Role of transcranial Doppler ultrasonography in assessing stenosis after flow diversion

Prospective study on ultrasound-guided stellate ganglion block improves cerebral blood flow in patients with stroke

OBJECTIVES

The effect of routine internal medicine and stroke rehabilitation treatment was not good. To confirm that ultrasound-guided stellate ganglion block (SGB) can improve cerebral blood flow in patients with stroke, Transcranial Doppler (TCD) and carotid ultrasound were used to monitor the cerebral blood flow parameters of ultrasound-guided SGB in patients with stroke.

METHODS

A prospective study of 40 patients with stroke from January 2021 to October 2022 randomly divided into two groups (group SGB: undergoing ultrasound-guided SGB and standard medical procedures, control group: undergoing standard medical procedures) with 20 cases in each was conducted in People's Hospital of Chongqing Liang Jiang New Area. TCD and carotid artery ultrasound were monitored before and after treatment. There were no significant differences in general data on age, gender, disease course, and stroke type between two groups (P>0.05).

RESULTS

After treatment, the bilateral ACA Vm of group SGB was significantly higher, the bilateral internal carotid artery RI and left VA RI were significantly lower than in control group (P<0.05). In group SGB, the Vm of bilateral MCA, bilateral PCA, right ACA, bilateral VA, and BA after treatment were significantly (P<0.05) increased compared to before treatment. PI of bilateral MCA, right ACA, and left VA after treatment were significantly (P<0.05) decreased compared to before treatment. RI of bilateral MCA, bilateral PCA, and bilateral VA after treatment were significantly (P<0.05) decreased compared to before treatment. Right internal carotid artery D after treatment was significantly (P<0.05) higher than before treatment. RI of bilateral internal carotid artery after treatment was significantly (P<0.05) lower than before treatment.

CONCLUSIONS

Ultrasound-guided stellate ganglion block could improve local cerebral blood flow and vascular compliance in patients with stroke, and reduce vascular resistance.

Doppler flow morphology characteristics of epiaortic arteries in aortic valve pathologies: a retrospective study on a cohort of patients with ischemic stroke

BACKGROUND AND AIMS

Neurovascular ultrasound (nvUS) of the epiaortic arteries is an integral part of the etiologic workup in patients with ischemic stroke. Aortic valve disease shares similar vascular risk profiles and therefore not only presents a common comorbidity, but also an etiologic entity. The aim of this study is to investigate the predictive value of specific Doppler curve flow characteristics in epiaortic arteries and the presence of aortic valve disease.

METHODS

Retrospective, single-center analysis of ischemic stroke patients, both receiving full nvUS of the extracranial common- (CCA), internal- (ICA) and external carotid artery (ECA) and echocardiography (TTE/TEE) during their inpatient stay. A rater blinded for the TTE/TEE results investigated Doppler flow curves for the following characteristics: 'pulsus tardus et parvus' for aortic valve stenosis (AS) and 'bisferious pulse', 'diastolic reversal', 'zero diastole' and 'no dicrotic notch' for aortic valve regurgitation (AR). Predictive value of these Doppler flow characteristics was investigated using multivariate logistic regression models.

RESULTS

Of 1320 patients with complete examination of Doppler flow curves and TTE/TEE, 75 (5.7%) showed an AS and 482 (36.5%) showed an AR. Sixty-one (4.6%) patients at least showed a moderate-to-severe AS and 100 (7.6%) at least showed a moderate-to-severe AR. After adjustment for age, coronary artery disease, arterial hypertension, diabetes mellitus, smoking, peripheral arterial disease, renal failure and atrial fibrillation, the following flow pattern predicted aortic valve disease: 'pulsus tardus et parvus' in the CCA and ICA was highly predictive for a moderate-to-severe AS (OR 1158.5, 95% CI 364.2-3684.8, p < 0.001). 'No dicrotic notch' (OR 102.1, 95% CI 12.4-839.4, p < 0.001), a 'bisferious pulse' (OR 10.8, 95% CI 3.2-33.9, p < 0.001) and a 'diastolic reversal' (OR 15.4, 95% CI 3.2-74.6, p < 0.001) in the CCA and ICA predicted a moderate-to-severe AR. The inclusion of Doppler flow characteristics of the ECA did not increase predictive value.

CONCLUSIONS

Well defined, qualitative Doppler flow characteristics detectable in the CCA and ICA are highly predictive for aortic valve disease. The consideration of these flow characteristics can be useful to streamline diagnostic and therapeutic measures, especially in the outpatient setting.

Diagnosis of middle cerebral artery stenosis using the transcranial Doppler images based on convolutional neural network

BACKGROUND

The purpose of this study was to explore the diagnostic value of convolutional neural networks (CNNs) in middle cerebral artery (MCA) stenosis by analyzing the transcranial Doppler (TCD) images.

METHODS

Overall 278 patients who underwent cerebral vascular TCD and cerebral angiography were enrolled and classified into stenosis and non-stenosis groups based on cerebral angiography findings. Manual measurements were performed on TCD images. The patients were divided into a training set and a test set, and the CNNs architecture was used to classify TCD images. The diagnostic accuracies of manual measurements, CNNs, and TCD parameters for MCA stenosis were calculated and compared.

RESULTS

Overall, 203 patients without stenosis and 75 patients with stenosis were evaluated. The sensitivity, specificity, and area under the curve (AUC) for manual measurements of MCA stenosis were 0.80, 0.83, and 0.81, respectively. After 24 iterations of the running model in the training set, the sensitivity, specificity, and AUC of the CNNs in the test set were 0.84, 0.86, and 0.80, respectively. The diagnostic value of CNNs differed minimally from that of manual measurements. Two parameters of TCD, peak systolic velocity and mean flow velocity, were higher in patients with stenosis than in those without stenosis; however, their diagnostic values were significantly lower than those of CNNs (P < 0.05).

CONCLUSIONS

The diagnostic value of CNNs for MCA stenosis based on TCD images paralleled that of manual measurements. CNNs could be used as an auxiliary diagnostic tool to improve the diagnosis of MCA stenosis.