Abstract
In order to investigate the value of multimodal CT for quantitative assessment of collateral circulation, ischemic semidark zone, core infarct volume in patients with acute ischemic stroke (AIS), and prognosis assessment in intravenous thrombolytic therapy, segmentation model which is based on the self-attention mechanism is prone to generate attention coefficient maps with incorrect regions of interest. Moreover, the stroke lesion is not clearly characterized, and lesion boundary is poorly differentiated from normal brain tissue, thus affecting the segmentation performance. To address this problem, a primary and secondary path attention compensation network structure is proposed, which is based on the improved global attention upsampling U-Net model. The main path network is responsible for performing accurate lesion segmentation and outputting segmentation results. Likewise, the auxiliary path network generates loose auxiliary attention compensation coefficients, which compensate for possible attention coefficient errors in the main path network. Two hybrid loss functions are proposed to realize the respective functions of main and auxiliary path networks. It is experimentally demonstrated that both the improved global attention upsampling U-Net and the proposed primary and secondary path attention compensation networks show significant improvement in segmentation performance. Moreover, patients with good collateral circulation have a small final infarct area volume and a good clinical prognosis after intravenous thrombolysis. Quantitative assessment of collateral circulation and ischemic semidark zone by multimodal CT can better predict the clinical prognosis of intravenous thrombolysis.
Highlights
Good collateral circulation is associated with a longer survival time, higher revascularization rate, and better neurological recovery. erefore, accurate assessment of the collateral circulation and ischemic semidark zone in acute ischemic stroke (AIS) patients is the basis for treatment planning. e purpose of this paper is to investigate the relationship between different collateral circulation grades and ischemic semidark zone, infarct size, and the prognostic value of clinical intravenous thrombolytic therapy using multimodal CT
Experimental Results and Analysis e proposed Global Attention Upsample (GAU)-A-UNet and PAPAC-Net networks were firstly validated and explained in detail using the opensource stroke lesion segmentation dataset Atlas, and the comparative experimental results of different models in this dataset are presented in Section 5 4.5 and 4.6 further validates the proposed method using another Ischemic Stroke Lesion Segmentation (ISLES) dataset (2018 version)
Since all the magnetic resonance imaging (MRI) image data had already undergone brain image alignment, image normalization, and bias field correction in the original dataset, no additional preprocessing operations were performed, and the original image size was only changed by cropping the excess background black edges to fit the input requirements of the network structure. e Dice Similarity Coefficient (DSC), F2score (F2), accuracy PRE (Precision), recall RE (Recall), and false positive rate were used as evaluation metrics. e F2score reflects the level of false positives and is only used in the PAPAC-Net to equate the level of relaxation of the generated attention factor maps
Summary
Multimodal CT was performed using a Toshiba Aquilion one 320-row volumetric CT, including plain scan, angiographic CTA, and perfusion imaging CTP. 50 ml of nonionic contrast was injected at a rate of 5 ml/s using a double-barrel high-pressure syringe, and 30 ml of saline was injected at the same rate. Multimodal CT was performed using a Toshiba Aquilion one 320-row volumetric CT, including plain scan, angiographic CTA, and perfusion imaging CTP. E whole-brain dynamic volume data were obtained in 19 time phases. Each frame of the original image was subtracted from the baseline image using the flat-scan image as the baseline, and each phase of the subtracted image was arranged in the temporal order of the scan to obtain a time-distributed cerebral blood flow image. Using the American ASITN/SIR collateral circulation grading system, the status of cerebral collateral circulation was classified into 5 levels [4]: level 0: no collateral vessels on the ischemic side; level 1: partial collateral circulation formation in the late venous phase; level 2: partial collateral circulation formation in the ischemic area before the venous phase; level 3: complete blood flow to the ischemic foci in the late venous phase; level 4: complete collateral circulation formation before the venous phase (Figures 1 to 3). Two imaging physicians were blinded to the grade of collateral circulation and recorded separately
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