Clinical Study On The Evaluation Of Blood Perfusion Improvement Of Near-occlusive Lesions Of Carotid Artery By Carotid Endarterectomy And The Exploration And Application Of Imaging Omics Evaluation Technology For Carotid Plaque Stabilit

Purpose:near-occlusion(NO)is a special subtype of carotid stenosis,defined as severe carotid artery stenosis with downstream artery collapse.Compared with common carotid stenosis patients,NO patients have higher risk of cerebral artery events.Carotid endarterectomy(CEA)has been known to improve prognosis of carotid stenosis patients,but assessment about safety or efficiency for NO patients,who generally have higher operative risk,has not yet been done.In recent years,cerebral blood perfusion is getting approved to be a new index to assess surgery efficiency,since it is closely related to clinical symptoms,such as cognition.However,post-surgery perfusion improvement in NO patients has not been well studied.Thus,we designed a prospective study to evaluate safety and efficiency for CEA in NO patients.Methods:we prospectively recruited 93 carotid stenosis patients during July,2020 and February,2022.All patients received pre-operative computed tomography angiography(CTA),also magnetic resonance imaging(MRI)-arterial spin labelling(ASL)twice,within 2 weeks before surgery,and within 1 week after surgery.We divided 93 patients into NO(17,18.3%)and common stenosis(76,81.7%)patients according to preoperative CTA,and compared symptoms,perfusion and perioperative safety between 2 subgroups.Primary endpoints are perioperative events,which include stroke,transient ischemic attacks(TIA),myocardial infarction(MI)and death during hospital stay.20 patients received both pre-surgery and post-surgery cognition test.For this subgroup,we also analysis improvement of cognition as an index for safety.For perfusion,cerebral blood flow(CBF)and arterial transit times(ATT)from anterior cerebral artery(ACA),middle cerebral artery(MCA)and posterior cerebral artery(PCA)were collected.We compared change of CBF and ATT,and see whether perfusion was improved after surgery or not.Results:no significant difference between NO and stenosis patients exists when comparing symptoms,including impairment of cognition.Incidence of perioperative events was low,with only 1(1.3%)stroke in NO patients and 1(1.3%)TIA,1(1.3%)MI in non-NO patients.No perioperative death occurred.No difference existed between 2 groups(5.9%vs.2.6%,p=0.4583).NO patients had significant improvement at territory of MCA(ATT:-223.10 vs.50.07,p=0.0000;CBF:11.84 vs.3.39,p=0.0164)and PCA(ATT:-70.30 vs.44.59,p=0.0182;CBF:8.57 vs.3.21,p=0.0838),but not ACA(ATT:-52.56 vs.34.86,p=0.0847;CBF:7.52 vs.2.28,p=0.1694).When comparing NO patients with non-NO patients,we found significantly higher improvement also at territory of MCA(ATT:-223.10 vs.-55.64,p=0.0000,CBF:11.84 vs.5.08,p=0.0020)and PCA(ATT:-70.30 vs.1.11,p=0.0139;CBF:8.57 vs.4.27,p=0.0450).Conclusion:though NO patients didn’t have significant improvement after CEA for perfusion at territory of ACA,improvement at territory of MCA and PCA was significant,and NO patients had significantly higher improvement at territory of MCA and PCA comparing with common stenosis patients.High surgery safety was observed in all patients without statistical difference.Based on these findings,we believe that surgical intervention is recommended to all NO patients who can tolerate CEA.Purpose:ischemic stroke is one of the leading diseases threatening lives of humankind,and intracranial infarction caused by ruptured unstable carotid plaque is an important reason of ischemic stroke.Latest guildelines of European Society of Cardiology(ESC)claimed the necessity of pre-surgery assessment for carotid plaque stability,and active surgical intervention is recommended for those with vulnerable plaques.However,current non-invasive imaging technologies can only diagnose some features of carotid plaque,such as intraplaque hemorrhage,lipid core,etc.,but not plaque stability.As there is no non-invasive imaging technologies able to assess carotid plaque stability,diagnosis of unstable carotid plaque is still highly dependent on result of postsurgery pathology.Failure of pre-surgery diagnosis may lead to misclassification of carotid plaque,and further wrong surgery indication.Thus,we hereby apply radiomics to discover imaging features unrecognizable to human eye,and combine proteomics to explore the possibility of pre-surgery diagnosis of unstable carotid plaque via imaging.Methods:we recruited patients receiving carotid endarterectomy(CEA)at Department of Vascular Surgery in Peking Union Medical College Hospital during 2014 and 2021.All patients should have intact inpatient medical record,pre-surgery computed tomography angiography(CTA)and postsurgery plaque.For pre-surgery CTA,ITK-SNAP was applied to label region of interest,and radiomics features were extracted using pyradiomics.For post-surgery plaques,hematoxylin-eosin(HE),CD34,CD68 and Masson staining were used to recognize pathological features,classification according to American heart association(AHA)and stability.Extracted radiomics features were screened for prediction of 10 proteins which are known to be related with carotid plaque stability.The final stability model was built based on results of 3 proteins which were precisely predicted.Results:82 patients with carotid stenosis were recruited,including 37 patients with stable plaque and 45 patients with unstable plaque according to post-surgery pathology.No significant differences existed between gender,age,history of past illness,abuse of tobacco or alcohol,or other artery diseases,but degree of stenosis was significantly higher in patients with stable plaque.AHA classification included 31 level Ⅳ,19 level Ⅴ and 32 level Ⅵ plaques.We observed no significant differences between diameter of lipid core,maximum diameter of necrotic core,thickness of fibril cap or number of neovascularization.A total of 2071 radiomics features were extracted.4 proteins failed to screen valid radiomics features,3 proteins had poor prediction results using screened features with area under curve(AUC)below 0.60,and the other 3 proteins were successfully predicted with AUC above 0.60.We rescreened features based on 3 successfully predicted proteins,and built a model with these features.Logistic regression is the best model with a AUC of 0.65.Conclusion:this is the first research using radiomics combined with proteomics to predict stability of carotid plaque,indicating the possibility of radiomics to predict carotid plaque stability and its clinical value,filling the gap of this field.Also,we will continue improving this prediction model,taking more proteins with known radiomics features and clinical data into consideration to further higher precision of prediction model and clinical benefit to patients.