It has good segmentation accuracy and high consistency with manual segmentation,which can provide an auxiliary decision-making tool for the selection of treatment plans.