Application of transcranial Doppler in cerebrovascular diseases

Introduction

Transcranial Doppler (TCD), a diagnostic method first proposed by Aaslid et al. (1982), can non-invasively and inexpensively examine the characteristics of blood velocity in the cerebral basilar artery and cerebrovascular hemodynamics. Currently, TCD is increasingly used in the evaluation of cerebrovascular disease (CVD) because it allows continuous measurements, real-time responses, and bedside operation (Lau et al., 2020). TCD is a non-invasive, portable, and radiation-free way to assess cerebral circulation as well as the diagnosis and follow-up of intracranial mass occupying lesions (Blanco and Abdo-Cuza, 2018). CVD mainly refers to abnormal function of the central nervous system induced by stenosis, blockage, or rupture and bleeding of intracranial blood vessels due to various causes. Currently, the incidence of CVD is increasing worldwide (Wang, 2011). A timely and effective response to the changes in cerebral blood velocity (CBV) is important for early diagnosis, formulation of treatment plans, and avoidance of adverse events in CVD patients. At present, digital subtraction angiography (DSA) serves as the gold standard for diagnosing CVD due to its ability to obtain clear vascular images through the process of subtraction, enhancement, and re-imaging of X-ray images. However, the application of DSA is limited in some CVDs because DSA is an invasive test (D’Andrea et al., 2016). Magnetic resonance imaging (MRI) can display intracranial tissue clearly but cannot provide hemodynamic data (Zhou et al., 2021). Therefore, TCD has become an important imaging modality for evaluating CVD.

Basic principles and development of transcranial Doppler

The development of TCD is based on the Doppler effect. Specifically, low-frequency ultrasound waves emitted by a Doppler probe were transmitted through the skull and reflected by red blood cells that moved within the blood vessels. The frequency difference between the transmitted and reflected waves, known as the “Doppler shift,” is proportional to the moving speed of red blood cells in blood vessels (Robba et al., 2019). Because CBV in the vasculature is laminar, different Doppler frequency shifts can be displayed and form a spectrum of the velocity distribution of individual red blood cells on the TCD monitor. The formula describing the relationship between CBV and Doppler shift frequency was shown as follows:

$\text{CBV}\left(\text{cm}/\text{s}\right)=(\mathrm{Doppler}\mathrm{shift}\times \mathrm{wave}\mathrm{propagation}\mathrm{speed}\mathrm{in}\mathrm{the}\mathrm{medium})/(2\times \mathrm{emission}\mathrm{frequency}\times \text{cos}\mathrm{\Theta }).$

The propagation speed of the wave in the medium is constant. Theta (Θ) is the angle of the emitted wave relative to the direction of blood velocity. If the angle is 0° or 180°, the cosΘ is 1, indicating extremely accurate measurement. Therefore, the angle needs to keep a minimum value during the process of measurement to reduce errors (Purkayastha and Sorond, 2012).

In intracranial Doppler studies, the high-frequency ultrasound cannot effectively penetrate the skull due to weak penetration. Hence, low-frequency ultrasound (2.0–3.5 MHz) is commonly applied in TCD examinations. Moreover, the transmission of sound waves needs to be selected to penetrate the thinner areas of the skull (acoustic windows) in order to cause resonance in the cerebral arteries. There are four major acoustic windows, containing the temporal lobe window, the submandibular window, the orbital hilum, and the suboccipital window (D’Andrea et al., 2016; Couture et al., 2017).

Based on the above principles, the first TCD was established by Aaslid et al. (1982) using low-frequency ultrasound and an appropriate acoustic window, which was a significant breakthrough in imaging technique. However, TCD examinations are dependent on the expertise and experience of operators due to the absence of guidance with two-dimensional imaging, which leads to blindness, randomness, and poor repeatability of results (Hakimi et al., 2020). Therefore, transcranial color Doppler ultrasonography (TCCD) has been developed. TCCD can identify the artery at an anatomical location through combination with the cross-section of the resonance region. In addition, by correcting the angle of the emitted wave and the direction of blood velocity, measurement errors of TCCD can be minimized (Swiat et al., 2009). In summary, TCCD promotes the widespread use of TCD.

Clinical application of transcranial Doppler

Evaluation of cerebral artery stenosis/occlusive disease

Intracranial artery stenosis/occlusion mainly caused by intracranial atherosclerosis is an important factor causing ischemic brain disease and an independent factor inducing stroke recurrence (Holmstedt et al., 2013). Currently, TCCD, as the most widely applied method to detect cerebral artery, can examine the degree of stenosis/occlusion of the proximal middle cerebral artery (MCA), anterior cerebral artery, posterior cerebral artery, basilar artery, and bilateral vertebral arteries (VA) by non-invasive, continuous monitoring of the CBV (Finnsdottir et al., 2020; Spence, 2020; Adıyaman et al., 2021). Additionally, compared with the anterior circulation, there is greater tortuosity and variability in the posterior circulation; predictably, the sensitivity and specificity of TCCD are higher in the anterior circulation (Jaiswal et al., 2019). A single-center retrospective study analyzed the stenosis of 720 cerebral arteries from 80 patients by TCCD and magnetic resonance angiography (MRA) (Mowla et al., 2020). The results exhibited higher specificity and accuracy of TCCD than cranial MRA, confirming the suitability of TCCD for the screening of intracranial stenosis.

Evaluation of compensatory opening of cerebral collateral circulation

Normally, the collateral circulation is in a low-flow state. When there is a pressure difference between two arteries, collateral arteries are recruited to divert blood around obstructions. This recruitment of collateral vessels indicates the presence of diseased blood vessels and the possibility of ischemic stroke (Luo et al., 2017; Saqqur et al., 2018). Evidence has revealed that the collateral grades significantly correlate with infarct size and prognosis in patients with ischemic stroke (Seyman et al., 2016).

The anterior and posterior communicating arteries, as the main pathways of intracranial collateral circulation, can supply continuous perfusion of blood to the brain in the case of cerebral arterial stenosis or occlusion (Guan et al., 2013). Despite acting as the gold standard to evaluate the lesions of collateral circulation, the application of DSA is limited by its adverse effects (cerebral arterial spasm after angiography) and invasive disadvantage. Therefore, non-invasive TCD with a high degree of repeatability is applied in the indirect assessment of collateral circulation. TCD allows for real-time monitoring of the known direction and CBV in intracranial collateral circulation, as well as identification of the direction of these collaterals and the donor and recipient arterial systems (Wei et al., 2019). The Chinese consensus group on collateral circulation for ischemic stroke (Liu et al., 2014) noted that cerebral collateral circulation may increase the blood perfusion at the infarcted site, enhance ischemic tolerance, and improve drug delivery, thereby enhancing therapeutic effects. Hence, continuously monitoring the cerebral collateral circulation by TCD is of great significance to determine the treatment plan and predict the cerebral infarction volume and prognosis of patients with ischemic stroke.

Guidance on thrombolysis

As for the thrombolytic therapy of patients with acute stroke, TCCD is primarily used to evaluate the degree of cerebral artery occlusion before or during the treatment of intravenous thrombolysis (Mazya et al., 2018). Studies have stated that continuous monitoring of TCCD combined with anticoagulant drugs can greatly increase the success rate of thrombolysis but not increase the incidence of complications such as cerebral hemorrhage (Kramer et al., 2011). A study (Brunser et al., 2016) showed that TCCD examination in the first 4.5 h acute ischemic stroke allowed the treatment plan adjustment by providing more information on CBV, thereby changing the results for some patients.

Monitoring of subarachnoid hemorrhage and cerebral vasospasm

Cerebral vasospasm (VSP) is a common complication in patients with aneurysmal subarachnoid hemorrhage (SAH), and more than half of these patients suffer neurocognitive decline. There is a direct correlation between the severity of VSP after SAH and the blood velocity in cerebral arteries. TCD contributes to monitoring the angiography of VSP after SAH to guide the timing of diagnostic and therapeutic angiographic interventions; specifically, the CBV in the MCA and VA was measured to obtain a more accurate detection result of VSP (Wang et al., 2018; Santos-Teles et al., 2019; Roa et al., 2020).

In a follow-up study of 47 patients with SAH (Djelilovic-Vranic et al., 2017), the mean CBV was 130 cm/s in the MCA; the sensitivity and specificity of TCD for the detecting of VSP were 73 and 100%, respectively. Furthermore, under the conditions of aneurysm, hypertension, smoking, etc., about a quarter of patients with SAH showed a slight increase of CBV in the first few days by TCD monitoring; at the second week, all patients presented a significant increase in CBV; until the third week, there were about 1/4 of the patients with a slight increase in CBV. The above findings indicate that an ischemic condition may be present in the brain. TCD is the preferred method for managing VSP after SAH because it allows a long-term continuous monitoring and can prevent delayed cerebral ischemia.

Monitoring of microemboli

Microemboli (MES), primarily composed of gas and debris generated during extracorporeal circulation and surgery, are generally less than 500 μm in diameter. Previously, MES could not be detected. Now, TCD provides real-time monitoring of MES in cerebral circulation based on the backscatter of ultrasound waves from emboli. Specifically, the backscatter of ultrasound from gaseous emboli is higher than that from the solid emboli and red blood cells (Wojczal et al., 2002). Studies have demonstrated that patients with MES are prone to re-occurrence of cerebral ischemia (HR: 4.90, 95% CI 2.16–11.09, P < 0.001) and a more severe functional impairment after thrombosis (OR: 3.31, 95% CI 1.22–8.99, P = 0.019) (Das et al., 2020). Sheriff et al. (2020) utilized TCD to monitor microembolic signals in the patients after successful thrombectomy and the patients with anterior circulation occlusion. In brief, MES signals were detected in 43 of 111 patients, with a median rate of 4 times/h; on 24-h computed tomography, similar infarct volume [adjusted β = 11.2 (95% CI: −46.6 to 22.9), P = 0.51] was observed in patients with or without MES; besides, MES also predicted new embolic events [Cox hazard ratio 6.78 (CI 95% 1.63–27.8), P = 0.01]. The above outcomes verified that TCD had a good predictive value for short-term stroke and transient cerebral ischemia by monitoring for MES signals in the patients with anterior circulation occlusion treated with endovascular therapy and anterior circulation vascular occlusion.

Carotid endarterectomy and carotid artery stenting monitoring

Carotid endarterectomy (CEA) and carotid artery stenting (CAS) are important procedures to reduce carotid artery stenosis, improve blood velocity, and prevent ischemic stroke. However, intraoperative cerebral ischemia and postoperative hyperperfusion-induced cerebral hemorrhage bring a high mortality to patients receiving CEA or CAS treatment (Udesh et al., 2017; Moniche et al., 2020). Therefore, it is necessary to provide a real-time monitoring for the CBV during the operation. By virtue of TCD, clinicians can take appropriate measures to restore intracranial blood velocity according to the changes of CBV, thereby avoiding intraoperative cerebral ischemia and postoperative cerebral hemorrhage. In a retrospective study (Spence, 2017), 24 patients with cerebrovascular complications were screened using TCD to monitor various stages of CEA in 500 patients with CEA. Clinicians took the corresponding measures in light of TCD signals, and patients with permanent postoperative defects decreased from 7% of the first 100 cases to 2% of the last 400 cases (P < 0.01). The study of CAS (Garami et al., 2009) also stated that intraoperative cerebrovascular complications and postoperative neurological damage could be effectively reduced after the application of TCD in the submandibular window and the transtemporal window to monitor each stage of CAS in real time. The use of TCD in patients undergoing CEA contributes to the early detection of intraoperative and postoperative cerebral hyperperfusion, which is the key to reducing postoperative cerebral hemorrhage (Tong et al., 2014). In a nutshell, the surgical outcome and prognosis could be improved by the intraoperative and postoperative monitoring with TCD in patients undergoing CEA and CAS.

Prediction of sickle cell disease

As a genetic disorder, sickle cell disease (SCD) is characterized by chronic hemolysis-caused chronic anemia. Inflammation and intracranial arterial stenosis can be induced by the interaction of sickled red blood cells with endothelial cells, which is highly associated with stroke in children. By the way, the transfusions of blood transfusions can reduce the probability of stroke. TCD has been confirmed to accurately predict the risk of stroke in the children with SCD. Therefore, TCD can be used to continuously monitor the children with SCD and allows for earlier recognition and preventive treatment of SCD (Crow, 2020; DeBaun et al., 2020). In the previous study (Kirkham and Lagunju, 2021), TCD screening showed that the incidence of stroke was reduced by a factor of 10 in children (with an average maximum velocity >200 cm/s) receiving prophylactic chronic blood transfusion. Similar findings were found in another stroke prevention trial (Fullerton et al., 2004). Briefly speaking, TCD was used for long-term monitoring of children (with SCD but without a history of stroke) who had a threshold of 200 cm/s; prophylactic blood transfusion was given based on the average flow velocity observed during monitoring; after that, the risk of stroke was reduced by 92% in children.

Weaknesses of transcranial Doppler

Transcranial Doppler is highly dependent on the operator’s experience and affected by various pathological and physiological parameters, so the technicians are required to have the detailed three-dimensional knowledge of cerebral vascular anatomy. Additionally, the results of TCD are affected by a poor acoustic window due to individual differences, including the skull thickness around the acoustic window or other reasons causing attenuation of ultrasound energy.

Various physiological parameters (age, gender, blood viscosity, and blood pressure) also affect the measurement of CBV using TCD. It is reported that CBV was decreased at a rate of about 0.3–0.5% per year with the growth of age. Moreover, age is regarded as one of the most influential factors in the blood velocity of MCA. Generally, the CBV in young women is higher than that in young men (Lefferts et al., 2020; Alwatban et al., 2021). Besides, hematocrit and viscosity are negatively correlated with CBV, while blood pressure is positively associated with CBV (Santos-Galduroz et al., 2012; Willie et al., 2014). Furthermore, factors such as mental state and temperature have also been reported to affect CBV. Therefore, the evaluation of CVD based on CBV still needs additional data support.

Future outlook

Cerebral autoregulation

Cerebral autoregulation is an intrinsic property of blood vessels and maintains a relatively constant CBV by rapidly adjusting cerebrovascular resistance and compensating for fluctuations in cerebral perfusion pressure (Tan and Taylor, 2014). Abnormal cerebral autoregulation occurs in many diseases, such as stroke, SAH, and eclampsia (Castro et al., 2018; Kamerić et al., 2021). Currently, studies of CBV regulation rely on steady-state blood pressure. This method is time-consuming and requires invasive procedures, such as the Kety-Schmidt technique using Xenon Xe 133 as a tracer. Dynamic vascular changes cannot be identified with the technique relying on steady-state blood pressure due to a lack of temporal resolution. As a powerful and non-invasive tool with a high temporal resolution, TCD ultrasound is useful for assessing dynamic changes of CBV under various conditions, including changes in arterial pressure. TCD has become the most commonly used tool in the study of CBV regulation in humans. In clinical practice, the change of CBV was measured by TCD after the alteration of blood pressure to evaluate cerebral autoregulation. Rynkowski et al. (2019) evaluated the cerebral autoregulation in SAH patients by TCD to predict postoperative functional recovery and prognosis. Shortly speaking, the blood pressure was changed by temporarily compressing the common carotid artery, and the change of CBV during this period was measured by TCD; cerebral autoregulation was considered to be preserved when an increase ≥9% of baseline systolic velocity was present. The results showed that the injury of cerebral autoregulation was associated with poor prognosis of patients with SAH. There are many ways to change the blood pressure of a patient in clinical practice, such as changing posture, drug intervention, and Valsalva maneuver (Mankovsky et al., 2003; Vagli et al., 2020). Although TCD cannot directly measure the self-regulation of brain parenchyma, the change of CBV in main arteries is closely related to cerebral perfusion. What is more, TCD also provides a simple method for the clinical evaluation of cerebral autoregulation.

Default mode network

Default mode network (DMN) is a hot spot in the research on resting-state brain functional networks; despite no studies on this subject previously, a large amount of data have been accumulated. In 1990, Raichle used fMRI to track the changes in blood oxygen in the human brain during non-directed mental activity. In his finding, when the human brain was awake and in a resting state, strong signals as well as strong and regular activities were presented in certain areas of the brain. According to this finding, Raichle and Snyder (2007) proposed the hypothesis of resting-state activity.

Buckner (2013) defined the DMN of the brain in a meta-analysis of brain imaging. In their meta-analysis, the DMN was an anatomically defined brain system. Furthermore, functional anatomy suggested that the medial temporal lobe system provided the information from previous experiences in the form of memory and association, and the medial prefrontal lobe system contributed to the construction of self-relevant psychology. Also, the importance of DMN in the understanding of mental disorders was discussed (autism, schizophrenia, Alzheimer’s disease, etc.). Alterations in DMN have been reported in patients with Alzheimer’s disease (Li et al., 2012), schizophrenia (Orliac et al., 2013), and brain injury (Abbas et al., 2015) even before the onset of clinical symptoms. In fact, patients with normal TCD and MRI/MRA still have cognitive deficits dominated by attention, memory, and executive functions that do not adequately explain poor cognitive performance (Bernaudin et al., 2000; Brousse et al., 2015). In a study of SCD (Colombatti et al., 2016), the DMN was assessed by TCD, MRI, MRA, etc. The outcomes revealed that a selective disruption of connections between related brain regions in children with SCD may lead to cognitive decline and altered functional brain dynamics. Therefore, the combination of functional MRI, TCD, and other brain imaging techniques in the study of brain anatomy and functional alterations in DMN should help to evaluate the cognitive dysfunction of patients.

Conclusion

Transcranial Doppler is an inexpensive, simple, and non-invasive imaging method that is widely used in clinical practice. In brief, TCD can aid in the clinical diagnosis, intraoperative monitoring and management, and prognosis evaluation of CVD by effectively reflecting cerebral hemodynamic characteristics. Besides, TCD plays a vital role in the diagnosis of ischemic stroke, VSP, and cerebral MES, the intraoperative management of CEA and CAS, the evaluation of collateral compensation, and the monitoring of children with SCD and other CVDs. Notably, TCD also plays an indispensable role in the research of cerebrovascular physiology including cerebral autoregulation.

Author contributions

YW and YY designed the study and wrote the manuscript. XT and SL collected and analyzed the data. All authors contributed to the article and approved the submitted version.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

Aaslid, R., Markwalder, T. M., and Nornes, H. (1982). Noninvasive transcranial doppler ultrasound recording of flow velocity in basal cerebral arteries. J. Neurosurg. 57, 769–774. doi: 10.3171/jns.1982.57.6.0769

PubMed Abstract | CrossRef Full Text | Google Scholar

Abbas, K., Shenk, T. E., Poole, V. N., Breedlove, E. L., Leverenz, L. J., Nauman, E. A., et al. (2015). Alteration of default mode network in high school football athletes due to repetitive subconcussive mild traumatic brain injury: A resting-state functional magnetic resonance imaging study. Brain Connect. 5, 91–101. doi: 10.1089/brain.2014.0279

PubMed Abstract | CrossRef Full Text | Google Scholar

Adıyaman, D., Atakul, B. K., Kuyucu, M., Gölbaşğ, H., and Ekin, A. (2021). Difference between near-field and far-field of middle cerebral artery doppler pulsatility index and peak systolic velocity: A prospective study. Clin. Exp. Obstet. Gyn. 48, 66–72. doi: 10.31083/j.ceog.2021.01.2228

PubMed Abstract | CrossRef Full Text | Google Scholar

Alwatban, M. R., Aaron, S. E., Kaufman, C. S., Barnes, J. N., Brassard, P., Ward, J. L., et al. (2021). Effects of age and sex on middle cerebral artery blood velocity and flow pulsatility index across the adult lifespan. J. Appl. Physiol. 130, 1675–1683. doi: 10.1152/japplphysiol.00926.2020

PubMed Abstract | CrossRef Full Text | Google Scholar

Bernaudin, F., Verlhac, S., Fréard, F., Roudot-Thoraval, F., Benkerrou, M., Thuret, I., et al. (2000). Multicenter prospective study of children with sickle cell disease: Radiographic and psychometric correlation. J. Child Neurol. 15, 333–343. doi: 10.1177/08830738000150051

CrossRef Full Text | Google Scholar

Blanco, P., and Abdo-Cuza, A. (2018). Transcranial doppler ultrasound in neurocritical care. J. Ultrasound 21, 1–16. doi: 10.1007/s40477-018-0282-9

PubMed Abstract | CrossRef Full Text | Google Scholar

Brousse, V., Kossorotoff, M., and de Montalembert, M. (2015). How i manage cerebral vasculopathy in children with sickle cell disease. Br. J. Haematol. 170, 615–625. doi: 10.1111/bjh.13477

PubMed Abstract | CrossRef Full Text | Google Scholar

Brunser, A. M., Mansilla, E., Hoppe, A., Olavarria, V., Sujima, E., and Lavados, P. M. (2016). The role of TCD in the evaluation of acute stroke. J. Neuroimaging 26, 420–425. doi: 10.1111/jon.12334

PubMed Abstract | CrossRef Full Text | Google Scholar

Buckner, R. L. (2013). The brain’s default network: Origins and implications for the study of psychosis. Dialogues Clin. Neurosci. 15, 351–358. doi: 10.31887/DCNS.2013.15.3/rbuckner

PubMed Abstract | CrossRef Full Text | Google Scholar

Castro, P., Azevedo, E., and Sorond, F. (2018). Cerebral autoregulation in stroke. Curr. Atheroscler. Rep. 20:37. doi: 10.1007/s11883-018-0739-5

PubMed Abstract | CrossRef Full Text | Google Scholar

Colombatti, R., Lucchetta, M., Montanaro, M., Rampazzo, P., Ermani, M., Talenti, G., et al. (2016). Cognition and the default mode network in children with sickle cell disease: A resting state functional MRI study. PLoS One 11:e0157090. doi: 10.1371/journal.pone.0157090

PubMed Abstract | CrossRef Full Text | Google Scholar

Couture, E. J., Desjardins, G., and Denault, A. Y. (2017). Transcranial Doppler monitoring guided by cranial two-dimensional ultrasonography. Can. J. Anaesth. 64, 885–887. doi: 10.1007/s12630-017-0898-9

PubMed Abstract | CrossRef Full Text | Google Scholar

Crow, A. (2020). Transcranial doppler in children with sickle cell disease: Five years of screening experience. Australas. J. Ultrasound Med. 23, 39–46. doi: 10.1002/ajum.12192

PubMed Abstract | CrossRef Full Text | Google Scholar

D’Andrea, A., Conte, M., Cavallaro, M., Scarafile, R., Riegler, L., Cocchia, R., et al. (2016). Transcranial doppler ultrasonography: From methodology to major clinical applications. World J. Cardiol. 8, 383–400. doi: 10.4330/wjc.v8.i7.383

PubMed Abstract | CrossRef Full Text | Google Scholar

Das, A. S., Regenhardt, R. W., LaRose, S., Monk, A. D., Castro, P. M., Sheriff, F. G., et al. (2020). Microembolic signals detected by transcranial doppler predict future stroke and poor outcomes. J. Neuroimaging 30, 882–889. doi: 10.1111/jon.12749

PubMed Abstract | CrossRef Full Text | Google Scholar

DeBaun, M. R., Jordan, L. C., King, A. A., Schatz, J., Vichinsky, E., Fox, C. K., et al. (2020). American Society of hematology 2020 guidelines for sickle cell disease: Prevention, diagnosis, and treatment of cerebrovascular disease in children and adults. Blood Adv. 4, 1554–1588. doi: 10.1182/bloodadvances.2019001142

PubMed Abstract | CrossRef Full Text | Google Scholar

Djelilovic-Vranic, J., Basic-Kes, V., Tiric-Campara, M., Djozic, E., and Kulenovic, J. (2017). Follow-up of vasospasm by transcranial doppler sonography (TCD) in subarachnoid hemorrhage (SAH). Acta Inform. Med. 25, 14–18. doi: 10.5455/aim.2017.25.14-18

PubMed Abstract | CrossRef Full Text | Google Scholar

Finnsdottir, H., Szegedi, I., Olah, L., and Csiba, L. (2020). The applications of transcranial doppler in ischemic stroke. Ideggyogy. Sz. 73, 367–378. doi: 10.18071/isz.73.0367

PubMed Abstract | CrossRef Full Text | Google Scholar

Fullerton, H. J., Adams, R. J., Zhao, S., and Johnston, S. C. (2004). Declining stroke rates in Californian children with sickle cell disease. Blood 104, 336–339. doi: 10.1182/blood-2004-02-0636

PubMed Abstract | CrossRef Full Text | Google Scholar

Garami, Z. F., Bismuth, J., Charlton-Ouw, K. M., Davies, M. G., Peden, E. K., and Lumsden, A. B. (2009). Feasibility of simultaneous pre- and postfilter transcranial doppler monitoring during carotid artery stenting. J. Vasc. Surg. 49, 340–4, 345.e1–2. doi: 10.1016/j.jvs.2008.08.102

PubMed Abstract | CrossRef Full Text | Google Scholar

Guan, J., Zhang, S., Zhou, Q., Li, C., and Lu, Z. (2013). Usefulness of transcranial doppler ultrasound in evaluating cervical-cranial collateral circulations. Interv. Neurol. 2, 8–18. doi: 10.1159/000354732

PubMed Abstract | CrossRef Full Text | Google Scholar

Hakimi, R., Alexandrov, A. V., and Garami, Z. (2020). Neuro-ultrasonography. Neurol. Clin. 38, 215–229. doi: 10.1016/j.ncl.2019.09.006

PubMed Abstract | CrossRef Full Text | Google Scholar

Holmstedt, C. A., Turan, T. N., and Chimowitz, M. I. (2013). Atherosclerotic intracranial arterial stenosis: Risk factors, diagnosis, and treatment. Lancet Neurol. 12, 1106–1114. doi: 10.1016/S1474-4422(13)70195-9

CrossRef Full Text | Google Scholar

Jaiswal, S. K., Fu-Ling, Y., Gu, L., Lico, R., Changyong, F., and Paula, A. (2019). Accuracy of transcranial doppler ultrasound compared with magnetic resonance angiography in the diagnosis of intracranial artery stenosis. J. Neurosci. Rural Pract. 10, 400–404. doi: 10.1055/s-0039-1696586

PubMed Abstract | CrossRef Full Text | Google Scholar

Kamerić, L., Cerovac, A., Rizvanović, M., Kamerić, A., Jahiæ, M., and Habek, D. (2021). Frequency of cesarean section in pregnant women with risk factors for preeclampsia: Prospective cohort study. Clin. Exp. Obstet. Gyn. 48, 561–566. doi: 10.31083/j.ceog.2021.03.2369

PubMed Abstract | CrossRef Full Text | Google Scholar

Kirkham, F. J., and Lagunju, I. A. (2021). Epidemiology of stroke in sickle cell disease. J. Clin. Med. 10, 4232. doi: 10.3390/jcm10184232

PubMed Abstract | CrossRef Full Text | Google Scholar

Kramer, C., Aguilar, M. I., Hoffman-Snyder, C., Wellik, K. E., Wingerchuk, D. M., and Demaerschalk, B. M. (2011). Safety and efficacy of ultrasound-enhanced thrombolysis in the treatment of acute middle cerebral artery infarction: A critically appraised topic. Neurologist 17, 346–351. doi: 10.1097/NRL.0b013e318236e041

PubMed Abstract | CrossRef Full Text | Google Scholar

Lau, V. I., Jaidka, A., Wiskar, K., Packer, N., Tang, J. E., Koenig, S., et al. (2020). Better with ultrasound: Transcranial doppler. Chest 157, 142–150. doi: 10.1016/j.chest.2019.08.2204

PubMed Abstract | CrossRef Full Text | Google Scholar

Lefferts, W. K., DeBlois, J. P., Augustine, J. A., Keller, A. P., and Heffernan, K. S. (2020). Age, sex, and the vascular contributors to cerebral pulsatility and pulsatile damping. J. Appl. Physiol. 129, 1092–1101. doi: 10.1152/japplphysiol.00500.2020

PubMed Abstract | CrossRef Full Text | Google Scholar

Li, R., Wu, X., Fleisher, A. S., Reiman, E. M., Chen, K., and Yao, L. (2012). Attention-related networks in alzheimer’s disease: A resting functional MRI study. Hum. Brain Mapp. 33, 1076–1088. doi: 10.1002/hbm.21269

PubMed Abstract | CrossRef Full Text | Google Scholar

Liu, L. P., Xu, A. D., Wong, L. K., Wang, D. Z., Wang, Y. J., Expert consensus group of the evaluation & intervention of collateral circulation for ischemic stroke, et al. (2014). Chinese consensus statement on the evaluation and intervention of collateral circulation for ischemic stroke. CNS Neurosci. Ther. 20, 202–208. doi: 10.1111/cns.12226

PubMed Abstract | CrossRef Full Text | Google Scholar

Luo, C., Liang, F., Ren, H., Yao, X., Liu, Q., Li, M., et al. (2017). Collateral blood flow in different cerebrovascular hierarchy provides endogenous protection in cerebral ischemia. Brain Pathol. 27, 809–821. doi: 10.1111/bpa.12458

PubMed Abstract | CrossRef Full Text | Google Scholar

Mankovsky, B. N., Piolot, R., Mankovsky, O. L., and Ziegler, D. (2003). Impairment of cerebral autoregulation in diabetic patients with cardiovascular autonomic neuropathy and orthostatic hypotension. Diabet. Med. 20, 119–126. doi: 10.1046/j.1464-5491.2003.00885.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Mazya, M. V., Ahmed, N., Azevedo, E., Davalos, A., Dorado, L., Karlinski, M., et al. (2018). Impact of transcranial doppler ultrasound on logistics and outcomes in stroke thrombolysis: Results from the SITS-ISTR. Stroke 49, 1695–1700. doi: 10.1161/STROKEAHA.118.021485

PubMed Abstract | CrossRef Full Text | Google Scholar

Moniche, F., Escudero-Martinez, I., Mancha, F., Tomasello, A., Ribo, M., Delgado-Acosta, F., et al. (2020). The value of transcranial doppler sonography in hyperperfusion syndrome after carotid artery stenting: A nationwide prospective study. J. Stroke 22, 254–257. doi: 10.5853/jos.2020.00682

PubMed Abstract | CrossRef Full Text | Google Scholar

Mowla, A., Shakibajahromi, B., Kabir, R., Garami, Z., and Volpi, J. J. (2020). Transcranial doppler and magnetic resonance angiography assessment of intracranial stenosis: An analysis of screening modalities. Brain Circ. 6, 181–184. doi: 10.4103/bc.bc_21_20

CrossRef Full Text | Google Scholar

Orliac, F., Naveau, M., Joliot, M., Delcroix, N., Razafimandimby, A., Brazo, P., et al. (2013). Links among resting-state default-mode network, salience network, and symptomatology in schizophrenia. Schizophr. Res. 148, 74–80. doi: 10.1016/j.schres.2013.05.007

PubMed Abstract | CrossRef Full Text | Google Scholar

Purkayastha, S., and Sorond, F. (2012). Transcranial doppler ultrasound: Technique and application. Semin. Neurol. 32, 411–420. doi: 10.1055/s-0032-1331812

PubMed Abstract | CrossRef Full Text | Google Scholar

Raichle, M. E., and Snyder, A. Z. (2007). A default mode of brain function: A brief history of an evolving idea. Neuroimage 37, 1083–1090. doi: 10.1016/j.neuroimage.2007.02.041

PubMed Abstract | CrossRef Full Text | Google Scholar

Roa, J. A., Sarkar, D., Zanaty, M., Ishii, D., Lu, Y., Karandikar, N. J., et al. (2020). Preliminary results in the analysis of the immune response after aneurysmal subarachnoid hemorrhage. Sci. Rep. 10:11809. doi: 10.1038/s41598-020-68861-y

PubMed Abstract | CrossRef Full Text | Google Scholar

Robba, C., Goffi, A., Geeraerts, T., Cardim, D., Via, G., Czosnyka, M., et al. (2019). Brain ultrasonography: Methodology, basic and advanced principles and clinical applications. a narrative review. Intensive Care Med. 45, 913–927. doi: 10.1007/s00134-019-05610-4

PubMed Abstract | CrossRef Full Text | Google Scholar

Rynkowski, C. B., de Oliveira Manoel, A. L., Dos Reis, M. M., Puppo, C., Valdeci Worm, P., Zambonin, D., et al. (2019). Early transcranial doppler evaluation of cerebral autoregulation independently predicts functional outcome after aneurysmal subarachnoid hemorrhage. Neurocrit. Care 31, 253–262. doi: 10.1007/s12028-019-00732-5

PubMed Abstract | CrossRef Full Text | Google Scholar

Santos-Galduroz, R. F., Bueno, O. F., Yamaga, L. I., Armani, F., and Galduroz, J. C. (2012). Influence of blood viscosity to cerebral blood flow in older humans compared to young subjects. Clin. Neurophysiol. 123, 117–120. doi: 10.1016/j.clinph.2011.05.025

PubMed Abstract | CrossRef Full Text | Google Scholar

Santos-Teles, A. G., Passos, R. H., Panerai, R. B., Ramalho, C., Farias, S., Rosa, J. G., et al. (2019). Intravenous administration of milrinone, as an alternative approach to treat vasospasm in subarachnoid hemorrhage: A case report of transcranial doppler monitoring. Clin. Case Rep. 7, 648–652. doi: 10.1002/ccr3.2034

PubMed Abstract | CrossRef Full Text | Google Scholar

Saqqur, M., Khan, K., Derksen, C., Alexandrov, A., and Shuaib, A. (2018). Transcranial doppler and transcranial color duplex in defining collateral cerebral blood flow. J. Neuroimaging 28, 455–476. doi: 10.1111/jon.12535

PubMed Abstract | CrossRef Full Text | Google Scholar

Seyman, E., Shaim, H., Shenhar-Tsarfaty, S., Jonash-Kimchi, T., Bornstein, N. M., and Hallevi, H. (2016). The collateral circulation determines cortical infarct volume in anterior circulation ischemic stroke. BMC Neurol. 16:206. doi: 10.1186/s12883-016-0722-0

PubMed Abstract | CrossRef Full Text | Google Scholar

Sheriff, F., Diz-Lopes, M., Khawaja, A., Sorond, F., Tan, C. O., Azevedo, E., et al. (2020). Microemboli after successful thrombectomy do not affect outcome but predict new embolic events. Stroke 51, 154–161. doi: 10.1161/STROKEAHA.119.025856

PubMed Abstract | CrossRef Full Text | Google Scholar

Spence, J. D. (2017). Transcranial doppler monitoring for microemboli: A marker of a high-risk carotid plaque. Semin. Vasc. Surg. 30, 62–66. doi: 10.1053/j.semvascsurg.2017.04.011

PubMed Abstract | CrossRef Full Text | Google Scholar

Spence, J. D. (2020). Uses of ultrasound in stroke prevention. Cardiovasc. Diagn. Ther. 10, 955–964. doi: 10.21037/cdt.2019.12.12

PubMed Abstract | CrossRef Full Text | Google Scholar

Swiat, M., Weigele, J., Hurst, R. W., Kasner, S. E., Pawlak, M., Arkuszewski, M., et al. (2009). Middle cerebral artery vasospasm: Transcranial color-coded duplex sonography versus conventional nonimaging transcranial doppler sonography. Crit. Care Med. 37, 963–968. doi: 10.1097/CCM.0b013e31819b8165

PubMed Abstract | CrossRef Full Text | Google Scholar

Tan, C. O., and Taylor, J. A. (2014). Integrative physiological and computational approaches to understand autonomic control of cerebral autoregulation. Exp. Physiol. 99, 3–15. doi: 10.1113/expphysiol.2013.072355

PubMed Abstract | CrossRef Full Text | Google Scholar

Tong, Z. Y., Liu, Y., Tie, X. X., Zhang, J. S., Liang, C. S., and Wang, Y. J. (2014). Clinical study of cerebral hyperperfusion following carotid endarterectomy according to transcranial doppler ultrasonography monitoring. Chin. J. Contemp. Neurol. Neurosurg. 14, 25–29.

Google Scholar

Udesh, R., Natarajan, P., Thiagarajan, K., Wechsler, L. R., Crammond, D. J., Balzer, J. R., et al. (2017). Transcranial doppler monitoring in carotid endarterectomy: A systematic review and meta-analysis. J. Ultrasound Med. 36, 621–630. doi: 10.7863/ultra.16.02077

PubMed Abstract | CrossRef Full Text | Google Scholar

Vagli, C., Fisicaro, F., Vinciguerra, L., Puglisi, V., Rodolico, M. S., Giordano, A., et al. (2020). Cerebral hemodynamic changes to transcranial doppler in asymptomatic patients with Fabry’s disease. Brain Sci. 10:546. doi: 10.3390/brainsci10080546

PubMed Abstract | CrossRef Full Text | Google Scholar

Wang, W. Z. (2011). The present status and direction of prevention, treatment and research on cerebrovascular diseases in China. Chin. J. Contemp. Neurol. Neurosurg. 11, 134–137.

Google Scholar

Wang, Y., Ma, Y., Hui, P., Liu, G., Luan, Y., and Wang, C. (2018). Evaluation of application value of transcranial doppler (TCD) in the inspection of cerebral vasospasm after the treatment of intracranial aneurysm. Curr. Med. Imaging Rev. 14, 143–146. doi: 10.2174/1573405613666170504150537

PubMed Abstract | CrossRef Full Text | Google Scholar

Wei, W., Yi, X., Ruan, J., Duan, X., Luo, H., and Lv, Z. (2019). Influence of collateral circulation on cerebral blood flow and frontal lobe cognitive function in patients with severe internal carotid artery stenosis. BMC Neurol. 19:151. doi: 10.1186/s12883-019-1380-9

PubMed Abstract | CrossRef Full Text | Google Scholar

Willie, C. K., Tzeng, Y. C., Fisher, J. A., and Ainslie, P. N. (2014). Integrative regulation of human brain blood flow. J. Physiol. 592, 841–859. doi: 10.1113/jphysiol.2013.268953

PubMed Abstract | CrossRef Full Text | Google Scholar

Wojczal, J., Szczepanska-Szerej, A., Belniak, E., and Stelmasiak, Z. (2002). [Detection of cerebral microemboli by transcranial doppler. technical aspects]. Neurol. Neurochir. Pol. 36, 791–799.

PubMed Abstract | Google Scholar

Zhou, J., Shan, Y., and Hu, P. (2021). A systematic review and meta-analysis on transcranial doppler in diagnosing ischemic cerebrovascular disease. Ann. Palliat. Med. 10, 8963–8971. doi: 10.21037/apm-21-1759

PubMed Abstract | CrossRef Full Text | Google Scholar