Chapter 11 – Cerebral Small-Vessel Disease

Chapter 11 Cerebral Small-Vessel Disease

Wolf-Dieter Heiss , Michael Brainin , and Alina Schwarz

Introduction

Small-vessel disease (SVD) of the brain denotes a group of diseases with chronic pathological changes in the small vasculature of the brain, most often due to hypertension-related atherothrombosis. Other determinants include genetic dispositions, Alzheimer-related changes and deposits, and chronic lacunes, as well as unspecific changes including atrophy and microhemorrhages and in the subcortex of the brain hemispheres. A classification of different causes of cerebral SVD is given in Table 11.1.

Table 11.1 Classification of small-vessel diseases

Subtype	Name	Examples (where relevant)
1	Arteriolosclerosis
2	Cerebral amyloid angiopathy (hereditary and sporadic)
3	Inherited/genetic SVDs	CADASIL, MELAS, Fabry disease
4	Inflammatory/immunologically mediated SVDs	Nervous system vasculitides (e.g. SLE, scleroderma, ANCA-associated); nervous system vasculitiedes secondary to infection
5	Venous collagenosis
6	Other	Post-radiation angiopathy
Abbreviations:
CADASIL	Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy
MELAS	Mitochondrial encephalopathy lactic acidosis and stroke-like episodes
ANCA	Anti-neutrophil cytoplasmic antibody
SLE	Systemic lupus erythematosus

Source: Banerjee et al. [1], with permission from the publisher.

Recently, consensus diagnostic criteria of subcortical SVD have been published [2] and also the imaging standards for research have been determined [3]. It is important to realize that SVD of the brain primarily affects cogntive and emotional domains and usually does not lead to sudden and dramatic motor impairments as is seen in large-vessel occlusions of the brain. It is much more frequent than previously thought and a leading cause of cognitive decline and functional loss in the elderly [4]. Because the diagnosis of SVD is largely confirmed by imaging, recent advances in the imaging modalities used for clinical routine as well as for research are reported in this chapter.

First, it is important to differentiate between vascular dementia and vascular cognitive decline. Whereas vascular dementia has been well noted since the 1970s, vascular cognitive decline has not been used as a standard diagnosis until the recent revision of the Diagnostic and Statistical Manual of Mental Disorders (DSM) which allows to determine mild cognitive impairment (MCI) of vascular cause.

Vascular Dementia and SVD

Vascular etiologies are the third most common cause of dementia (∼8–10%), following Alzheimer’s disease (AD) (60–70%), and dementia with Lewy bodies (DLB) (10–25%) [5], but these numbers vary considerably according to the different criteria used for vascular dementia (VaD). Furthermore, it is evident from autopsy studies that many patients have mixed dementias, often vascular disease with other conditions [5]. Old criteria for VaD only included multi-infarct dementia [6] or dementia resulting from the cumulative effects of several clinically significant strokes, but the current criteria consider multi-infarct dementia as only one of several subtypes of VaD, including single-stroke dementia and SVD. The three main neuroimaging patterns in VaD are large vessels strokes (macroangiopathy, arteriosclerosis), SVD (microangiopathy, arteriolosclerosis), and microhemorrhages. Single large territorial strokes, especially in the middle cerebral artery (MCA) territory of the dominant hemisphere, or multiple smaller strokes in bilateral anterior cerebral artery (ACA) or posterior cerebral artery (PCA) territories, cause dementia in ∼30% of stroke survivors [5–7]. Single smaller strokes can also cause significant cognitive dysfunction when occurring in particular locations, such as the watershed territories, including the bilateral superior frontal gyrus or bilateral orbitofrontal (ACA/MCA), angular gyrus (ACA/MCA/PCA), temporo-occipital junction, and inferior temporal gyrus (MCA/PCA) [8].

Cerebral SVD is a condition resulting from damage to the cerebral microcirculation; it causes incomplete or complete infarcts in the white matter or in subcortical gray matter nuclei [3–9], which are usually clinically “silent.” Advanced SVD is characterized by white matter hyperintensities (WMHs), enlarged perivascular spaces (PVS), lacunes, microbleeds, and cerebral atrophy [10]. These abnormalities are seen in up to 10% of persons in the seventh decade and in above 85% in their ninth decade. Lacunes must be differentiated from perivascular Virchow-Robin spaces. Lacunar strokes are small complete infarcts (2–15 mm). When located in the caudate head, anterior thalamus, or the mamillothalamic tract [11], lacunas can cause significant cognitive and/or behavioral dysfunction due to the extended functional deafferentation of the cortical areas.

Current criteria consider multi-infarct dementia as only one of several subtypes of vascular dementia, including single-stroke dementia and SVD. The three main neuroimaging patterns in VaD are large vessels strokes, SVD, and microhemorrhages.

SVD results from damage to the cerebral microcirculation and causes incomplete or complete infarcts. When located in the caudate head, anterior thalamus, or the mamillothalamic tract, lacunar strokes (small complete infarcts – 2–15 mm) can cause significant cognitive and/or behavioral dysfunction due to the extended functional deafferentation of the cortical areas.

Imaging Morphologic Substrates of VaD

Neuroimaging provides important information on neuroanatomical substrate of the disorder, plays an important role in the diagnosis, and adds to prediction of VaD (Figure 11.1).

Figure 11.1 Imaging markers of small-vessel disease.

ASL – arterial spin labeling; CMB – cerebral microbleed; cSS – cortical superficial siderosis, DTI – diffusion tensor imaging; EPVS – enlarged perivascular spaces; FDG – fludeoxyglucose; fMRI – functional MRI; ICH – intracerebral hemorrhage; MRI – magnetic resonance imaging; PET – positron emission tomography; WMHs – white matter hyperintensities.

Source: Banerjee et al. [1], with permission from the publisher.

Most acute stroke patients undergo computed tomography (CT) brain imaging; thus studies using CT are representative of the whole clinical population. In clinical practice, CT is performed primarily to exclude hemorrhage and some stroke mimics (such as brain tumors), and can often demonstrate early signs of ischemia (e.g. swelling, hypodensity, and hyperdense vessels) and old stroke lesions. Furthermore, the presence and severity of white matter lesions (WMLs) and brain atrophy can also be readily determined from CT brain scans – features which may predict subsequent cognitive impairment and dementia. There is very good agreement between brain atrophy and presence of moderate-severe WMLs on CT and MRI measures [12, 13].

Magnetic resonance imaging (MRI) remains the key neuroimaging modality in VaD [14]. If not contraindicated, MRI, rather than CT, is preferred for research and routine clinical use because it has higher sensitivity and specificity for detecting pathological changes [15] (Figure 11.2).

Figure 11.2 (A) Periventricular and deep white matter lesion in centrum semiovale and dilated lateral ventricles in 65-year-old woman with VCI. (B) Focal myelin pallor in periventricular frontal white matter in patient with dysexecutive syndrome. Insert: Perivascular lacunes around fibrotic arterioles in frontal white matter. Klüver-Barrera, ×200.

(Modified from Jellinger [5], with permission from the publisher.)

Standards for neuroimaging with a widely accepted terminology permitting comparison of findings between centers have been recommended (STandards for ReportIng Vascular changes on nEuroimaging, STRIVE) [3]. Numerous studies identified MRI markers of SVD (lacunes, WMHs, cerebral microbleeds, silent infarcts, white matter changes, global cerebral atrophy, medial-temporal lobe atrophy) as determinants of VaD. Vascular lesions traditionally attributed to VaD comprise subcortical areas of the brain, especially sub-frontal white matter circuits, strategic areas of single infarction such as the dominant thalamus or angular gyrus, deep frontal areas and the left hemisphere, and bilateral brain infarcts or volume-driven cortical-subcortical infarctions reaching a critical threshold of tissue loss or injury [5]. Recently, also enlargements of perivascular spaces were identified as MRI markers of SVD; these are associated with the pathogenesis of vascular-related cognitive impairment in older individuals [16].

SVD identified on MRI in the white matter is called leukoaraiosis [17] (Figure 11.3).

Figure 11.3 Different stages of WMC assessed on transverse, (A)–(C) fluid-attenuated inversion-recovery MR and (D)–(F), CT images in the same patients. MR imaging shows higher sensitivity in the detection of subtle WMCs, especially small punctuate lesions (arrow in [A]). However, some of those focal lesions can also be seen on CT images (arrow in [D]). Beginning confluent white matter lesions (arrowhead in [B] and [E]) can almost equally be assessed on MR and CT images. Confluent WMCs ([C] and [F]) can be equally detected on MR and CT images.

(Modified from Wattjes et al. [12], with permission from the publisher.)

Leukoaraiosis presents as multiple punctuate or confluent lesions, but more often as incomplete infarcts, and is commonly seen in healthy elderly patients and in subjects with migraine. The markers of SVD – WMHs, lacunes, dilated vascular spaces, microbleeds, and brain volume – are related to decrease in regional cerebral blood flow [18] and must be clearly defined to be reliably used for the diagnosis of this vascular disorder and its progression [19, 20]. Some studies have suggested that to assess in single cases how much the lesion load affects cognition, a threshold of 10 cm² [21] or 25% of total white matter [22] is required before VaD is detectable clinically. On FLAIR images, incomplete infarcts present as hyperintensities, whereas complete infarcts present as lacunas, which are hypointense in relation to the brain and isointense to the cerebrospinal fluid. After stroke, medial temporal lobe atrophy is rather related to cognitive impairment than markers of SVD [23] (Figure 11.4). When SVD causes subcortical VaD, this is associated with the pathology of Binswanger’s disease [24].

Figure 11.4 Secondary brain atrophy in a 55-year-old patient with documented SVD Baseline (middle). The follow-up scan (T1-weighted MRI; right) shows clear sulcal widening (arrow B, C, and D), particularly in occipital regions, and ventricular enlargement (arrow A) without new infarctions during the observational period. Fluid-attenuated inversion recovery image (left) shows substantial white matter hyperintensity.

(From Wardlaw et al. [3], with permission from the publisher.)

MRI remains the key neuroimaging modality in vascular dementia. Numerous studies identified MRI markers of SVD – lacunes, WMHs, cerebral microbleeds, silent infarcts, white matter changes, global cerebral atrophy, medial-temporal lobe atrophy – as determinants of vascular dementia. SVD identified on MRI in the white matter is called leukoaraiosis.

Microhemorrhages are the third major neuroimaging aspect of VaD (Figure 11.5), and in one study they were found in 65% of VaD cases [25]. While macrohemorrhages associated with cognitive impairment (e.g. venous infarcts) can be seen on conventional T1- and T2-weighted spin echo images, microhemorrhages often cannot be seen in these sequences, but can be detected accurately using T2*-weighted gradient echo images (Figures 11.5 and 11.6). In many cases, it is likely that microhemorrhages and white matter ischemic disease are caused by systemic hypertension [26].

Figure 11.5 Illustrative imaging of brain microbleed (BMBs) and their mimics. (A) BMBs (short arrows). Note also the old intracerebral hemorrhage in the right occipital region (long arrow). Not all BMBs are marked as they are too numerous. (B) Basal ganglia calcification (arrows) on MRI (left) and CT (right). (C) Calcification (long arrow) mimicking a BMB on MRI (left), CT (right). Also true BMBs (arrowheads) and old intracerebral hemorrhage (short arrow). (D) Flow void mimicking a BMB (left, circled), enlarged on right. Note the vessel in a sulcus leading up to the black dot indicating that it is a vessel flow void in cross section.

(From Cordonnier et al. [27], with permission from the publisher.)

Microhemorrhages can be detected accurately using T2*-weighted gradient echo images.

Molecular Imaging in the Diagnosis of Vascular Dementia

The diagnosis of vascular cognitive impairment (VCI) is difficult because there is no consensus on clinical criteria. Additionally, cerebral arteriosclerosis frequently is present in elderly patients and even small infarcts or WMLs occur in elderly subjects without either cognitive impairment or degenerative dementia. There is a tendency to diagnose VCI on the basis of MRI, which has a high sensitivity for WMHs, which may be seen in normal elderly as well as those with VCI. Pathological studies reveal a high incidence of both vascular and degenerative pathology of the Alzheimer type. This leads to diagnostic confusion when only the MRI is used, and there are mixed pathologies. PET provides additional information, which increases the diagnostic certainty (Figure 11.6).

Figure 11.6 Recently identified imaging findings observed in SVD. (A) Strictly lobar microbleeds in a patient with CAA. (B) Mixed, but predominantly deep, microbleeds in a patient presenting with a spontaneous intracerebral hemorrhage. (C) Cortical superficial siderosis in a patient with CAA. (D) Enlarged perivascular spaces in the cortical white matter. (E) DTI map showing color-coded tract directionality in a patient with ischemic stroke. (F) PiB amyloid PET (top) and MRI in a patient with extensive WMHs and amyloid retention.

(Modified from Banerjee et al. [1], with permission from the publisher.)

PET can support the clinical diagnosis by visualizing cerebral functions in typically affected brain regions. PET of ¹⁸F-2-fluoro-2-deoxy-D-glucose (FDG) for measurement of regional cerebral glucose metabolism (rCMRGl) has shown a typical metabolic pattern in patients with probable AD: hypometabolism in temporoparietal and frontal association areas, but relative recessing of primary cortical areas, basal ganglia, and cerebellum. In VCI a different pattern is seen [28]: in VCI FDG-PET can clearly differentiate scattered areas of focal cortical and subcortical hypometabolism that differ from the typical metabolic pattern seen in AD with marked hypometabolism affecting the association areas [29]. In VCI patients [30] a significant reduction of regional cerebral glucose metabolism (rCMRglc) in comparison to normal patients was observed in widespread cerebral regions (middle frontal cortex, temporoparietal cortex, basal ganglia, cerebellum, and brainstem) (Figure 11.7).

Figure 11.7 Widespread SVD affecting cortex, basal ganglia, and white matter causing severe reduction of glucose metabolism in gray matter structures detected by FDG-PET.

(Courtesy of Professor Wolf-Dieter Heiss.)

In subcortical areas and primary sensorimotor cortex this hypometabolism was more marked than in AD while the association areas were less affected than in AD. A metabolic ratio (rCMRglc of association areas divided by rCMRglc of primary areas, basal ganglia, cerebellum, and brainstem) mainly reflecting the contrast between association areas and subcortical regions was significantly lower in AD than that in VCI. Whereas it was not possible to identify a single region that could discriminate between VCI and AD, the composite pattern, as expressed in the metabolic ratio, was significantly different. Considering that the VCI patients in that study had mainly WMHs and small subcortical infarcts, it suggests furthermore that even small infarcts in combination with WMHs may contribute to cognitive decline. Rather than the total volume of infarction, the volume of functional tissue loss is more important, since it also includes the effects of incompletely infarcted tissue and morphologically intact but deafferented cortex. Subcortical ischemic vascular disease (SIVD) can be distinguished from clinically probable AD by a more diffuse pattern of hypometabolism involving also the primary cortices, basal ganglia, thalamus, and cerebellum (Figure 11.8).