Vascular Dementia (VaD) and Neuropsychiatric Symptoms (NPS)

Normal Elderly vs. VaD brain
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Axial FLAIR MRI scans of elderly brains

Neuropsychiatric symptoms (NPS) are common in patients with dementia. The most common NPS encountered in dementia are apathy, irritability, agitation, depression, delusions, hallucinations, anxiety, disinhibition, aberrant motor behaviour, sleep disturbances, and eating abnormailities[1]. These symptoms are a major source of patients’ distress, caregiver burden and a primary contributor to institutionalization[2]. Moreover, while psychotropic drugs may alleviate certain NPS, some may have severe adverse effects. Therefore, it is important to better comprehend these symptoms as they have implications for treatment and care. Currently, studies analyzing NPS in vascular dementia (VaD) are becoming more prominent, especially in comparison to the most common dementia type, Alzheimer's disease. Future directions are looking towards not only quantifying these NPS in various dementia types, but are also relating them to specific neuroanatomical correlates, such as white matter hyperintensities and localized regions of atrophy. Because both VaD and AD have specific phenotypes upon MRI analysis, the ultimate goal is to be able to utilize both the classic MRI scans and knowledge of NPS prevalence to better characterize vascular dementia and other dementia types.

Comparing the prevalence of NPS in VaD and Alzheimer's disease (AD)

The Neuropsychiatric Inventory (NPI)

A standardized method to evaluate NPS is by using a Neuropsychiatric Inventory (NPI), which was developed by Cummings (1997)[1]. An NPI contains the twelve most common NPS previously mentioned and it is administered to the patient’s caregiver. The caregiver is asked a series of scripted questions regarding each particular symptom and is then asked to rate the frequency and severity of each NPS[3]. The NPI is a commonly used scale to assess patients with dementia subtypes and other neurological disorders with acceptable validity and reliability in outpatient settings[3].

NPS frequencies in VaD and AD

Previous studies have compared the frequencies of NPS in various dementia types. However, the findings remain inconclusive[4]. Some have reported irritability[5], depression, and anxiety[4] to be significantly more prevalent in AD than VaD, while other studies have suggested the converse to be true[6]. Futhermore, other studies have suggested no significant differences in NPS between the two diagnoses[7-8]. Delving further into one of said studies, Echávarri and colleagues (2013) had pathologically demonstrated for the first time that unlike what has been previously reported in the literature with regards to comparing the prevalence of NPS in VaD and AD, that there were no significant differences[7]. The primary strength of this study is that for each diagnosed dementia group, the samples obtained had confirmed pathology with specific biomarkers being detected post-mortem. However, it must also be noted that this was a retrospective study and, therefore, certain limitations with this methodology should also be taken into account. Specifically, the caveat is a result of various time frames of approximately 5.6 months with a range of one month to two years between the last neuropsychiatric assessment and death[7]. Since neurodegenerative processes progress rapidly towards the later stages in the trajectory of the disease, two years can arguably be considered a significant time frame with much opportunity for drastic changes manifesting in the form of more severe NPS. In addition, the NPS were not measured with standardized testing such as the NPI[1]. Similar to this study, Srikanth (2005) also demonstrated no difference of NPS between AD and VaD; however, their sample size was relatively small and the VaD group lacked homogeneity with regards to the localization of infarcts and ischemic patterns of change[8]. The lack of concurrence in these cases, therefore, emphasizes the difficulty in comparing and attempting to characterize certain NPS with many dementia types.

Summary of Previous NPS comparisons in VaD and AD
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Venn Diagram highlighting key comparative studies and their findings

A general but essential step in the methodology of studies comparing NPS is not only the use of a standardized measure to compare prevalence, but also to consider possible confounds that may be driving the severity of NPS. For example, age is a major predictor and risk factor for developing dementia. Moreover, age has been shown to be one of many other factors that increases the risk of mortality post-dementia diagnosis[9]. Along with age, Mini-Mental State Examination (MMSE)[10] and Clinical Dementia Rating (CDR)[11] scores are evaluations that should also be considered when comparing prevalence of NPS as they hone in on cognitive abilities and severity of dementia. Basic demographics such as gender, race, number of years of education, marital status among others also allude to other genetic and environmental effects that may or may not be at play. Finally, as previously indicated, the use of psychotropic drugs would be expected to reduce certain NPS if prescribed and, therefore, be less prevalent in those patients compliant with their medications. This remains a major limitation to many retrospective studies as it is difficult to account for the use of said medications, as it presumes that the data being obtained contains a complete and reliable list of medications used at the time the symptoms presented. Thus, it would be interesting to increase the number of studies adopting prospective methodologies to better control for these factors.

Relating NPS to neuroanatomical correlates

Key radiographic findings for a VaD brain on MRI images

White matter lesions (WML) increase with age
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In this graph, women:inverted∆, broken line; Men:•, solid line
Data obtained from Ikram, M.A., Vrooman, H.A., Vernooij, M.W., van der Lijn, F. Hofman, A., van der Lugt, A., et al. (2008)
Brain tissue volumes in the general elderly population.The Rotterdam Study. Neurobiol Aging, 29(6), 886.[28]

While the association between cerebrovascular disease and AD has been known for quite some time, there has been challenges in refining the exact underlying pathology of VaD or the less severe precursor state vascular cognitive impairment (VCI)[12]. Because infarcts differ in size, locality, and number among cases and because these infarcts are also a typical finding in the elderly population irrespective of dementia diagnosis or clinical stroke, the search for defining VCI and later VaD becomes a challenge[12]. The spectrum used to discern the degree to which infarcts would be considered “abnormal” relies primarily on the pattern of ischemic changes. For instance, white matter hyperintensities (WMH) are one of the common findings in an elderly normal individual, but profuse WMH typically found in the deep and periventricular white matter are indicative of a greater white matter disease burden as seen in the significant micro-and macro-angiopathic changes[12].

It is not uncommon for infarcts to concur with Alzheimer's disease pathology in the brains of elderly people[13-16]. While the specific interaction of these underlying mechanisms remains uncertain, it has been suggested that the infarcts in those diagnosed with AD further disrupt cognitive function[16]. Because there is no established pathological criterion for mixed AD and VaD, the risk of clinically underdiagnosing and underestimating the additive effects remains a complex issue. There are also neuroimaging studies that have investigated and proposed that white matter degeneration and microbleeds may contribute to cognitive impairment, but again these conclusions remain unclear[17-18].

Fazekas Scale

Neuroimaging techniques are extremely useful for studying the underlying pathology of vascular dementia as well as other dementia types such as Alzheimer's disease. Specifically, T1-weighted images and fluid-attenuated inversion recovery (FLAIR), and diffusion tensor imaging (DTI) offer high resolution and efficient means to view the anatomy[12]. As previously noted, WMH and lacunes are common among the elderly population; this generally serves as evidence for small blood vessel disease. The Fazekas scale is commonly used to qualitatively assess these morphological changes as it provides an overall impression of the WMH for the entire brain[19]. The most effective means to obtain an accurate score is on the transverse T2 weighted or FLAIR images.

Fazekas Scale
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The scale was created and described in Fazekas, F., Chawluk, J.B., Alavi, A.,
Hurtig, H.I., Zimmerman, R.A. (1987) MR Signal Abnormalities 1.5 T in Alzheimer’s
Dementia and Normal Aging. American Journal of Roentgenology, 148(2), 351-356.

Each level corresponds to a higher degree of confluency of lesions
N.B. Fazekas score 0 (no lesions) is not shown[19]

For more extensive information on using MRI as a key tool in understanding VaD and other dementia types, please see[29]:
Barkhof, F., Hazewinkel, M., Binnewijzend, M, Smithuis, R. (2012) The Radiology Assistant, Dementia: Role of MRI
The Radiology Assistant

Relating white matter hyperintensities (WMH) with certain NPS

Studies relating the volumes of WMH and certain NPS in different dementia types are relatively new. Again, since WMH are present in normal aging brains, it is difficult to propose causational studies. The paradigm of the “chicken or the egg tale” poses a complex problem. Although, the current general hypothesis is that the WMH clinically contribute to the manifestation of NPS. Evidence for this suggested hypothesis is currently generated through correlational studies. Just as the studies that compared the prevalence of NPS focused on AD and VaD subjects, so too do the studies that relate NPS to WMH volumes. However, other dementia types are also being explored. Given that AD is the most common form of dementia, there have been studies specifically targeting AD as seen in the work of Starkstein and colleagues (2011). In their study, they found frontal and right parietal WMH to be the most robust anatomical correlates of depression and apathy[20]. This result has been further replicated in mild dementia patients[21]. Lastly, hallucinations, depression, and anxiety have been correlated to periventricular WMH volumes in those with AD and VaD type dementias[22].

Relating areas of atrophy with certain NPS

In addition to relating NPS with WMH, some studies have also looked into the relation between NPS and localized regions of atrophy. Since the ultimate goal of these investigations is to gain further insight on the neuroanatomical correlates in dementia, majority of research endeavours have concentrated on AD. However, future directions could use the results of current literature and determine whether the relation between NPS and the focal atrophy as seen in AD remains significant irrespective of the dementia type.

In reviewing the existing literature, it has been suggested that atrophy in the anterior cingulate in AD is related to apathy[23-24]. Additionally, atrophy in the amygdala has been linked to aberrant motor behaviours in early AD with possible relations with irritability and anxiety[25]; though the direction of correlation was not made clear. Irritability has also been negatively correlated with right posterior insular cortex atrophy in AD[26]. Lastly, Shanks and colleagues (2004) have shown delusions to be related to the anterior part of the right hemisphere in those with AD[27]. Having mentioned the above, much work is still needed to better characterize NPS not only with regards to localized neuroanatomical correlates but also to gain further insight on the clinical profile of various dementias, specifically the neuropsychiatric features.

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19. Fazekas, F., Chawluk, J.B., Alavi, A., Hurtig, H.I., Zimmerman, R.A. MR Signal Abnormalities 1.5 T in Alzheimer’s Dementia and Normal Aging. American Journal of Roentgenology. 148(2), 351-356 (1987).
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Images and external links:
28. Ikram, M.A., Vrooman, H.A., Vernooij, M.W., van der Lijn, F. Hofman, A., et al. Brain tissue volumes in the general elderly population.The Rotterdam Study. Neurobiol Aging. 29(6), 886 (2008).
29. Barkhof, F., Hazewinkel, M., Binnewijzend, M, Smithuis, R. The Radiology Assistant, Dementia: Role of MRI (2012).
http://www.radiologyassistant.nl/en/p43dbf6d16f98d/dementia-role-of-mri.html#i445b174abfa75

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