Introduction: Transcranial Doppler (TCD) sonography is a noninvasive tool for measuring cerebrovascular hemodynamics. Studies have reported alterations in cerebrovascular hemodynamics in normal aging, mild cognitive impairment (MCI), and dementia, as well as in different etiologies of dementia. This systematic review and meta-analysis was designed to investigate the relationship between cerebral blood velocity (CBv) and pulsatility index (PI) in the middle cerebral artery (MCA) in persons with MCI and dementia. Methods: A systematic literature search was conducted in Pubmed, Embase, Cochrane Library, Epistemonikos, PsychINFO, and CINAHL. The search was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. After screening of 33,439 articles, 86 were reviewed in full-text, and 35 fulfilled the inclusion criteria. Results: CBv was significantly lower and PI significantly higher in MCA in vascular dementia (VaD) and Alzheimer’s disease (AD) compared to cognitively normal (CN) older persons. Also, CBv was lower in MCI compared to CN. There were no significant differences in CBv in MCA in AD compared with VaD, although PI was higher in VaD compared to AD. Conclusion: Alterations in cerebrovascular hemodynamics are seen in AD, VaD, and MCI. While PI was slightly higher in VaD compared to AD, the reduction in CBv appears to be equally pronounced across neurodegenerative and vascular etiologies of dementia.

Dementia affects approximately 50 million persons worldwide and is a leading cause of mortality and morbidity in older persons. Whereas dementia implies cognitive impairment that affects activities of daily living, cognitive decline without impact on activities of daily living is referred to as mild cognitive impairment (MCI) [1]. With the increasing burden of MCI and dementia, there is a growing interest in identifying clinical tools for early detection of persons at risk of dementia, to differentiate between etiological subtypes of dementia, and eventually develop effective preventive strategies and treatments [2].

The most frequent subtype of dementia is Alzheimer’s disease (AD), which causes 60–80% of cases [3]. Vascular dementia (VaD) is caused by processes that damage precerebral or cerebral arteries causing reduction in blood flow in the brain, including chronic hypoperfusion from cerebral small vessel disease as well as from strategic or multiple infarctions [4]. VaD alone or in combination with AD causes 20–30% of dementia cases. Mixed etiologies of dementia with both neurodegenerative and vascular pathology are also common in older persons [2], and vascular risk factors, including hypertension, hyperlipidemia [5], diabetes [6], obesity [7], and smoking [8], have been associated with cognitive impairment of both vascular and degenerative etiologies [9].

Impaired intracerebral blood flow has been associated with cognitive decline and incident dementia [10]. Regional cerebral blood flow can be assessed through brain imaging techniques including single-photon emission computed tomography [11] and positron emission tomography [12]. However, these techniques are expensive and involve radioactive substances and ionizing radiation. Conversely, transcranial Doppler (TCD) sonography is a noninvasive, inexpensive, and practical technique used for the recording of cerebral blood velocity (CBv) in the major cerebral arteries in the circle of Willis, most commonly, the middle cerebral artery (MCA). TCD also provides measures of downstream resistance in blood flow, i.e., resistance index and pulsatility index (PI) [13].

Several TCD studies have found decreased CBv in dementia compared to cognitively normal (CN) [14‒16], and reduced CBv has been associated with reduced hippocampal and amygdalar volumes [10]. It is not clear whether alterations in cerebral hemodynamics are caused by preclinical neurodegeneration resulting in reduced brain blood flow, or if impaired cerebral perfusion precedes and contributes to cognitive decline and incident dementia, with reduced beta-amyloid clearance due to brain hypoperfusion as a possible mechanism [17].

A meta-analysis of TCD studies from 2012 reported disturbances in intracerebral hemodynamics in dementia compared to CN [18]. Since then, several new studies, including studies of cerebral hemodynamics in MCI, have been published [19‒21].

TCD has emerged as a useful technology in the diagnosis of dementia and cognitive impairment [22], and the role of intracerebral hemodynamics in dementia requires further investigation. The present meta-analysis was performed to study the potential association between TCD measurements of intracerebral hemodynamics and MCI and dementia of vascular and neurodegenerative etiologies.

Search Strategy

After registering the predefined study review protocol in the International Prospective Register of Systematic Reviews (PROSPERO) (CRD42022346265), the following databases were searched systematically to identify studies on TCD and dementia: Medline, EMBASE, Cochrane Library, PsycINFO, CINAHL, and Epistemonikos. The search criteria included the following: (1) individuals with cognitive impairment; (2) measurement with TCD; (3) clearly defined dementia or MCI diagnosis; (4) observational studies. The search was performed in September 2022 by a trained information specialist with search terms including the following: “cognitive dysfunction,” “mild cognitive impairment,” “dementia,” “Alzheimer’s disease,” “Doppler,” “transcranial,” “ultrasound,” “tcd.” The literature search was limited to studies in English, Swedish, Norwegian, and Danish languages. For the full search strategy, see online supplementary material (for all online suppl. material, see https://doi.org/10.1159/000535422).

Selection Criteria

The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) [23] were used in the present systematic review and meta-analysis. Titles and abstracts were screened for inclusion by two investigators (D.F. and B.F.). After screening, the articles were assessed in detail considering the following prespecified selection criteria (PICOS): (1) population: persons with dementia or MCI; (2) intervention: investigation of cerebral hemodynamics using TCD; (3) comparison: cognitively healthy age-matched controls with no comorbid neurological, psychiatric, vascular, or hematological disorders; (4) outcome: the association between dementia and cerebrovascular hemodynamics, more specifically CBv and PI; and (5) study design: observational studies. Right-side TCD values in MCA were selected for analyses in studies providing both left- and right-side measures.

Data Extraction and Analyses

Data extraction was performed independently by two investigators (D.F. and B.F.) and registered in a designed table including the following study characteristics: first author and year of publication, country and research setting, study design, number of patients included and patient demographics, measurement of cerebral hemodynamics including side and location of measurements for both CBv and PI, and criteria used for ascertainment of MCI and dementia.

Statistics

Differences in cerebral hemodynamics in MCA between persons with (1) AD and CN, (2) VaD and CN, (3) AD and VaD, and (4) MCI and CN were studied. Meta-analyses were carried out with inverse variance methodology, using RevMan 5.4.1.22, and weights were assigned automatically by the program algorithm. A random-effects model was used for analyses of pooled data due to evidence of large study heterogeneity according to the standard RevMan I2 output, and 2-sided p values were used. Effect estimates were reported as mean difference (MD) with 95% confidence interval (CI). When studies presented CBv or PI with CI instead of standard deviation (SD), SD was calculated using the formula recommended in the Cochrane Handbook: SD = square root of N × (upper limit – lower limit)/3.92 [24].

Quality Assessment and Risk of Bias

The quality of included studies, including risk of bias, was assessed independently by two investigators (D.F. and B.F.), using the Center for Evidence-Based Management (CEBM) checklist designed for cross-sectional studies [25]. Although some of the included studies were longitudinal, all data used in meta-analyses were cross-sectional, i.e., performed at baseline. The overall confidence in the effect estimates across studies for each pooled outcome was determined independently by the same two reviewers according to the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) tool [26].

Disagreements between Individual Judgements

Any disagreements in the study selection process, data extraction, or quality assessment of included studies were resolved by consensus.

Literature Search

A total of 35 studies [14‒16, 19‒21, 27‒55] were included in the review and meta-analysis after full-text review of 86 articles, as shown in Figure 1. Reasons for exclusion of studies that did not fulfill the eligibility criteria are shown in online supplementary material 2.

Fig. 1.

PRISMA flowchart showing the inclusion process.

Fig. 1.

PRISMA flowchart showing the inclusion process.

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Study Characteristics

The general characteristics of the included studies are shown in Table 1 [40, 19, 51, 38, 48, 52, 20, 41, 42, 43, 14, 44, 55, 27, 34, 45, 53, 28, 46, 16, 49, 29, 30, 31, 47, 39, 32, 21, 54, 37, 33, 50, 15, 36, 35]. Studies included in the meta-analysis were published between 1989 and 2021. The most frequently used diagnostic criteria for dementia were the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association Criteria for AD, the National Institute of Neurological Disorders and Stroke and Association Internationale pour la Recherche et l’Enseignement en Neurosciences criteria for VaD and Petersen’s criteria for MCI. Mini-Mental State Examination (MMSE) scores in AD ranged from 13 [44, 51] to 25 [41], in VaD from 12 [51] to 24.6 [52], in MCI from 23.7 [21] to 29 [37], and in CN from 24.7 [35] to 29.7 [40].

Table 1.

General characteristics of the included studies

Author and year of publicationCountryStudy designSettingSample and number of subjectsDiagnostic criteria for dementiaAge, mean (SD)Sex (Female), N (%)Education, years (SD)MMSE, mean (SD) if not specified otherwise
Alwatban et al. [40] (2019) USA Cross-sectional University hospital AD, 10; CN, 9; preclinical AD, 8 NR AD, 68.1 (5.1); CN, 71.3 (3.8) 11 (57.9) AD, 16.4 (3.8); CN, 17.4 (2) AD, 21.2 (5.9); CN, 29.7 (0.7) 
Batistella et al. [19] (2020) Brazil Cross-sectional University hospital AD, 31; VaD, 12; aMCI, 18; CN, 10 AD, NIA-AA and neuronal injury biomarker evidence on magnetic resonance imaging tomography or CT; VaD, NINDS-AIREN; aMCI, NIA-AA AD, 79 (6.8); VaD, 79 (5.1); aMCI 70 (10); CN, 74 (5.3) 53 (74.6) School ≥8 years n (%): AD, 2 (6); VaD, 0; aMCI, 7 (39); CN, 6 (60) AD, 15 (6.4); VaD, 18 (5.7); aMCI, 27 (3.1); CN, 27 (1.2) 
Biedert et al. [51] (1990) Germany Cross-sectional Hospital AD, 17; VaD, 14; CN, 27 AD, NINCDS-ADRDA and DSM-III-R; VaD, DSM-III-R, and clinical and CT alterations characteristic of VaD Study population, 60–69 years 31 (53.4) NR AD, 13; VaD, 12; CN, 29 or 30 
Biedert et al. [38] (1995) Germany Cross-sectional AD, 23; VaD, 19; CN, 36 AD, NINCDS-ADRDA, and DSM III-R; VaD DSM-III-R Study population, 60–69 years 37 (47.4) NR AD, 14; VaD, 13; CN 29 or 30 
Bressi et al. [48] (1992) Italy Cross-sectional University hospital memory clinic, neurology department AD, 23; CN, 10 NINCDS-ADRDA AD, 64 (8.6); CN, 62 (7.3) AD 12 (52.2); CN NR NR AD, 20.11 (3.71); CN, NR 
Caamaño et al. [52] (1993) Spain Cross-sectional Department of Psychogeriatrics, Neurosciences research center AD, 12; VaD, 12; CN, 12 AD and VaD, NINCDS-ADRDA, and DSM-III-R AD, 63.5 (6.6); VaD, 72.8 (9.0); CN, 57.2 (7.5) 22 (68.8) NR AD, 23.0 (4.3); VaD, 24.6 (5.2) 
Cipollini et al. [20] (2019) Italy Cross-sectional University hospital AD, 35; CN, 17 NINCDS-ADRDA AD, 72.5 (5.1); CN, 70.4 (5.6) 32 (61.5) AD, 9.6 (4.2); CN, 10.2 (3.3) AD, 22.6 (4.6); CN, 29.4 (0.6) 
Claassen et al. [41] (2009) USA Cross-sectional Memory clinic AD, 9; CN, 8 NINCDS-ADRDA AD, 67.9 (5.5); CN, 64.5 (4.0) 10 (58.8) NR AD, 25 (3.2); CN, 29 (0.5) 
De Heus et al. [42] (2018) The Netherlands Cross-sectional Memory clinic AD, 53; MCI, 37; CN, 47 AD and MCI, NIA-AA AD, 73.1 (95% CI, 71.4–74.8); MCI, 69.2 (95% CI, 66.4–72.0); CN, 69.4 (95% CI, 68.3–70.5) 61 (44.5) NR AD, 20.6 (95% CI, 19.7–21.6); MCI, NR; CN, 28.6 (95% CI, 28.2–29.0) 
Diomedi et al. [43] (2021) Italy Cross-sectional University hospital, memory Clinic AD (tau+ and amyloid+), 37; CN, 17 NIA-AA AD, 71.22 (5.38); CN, 68.47 (8.07) 24 (44.4) NR AD, 23.0 (3.9); CN, NR 
Doepp et al. [14] (2006) Germany Cross-sectional Outpatient department of neurological clinic AD, 20; VaD, 20; CN 12 AD, NINCDS-ADRDA; VaD, NINDS-AIREN AD, 66 (13); VaD, 71 (11); CN, 65 (8) 29 (55.8) NR AD, 18 (7); VD, 20 (7); CN, NR 
Foerstl et al. [44] (1989) Germany Cross-sectional NR AD, 9; VaD, 9; CN, 14 AD, NINCDS-ADRDA; VaD, DSM-III-R 60–69 years 17 (53) NR AD, 13; VaD, 12; CN, 29 or 30 
Franceschi et al. [55] (1995) Italy Cross-sectional Department of Neurology AD, 17; CN, 20 NINCDS-ADRDA AD, 65.7 (6.9); CN, 63.2 (7.9) 10 (33.3) AD, 7.6 (3.6); CN, NR AD, 18.4 (4.8); CN, NR 
Gao et al. [27] (2013) China Cross-sectional University hospital AD, 26; VaD, 23 AD, NINCDS-ADRDA, VaD, NINDS-AIREN AD, 70.5 (8.3); VaD, 68.7 (8.4) 21 (42.9) AD, 10.9 (2.5); VaD. 11.5 (2.5) AD, 22.8 (4.1); VaD, 21.6 (0.7) 
Gommer et al. [34] (2012) The Netherlands Cross-sectional University hospital, Neurology outpatient clinic AD, 15; MCI, 19; CN, 20 AD, DSM-IV, and NINCDS-ADRDA; MCI, Petersen’s criteria AD, 72; MCI, 70; CN, 70 25 (46.3) AD, 53% low, 33% middle, 13% high; MCI, 37% lower, 16% middle, 47% higher; CN, 45% low, 35% middle, 20% high AD, 19.8; MCI, 27.6; CN, 29.0 
Gongora-Rivera et al. [45] (2018) Mexico Cross-sectional University hospital, Department of Neurology AD, 26; CN, 19 DSM IV and NINCDS-ADRA AD, 78 (range 67–93); CN, 78 (range 59–90) 36 (80) AD, 3 (range 0–15); CN, 6 (range 0–16) AD, 14.08 (5.80); CN, 27 (3.20) 
Kongdong et al. [53] (2011) China Cross-sectional Neurology Clinic of University Hospital AD, 30; VaD, 34; CN, 40 AD NINCDS-ADRDA; VaD NINDS-AIREN AD, 71.4 (2.3); VaD, 71.6 (2.5); CN, 71.2 (2.6) 52 (50) NR AD, 16.0 (range 10–25); VaD, 16.5 (range 10–25); CN, 28.0 (range 27–30) 
Kouzuki et al. [28] (2018) Japan Cross-sectional University hospital AD, 42; aMCI, 20; CN 18 AD, DSM-V, and NINCDS-ADRDA; aMCI, Petersen’s criteria AD, 80.5 (5.7); aMCI, 78.4 (4.0); CN, 75.6 (5.5) 52 (65) NR AD, 20.4 (3.6); aMCI, 25.5 (2.2); CN, 27.9 (2.4) 
Lee et al. [46] (2007) Korea Cross-sectional University hospital, Department of Neurology AD, 17; CN, 17 NINCDS-ADRDA AD, 67.1 (5.9); CN, 67.1 (5.9) 20 (58.8) NR AD, 22.1 (4.9); CN, 28.7 (0.6) 
Liu et al. [16] (2021) China Cohort Hospital AD, 30; VaD, 44; CN, 30 AD, DSM-V, and IWG-2; VaD, DSM-V and VasCog AD, 68.7 (8.8); VaD, 71.6 (7.9); CN, 66.2 (6.3) 58 (55.8) AD, 10.4 (4.5); VaD, 10.2 (2.6); CN, 11.3 (3.4) AD, 19.6 (2.4); VaD, 20.4 (3.2); CN, 28.2 (1.2) 
Meel-van den Abeelen et al. [49] (2014) The Netherlands Cross-sectional University hospital, Department of Geriatric Medicine AD, 12; CN, 24 NINCDS-ADRDA AD, 74 (4); CN, 76 (4) 9 (25) NR AD, 22 (5); CN, 29 (1) 
Ni et al. [29] (1994) Austria Cross-sectional University hospital AD, 21; VaD, 19; CN, 20 AD, NINCDS-ADRDA; VaD, NINDS-AIREN AD, 70.4 (7.7); VaD, 69.3 (11.8); CN, 69.7 (3.3) 42 (70) NR AD, 17.4 (7.4); VaD, 20.1 (8.8); CN, ≥27 
Ortner et al. [30] (2019) Germany Cross-sectional Outpatient unit for cognitive disorders, Department of Psychiatry AD, 12; MCI, 16; CN, 14 AD and MCI, NIA-AA AD, 71.3 (9.5); NC, 65.4 (7.9) 14 (53.8) NR MMSE Z-scores: AD, −9.9 (7.1); CN, −0.2 (1.1) 
Provinciali et al. [31] (1990) Italy Cross-sectional Regional hospital AD, 20; VaD, 20; CN, 25 AD, DSM-3; VaD, DSM-3, and modified Hachinski ischemic scale AD, 67.8 (4.7); VaD, 64.7 (7.3); CN, NR NR NR NR 
Ries et al. [47] (1993) Germany Cross-sectional University hospital AD, 24; VaD, 17; CN, 64 AD, DSM-III-R, and NINCDS-ADRDA; VaD, DSM-III-R, Hachinski score >6 AD, 65.8 (9.0); VaD, 69.1 (8.5); CN, 61 (11.1) 61 (58.1) NR AD, 18.3; VaD, 20.2; CN, NR 
Roher et al. [39] (2011) USA Cross-sectional Research Institute AD, 42; MCI, 11; CN, 50 NINDS-ADRDA; MCI, Petersen’s criteria AD, 80 (6.5); MCI, 80 (4.7); CN, 79 (6.4) 53 (51.4) Subjects had at least a 6th grade education AD, 19 (6.7); MCI, 26 (1.9); CN, 29 (1.1) 
Rundek et al. [32] (1995) Croatia and USA Cross-sectional NR AD, 45; VaD, 30 AD, DSM-IIIR, NINCDS-ADRDA; VaD, NINDS-AIREN AD, 78.3 (8.5); VaD, 71.6 (7.5) 32 (33.7) NR AD, 20.2 (6.2); VaD, 22.2 (3.4) 
Shim et al. [21] (2015) Korea Cross-sectional Neurology Department of University Hospital AD, 67; MCI, 75; CN, 52 NINDS-ADRDA; MCI, Petersen’s criteria AD, 74.6 (6.2); MCI, 69.4 (8.2); CN, 66.2 (6.5) 139 (71.6) AD, 5.0 (4.4); MCI, 7.7 (4.5); CN, 10.5 (4.0) AD, 17.2 (4.5); MCI, 23.7 (3.0); CN, 28.2 (1.5) 
Staszewski et al. [54] (2021) Poland Cross-sectional Neurology Department VaD, 20; CN, 20 NINDS-AIREN VaD, 72.2 (6.8); CN, 71.9 (3.2) 20 (50) NR NR 
Tomoto et al. [37] (2020) USA Cross-sectional University hospital, Alzheimer’s Disease center aMCI, 53; CN, 22 aMCI, Petersen’s criteria aMCI, 64.0 (5.8); CN 65.8 (7.4) 40 (53.3) aMCI, 15.9 (2.4); CN, 16.7 (2.1) aMCI, 29.0 (1.3); CN, 29.1 (0.9) 
Urbanova et al. [33] (2018) Czech Republic Cross-sectional University hospital memory clinic, Department of Neurology AD, 14; MCI, 24; CN, 24 AD, NINCDS-ADRDA and DSM-IV; MCI, Petersen’s criteria AD, 67.9 (11.1); MCI, 71.9 (7.3); CN, 67.8 (6.4) 32 (51.6) AD, 12.8 (2.8); MCI, 15.5 (3.1); CN, 16.0 (2.6) AD, 18.0 (4.6); MCI, 28.0 (1.6); CN, 29.1 (1.2) 
Van Beek et al. [50] (2012) Netherlands Cross-sectional University hospital, memory clinic AD, 21; CN, 20 NINCDS-ADRDA AD, 72.3 (5.7); CN, 74.5 (2.8) 18 (43.9) NR AD, 21.3 (4.7); CN, 29.3 (1.2) 
Vicenzini et al. [15] (2007) Italy Cross-sectional University hospital memory clinic, neurology department AD, 60; VaD, 58; CN, 62 AD, NINCDS-ADRDA; VaD, NINDS-AIREN AD, 70.7 (2.4); VaD, 68.9 (2.9); CN, 69.9 (3.1) 87 (48.3) NR AD, 19.9 (2.6); VaD, 20.1 (2.3); CN, 29.2 (0.8) 
Viola et al. [36] (2013) Italy Cross-sectional Neurology department aMCI, 21; CN, 10 aMCI, Petersen criteria aMCI, 70.2 (7.3); CN, 69.5 (6.8) 17 (54.8) NR aMCI, range 24–28; CN, range 29–30 
Zhou et al. [35] (2019) China Cross-sectional Neurology Department of University Hospital AD, 31; CN, 30 NINCDS-ADRDA AD, 69.64 (7.67); CN, 69.63 (7.29) 30 (49.2) AD, 8.65 (5.04); CN, 8.73 (5.04) AD, 15.84 (6.97); CN, 24.70 (6.03) 
Author and year of publicationCountryStudy designSettingSample and number of subjectsDiagnostic criteria for dementiaAge, mean (SD)Sex (Female), N (%)Education, years (SD)MMSE, mean (SD) if not specified otherwise
Alwatban et al. [40] (2019) USA Cross-sectional University hospital AD, 10; CN, 9; preclinical AD, 8 NR AD, 68.1 (5.1); CN, 71.3 (3.8) 11 (57.9) AD, 16.4 (3.8); CN, 17.4 (2) AD, 21.2 (5.9); CN, 29.7 (0.7) 
Batistella et al. [19] (2020) Brazil Cross-sectional University hospital AD, 31; VaD, 12; aMCI, 18; CN, 10 AD, NIA-AA and neuronal injury biomarker evidence on magnetic resonance imaging tomography or CT; VaD, NINDS-AIREN; aMCI, NIA-AA AD, 79 (6.8); VaD, 79 (5.1); aMCI 70 (10); CN, 74 (5.3) 53 (74.6) School ≥8 years n (%): AD, 2 (6); VaD, 0; aMCI, 7 (39); CN, 6 (60) AD, 15 (6.4); VaD, 18 (5.7); aMCI, 27 (3.1); CN, 27 (1.2) 
Biedert et al. [51] (1990) Germany Cross-sectional Hospital AD, 17; VaD, 14; CN, 27 AD, NINCDS-ADRDA and DSM-III-R; VaD, DSM-III-R, and clinical and CT alterations characteristic of VaD Study population, 60–69 years 31 (53.4) NR AD, 13; VaD, 12; CN, 29 or 30 
Biedert et al. [38] (1995) Germany Cross-sectional AD, 23; VaD, 19; CN, 36 AD, NINCDS-ADRDA, and DSM III-R; VaD DSM-III-R Study population, 60–69 years 37 (47.4) NR AD, 14; VaD, 13; CN 29 or 30 
Bressi et al. [48] (1992) Italy Cross-sectional University hospital memory clinic, neurology department AD, 23; CN, 10 NINCDS-ADRDA AD, 64 (8.6); CN, 62 (7.3) AD 12 (52.2); CN NR NR AD, 20.11 (3.71); CN, NR 
Caamaño et al. [52] (1993) Spain Cross-sectional Department of Psychogeriatrics, Neurosciences research center AD, 12; VaD, 12; CN, 12 AD and VaD, NINCDS-ADRDA, and DSM-III-R AD, 63.5 (6.6); VaD, 72.8 (9.0); CN, 57.2 (7.5) 22 (68.8) NR AD, 23.0 (4.3); VaD, 24.6 (5.2) 
Cipollini et al. [20] (2019) Italy Cross-sectional University hospital AD, 35; CN, 17 NINCDS-ADRDA AD, 72.5 (5.1); CN, 70.4 (5.6) 32 (61.5) AD, 9.6 (4.2); CN, 10.2 (3.3) AD, 22.6 (4.6); CN, 29.4 (0.6) 
Claassen et al. [41] (2009) USA Cross-sectional Memory clinic AD, 9; CN, 8 NINCDS-ADRDA AD, 67.9 (5.5); CN, 64.5 (4.0) 10 (58.8) NR AD, 25 (3.2); CN, 29 (0.5) 
De Heus et al. [42] (2018) The Netherlands Cross-sectional Memory clinic AD, 53; MCI, 37; CN, 47 AD and MCI, NIA-AA AD, 73.1 (95% CI, 71.4–74.8); MCI, 69.2 (95% CI, 66.4–72.0); CN, 69.4 (95% CI, 68.3–70.5) 61 (44.5) NR AD, 20.6 (95% CI, 19.7–21.6); MCI, NR; CN, 28.6 (95% CI, 28.2–29.0) 
Diomedi et al. [43] (2021) Italy Cross-sectional University hospital, memory Clinic AD (tau+ and amyloid+), 37; CN, 17 NIA-AA AD, 71.22 (5.38); CN, 68.47 (8.07) 24 (44.4) NR AD, 23.0 (3.9); CN, NR 
Doepp et al. [14] (2006) Germany Cross-sectional Outpatient department of neurological clinic AD, 20; VaD, 20; CN 12 AD, NINCDS-ADRDA; VaD, NINDS-AIREN AD, 66 (13); VaD, 71 (11); CN, 65 (8) 29 (55.8) NR AD, 18 (7); VD, 20 (7); CN, NR 
Foerstl et al. [44] (1989) Germany Cross-sectional NR AD, 9; VaD, 9; CN, 14 AD, NINCDS-ADRDA; VaD, DSM-III-R 60–69 years 17 (53) NR AD, 13; VaD, 12; CN, 29 or 30 
Franceschi et al. [55] (1995) Italy Cross-sectional Department of Neurology AD, 17; CN, 20 NINCDS-ADRDA AD, 65.7 (6.9); CN, 63.2 (7.9) 10 (33.3) AD, 7.6 (3.6); CN, NR AD, 18.4 (4.8); CN, NR 
Gao et al. [27] (2013) China Cross-sectional University hospital AD, 26; VaD, 23 AD, NINCDS-ADRDA, VaD, NINDS-AIREN AD, 70.5 (8.3); VaD, 68.7 (8.4) 21 (42.9) AD, 10.9 (2.5); VaD. 11.5 (2.5) AD, 22.8 (4.1); VaD, 21.6 (0.7) 
Gommer et al. [34] (2012) The Netherlands Cross-sectional University hospital, Neurology outpatient clinic AD, 15; MCI, 19; CN, 20 AD, DSM-IV, and NINCDS-ADRDA; MCI, Petersen’s criteria AD, 72; MCI, 70; CN, 70 25 (46.3) AD, 53% low, 33% middle, 13% high; MCI, 37% lower, 16% middle, 47% higher; CN, 45% low, 35% middle, 20% high AD, 19.8; MCI, 27.6; CN, 29.0 
Gongora-Rivera et al. [45] (2018) Mexico Cross-sectional University hospital, Department of Neurology AD, 26; CN, 19 DSM IV and NINCDS-ADRA AD, 78 (range 67–93); CN, 78 (range 59–90) 36 (80) AD, 3 (range 0–15); CN, 6 (range 0–16) AD, 14.08 (5.80); CN, 27 (3.20) 
Kongdong et al. [53] (2011) China Cross-sectional Neurology Clinic of University Hospital AD, 30; VaD, 34; CN, 40 AD NINCDS-ADRDA; VaD NINDS-AIREN AD, 71.4 (2.3); VaD, 71.6 (2.5); CN, 71.2 (2.6) 52 (50) NR AD, 16.0 (range 10–25); VaD, 16.5 (range 10–25); CN, 28.0 (range 27–30) 
Kouzuki et al. [28] (2018) Japan Cross-sectional University hospital AD, 42; aMCI, 20; CN 18 AD, DSM-V, and NINCDS-ADRDA; aMCI, Petersen’s criteria AD, 80.5 (5.7); aMCI, 78.4 (4.0); CN, 75.6 (5.5) 52 (65) NR AD, 20.4 (3.6); aMCI, 25.5 (2.2); CN, 27.9 (2.4) 
Lee et al. [46] (2007) Korea Cross-sectional University hospital, Department of Neurology AD, 17; CN, 17 NINCDS-ADRDA AD, 67.1 (5.9); CN, 67.1 (5.9) 20 (58.8) NR AD, 22.1 (4.9); CN, 28.7 (0.6) 
Liu et al. [16] (2021) China Cohort Hospital AD, 30; VaD, 44; CN, 30 AD, DSM-V, and IWG-2; VaD, DSM-V and VasCog AD, 68.7 (8.8); VaD, 71.6 (7.9); CN, 66.2 (6.3) 58 (55.8) AD, 10.4 (4.5); VaD, 10.2 (2.6); CN, 11.3 (3.4) AD, 19.6 (2.4); VaD, 20.4 (3.2); CN, 28.2 (1.2) 
Meel-van den Abeelen et al. [49] (2014) The Netherlands Cross-sectional University hospital, Department of Geriatric Medicine AD, 12; CN, 24 NINCDS-ADRDA AD, 74 (4); CN, 76 (4) 9 (25) NR AD, 22 (5); CN, 29 (1) 
Ni et al. [29] (1994) Austria Cross-sectional University hospital AD, 21; VaD, 19; CN, 20 AD, NINCDS-ADRDA; VaD, NINDS-AIREN AD, 70.4 (7.7); VaD, 69.3 (11.8); CN, 69.7 (3.3) 42 (70) NR AD, 17.4 (7.4); VaD, 20.1 (8.8); CN, ≥27 
Ortner et al. [30] (2019) Germany Cross-sectional Outpatient unit for cognitive disorders, Department of Psychiatry AD, 12; MCI, 16; CN, 14 AD and MCI, NIA-AA AD, 71.3 (9.5); NC, 65.4 (7.9) 14 (53.8) NR MMSE Z-scores: AD, −9.9 (7.1); CN, −0.2 (1.1) 
Provinciali et al. [31] (1990) Italy Cross-sectional Regional hospital AD, 20; VaD, 20; CN, 25 AD, DSM-3; VaD, DSM-3, and modified Hachinski ischemic scale AD, 67.8 (4.7); VaD, 64.7 (7.3); CN, NR NR NR NR 
Ries et al. [47] (1993) Germany Cross-sectional University hospital AD, 24; VaD, 17; CN, 64 AD, DSM-III-R, and NINCDS-ADRDA; VaD, DSM-III-R, Hachinski score >6 AD, 65.8 (9.0); VaD, 69.1 (8.5); CN, 61 (11.1) 61 (58.1) NR AD, 18.3; VaD, 20.2; CN, NR 
Roher et al. [39] (2011) USA Cross-sectional Research Institute AD, 42; MCI, 11; CN, 50 NINDS-ADRDA; MCI, Petersen’s criteria AD, 80 (6.5); MCI, 80 (4.7); CN, 79 (6.4) 53 (51.4) Subjects had at least a 6th grade education AD, 19 (6.7); MCI, 26 (1.9); CN, 29 (1.1) 
Rundek et al. [32] (1995) Croatia and USA Cross-sectional NR AD, 45; VaD, 30 AD, DSM-IIIR, NINCDS-ADRDA; VaD, NINDS-AIREN AD, 78.3 (8.5); VaD, 71.6 (7.5) 32 (33.7) NR AD, 20.2 (6.2); VaD, 22.2 (3.4) 
Shim et al. [21] (2015) Korea Cross-sectional Neurology Department of University Hospital AD, 67; MCI, 75; CN, 52 NINDS-ADRDA; MCI, Petersen’s criteria AD, 74.6 (6.2); MCI, 69.4 (8.2); CN, 66.2 (6.5) 139 (71.6) AD, 5.0 (4.4); MCI, 7.7 (4.5); CN, 10.5 (4.0) AD, 17.2 (4.5); MCI, 23.7 (3.0); CN, 28.2 (1.5) 
Staszewski et al. [54] (2021) Poland Cross-sectional Neurology Department VaD, 20; CN, 20 NINDS-AIREN VaD, 72.2 (6.8); CN, 71.9 (3.2) 20 (50) NR NR 
Tomoto et al. [37] (2020) USA Cross-sectional University hospital, Alzheimer’s Disease center aMCI, 53; CN, 22 aMCI, Petersen’s criteria aMCI, 64.0 (5.8); CN 65.8 (7.4) 40 (53.3) aMCI, 15.9 (2.4); CN, 16.7 (2.1) aMCI, 29.0 (1.3); CN, 29.1 (0.9) 
Urbanova et al. [33] (2018) Czech Republic Cross-sectional University hospital memory clinic, Department of Neurology AD, 14; MCI, 24; CN, 24 AD, NINCDS-ADRDA and DSM-IV; MCI, Petersen’s criteria AD, 67.9 (11.1); MCI, 71.9 (7.3); CN, 67.8 (6.4) 32 (51.6) AD, 12.8 (2.8); MCI, 15.5 (3.1); CN, 16.0 (2.6) AD, 18.0 (4.6); MCI, 28.0 (1.6); CN, 29.1 (1.2) 
Van Beek et al. [50] (2012) Netherlands Cross-sectional University hospital, memory clinic AD, 21; CN, 20 NINCDS-ADRDA AD, 72.3 (5.7); CN, 74.5 (2.8) 18 (43.9) NR AD, 21.3 (4.7); CN, 29.3 (1.2) 
Vicenzini et al. [15] (2007) Italy Cross-sectional University hospital memory clinic, neurology department AD, 60; VaD, 58; CN, 62 AD, NINCDS-ADRDA; VaD, NINDS-AIREN AD, 70.7 (2.4); VaD, 68.9 (2.9); CN, 69.9 (3.1) 87 (48.3) NR AD, 19.9 (2.6); VaD, 20.1 (2.3); CN, 29.2 (0.8) 
Viola et al. [36] (2013) Italy Cross-sectional Neurology department aMCI, 21; CN, 10 aMCI, Petersen criteria aMCI, 70.2 (7.3); CN, 69.5 (6.8) 17 (54.8) NR aMCI, range 24–28; CN, range 29–30 
Zhou et al. [35] (2019) China Cross-sectional Neurology Department of University Hospital AD, 31; CN, 30 NINCDS-ADRDA AD, 69.64 (7.67); CN, 69.63 (7.29) 30 (49.2) AD, 8.65 (5.04); CN, 8.73 (5.04) AD, 15.84 (6.97); CN, 24.70 (6.03) 

AD, Alzheimer’s disease; aMCI, amnestic mild cognitive impairment; CDR, Clinical Dementia Rating Scale; CN, cognitively normal; CT, computed tomography; DSM-IV, Diagnostic and Statistical Manual of Mental Disorders 4th edition; DSM-III, Diagnostic and Statistical Manual of Mental Disorders 3rd edition; DSM-III-TR, Diagnostic and Statistical Manual of Mental Disorders 3rd edition, text revised; MCI, mild cognitive impairment; MMSE, Mini-Mental State Examination; NIA-AA, National Institute on Aging and Alzheimer’s Association; NINCDS-ADRDA, National Institute of Neurological and Communicative Diseases and Stroke/Alzheimer’s Disease and Related Disorders Association; NINDS-AIREN, National Institute of Neurological Disorders and Stroke and Association Internationale pour la Recherche et l’Enseignement en Neurosciences; VasCog, The International Society of Vascular Behavioural and Cognitive Disorders; SD, standard deviation; VaD, vascular dementia.

Meta-Analysis

Data from all the included studies were used for the meta-analyses, involving 765 persons with AD, 354 with VaD, 294 with MCI, and 773 with CN. Sample sizes ranged from 17 [41] to 194 [21]. CBv was significantly lower in MCA in AD (MD = −8.42, 95% CI: −10.56 to −6.28, p < 0.001, I2 85%, n = 1,519), in VaD (MD = −11.75, 95% CI: −14.68 to −8.82, p < 0.001, I2 79%, n = 670), and in MCI (MD = −4.19, 95% CI: −5.52 to −2.85, p < 0.001, I2 0%, n = 548) compared to CN, shown in Figure 2a–c. However, no significant difference was observed between the AD and VaD groups (MD = 2.79, 95% CI: −0.78 to 6.35, p = 0.13, I2 90%, n = 676), shown in Figure 2d.

Fig. 2.

a Forest plot showing the mean difference of CBv in the MCA in persons with AD compared to CN older persons. SD, standard deviation; CI, confidence interval; IV, inverse variance. b Forest plot showing the mean difference of CBv in the MCA in persons with vascular dementia compared to CN. SD, standard deviation; CI, confidence interval; IV, inverse variance. c Forest plot showing the mean difference of CBv in the MCA in persons with mild cognitive impairment compared to CN. SD, standard deviation; CI, confidence interval; IV, inverse variance. d Forest plot showing the mean difference of CBv in the MCA in persons with AD compared to vascular dementia. SD, standard deviation; CI, confidence interval; IV, inverse variance. e Forest plot showing the mean difference of PI in the MCA in persons with AD compared to CN. SD, standard deviation; CI, confidence interval; IV, inverse variance. f Forest plot showing the mean difference of PI in the MCA in persons with vascular dementia compared to CN. SD, standard deviation; CI, confidence interval; IV, inverse variance. g Forest plot showing the mean difference of PI in the MCA in persons with AD compared to vascular dementia. SD, standard deviation; CI, confidence interval; IV, inverse variance.

Fig. 2.

a Forest plot showing the mean difference of CBv in the MCA in persons with AD compared to CN older persons. SD, standard deviation; CI, confidence interval; IV, inverse variance. b Forest plot showing the mean difference of CBv in the MCA in persons with vascular dementia compared to CN. SD, standard deviation; CI, confidence interval; IV, inverse variance. c Forest plot showing the mean difference of CBv in the MCA in persons with mild cognitive impairment compared to CN. SD, standard deviation; CI, confidence interval; IV, inverse variance. d Forest plot showing the mean difference of CBv in the MCA in persons with AD compared to vascular dementia. SD, standard deviation; CI, confidence interval; IV, inverse variance. e Forest plot showing the mean difference of PI in the MCA in persons with AD compared to CN. SD, standard deviation; CI, confidence interval; IV, inverse variance. f Forest plot showing the mean difference of PI in the MCA in persons with vascular dementia compared to CN. SD, standard deviation; CI, confidence interval; IV, inverse variance. g Forest plot showing the mean difference of PI in the MCA in persons with AD compared to vascular dementia. SD, standard deviation; CI, confidence interval; IV, inverse variance.

Close modal

PI in MCA was significantly higher in AD (MD = 0.16, 95% CI: 0.11–0.21, p < 0.001, I2 85%, n = 882) and VaD (MD = 0.32, 95% CI: 0.26–0.38, p < 0.001, I2 74%, n = 395) compared to CN, as shown in Figure 2e and f, respectively. In addition, PI was higher in VaD compared to AD (MD = −0.14, 95% CI: −0.25 to −0.04, p = 0.005, I2 92%, n = 399), as shown in Figure 2g.

Quality Assessment of the Included Studies

Quality assessments of the included studies according to the CEBM checklist designed for cross-sectional studies are shown in Table 2 [40, 19, 51, 38, 48, 52, 20, 41, 42, 43, 14, 44, 55, 27, 34, 45, 53, 28, 46, 16, 49, 29, 30, 31, 47, 39, 32, 21, 54, 37, 33, 50, 15, 36, 35], with an unclear risk of bias for most of the included studies. The certainty in the pooled estimates was evaluated using GRADE, shown in Tables 3-6. Our confidence in the pooled estimates ranged from very low to moderate and further studies are therefore likely to impact some of the results.

Table 2.

Quality assessment of included cross-sectional studies according to the CEBM checklist for cross-sectional studies (Q 1–6, 8–10, 12)

Author, year of publicationDid the study address a clearly focused question/issue?Is the research method (study design) appropriate for answering the research question?Is the method of selection (employees, teams, divisions, organizations) clearly designed?Could the way the sample was obtained introduce (selection) bias?Was the sample of subjects representative with regard to the population to which the findings will be referred?Was the sample size based on pre-study considerations of statistical power?Are the measurements (questionnaires) likely to be valid and reliable?Was the statistical significance assessed?Are confidence intervals given?Can the results be applied to your organization?Overall assessment
Alwatban et al. [40] (2019) − 
Battistella et al. [19] (2020) − 
Biedert et al. [51] (1990) − 
Biedert et al. [38] (1995) − 
Bressi et al. [48] (1992) − 
Caamaño et al. [52] (1990) − 
Cipollini et al. [20] (2019) − 
Claassen et al. [41] (2009) − 
De Heus et al. [42] (2018) 
Diomedi et al. [43] (2021) − 
Doepp et al. [14] (2006) − 
Foerstl et al. [44] (1989) − 
Franceschi et al. [55] (1995) − 
Gao et al. [27] (2013) − 
Gommer et al. [34] (2012) − 
Gongora-Rivera et al. [45] (2018) − 
Kong et al. [53] (2011) − 
Kouzuki et al. [28] (2018) − 
Lee et al. [46] (2007) − 
Liu et al. [16] (2021) − 
Meel-van den Abeelen et al. [49] (2014) − 
Ni et al. [29] (1994) − 
Ortner et al. [30] (2019) 
Provinciali et al. [31] (1990) − 
Ries et al. [47] (1993) − 
Roher et al. [39] (2011) − 
Rundek et al. [32] 1995 − 
Shim et al. [21] (2015) − 
Staszewski et al. [54] (2021) − 
Tomoto et al. [37] 2020 − 
Urbanova et al. [33] (2018) − 
Van Beek et al. [50] (2012) − 
Vicenzini et al. [15] (2007) − 
Viola et al. [36] (2013) − 
Zhou et al. [35] (2019) − 
Author, year of publicationDid the study address a clearly focused question/issue?Is the research method (study design) appropriate for answering the research question?Is the method of selection (employees, teams, divisions, organizations) clearly designed?Could the way the sample was obtained introduce (selection) bias?Was the sample of subjects representative with regard to the population to which the findings will be referred?Was the sample size based on pre-study considerations of statistical power?Are the measurements (questionnaires) likely to be valid and reliable?Was the statistical significance assessed?Are confidence intervals given?Can the results be applied to your organization?Overall assessment
Alwatban et al. [40] (2019) − 
Battistella et al. [19] (2020) − 
Biedert et al. [51] (1990) − 
Biedert et al. [38] (1995) − 
Bressi et al. [48] (1992) − 
Caamaño et al. [52] (1990) − 
Cipollini et al. [20] (2019) − 
Claassen et al. [41] (2009) − 
De Heus et al. [42] (2018) 
Diomedi et al. [43] (2021) − 
Doepp et al. [14] (2006) − 
Foerstl et al. [44] (1989) − 
Franceschi et al. [55] (1995) − 
Gao et al. [27] (2013) − 
Gommer et al. [34] (2012) − 
Gongora-Rivera et al. [45] (2018) − 
Kong et al. [53] (2011) − 
Kouzuki et al. [28] (2018) − 
Lee et al. [46] (2007) − 
Liu et al. [16] (2021) − 
Meel-van den Abeelen et al. [49] (2014) − 
Ni et al. [29] (1994) − 
Ortner et al. [30] (2019) 
Provinciali et al. [31] (1990) − 
Ries et al. [47] (1993) − 
Roher et al. [39] (2011) − 
Rundek et al. [32] 1995 − 
Shim et al. [21] (2015) − 
Staszewski et al. [54] (2021) − 
Tomoto et al. [37] 2020 − 
Urbanova et al. [33] (2018) − 
Van Beek et al. [50] (2012) − 
Vicenzini et al. [15] (2007) − 
Viola et al. [36] (2013) − 
Zhou et al. [35] (2019) − 

CEBM, Center for Evidence-Based Management.

Q, Question; +, yes; ?, can’t tell; −, no.

Table 3.

GRADE evidence table with assessments of our confidence in the estimates of cerebral blood velocity and pulsatility index in the middle cerebral artery in Alzheimer’s disease versus cognitively normal

Certainty assessmentPatients, nEffectCertaintyImportance
studies, nstudy designrisk of biasinconsistencyindirectnessimprecisionother considerationstranscranial Doppler in Alzheimer’s diseasetranscranial Doppler in controlsrelative (95% CI)absolute (95% CI)
Cerebral blood velocity in the middle cerebral artery in Alzheimer’s disease compared to cognitively normal 
 29 Observational studies Not serious Not serious Not serious Seriousa Strong association 765 754 Mean difference 8.42 cm/s lower (10.56 lower to 6.28 lower) ⊕⊕◯◯ Low IMPORTANT 
Pulsatility index in persons with Alzheimer’s disease compared to cognitively normal 
 17 Observational studies Not serious Not serious Not serious Seriousa Very strong association 458 424 Mean difference 0.16 higher (0.11 higher to 0.21 higher) ⊕⊕⊕◯ Moderate IMPORTANT 
Certainty assessmentPatients, nEffectCertaintyImportance
studies, nstudy designrisk of biasinconsistencyindirectnessimprecisionother considerationstranscranial Doppler in Alzheimer’s diseasetranscranial Doppler in controlsrelative (95% CI)absolute (95% CI)
Cerebral blood velocity in the middle cerebral artery in Alzheimer’s disease compared to cognitively normal 
 29 Observational studies Not serious Not serious Not serious Seriousa Strong association 765 754 Mean difference 8.42 cm/s lower (10.56 lower to 6.28 lower) ⊕⊕◯◯ Low IMPORTANT 
Pulsatility index in persons with Alzheimer’s disease compared to cognitively normal 
 17 Observational studies Not serious Not serious Not serious Seriousa Very strong association 458 424 Mean difference 0.16 higher (0.11 higher to 0.21 higher) ⊕⊕⊕◯ Moderate IMPORTANT 

CI, confidence interval.

aSmall studies, broad confidence intervals.

Table 4.

GRADE evidence table with assessments of our confidence in the estimates of cerebral blood velocity and pulsatility index in the middle cerebral artery in Alzheimer’s disease versus vascular dementia

Certainty assessmentPatients, nEffectCertaintyImportance
studies, nstudy designrisk of biasinconsistencyindirectnessimprecisionother considerationstranscranial Doppler in persons with Alzheimer’s diseasetranscranial Doppler in persons with vascular dementiarelative (95% CI)absolute (95% CI)
Cerebral blood velocity in persons with Alzheimer’s disease compared to persons with vascular dementia 
 14 Observational studies Not serious Seriousa Not serious Seriousb None 345 331 Mean difference 2.79 cm/s lower (6.35 lower to 0.78 higher) ⊕◯◯◯ Very low IMPORTANT 
Pulsatility index in persons with Alzheimer`s disease compared to persons with vascular dementia 
 8 Observational studies Not serious Not serious Not serious Seriousb Strong association 205 194 Mean difference 0.14 lower (0.25 lower to 0.04 lower) ⊕⊕◯◯ Low IMPORTANT 
Certainty assessmentPatients, nEffectCertaintyImportance
studies, nstudy designrisk of biasinconsistencyindirectnessimprecisionother considerationstranscranial Doppler in persons with Alzheimer’s diseasetranscranial Doppler in persons with vascular dementiarelative (95% CI)absolute (95% CI)
Cerebral blood velocity in persons with Alzheimer’s disease compared to persons with vascular dementia 
 14 Observational studies Not serious Seriousa Not serious Seriousb None 345 331 Mean difference 2.79 cm/s lower (6.35 lower to 0.78 higher) ⊕◯◯◯ Very low IMPORTANT 
Pulsatility index in persons with Alzheimer`s disease compared to persons with vascular dementia 
 8 Observational studies Not serious Not serious Not serious Seriousb Strong association 205 194 Mean difference 0.14 lower (0.25 lower to 0.04 lower) ⊕⊕◯◯ Low IMPORTANT 

CI, confidence interval.

aStudy results pointing in different directions.

bSmall studies, broad confidence intervals.

Table 5.

GRADE evidence table with assessments of our confidence in the estimates of cerebrovascular hemodynamics in vascular dementia versus cognitively normal

Certainty assessmentPatients, nEffectCertaintyImportance
studies, nstudy designrisk of biasinconsistencyindirectnessimprecisionother considerationstramscranial Doppler in vascular dementiatranscranial Doppler in controlsrelative (95% CI)absolute (95% CI)
Cerebral blood velocity in persons with vascular dementia compared to cognitively normal 
 13 Observational studies Not serious Not serious Not serious Seriousa Very strong association 298 372 Mean difference 11.75 cm/s lower (14.68 lower to 8.82 lower) ⊕⊕⊕◯ Moderate IMPORTANT 
Pulsatility index in persons with vascular dementia compared to cognitively normal 
 8 Observational studies Not serious Not serious Not serious Seriousa Very strong association 194 201 Mean difference 0.32 higher (0.26 higher to 0.38 higher) ⊕⊕⊕◯ Moderate IMPORTANT 
Certainty assessmentPatients, nEffectCertaintyImportance
studies, nstudy designrisk of biasinconsistencyindirectnessimprecisionother considerationstramscranial Doppler in vascular dementiatranscranial Doppler in controlsrelative (95% CI)absolute (95% CI)
Cerebral blood velocity in persons with vascular dementia compared to cognitively normal 
 13 Observational studies Not serious Not serious Not serious Seriousa Very strong association 298 372 Mean difference 11.75 cm/s lower (14.68 lower to 8.82 lower) ⊕⊕⊕◯ Moderate IMPORTANT 
Pulsatility index in persons with vascular dementia compared to cognitively normal 
 8 Observational studies Not serious Not serious Not serious Seriousa Very strong association 194 201 Mean difference 0.32 higher (0.26 higher to 0.38 higher) ⊕⊕⊕◯ Moderate IMPORTANT 

CI, confidence interval.

aSmall studies, broad confidence intervals.

Table 6.

GRADE evidence table with assessments of our confidence in the estimates of cerebral blood velocity in the middle cerebral artery in mild cognitive impairment versus cognitively normal

Certainty assessmentPatients, nEffectCertaintyImportance
Studies, nstudy designrisk of biasinconsistencyindirectnessimprecisionother considerationstranscranial Doppler in persons with mild cognitive impairmenthealthy controlsrelative (95% CI)absolute (95% CI)
Cerebral blood velocity in persons with mild cognitive impairment compared to cognitively normal 
 10 Observational studies Not serious Not serious Not serious Seriousa None 286 262 Mean difference 4.19 cm/s lower (5.52 lower to 2.85 lower) ⊕◯◯◯ Very low IMPORTANT 
Certainty assessmentPatients, nEffectCertaintyImportance
Studies, nstudy designrisk of biasinconsistencyindirectnessimprecisionother considerationstranscranial Doppler in persons with mild cognitive impairmenthealthy controlsrelative (95% CI)absolute (95% CI)
Cerebral blood velocity in persons with mild cognitive impairment compared to cognitively normal 
 10 Observational studies Not serious Not serious Not serious Seriousa None 286 262 Mean difference 4.19 cm/s lower (5.52 lower to 2.85 lower) ⊕◯◯◯ Very low IMPORTANT 

CI, confidence interval.

aSmall studies, broad confidence intervals.

This systematic review and meta-analysis of TCD studies show that persons with AD and VaD have lower CBv and higher PI in comparison with CN, with moderate confidence in our pooled estimates according to GRADE. CBv did not differ significantly between AD and VaD, although PI was higher in VaD. In addition, CBv was lower in MCI than in CN.

The cerebrovascular hypothesis of dementia recognizes disturbances in cerebral blood flow as an important mechanism of neurodegeneration and cognitive dysfunction [56], and impairments in brain blood flow have been associated with decline in cognitive function and progression to dementia [10]. A previous meta-analysis of TCD studies from 2012 by Sabayan et al. [18] showed disturbances in cerebral hemodynamics in dementia in comparison with CN. This is in line with the results from the current meta-analysis, although CBv did not differ between AD and VaD in contrast to the meta-analysis and review by Sabayan et al. [18], where cerebral blood flow disturbances were more pronounced in VaD than in AD.

TCD measures of CBv in MCA correspond well with measurements using neuroimaging techniques [57], and a large number of TCD studies have assessed the relationship between cerebrovascular hemodynamics and dementia, with most of them reporting significant alterations in CBv in comparison with CN [14‒16, 19‒21, 34, 38, 39, 41, 42, 45, 48, 52‒55], while some did not [29, 33, 35, 40, 43, 46, 49, 50]. Since studies were published between 1989 [44] and 2021 [16], disagreements in study results could be due to differences in TCD equipment – with more advanced imaging and thus more accurate measurements in newer ultrasound machines used in recent studies compared to machines used in the studies from the 1990s, sometimes without an angle correction function – although we performed a sensitivity analysis based on publications before and after 2005 and found no statistically significant difference between older and newer studies. Further, the numbers of participants differ across studies, with sample sizes ranging from 17 [41] to 194 [21]. In addition, the MMSE cut-off values for dementia varied between studies, with the lowest reported MMSE score for CN at 24.7 points [35], which is a lower score than the highest reported for dementia, i.e., 25 points [41].

This review and meta-analysis does not answer the question regarding whether disturbances in cerebral hemodynamics play a role in the neurodegenerative process or are merely prodromal to cognitive decline and dementia. Vascular risk factors and vascular disturbances with subsequent brain hypoperfusion are considered part of the pathophysiological process in VaD, and increasing evidence shows that vascular risk factors and atherosclerosis may contribute in the AD process as well [58, 59]. It is possible that reduced blood flow to the brain with subsequent cerebral hypoperfusion could result in nerve cell dysfunction and death, particularly in vulnerable areas including the hippocampi. A longitudinal study by Ruitenberg et al. [10], including measures of hippocampal and amygdalar volumes from 170 participants, found a negative association between CBv and brain volumes in these areas, which was not mediated by cerebrovascular disease. Cerebral hypoperfusion could promote neurodegeneration through oxidative stress [60], impaired beta-amyloid clearance [17], increased white matter lesion burden [61], and possibly reduced functioning in the brain’s glymphatic system [62], although it cannot be excluded that reduced cerebral blood flow simply reflects a decreased metabolic demand due to neuronal loss and brain atrophy, since none of the included studies adjusted for the level of brain atrophy in measures of CBv.

While our results showed similar decrease in CBv and increased PI in both AD and VaD compared with CN, the increase in PI in VaD compared to AD could indicate differences in type, distribution, and severity of vascular pathology in different forms of dementia. Although PI often is interpreted as a measure of cerebrovascular resistance, it has been shown that PI is dependent on several hemodynamic parameters, such as the cerebral perfusion pressure, arterial blood pressure, and heart rate [63]. Still, elevated PI is reported to be strongly correlated with magnetic resonance imaging evidence of cerebral small vessel disease, including severity of small vessel changes [64]. An alternative explanation might be that mixed etiologies of dementia, with both neurodegenerative pathology and vascular disease, could overestimate the role of cerebrovascular disturbances in dementia of neurodegenerative etiology, i.e., in “pure AD.”

Interestingly, a recent systematic review found no difference in cerebral dynamic autoregulation between persons with AD, MCI, and healthy controls [63]. It is not known why PI increases whereas dynamic cerebral autoregulation is unchanged in people with AD and MCI. One possible hypothesis could be that PI primarily is a function of microvascular changes with increased resistance in arterioles and capillaries, e.g., due to deposits of amyloid in vessel walls [65], while cerebral autoregulation is modulated via larger proximal arteries in the circle of Willis which are unaffected by amyloid angiopathy and, therefore, respond with normal dynamic autoregulation in AD.

Cerebral blood flow decreases as part of the aging process [66], and the results from this meta-analysis show that CBv is further decreased in persons with MCI in comparison to CN. This is in agreement with a systematic review of cerebral blood flow measures in MCI from 2017, which reported clear disturbances in cerebrovascular hemodynamics even in the early stages of cognitive decline [67]. Since dementia is a slowly progressing condition where the start of the disease can precede the onset of clinical symptoms by decades [68], there is clinical value in finding biomarkers for predicting conversion from MCI to dementia. Indeed, a recent study that followed 68 persons with MCI for 24 months found that changes in cerebrovascular hemodynamics evaluated by TCD were associated with cognitive decline and dementia [69]. Further, a study of persons with high-grade carotid artery stenosis showed that cognitive impairment correlated linearly with cerebral blood flow when CBv was below 45 cm/s. This suggests a threshold effect [70], where less severe disturbances in cerebrovascular hemodynamics may not have an impact on cognitive decline. In the present meta-analysis, average CBv ranged from 19.0 [28] to 61.37 cm/s [35], which could be a cause for disparities in study results.

The present review and meta-analysis has some limitations: (1) although the literature search was comprehensive and performed by an experienced information specialist, we may have missed some relevant studies; (2) measures of cerebrovascular hemodynamics were only measured in MCA, which is the main vessel responsible for brain parietotemporal blood supply [71]; (3) TCD cannot be used to assess the extent of brain atrophy which is a potential cause for reduced blood flow to the brain due to neuronal death and reduced metabolic demand; (4) some of the analyses included few studies with small samples, resulting in a low confidence in our pooled estimates according to GRADE; and (5) heterogeneity was high for most of the forest plots, which could be explained by uncertain risk of bias due to observational study design, different countries, and times of publication ranging from the late 1980s to today. Strengths of the present study are the transparent methodology using PRISMA, and the moderate confidence in our main results of cerebrovascular hemodynamics in persons with dementia in comparison with CN, according to GRADE.

In conclusion, there is moderate evidence of lower CBv and higher PI in persons with dementia, of both neurodegenerative and vascular etiology, in comparison with CN. In addition, CBv was lower in MCI than in CN. This supports the possible add-on clinical value of hemodynamic parameters measured with TCD in diagnosing cognitive impairment and dementia. Further studies should adjust results of intracerebral hemodynamics for the degree of cerebral atrophy.

The literature search was performed by information specialist Mathias Lindberg at the Central Hospital Karlstad Library. The authors would like to thank him for his excellent support and assistance with the present systematic review and meta-analysis.

An ethics statement is not applicable because this study is based exclusively on published literature. This is in accordance with Swedish law and guidelines of the Ethical Committee of Uppsala University, Sweden.

The authors have no conflicts of interest to declare.

The study was funded by (1) Örebro University School of Medical Sciences, Örebro, Sweden, and (2) Central Hospital Karlstad, Karlstad, Sweden.

The study was conceived and designed by David Fresnais and Brynjar Fure, who also carried out the data extraction, quality assessment of included studies, and meta-analyses. David Fresnais wrote the first draft of the manuscript as well as revisions of drafts. Brynjar Fure reviewed and contributed to revision of all the drafts. David Fresnais, Brynjar Fure, Håkon Ihle-Hansen, Erik Lundström, and Åsa Andersson revised the manuscript critically for important intellectual content.

All study data included in or generated through analysis of data in this study can be found in the study manuscript and the online supplementary material files. Further inquiries can be directed to the corresponding author.

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