Neuroimaging in Vascular Cognitive Impairment and Dementia: A Systematic Review

Abstract

Cerebrovascular diseases are well established causes of cognitive impairment. Different etiologic entities, such as vascular dementia (VaD), vascular cognitive impairment, subcortical (ischemic) VaD, and vascular cognitive disorder, are included in the umbrella definition of vascular cognitive impairment and dementia (VCID). Because of the variability of VCID clinical presentation, there is no agreement on criteria defining the neuropathological threshold of this disorder. In fact, VCID is characterized by cerebral hemodynamic alteration which ranges from decreased cerebral blood flow to small vessels disease and involves a multifactorial process that leads to demyelination and gliosis, including blood-brain barrier disruption, hypoxia, and hypoperfusion, oxidative stress, neuroinflammation and alteration on neurovascular unit coupling, cerebral microbleeds, or superficial siderosis. Numerous criteria for the definition of VaD have been described: the National Institute of Neurological Disorders and Stroke Association Internationale pour Recherche'-et-l’Enseignement en Neurosciences criteria, the State of California Alzheimer’s Disease Diagnostic and Treatment Centers criteria, DSM-V criteria, the Diagnostic Criteria for Vascular Cognitive Disorders (a VASCOG Statement), and Vascular Impairment of Cognition Classification Consensus Study. Neuroimaging is fundamental for definition and diagnosis of VCID and should be used to assess the extent, location, and type of vascular lesions. MRI is the most sensible technique, especially if used according to standardized protocols, even if CT plays an important role in several conditions. Functional neuroimaging, in particular functional MRI and PET, may facilitate differential diagnosis among different forms of dementia. This systematic review aims to explore the state of the art and future perspective of non-invasive diagnostics of VCID.

Keywords

Brain vascular disorders functional neuroimaging MRI neuroimaging PET vascular dementia

INTRODUCTION

Cerebrovascular disease has long been recognized as an important cause of cognitive impairment, but the conceptualization of the resulting disorder presented considerable methodological complexities. Cerebrovascular pathology, including microinfarcts, lacunar infarcts, larger infarcts (of embolic or thrombotic origin), and white matter lesions, is moderately to strongly associated with cognitive decline [1 –5]. Numerous subsequent proposals have tried to capture the clinical and etiologic complexity of cognitive impairment caused by heterogeneous cerebrovascular disease and pathologies [6 –8]. The term vascular cognitive impairment and dementia (VCID) is recently being used as an umbrella term [9] that include vascular dementia (VaD), vascular cognitive impairment (VCI), subcortical (ischemic) VaD, and vascular cognitive disorder. Nevertheless, several criteria and research guidelines have been produced in order to focus on this group of pathologies [2 , 10–13]. These factors contribute to variable prevalence estimates in the literature, as do descriptions of clinical manifestations. Although the term VaD is used to describe a severe form in the continuum of the VCID spectrum, it represents the second most common cause of dementia after Alzheimer’s disease (AD) [9, 14]. Recently, due to this heterogeneity, the Society for Vascular Behavioral and Cognitive Disorders (VASCOG) produced criteria for vascular cognitive disorder [15], which can be harmonized with the DSM-5 criteria. Core features include stepwise progression, focal neurological signs and symptoms, unequal distribution of cognitive deficits, history of multiple ischemic strokes, neuroimaging evidence of cerebrovascular disease and temporal relationship between cerebrovascular disease and cognitive impairment, even neuropsychiatric symptoms in temporal lobe stroke subtypes [16, 17]. The signs or symptoms that occur during the disease depend on the type, extent, and location of the underlying cerebrovascular pathology [18]. The National Institute of Neurological Disorders and Stroke Association Internationale pour Recherche'-et-l’Enseignement en Neurosciences (NINDS-AIREN) criteria require “multiple large-vessel strokes” or “a single strategically placed infarct” (angular gyrus, thalamus, basal forebrain, or posterior carotid artery or anterior carotid artery territories), “multiple basal ganglia and white matter lacunes,” or “extensive periventricular white matter lesions” [19, 20]. A single large vessel infarct may be sufficient to produce mild VCID, but it must either be strategically placed or be very extensive to cause a VaD [15, 21]. For the latter, multiple large vessel infarcts are usually necessary, which are more likely to be in the left hemisphere and are often bilateral [22] and at least one of these should be outside the cerebellum. Furthermore, a temporal association should be reported, with the cognitive impairment being evident within 3 months of the infarction and persisting beyond that period [23]. Generally, more than 2 lacunes outside the brainstem are considered necessary to support a diagnosis of VCID [24]. Nevertheless, a single large lacune placed strategically in the striatum or the thalamus may lead to a VCID diagnosis if a temporal relationship with the cognitive syndrome is present [25], or when associated with extensive periventricular and deep white matter lesions (WMLs) [26]. VCID may be present in the absence of lacunar or large infarcts if extensive WMLs are present. WMLs may be focal or multifocal and confluent. WMLs are nonspecific but, according to literature data in old subjects, mainly ischemic in origin [12, 27]. However, WMLs are also common in AD, dementia with Lewy bodies, and frontotemporal dementia, but they may also be related to mixed pathologies. For mild VCID, WMLs may be sufficient in the absence of other vascular pathology. For VaD, the additional evidence of vascular pathology signs is necessary, better if supported by temporal relationship to the cognitive impairment [28]. WMLs are more extensive in the periventricular regions and extend to the deep white matter [20, 29]. Cognitive disorders have been associated with subarachnoid hemorrhage due to vascular pathology, while subdural hemorrhage is an uncommon cause of the cognitive disorder, usually a result of trauma [30]. Multiple hemorrhages or hemorrhagic infarcts caused by cardiovascular risk factors (for example, hypertension) and sporadic or hereditary conditions associated with cerebral amyloid angiopathy (CAA) are closely tied to VCID development, as well cortical and subcortical microbleeds [13 , 32]. The distinction between the mild and major (or dementia) levels is based on the severity of cognitive deficits, and even more on the functional impairment secondary to them. It is also particularly important in the VCID that impairment should be attributable to cognitive and not a motor, sensory, or speech impairment [15]. The mild disorder can also affect functioning but in general, such individuals can function close to their previous levels by instituting compensatory strategies with the maintenance of independent functioning. The commonly used definitions of VaD, for example, NINCDS-AIREN [19], require impairment in≥2 cognitive domains, with memory being one of these domains. However, an individual with severe impairment in one cognitive domain may in some cases have enough consequent disability to justify a diagnosis of VaD [15]. Dementia after ischemic stroke appears a result of multiple independent factors as stroke features (dysphasia, major dominant stroke syndrome), host characteristics (educational level), and prior cerebrovascular disease each independently contributes to the risk [22].

MECHANISMS/PATHOPHYSIOLOGY

The heterogeneity of cerebrovascular disease makes it challenging to elucidate the neuropathological substrates and mechanisms of VCID. VCID is an entity whose heterogeneous clinical manifestations are due to a substrate of multiple pathogenic and structural factors and several biological mechanisms might link the vascular disease to cognitive impairment. Due to the variability of cerebrovascular disease, the common comorbid pathologies, and the diverse clinical phenotypes of VCID, no widely accepted criteria defining the neuropathological threshold of this disorder are available [33, 34]. Nevertheless, decreased cerebral blood flow is the major cerebral hemodynamic alteration in VCID and pathologies, which cause a reduction in global cerebral blood flow, such as atherosclerosis and arterial stenosis are involved [3 , 35–37]. Factors that define the subtypes of VCID include the nature and extent of vascular pathologies (such as ischemic infarcts, hemorrhages, and white matter changes), the degree of involvement of extra and intracranial vessels, and the anatomical location of tissue changes. One prospective screening study showed that seven pathologies, including large infarcts, lacunar infarcts, microinfarcts, myelin loss, arteriolosclerosis, leptomeningeal CAA, and perivascular space dilation, predicted cognitive impairment [38 –41]. Neuroimaging and neuropathology studies have established that clinically silent cerebrovascular disease is sufficient to cause relevant cognitive impairment in the absence of stroke [15]; small vessel disease (SVD) is, in fact, the most common damage in VCID [42, 43]. SVD is characterized by arteriolosclerosis and lacunar infarcts, and causes cortical and subcortical microinfarcts and diffuse damage to the white matter (ischemic leukoencephalopathy) [38, 44], usually mainly localized in frontal and occipital regions [45 –47]. Vessel wall modifications, such as arteriolosclerosis, atherosclerosis, and CAA, have been suggested to be very common and of key importance in VCID [39, 48]. The mechanism underlying VCID damage involves a multifactorial process that leads to demyelination and gliosis, including blood-brain barrier disruption, hypoxia, and hypoperfusion, oxidative stress, neuroinflammation and alteration on neurovascular unit coupling, cerebral microbleeds, or superficial siderosis [9]. Common radiologic features of SVD are lacunar infarcts, white matter lesions, brain atrophy, and visible enlarged perivascular spaces, but their relationship to VCI, however, is not well established [49]. Further causes of VCID described in the literature are arteritis, vasculitis [50], including both local and systemic inflammatory syndromes, subdural or subarachnoid hemorrhage, venous thromboses/infarcts, infectious vasculitis, hippocampal sclerosis, angiomatous lesions/vascular tumors with local steal phenomenon, and chronic migraine [2 , 52]. VCID is usually a sporadic disease; however, there are also monogenic forms that should be recognized to make an accurate diagnosis and a correct family counseling [9], as cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) [53 –55]), cerebral autosomal recessive arteriopathy with subcortical infarcts and leukoencephalopathy (CARASIL) [56], and the Cathepsin A-related arteriopathy with strokes and leukoencephalopathy (CARASAL) [57]. Moreover, other adult-onset genetic leukoencephalopathies have recently been described, such as hereditary diffuse leukoencephalopathy with spheroids [58]. In addition, other pathophysiological processes are likely to play a role in VCID within a mixed pathological process, including possible interactive injury with AD and other neuropathological processes, including α-synucleinopathy, tau pathology, TAR DNA-binding protein pathology and microglial reactions, in addition to local tissue injury or dysfunction, including innate immune processes and disruption of the neurovascular unit leading to blood-brain barrier alterations [16, 59].

AIM AND PURPOSE

This systematic review aims to explore the state of the art and future perspective of non-invasive diagnostics of VCID. Vascular dementia is associated with multiple, asymmetric, perfusion deficits in multi-infarct dementia and evidence for significant vascular pathology in the brain are commonly reported by using magnetic resonance imaging (MRI) [4]. Nevertheless, nuclear medicine and, particularly, positron emission tomography (PET) provide functional information adding diagnostic and prognostic value [60]. PET can provide the necessary understanding of the abnormal cellular biochemical processes that occur in response to perfusion insufficiencies in humans [18]. Combining MRI and PET allows identification of patients with mixed dementia, with MRI showing white matter injury and PET demonstrating regional impairment of glucose metabolism and deposition of amyloid [61]. Nuclear medicine techniques such as perfusion single photon emission computed tomography (SPECT) and ¹⁸F-fluorodeoxyglucose (FDG)-PET described typical patterns of hypometabolism due to dementia with differences in term of accuracy [62]. Both FDG and amyloid brain PET or PET/computed tomography (CT) for patients with cognitive decline have been considered as parameters by the American College of Radiology and the American Society for Neuroradiology in dementia population [63].

METHODS

A literature search was performed from 1 January 1989 to 15 August 2019 including the following databases: Pubmed and Scopus. The terms used for Pubmed were: ((((“Positron-Emission Tomography”[Mesh]) OR “Magnetic Resonance Imaging”[Mesh]) OR “Radionuclide Imaging”[Mesh]) OR “Computed Tomography Angiography”[Mesh]) AND (“Dementia, Vascular/diagnosis”[Mesh] OR “Dementia, Vascular/diagnostic imaging”[Mesh]). The terms used for Scopus were: TITLE (“PET”) OR TITLE (“positron emission tomography”) OR TITLE (“magnetic resonance”) OR TITLE (“MRI”) OR TITLE (“nuclear medicine”) OR TITLE (“computed tomography”) AND TITLE-ABS (“vascular dementia”). The search was made both without and with addition of filters (such as the English language only; type of article: original article, research article, review article; human only). Two reviewers (V.F. and M.R.) performed the literature search and an independent review (A.P.) selected the studies eliminating off-topic articles and made data extraction in duplicate. Clinical reports, meeting abstracts, reviews, and editor comments were excluded. All the recognized records were combined, and the complete texts were recovered which were subsequently evaluated by all the reviewers. Selection process flowchart was shown in Fig. 1 and the presentation of results was made according to the PRISMA guidelines. The basics characteristics of the included studies are reported in Table 1.

Fig.1

Flowchart summarizing the selection process of included studies.

Table 1

Characteristics of selected studies

Authors	Year	Dementia categories	Imaging technique	Main result
Tohgi et al. [5]	1998	VaD	FDG-PET; MRI	rCBF and cerebral metabolic rate of oxygen at MRI and PET were significantly decreased in the frontal, parietal, and temporal cortex (p < 0.05) in patients with senile dementia of the Alzheimer’s type, and showed a significant correlation with the severity of dementia (p < 0.05)
Rockwood et al. [6]	2000	VCI, VaD and AD	MRI	The rate of WM changes at MRI was similar for VaD and AD/VaD, and markedly lower for both AD and other types of dementia. Many patients with VaD features clinically have radiographic features which do not completely correlate.
Cao et al. [7]	2010	VCI	CT	rCBF at CT was significantly reduced in VCI- no dementia subtypes, and was consistent with performance of neuropsychological assessment.
Li et al. [12]	2014	VCI	FDG-PET	Glucose metabolism at PET predicting the severity of ischemic lesions: CMRglu values were decreased in WM ischemic lesions, in particular in parietal lobe, frontal lobe, and WM centrum semiovale.
Gurol et al. [13]	2016	VCI	¹⁸F- Florbetapir PET	¹⁸F-Florbetapir PET provides a sensitivity of 100% (95% CI 66% -100%) and specificity of 89% (95% CI 51% -99%) for determination of probable CAA-related intracerebral hemorrhage.
Wong et al.[17]	2016	VCI and VaD	PiB-PET; MRI	¹¹C-PiB-PET data showed no evidence that significant amyloid retention contributed to the neuropsychiatric manifestations at 3 to 6 months after stroke or TIA. Frontal lobe atrophy at MRI was associated with the behavioral disturbance cluster only. WM changes, ventricular-brain ratio, and presence of old infarcts at MRI were not associated with the presence of any symptom.
Yang et al. [21]	2015	VCI and VaD	PiB-PET	AD-like PiB retention at PET was found in 29.7% and 7.7% (p = 0.032) of patients with and without incident dementia, respectively.
Tatemichi et al. [22]	1993	VaD	MRI	Stroke features at MRI associated with dementia included LI compared with all other subtypes (OR = 2.7) and hemispheric laterality in relation to brainstem or cerebellar location.
Pohjasvaara et al. [23]	1998	VaD	MRI	Stroke features at MRI contribute to diagnostic VaD. Left hemispheric stroke localization was more common in demented patients.
Swartz et al. [25]	2006	VCI and VaD	MRI	The anterior-medial thalamus hyperintensities > 55 mm³ at MRI represent a major and under-recognized contributor to cognitive impairment.
Jellinger et al. [28]	2008	VaD	MRI	A more severe myelin loss is evident at MRI in the frontal lobe in VaD compared to AD and DLB or elderly controls.
Kitagawa et al. [36]	2009	VCI	PET; MRI	A linear association was found between cerebral hypoperfusion at PET (CBF) and later cognitive decline.
Sabri et al. [37]	2000	VCI	PET; MRI; HMPAO SPECT	Patients with cerebral microangiopathy showed no significant reductions, in PET, of rCBF or rMRGlu either in the cortex or in the WM (p > 0.05), and they did not show changes in LI, DWML, or atrophy at MRI.
Kim et al. [39]	2014	VCI and VaD	PiB-PET; MRI	Positive DSM-IV criteria for vascular dementia, severe WMHs at MRI, younger age, greater number of lacunes, and lesser MTA are predictive of a PiB(-) PET scan in patients with VaD.
Sabri et al. [40]	1999	VCI and VaD	PET; MRI; HMPAO SPECT	Lacunar infarctions and DWML do not in themselves indicate cognitive impairment. Dementia or neuropsychological deficits are reflected exclusively by functional imaging parameters and cerebral atrophy. Neuropsychological deficits correlated well with decreased rCBF and rMRGlu at PET, whereas MRI patterns such as LI and DWML did not.
Sabri et al. [41]	1998	VCI and VaD	PET; MRI; HMPAO SPECT	Analysis of variance identified atrophy and neuropsychological deficits as the main determinants for reduced rCBF and rMRGlu values at PET and MRI (p < 0.05).
Kim et al. [43]	2015	VCI	PiB-PET; MRI	PiB retention ratio on PET was not associated with any WM network parameters. Greater WMH volumes or lacunae numbers at MRI were significantly associated with decreased network integration and increased network segregation
Mendez et al. [44]	1999	VCI and VaD	FDG-PET	Dementia patients with severe leukoaraiosis and bilateral temporoparietal hypometabolism at FDG-PET may have predominant AD; those who lack this pattern and have confluent leukoaraiosis may have a greater contribution from VaD.
Kim et al. [46]	2012	VCI and AD	PiB-PET; MRI	VaD without amyloid burden on PET may lead to substantial cortical atrophy. Moreover, characteristic topography of cortical thinning in PiB(-) VaD suggests different mechanisms of cortical thinning in PiB(-) VaD and AD.
Tullberg et al. [47]	2004	VCI and VaD	FDG-PET; MRI	The frontal lobes are most severely affected by subcortical ischemic vascular disease. WMHs at MRI are more abundant in the frontal region. WMHs are associated with frontal hypometabolism at PET and executive dysfunction.
Frantellizzi et al. [50]	2018	VCI	SPECT	Brain SPECT is able to monitor the disease in vasculitis, indicating the moment when an improvement of the cerebral perfusion is achieved.
Mancini et al. [51]	2019	VCI	SPECT	Brain SPECT hypoperfusion suggests a more extensive permanent neuronal loss and cystic fibrosis is a risk factor for hemiplegic migraine and stroke.
Kim et al. [52]	2015	VCI, VaD and AD	PiB-PET; MRI	Direct comparison on PET between PiB(-) VaD and PiB(+) AD demonstrated more inward deformity in the subiculum of the left hippocampus in PiB(+) AD. PiB(-) VaD patients have smaller hippocampal volumes at MRI, suggesting that cumulative ischemia without amyloid pathology could lead to hippocampal atrophy and shape changes.
Tatsch et al. [54]	2003	VCI (CADASIL)	FDG-PET	Cortical glucose metabolism at PET is significantly low in CADASIL patients, explained by a reduction of CBF and neuronal loss.
Bugiani et al. [57]	2016	VCI (CARASAL)	MRI	MRI showed a leukoencephalopathy that was disproportionately severe compared to the clinical characteristics of CARASAL.
Kim et al. [59]	2013	VCI and AD	PiB-PET; MRI	Hippocampal and amygdalar shape were used in the incremental learning method to discriminate mixed dementia from pure VaD. PET PiB(+) SVaD could be discriminated from PiB(-) SVaD with 77.9% accuracy (95.7% sensitivity and 68.9% specificity) in MRI positive SVaD.
Liu et al. [68]	1992	VaD	MRI	Both cortical and WM total infarction area measurements at MRI were strongly associated with dementia in stroke patients, suggesting that these factors strongly influenced the development of dementia following stroke. There was a strong association between dementia and left, but not right, hemisphere infarction area.
Scheltens et al. [71]	1992	VaD	MRI	MTA may be assessed quickly and easily with plain MRI films.
Ramirez et al. [76]	2015	VCI	MRI	Compared to NC, at MRI AD had significantly greater volumes of WMH (p < 0.01), lacunes (p < 0.001), and VRS in the WM (p < 0.01), but not in the basal ganglia (n.s.). Compared to women, demented and non-demented men had greater VRS in the WM (p < 0.001), but not in the basal ganglia (n.s.). Additionally, VRS were correlated with lacunes and WMH, but only in AD (r = 0.3, p < 0.01).
Tripathi et al. [77]	2014	VaD	FDG-PET	Concordance of visual evaluation of FDG-PET scans with clinical diagnosis of the dementia type was achieved in 90% of patients scanned.
Yoon et al. [78]	2013	VaD	PiB-PET	Patients with PET PiB- VaD were better at memory but worse at frontal function than patients with PET PiB(+) AD.
Seo et al. [79]	2009	VCI	FDG-PET	A direct comparison of glucose metabolism at PET between svMCI and aMCI showed that the glucose hypometabolism in patients with svMCI was more severe in the thalamus, brainstem, and cerebellum.
Nitkunan et al. [84]	2008	VCI and VaD	MRI	A multimodal MRI model explains a large proportion of the variation in executive function in cerebral SVD. DTI correlates best with executive function and is the most sensitive to change (FA histogram, r =&thinsp-0.640, p = 0.004).
Zarei et al. [86]	2009	VaD and AD	MRI	Integrating mean FA at MRI in the forceps minor to the Fazekas score provides a useful quantitative marker for differentiating AD from VaD. The best discriminant model was the combination of transcallosal prefrontal FA and Fazekas score with 87.5% accuracy, 100% specificity, and 93% sensitivity (p < 0.0001).
Baykara et al. [87]	2016	VCI and VaD	MRI	In longitudinal analysis, PSMD at MRI captured SVD progression better than other imaging markers. PSMD was associated with processing speed in SVD [p-values between 2.8×10(-3) and 1.8×10(-10)].
Goos et al. [88]	2009	AD	MRI	MBs are associated with the clinical manifestation and biochemical hallmarks of AD. Atrophy was not related to presence of MBs, but patients with multiple MBs had more WMHs at MRI (multiple MB: 8.8±4.8; no MB: 3.2±3.6, p < 0.05)
Wang et al. [91]	2019	VaD	MRI	The overall functional connectivity strength was lowest in the WM lesions at MRI in VaD patients and highest in the NC study participants.
Yu et al. [92]	2015	VCI and VaD	MRI	In subcortical VCI patients functional brain networks at MRI showed small-world attributes over a range of thresholds (0.15≤sparsity≤0.40).
Kerrouche et al. [98]	2006	VCI, VaD and AD	FDG-PET	At FDG-PET, the lower metabolism differentiating VaD from AD mainly concerned the deep gray nuclei, cerebellum, primary cortices, middle temporal gyrus, and anterior cingulate gyrus, whereas lower metabolism in AD versus VaD concerned mainly the hippocampal region and orbitofrontal, posterior cingulate, and posterior parietal cortices (72% sensitivity and 96% specificity).
Mielke et al. [99]	1994	VCI, VaD and AD	HMPAO SPECT; FDG-PET	Comparing the metabolic and perfusion ratio by receiver operating characteristic curves, PET differentiated AD from normal only marginally better than SPECT. Differentiation between AD and VaD was much better achieved by PET.
Duara et al. [100]	1989	VaD and AD	FDG-PET; MRI	There was no characteristic pattern of abnormality that distinguished VaD from AD patients. PET scan abnormalities occurred in about 90% of demented patients and in 54% of elderly and 34% of young NC.
Ikonomovic et al. [102]	2008	AD	PiB-PET	The strong direct correlation of in vivo PiB-PET retention with region-matched quantitative analyses of amyloid beta plaques in the same subject supports the validity of PiB-PET imaging as a method for in vivo evaluation of amyloid plaque burden.
Klunk et al. [103]	2004	AD	PiB-PET; FDG-PET	In AD, PiB-PET retention was increased most prominently in frontal cortex (1.94-fold, p = 0.0001), parietal (1.71-fold, p = 0.0002), temporal (1.52-fold, p = 0.002), and occipital (1.54-fold, p = 0.002) cortex and the striatum (1.76-fold, p = 0.0001). PiB retention was equivalent in AD patients and controls in areas known to be relatively unaffected by amyloid deposition (such as subcortical WM, pons, and cerebellum).
Yun et al. [104]	2017	VaD and AD	PiB-PET	SVaD patients showed large effect sizes (Cohen’s d >0.8) using all reference regions at PET. Findings were similar for AD patients. Cerebellar gray, whole cerebellum, and whole cerebellum+ brainstem, but not WM or pons, are reliable reference regions for amyloid imaging analysis in SVaD.
Gottesman et al. [105]	2017	VCI, VaD and AD	¹⁸F-Florbetapir PET	An increasing number of midlife vascular risk factors was significantly associated with elevated amyloid SUVR calculated from PET scans; this association was not significant for late-life risk factors. These findings are consistent with a role of vascular disease in the development of AD.
Lee et al. [106]	2011	VaD	PiB-PET; MRI	VaD without abnormal amyloid imaging at PET was more common than expected. Patients with VaD with and without abnormal amyloid imaging differed in clinical and MRI features, although there was considerable overlap
Mok et al. [107]	2010	VaD	PiB-PET; MRI	PiB-PET is feasible for the evaluation of VaD and PiB binding may be common in VaD. Whether presence of PiB binding is associated with a more rapid cognitive decline in VaD requires further study to confirm.
Dao et al. [108]	2015	VCI and VaD	PiB-PET	Increased global amyloid deposition at PiB-PET was significantly associated with greater memory and executive dysfunctions
Lee et al. [109]	2017	VCI and VaD	PiB-PET; MRI	Compared with Aβ-negative cognitively impaired patients with minimal WMH, Aβ-positive patients at PiB-PET with moderate to severe WMH were significantly more likely to exhibit diagonal earlobe crease (OR 7.3, 95% CI 3.4-16.0, p < 0.001).
Shea et al. [110]	2016	VaD and AD	PiB-PET; FDG-PET	On PiB-PET brain imaging, the rate of accurate initial clinical diagnosis (compared with the final post-imaging diagnosis) was 81.5%, 44.4%, 14.3%, 28.6%, 55.6% and 0% for AD, DLB, frontotemporal dementia, vascular dementia, other dementia, and mixed dementia, respectively.
Villemagne et al. [111]	2011	VaD and AD	¹⁸F-Florbetaben PET	¹⁸F-Florbetaben had high sensitivity for AD patients demonstrated significantly high SUVRs (p < 0.0001) in neocortical areas. Most AD patients (96%) and 60% of MCI subjects showed diffuse cortical (18)F-florbetaben retention. In contrast, only 9% of FTLD, 25% of VaD, 29% of DLB, and no PD patients and 16% of controls showed cortical binding.
Kim et al. [112]	2014	VCI and VaD	PiB-PET	Patients with PET PiB(-) svMCI exhibited frontal, language and retrieval type memory dysfunctions, which in patients with PiB(-) SVaD were further impaired and accompanied by visuospatial and recognition memory dysfunctions. Compared with NC, patients with PiB(-) svMCI exhibited cortical thinning in the frontal, perisylvian, basal temporal, and posterior cingulate regions. This atrophy was more prominent and extended further toward the lateral parietal and medial temporal regions in patients with PiB(-) SVaD.
Ye et al. [113]	2015	VCI and VaD	PiB-PET	In subcortical VaD patients, amyloid burden at PET, independently or interactively with SVD, contributed to longitudinal cognitive decline. Amyloid deposition was the strongest poor prognostic factor.
Johnson et al. [115]	2016	VCI, VaD and AD	¹⁸F -AV1451 PET; PiB-PET	¹⁸F-AV1451 PET could have value as a biomarker that reflects both the progression of AD tauopathy and the emergence of clinical impairment.
Scholl et al. [116]	2016	VCI, VaD and AD	¹⁸F - AV1451 PET	PET detection of tau in isocortical regions required the presence of cortical Aβ and was associated with decline in global cognition.

95% CI, 95% confidence interval; AD, Alzheimer’s disease; aMCI, amnestic mild cognitive impairment; Aβ, amyloid-β; CAA, cerebral amyloid angiopathy; CADASIL, cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy; CARASAL, cathepsin A-related arteriopathy with strokes and leukoencephalopathy; CBF, cerebral blood flow; CMRglu, cerebral metabolic rate of glucose; DLB, dementia with Lewy bodies; DTI, diffusion tensor imaging; DWML, deep white matter lesions; FA, fractional anisotropy; FDG, ¹⁸F-fluorodeoxyglucose; FTLD, frontotemporal lobar degeneration; HMPAO SPECT, single photon emission computed tomography with 99mTC hexamethylpropyleneamine oxime; LI, lacunar infarctions; MBs, microbleeds; MCI, mild cognitive impairment; MRI, magnetic resonance imaging; MTA, medial temporal lobe atrophy; NC, normal controls; OR, odds ratio; PD, Parkinson’s disease; PET, positron emission tomography; PiB, 11C-Pittsburgh Compound-B; PSMD, peak width of skeletonized mean diffusivity; rCBF, regional cerebral blood flow; rMRGlu, glucose metabolism; SUVR, standardized uptake value ratio; SVaD, subcortical vascular dementia; SVD, small vessel disease; svMCI, subcortical vascular mild cognitive impairment; TIA, transient ischemic attack; VaD, vascular dementia; VCI, vascular cognitive impairment; VRS, Virchow-Robin spaces; WM, white matter; WMH, white matter hyperintensities.

NEUROIMAGING IN VASCULAR DEMENTIA

Neuroimaging is an essential part of the workup of patients presenting for the first time with cognitive decline [64 –66]. In patients with suspected VCID, neuroimaging should be used to assess the extent, location, and type of vascular lesions. Evidence for significant vascular pathology in the brain usually relies on CT or structural MRI, with the latter being more sensitive, especially if the standardized protocols recommended by the harmonization group are followed [67]. The first applications of brain MRI were developed to understand and analyze the morphological alterations induced on white and grey matter, by using specialized software [68 –70]. The data obtained from these elaborations were used to characterize the neurodegenerative processes and related to the affected physical areas with the associated cognitive functions [71]. While atrophy or deformation of gray matter integrity is visualizable and measurable through macrostructural evaluations, white matter lesions are often injuries at the microstructural level, thus not measurable in macroscopic morphology [72]. MRI should include T1-weighted imaging to detect atrophy, T2-weighted imaging to detect lacunar infarcts and fluid-attenuated inversion recovery (FLAIR) sequences to detect white matter lesions. Furthermore, susceptibility-weighted imaging may detect microbleeds and superficial siderosis. Also, diffusion tensor imaging (DTI) can detect microinfarcts and changes in the white matter tracts; however, these advanced MRI techniques are not routine in clinical practice and are only used in research settings [72, 73]. Another structural hallmark of SVD is the alteration of the Virchow–Robin or perivascular spaces (PVS) [74]. In healthy tissue, these spaces are proposed to form part of a complex brain fluid drainage system that supports interstitial fluid exchange and may also facilitate the clearance of waste products from the brain. The pathophysiological signature of PVS and what this implies regarding their function and interaction with the brain microcirculation, as well as the subsequent downstream effects on the development of lesions in the brain has not been established [75]. It is possible to evaluate the PVS alterations both with a semi-quantitative grading system or with quantitative automatic methods [72, 76]. The latter category produces quantitative measures, which can contribute to an estimate of the global cerebrovascular risk, together with other brain measurements [72]. Also, CT can be used to detect atrophy and some vascular lesions [16]. The findings are varied and should be interpreted in the clinical context, and their nature, severity, location, and no feature are pathognomonic of VCID. PET imaging with FDG describe regional cortical hypometabolism corresponding to a vascular territory injury both in large vessel injuries and in lacunes [77]. Amyloid PET tracers appear to label vascular amyloid in patients with CAA-related, improving differential diagnosis [13]. In fact, patients with negative amyloid imaging and VaD were better at memory but worse at frontal function than patients with AD [78] and VCID was distinct from mild cognitive impairment due to AD in terms of neuropsychological and PET findings [79]. Lacunar infarction appears on T1-weighted or T2-weighted MRI FLAIR sequence as a small hypointense area, surrounded by a rim of hyperintensity, although in some cases the central cavity fluid is not suppressed on FLAIR and it can appear entirely hyperintense despite a clear cerebrospinal fluid-like intensity on other sequences. A lacune has most commonly been regarded as a lesion between 3 and 15 mm [80, 81] (the VCID harmonization standards recommend that up to 1 cm be classified as “small” infarcts) [43, 67]. Because of the poorer spatial resolution of CT, lacunes are seen as small hypodensities areas but they are more likely to be missed. Microinfarcts, which are not visible on gross neuropathological examination, nor generally with neuroimaging, cannot be taken into account for clinical diagnosis [15, 80]. On CT, WMLs are seen as hypodensities or leukoaraiosis described as “extensively patchy or diffuse areas of low attenuation with ill-defined margins extending to the centrum semiovale (from the ventricular margin)” [15]. On MRI, which is much more sensitive to white matter pathology than CT, WMLs are hypointense areas on T1-weighted and hyperintensities on T2-weighted imaging. The T2-FLAIR sequence is useful to high light regions of T2 prolongation in the white matter, corresponding to regions of increased water content with respect to normal white matter. Hyperintensity in the T2-FLAIR sequence represents a region where the white matter is undergoing a process of demyelination or axonal loss (generally present in SVD) [72, 82]. Characterization of WMLs was first qualitative (based on the appearance and position of the identifiable lesions), then, quantitative trough software improvements that allow the quantification of the volume of white matter involved [83]. The WMLs are described in T2 MRI as “hyperintensities extending into the periventricular and deep white matter; extending caps (>10 mm as measured parallel to the ventricle) or irregular halo (>10 mm with broad, irregular margins and extending into deep white matter) and diffusely confluent hyperintensities (>25 mm, irregular shape) or extensive white matter changes (diffuse hyperintensity without focal change)”[15]. DTI is a technique that can be used to obtain a parametric representation of the microstructural organization of structures like the myelinated axonal fibers composing the white matter [43]. The white matter which appears normal on T2-weighted imaging may also have abnormal anisotropy or diffusivity which relates to neuropathology and may have relevance for cognitive function [84]. Abnormalities on DTI are, however, not delineated well enough at present to be incorporated into diagnostic criteria. Nevertheless, a previous paper suggest that SVD alters white matter network integration and segregation, which further predicts cognitive dysfunction [43]. The main parameters obtained from DTI are fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AxD), and radial diffusivity (RD), allowing the assessment of the status of white matter microstructure. A decrease in FA can usually be considered an index of white matter fascicle disorganization due to demyelination or axonal degradation. One of the most common approaches used to analyze DTI is the use of tract-based spatial statistics (TBSS) [85], which acquires a group of images to a common space, projects the mean FA or MD values to the skeletonized profile of the white matter, and then computes cross-subject voxel wise statistics to assess the differences in some regions between various conditions. This method allows the identification of signs of damage and the differential diagnosis between VaD and pure [86]. Other approaches have tried to further increase the sensitivity of DTI to tackle rare genetic diseases such as CADASIL and compared to sporadic SVD and AD [87]. Cortical and subcortical bleeds are best visualized on T2-weighted gradient-recalled echo sequences and susceptibility-weighted MRI scans. The diagnosis of VCID due to microbleeds is an exclusion diagnosis: microbleeds are common in cognitively normal elderly, while microbleeds associated with hypertension are seen in the deep nuclei and brainstem and those with AD are generally lobar in location [88] (see Table 2).

Table 2

Imaging techniques in vascular dementia

Imaging technique	Dementia categories	Advantages	Weaknesses
Computed tomography (CT)	VaD	Detection of atrophy and large vessel vascular lesions	Poorer spatial resolution compared to MRI in macroscopic morphology
MRI T1-weighted imaging	VCI and VaD	Detection of atrophy or deformation of gray matter integrity	Low sensibility for the detection of white matter lesions and in injuries at the microstructural level
MRI T2-weighted imaging	VCI and VaD	Detection of atrophy or deformation of gray matter integrity; detection of lacunar infarcts and microbleeds	Low sensibility for the detection of white matter lesions and in injuries at the microstructural level
MRI fluid-attenuated inversion recovery (FLAIR)	VCI and VaD	Detection of white matter lesion, particularly useful in prodromal phase of VCI and in SVD, improve differential diagnosis	Not routine in clinical practice
MRI diffusion tensor imaging (DTI)	VCI and VaD	Detection of microinfarcts and changes in the white matter tracts, microbleeds and superficial siderosis, particularly useful in prodromal phase of VCI and in SVD	Not routine in clinical practice
PET/TC FDG	VCI and VaD	Vascular territory injury both in large vessel injuries and in lacunas	Not routine in clinical practice, poorer spatial resolution compared to MRI
PET/TC Amyloid	VCI and VaD	Vascular amyloid in patients with CAA-related, particularly useful in prodromal phase of VCI and in SVD	Not routine in clinical practice

FUTURE PERSPECTIVE

As mentioned above, DTI is an MRI technique capable of evaluating the integrity of white matter in greater detail, and will often detect abnormality not visible with other modalities. Its utility in discriminating VCID from other cognitive disorders remains to be established [72]. Functional MRI is a promising tool in neuroimaging research study field but is not suggested in clinical practice. The most common implementation of functional MRI is a T2-weighted sequence of images with a weighting approximatively equal to the tissues T2 relaxation time and with a scan time lower than 5 s to correctly sample the hemodynamic response function. Thus, the analysis of blood oxygen level-dependent signals allows for the indirect measurement of regions of brain activation, often performed during several kinds of stimuli. Therefore, a consistent pattern of synchronized activation in healthy subjects called functional networks has been described, closely associated with the cerebral function driven by those synchronized regions [72]. Further multicenter trials are needed to define a clear golden standard in algorithms, software, and techniques of functional MRI. AD research was one of the first fields where the use of functional MRI has brought major advancements to the understanding of the pathophysiological processes underlying the resulting cognitive decline. A consistent body of work demonstrated that AD alters the functional connectivity in the default mode network, a network that contributes to the default function of the brain and is deactivated during cognitively active tasks [89, 90]. After these first investigations, with the increase of available data and improvements in data quality, many projects have also focused on different functional networks and different degrees of cognitive impairment as well as considering mild cognitive impairment. Other reports evidenced different graph connection properties in patients stratified by the presence of white matter lesions and VaD, describing the constructive reorganization of brain networks secondary to WMLs [91, 92]. Cerebral perfusion is also assessed using SPECT and xenon-contrast CT in clinical practice, and even if rare diseases can be studied with these techniques, MRI is more sensitive [15, 93]. PET enables the imaging of regional glucose metabolic rates, using FDG, which may assist in the differential diagnosis of the various types of cognitive disorders describing several patterns of hypometabolism [94]. According to the EAMN-EAN consensus panel, the use of FDG-PET is supported to facilitate differential diagnosis among different forms of dementia [95, 96]. Literature searches, assessment, and consensual decisions answered the PICO questions whether FDG-PET should be performed, as adding diagnostic value (in terms of increased accuracy, and versus pathology, biomarker-based diagnosis or diagnosis at follow-up) as compared to standard clinical/neuropsychological assessment alone. PET imaging seems particularly useful to differentiate among main forms of dementia, e.g., between AD and VaD, and in patients with atypical presentation or atypical course [96, 97]. Associated patterns of hypometabolism include the thalamus, brainstem, and cerebellum in VaD, as opposed to the posterior cingulate and temporoparietal pattern of AD patients [79 , 99]; these results have not, however, been confirmed in other papers [100]. The main problems also according to panelists are the difficulty of using a clinical reference standard in the issue of mixed pathologies. Nevertheless, panelists supported the utility of FDG-PET in identifying AD in patients with vascular pathology if the characteristic AD pattern of bilateral posterior temporoparietal hypometabolism is present, providing the consideration that hypometabolic regions are not colocalized with large vessel cortical or subcortical infarcts on a structural scan [96]. Furthermore, PET also allows the imaging of specific molecular abnormalities. Further PET tracers are used to focus both on better knowledge about the pathophysiology and early diagnosis, with several implications in therapeutic management and clinical evidence. In vivo measurements of the cerebral amyloid burden (amyloid-β) have been used in the management of patients with AD, but seems promising also in the VCID research field. The imaging of amyloid with compounds, such as the radiolabeled Pittsburgh compound B (¹¹C-PiB) or [¹⁸F]-labelled amyloid-PET tracers such as Florbetapir, Flutemetamol, and Florbetaben, has received much interest and can be considered a biomarker of AD [101 –105]. Amyloid-β imaging has recently been used to support the diagnosis of pure subcortical VaD [106] as well as post-stroke dementia [107], suggesting that the latter is generally a combination of AD and VaD and helped improve the accuracy of diagnosis of dementia subtype [106 , 108–111]. Furthermore ¹¹C-PiB papers suggested that cumulative ischemia without amyloid pathology could lead to hippocampal atrophy and shape changes [52, 112], even if amyloid pathology and vascular pathology may have different effects on the shape of the hippocampus and amygdala [59]. In subcortical VaD patients, amyloid burden, independently or interactively with SVD, contributed to longitudinal cognitive decline [113]. Moreover, amyloid tracers binding may be common even in post-stroke dementia [107]. Furthermore, PET imaging with tau tracers ([¹⁸F]AV-1451, [¹⁸F]THK535149, and [¹¹C]PBB3) is a useful tool in AD research [114-116] and future involvement of these tracers in further dementia study protocols seems promising.

CONCLUSIONS

Cerebrovascular disease is a leading cause of cognitive impairment, accounting for up to 20% of cases of dementia. Neuroimaging is a rapidly developing field and future advances in the methodology will likely offer stronger support to increase the diagnostic accuracy of specific cognitive disorders. PET new tracers, such as amyloid-β and tau ligands, promise a significant impact on future research in dementia. Although vascular dementia is commonly studied using MRI, nuclear medicine provides functional information adding diagnostic and prognostic value.

As the take home message, the combination of MRI and PET allows the identification of patients with mixed dementia, with MRI showing lesions of white matter and PET demonstrating regional impairment of glucose metabolism and amyloid deposition. Functional neuroimaging, in particular, functional MRI and FDG-PET, allows the detection of the localized and/or diffuse metabolic disturbances, and are effective in differentiating vascular from degenerative dementia, like AD.

Footnotes

ACKNOWLEDGMENTS

This work was supported by Sapienza University of Rome, University grant for researcher “Progetti Ateneo 2018”.

Authors’ disclosures available online ().

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