Thalamic Lesions in Vascular Dementia

Neuroimaging in Dementia: More than Typical Alzheimer Disease

Alzheimer disease (AD) is the most common cause of dementia. The prevailing theory of the underlying pathology assumes amyloid accumulation followed by tau protein aggregation and neurodegeneration. However, the current antiamyloid and antitau treatments show only variable clinical efficacy. Three relevant points are important for the radiologic assessment of dementia. First, besides various dementing disorders (including AD, frontotemporal dementia, and dementia with Lewy bodies), clinical variants and imaging subtypes of AD include both typical and atypical AD. Second, atypical AD has overlapping radiologic and clinical findings with other disorders. Third, the diagnostic process should consider mixed pathologies in neurodegeneration, especially concurrent cerebrovascular disease, which is frequent in older age. Neuronal loss is often present at, or even before, the onset of cognitive decline. Thus, for effective emerging treatments, early diagnosis before the onset of clinical symptoms is essential to slow down or stop subsequent neuronal loss, requiring molecular imaging or plasma biomarkers. Neuroimaging, particularly MRI, provides multiple imaging parameters for neurodegenerative and cerebrovascular disease. With emerging treatments for AD, it is increasingly important to recognize AD variants and other disorders that mimic AD. Describing the individual composition of neurodegenerative and cerebrovascular disease markers while considering overlapping and mixed diseases is necessary to better understand AD and develop efficient individualized therapies.

Association of total cerebral small vessel disease burden with the cavitation of recent small subcortical infarcts

BACKGROUND

Recent small subcortical infarcts (RSSIs) could evolve into cavitation (lacunes) or non-cavitation (white matter hyperintensities or disappearance) during the chronic period, but the factors involved remain unclear.

PURPOSE

To explore the association between total cerebral small vessel disease (CSVD) burden and lesion cavitation.

MATERIAL AND METHODS

We retrospectively selected 202 inpatients with an isolated RSSI who underwent baseline and follow-up magnetic resonance imaging (median interval = 16.6 months; interquartile range [IQR]=8.2-30.1). Inpatients were divided into cavitation and non-cavitation groups depending on whether a fluid-filled cavity formed. Data including demographic, clinical, and radiological features were collected and analyzed. To determine total CSVD burden, four imaging markers, including lacunes, microbleeds, white matter hyperintensities, and enlarged perivascular spaces, were rated and summed as a final practical score between 0 and 4.

RESULTS

Overall, 137 (67.8%) patients progressed to cavitation and 65 (32.2%) to non-cavitation. Binary multivariable regression analysis showed that the baseline total CSVD burden (P = 0.005) and infarct diameter (P = 0.002) were independent risk factors for cavitation. A severe total burden (scores of 3-4) at baseline was independently related to cavitation (P = 0.001). Moreover, the total CSVD burden score varied from 2 (IQR=1-3) at baseline to 3 (IQR=2-4) at follow-up. The extent of the increase in total burden was correlated with cavitation (r = 0.201; P = 0.004).

CONCLUSION

Total CSVD burden, both the baseline value and extent of increase, was positively associated with cavitation. RSSIs with severe total CSVD burden at baseline have a greater potential to become cavitated.

Ontario Neurodegenerative Disease Research Initiative (ONDRI): Structural MRI Methods and Outcome Measures

The Ontario Neurodegenerative Research Initiative (ONDRI) is a 3 years multi-site prospective cohort study that has acquired comprehensive multiple assessment platform data, including 3T structural MRI, from neurodegenerative patients with Alzheimer's disease, mild cognitive impairment, Parkinson's disease, amyotrophic lateral sclerosis, frontotemporal dementia, and cerebrovascular disease. This heterogeneous cross-section of patients with complex neurodegenerative and neurovascular pathologies pose significant challenges for standard neuroimaging tools. To effectively quantify regional measures of normal and pathological brain tissue volumes, the ONDRI neuroimaging platform implemented a semi-automated MRI processing pipeline that was able to address many of the challenges resulting from this heterogeneity. The purpose of this paper is to serve as a reference and conceptual overview of the comprehensive neuroimaging pipeline used to generate regional brain tissue volumes and neurovascular marker data that will be made publicly available online.

Performance comparison of 10 different classification techniques in segmenting white matter hyperintensities in aging

INTRODUCTION

White matter hyperintensities (WMHs) are areas of abnormal signal on magnetic resonance images (MRIs) that characterize various types of histopathological lesions. The load and location of WMHs are important clinical measures that may indicate the presence of small vessel disease in aging and Alzheimer's disease (AD) patients. Manually segmenting WMHs is time consuming and prone to inter-rater and intra-rater variabilities. Automated tools that can accurately and robustly detect these lesions can be used to measure the vascular burden in individuals with AD or the elderly population in general. Many WMH segmentation techniques use a classifier in combination with a set of intensity and location features to segment WMHs, however, the optimal choice of classifier is unknown.

METHODS

We compare 10 different linear and nonlinear classification techniques to identify WMHs from MRI data. Each classifier is trained and optimized based on a set of features obtained from co-registered MR images containing spatial location and intensity information. We further assess the performance of the classifiers using different combinations of MRI contrast information. The performances of the different classifiers were compared on three heterogeneous multi-site datasets, including images acquired with different scanners and different scan-parameters. These included data from the ADC study from University of California Davis, the NACC database and the ADNI study. The classifiers (naïve Bayes, logistic regression, decision trees, random forests, support vector machines, k-nearest neighbors, bagging, and boosting) were evaluated using a variety of voxel-wise and volumetric similarity measures such as Dice Kappa similarity index (SI), Intra-Class Correlation (ICC), and sensitivity as well as computational burden and processing times. These investigations enable meaningful comparisons between the performances of different classifiers to determine the most suitable classifiers for segmentation of WMHs. In the spirit of open-source science, we also make available a fully automated tool for segmentation of WMHs with pre-trained classifiers for all these techniques.

RESULTS

Random Forests yielded the best performance among all classifiers with mean Dice Kappa (SI) of 0.66±0.17 and ICC=0.99 for the ADC dataset (using T1w, T2w, PD, and FLAIR scans), SI=0.72±0.10, ICC=0.93 for the NACC dataset (using T1w and FLAIR scans), SI=0.66±0.23, ICC=0.94 for ADNI1 dataset (using T1w, T2w, and PD scans) and SI=0.72±0.19, ICC=0.96 for ADNI2/GO dataset (using T1w and FLAIR scans). Not using the T2w/PD information did not change the performance of the Random Forest classifier (SI=0.66±0.17, ICC=0.99). However, not using FLAIR information in the ADC dataset significantly decreased the Dice Kappa, but the volumetric correlation did not drastically change (SI=0.47±0.21, ICC=0.95).

CONCLUSION

Our investigations showed that with appropriate features, most off-the-shelf classifiers are able to accurately detect WMHs in presence of FLAIR scan information, while Random Forests had the best performance across all datasets. However, we observed that the performances of most linear classifiers and some nonlinear classifiers drastically decline in absence of FLAIR information, with Random Forest still retaining the best performance.

The effect of hippocampal function, volume and connectivity on posterior cingulate cortex functioning during episodic memory fMRI in mild cognitive impairment

Objectives

Diminished function of the posterior cingulate cortex (PCC) is a typical finding in early Alzheimer’s disease (AD). It is hypothesized that in early stage AD, PCC functioning relates to or reflects hippocampal dysfunction or atrophy. The aim of this study was to examine the relationship between hippocampus function, volume and structural connectivity, and PCC activation during an episodic memory task-related fMRI study in mild cognitive impairment (MCI).

Method

MCI patients (n = 27) underwent episodic memory task-related fMRI, 3D-T1w MRI, 2D T2-FLAIR MRI and diffusion tensor imaging. Stepwise linear regression analysis was performed to examine the relationship between PCC activation and hippocampal activation, hippocampal volume and diffusion measures within the cingulum along the hippocampus.

Results

We found a significant relationship between PCC and hippocampus activation during successful episodic memory encoding and correct recognition in MCI patients. We found no relationship between the PCC and structural hippocampal predictors.

Conclusions

Our results indicate a relationship between PCC and hippocampus activation during episodic memory engagement in MCI. This may suggest that during episodic memory, functional network deterioration is the most important predictor of PCC functioning in MCI.

Key Points

• PCC functioning during episodic memory relates to hippocampal functioning in MCI.

• PCC functioning during episodic memory does not relate to hippocampal structure in MCI.

• Functional network changes are an important predictor of PCC functioning in MCI.

Electronic supplementary material

The online version of this article (doi:10.1007/s00330-017-4768-1) contains supplementary material, which is available to authorized users.

Automatic Detection of White Matter Hyperintensities in Healthy Aging and Pathology Using Magnetic Resonance Imaging: A Review

White matter hyperintensities (WMH) are commonly seen in the brain of healthy elderly subjects and patients with several neurological and vascular disorders. A truly reliable and fully automated method for quantitative assessment of WMH on magnetic resonance imaging (MRI) has not yet been identified. In this paper, we review and compare the large number of automated approaches proposed for segmentation of WMH in the elderly and in patients with vascular risk factors. We conclude that, in order to avoid artifacts and exclude the several sources of bias that may influence the analysis, an optimal method should comprise a careful preprocessing of the images, be based on multimodal, complementary data, take into account spatial information about the lesions and correct for false positives. All these features should not exclude computational leanness and adaptability to available data.

Subcortical hyperintensity volumetrics in Alzheimer's disease and normal elderly in the Sunnybrook Dementia Study: correlations with atrophy, executive function, mental processing speed, and verbal memory

INTRODUCTION

Subcortical hyperintensities (SHs) are radiological entities commonly observed on magnetic resonance imaging (MRI) of patients with Alzheimer's disease (AD) and normal elderly controls. Although the presence of SH is believed to indicate some form of subcortical vasculopathy, pathological heterogeneity, methodological differences, and the contribution of brain atrophy associated with AD pathology have yielded inconsistent results in the literature.

METHODS

Using the Lesion Explorer (LE) MRI processing pipeline for SH quantification and brain atrophy, this study examined SH volumes of interest and cognitive function in a sample of patients with AD (n = 265) and normal elderly controls (n = 100) from the Sunnybrook Dementia Study.

RESULTS

Compared with healthy controls, patients with AD were found to have less gray matter, less white matter, and more sulcal and ventricular cerebrospinal fluid (all significant, P <0.0001). Additionally, patients with AD had greater volumes of whole-brain SH (P <0.01), periventricular SH (pvSH) (P <0.01), deep white SH (dwSH) (P <0.05), and lacunar lesions (P <0.0001). In patients with AD, regression analyses revealed a significant association between global atrophy and pvSH (P = 0.02) and ventricular atrophy with whole-brain SH (P <0.0001). Regional volumes of interest revealed significant correlations with medial middle frontal SH volume and executive function (P <0.001) in normal controls but not in patients with AD, global pvSH volume and mental processing speed (P <0.01) in patients with AD, and left temporal SH volume and memory (P <0.01) in patients with AD.

CONCLUSIONS

These brain-behavior relationships and correlations with brain atrophy suggest that subtle, yet measurable, signs of small vessel disease may have potential clinical relevance as targets for treatment in Alzheimer's dementia.

An algorithmic approach to structural imaging in dementia

Accurate and timely diagnosis of dementia is important to guide management and provide appropriate information and support to patients and families. Currently, with the exception of individuals with genetic mutations, postmortem examination of brain tissue remains the only definitive means of establishing diagnosis in most cases, however, structural neuroimaging, in combination with clinical assessment, has value in improving diagnostic accuracy during life. Beyond the exclusion of surgical pathology, signal change and cerebral atrophy visible on structural MRI can be used to identify diagnostically relevant imaging features, which provide support for clinical diagnosis of neurodegenerative dementias. While no structural imaging feature has perfect sensitivity and specificity for a given diagnosis, there are a number of imaging characteristics which provide positive predictive value and help to narrow the differential diagnosis. While neuroradiological expertise is invaluable in accurate scan interpretation, there is much that a non-radiologist can gain from a focused and structured approach to scan analysis. In this article we describe the characteristic MRI findings of the various dementias and provide a structured algorithm with the aim of providing clinicians with a practical guide to assessing scans.

Cavitation after acute symptomatic lacunar stroke depends on time, location, and MRI sequence

BACKGROUND AND PURPOSE

Definitions for chronic lacunar infarcts vary. Recent retrospective studies suggest that many acute lacunar strokes do not develop a cavitated appearance. We determined the characteristics of acute lacunar infarcts on follow-up MRI in consecutive patients participating in prospective research studies.

METHODS

Patients with acute lacunar infarction on diffusion-weighted imaging were selected from 3 prospective cohort studies of minor stroke imaged within <24 hours of onset. Follow-up MRI was performed at 30 days (Vascular Imaging of Acute Stroke for Identifying Predictors of Clinical Outcome and Recurrent Ischemic Events [VISION] study, n=21) or 90 days (VISION-2 and CT and MRI in the Triage of TIA and Minor Cerebrovascular Events to Identify High Risk Patients [CATCH] studies, n=34). Evidence of cavitation on MRI was rated separately on fluid-attenuated inversion recovery, T1, and T2 sequences by 2 independent study physicians; discrepant readings were resolved by consensus.

RESULTS

Probable or definite cavitation on any sequence was more common at 90 days compared with 30 days (P≤0.001 for all sequences). At 90 days, evidence of cavitation was seen on at least 1 sequence in 33 of 34 patients (97%). The T1-weighted sequence was most sensitive to the presence of cavitation (94% at 90 days). By contrast, the fluid-attenuated inversion recovery sequence frequently failed to show evidence of cavitation in the brain stem or thalamus (only 10 of 18 [56%] showed cavitation).

CONCLUSIONS

MRI scanning at 90 days with T1-weighted imaging reveals evidence of cavitation in nearly all cases of acute lacunar infarction. By contrast, reliance on fluid-attenuated inversion recovery alone will miss many cavitated lesions in the thalamus and brain stem. These factors should be taken into account in the development of standardized criteria for lacunar infarction on MRI.

A short-term scan-rescan reliability test measuring brain tissue and subcortical hyperintensity volumetrics obtained using the lesion explorer structural MRI processing pipeline

Lesion Explorer (LE) is a reliable and comprehensive MRI-derived tissue segmentation and brain region parcellation processing pipeline for obtaining intracranial tissue and subcortical hyperintensity (SH) volumetrics. The processing pipeline segments: gray (GM) and white matter (WM); sulcal (sCSF) and ventricular cerebrospinal fluid (vCSF); periventricular (pvSH) and deep white subcortical hyperintensities (dwSH); and cystic fluid filled lacunar-like infarcts (Lacunar); into 26 regions of interest. A short-term scan-rescan reliability test was performed on 20 healthy volunteers: 10 older (mean = 77.7 years, SD = 11.1) and 10 younger (mean = 29.4 years, SD = 7.1). Each participant was scanned twice with an average interscan interval of 15.4 days (range: 29 min-50 days). Results suggest low technique-related error as indicated by excellent intraclass correlation coefficient (ICC) results, with ICCs above 0.90 (p < 0.05) for GM, WM, and CSF, in all 26 regions of interest (13 per hemisphere). Ventricular and lesion sub-type (pvSH, dwSH, and Lacunar) volumes also showed high scan-rescan reliability (dwSH = 0.9998, pvSH = 0.9998, Lacunar = 0.9859, p < 0.01). As indicated by the results of this short-term scan-rescan study, the LE structural MRI processing pipeline can be applied for longitudinal volumetric analyses with confidence.

Structural MRI

Clinical neuroimaging is increasingly being used in the diagnosis of neurodegenerative diseases and has become one of the most important paraclinical tools in the diagnosis of dementia. According to current guidelines, neuroimaging, preferably magnetic resonance imaging (MRI), should be performed at least once during the diagnostic work-up of patients with suspected or definite dementia. MRI is helpful in identifying or excluding potentially treatable causes of dementia; however, these account only for a small proportion of dementias. In addition, MRI is able to support the clinical diagnosis in a memory clinic setting by identifying certain patterns of atrophy and vascular damage. Visual rating scales are well-established methods in the clinical routine for the assessment and quantification of regional/global cortical atrophy, hippocampal atrophy and vascular damage. In addition, MRI is able to detect certain aspects of pathology associated with dementia, such as cerebral microbleeds which are related to cerebral amyloid angiopathy and Alzheimer pathology. This review paper aims to give an overview of the application of structural MRI in the diagnostic procedure for memory clinic patients in terms of excluding and supporting the diagnosis of various diseases associated with dementia.

Vascular chorea in adults and children

Chorea may occur as part of the symptomatology of acute stroke; it occasionally also may be delayed or progressive. Patients with vascular-related chorea typically present with an acute or subacute onset of chorea of one side of the body (hemichorea), contralateral to the lesion. Cerebrovascular disease is the most common cause of sporadic chorea. Lesions are most frequently found in the thalamus and lentiform nucleus, and less often in subthalamic nucleus. The differential diagnosis of choreic syndromes relies not so much on differences in the phenomenology of the hyperkinesia but the age at onset, mode of onset, time course, family history, drug use, distribution of chorea in the body, and presence of accompanying neurological findings. Magnetic resonance imaging is preferred to demonstrate the presence of strategic small lesions in regions that are difficult to image with computed tomography, such as the globus pallidus, thalamus, and subthalamic nucleus. Although the prognosis of hemichorea can be benign, the long-term prognosis is not specifically determined by the hemichorea but by the long-term prognosis of stroke patients. Symptomatic treatment with antichoreic drugs may be necessary in the acute phase. Surgery is rarely indicated to treat vascular chorea.

Brain Glucose Metabolism in Vascular White Matter Disease With Dementia

Background and Purpose— The boundary between vascular dementia and Alzheimer disease (AD) continues to be unclear. Some posit that gradually progressive vascular dementia, as with small vessel disease, is simply vascular disease plus AD. Because AD presents a characteristic pattern on fluorodeoxyglucose positron emission tomography, we sought to determine whether the fluorodeoxyglucose pattern of vascular dementia resembled more AD or the pattern in nondemented patients with severe microvascular brain disease.

Methods— Vascular disease patients were selected on the basis of confluent white matter lesions on both hemispheres. Among them, with a similar degree of vascular disease on MRI, neuropsychological testing separated groups with dementia and without dementia. Patients with AD and healthy controls were also studied. The 4 groups, with 12 subjects each, were matched by age, gender, and educational level. Fluorodeoxyglucose distribution was analyzed using both voxel-based and volume of interest methods.

Results— The AD group had the characteristic pattern of bilaterally decreased metabolism in parieto-temporal association cortex and precuneus. By contrast, patients with vascular disease and dementia had a similar anatomic pattern to that of the vascular patients without dementia, but with greater metabolic abnormalities, particularly in the frontal lobes and deep nuclei.

Conclusions— The anatomy of metabolic abnormalities in vascular disease with dementia suggests that, at least in some cases, dementia with vascular disease may be independent of AD. The metabolic abnormality involves the thalamus, caudate, and frontal lobe, a pattern concordant with the neuropsychological findings of impaired executive function characteristic of vascular dementia.

Automatic segmentation of white matter hyperintensities in the elderly using FLAIR images at 3T

Purpose

To determine the precision and accuracy of an automated method for segmenting white matter hyperintensities (WMH) on fast fluid-attenuated inversion-recovery (FLAIR) images in elderly brains at 3T.

Materials and Methods

FLAIR images from 18 individuals (60–82 years, 9 females) with WMH burdens ranging from 1–80 cm³ were used. The protocol included the removal of clearly hyperintense voxels; two-class fuzzy C-means clustering (FCM); and thresholding to segment probable WMH. Two false-positive minimization (FPM) methods using white matter templates were tested. Precision was assessed by adding synthetic hyperintense voxels to brain slices. Accuracy was validated by comparing automatic and manual segmentations. Whole-brain, voxel-wise metrics of similarity, under- and overestimation were used to evaluate both precision and accuracy.

Results

Precision was high, as the lowest accuracy in the synthetic datasets was 93%. Both FPM strategies successfully improved overall accuracy. Whole-brain accuracy for the FCM segmentation alone ranged from 45%–81%, which improved to 75%–85% using the FPM strategies.

Conclusion

The method was accurate across the range of WMH burden typically seen in the elderly. Accuracy levels achieved or exceeded those of other approaches using multispectral and/or more sophisticated pattern recognition methods. J. Magn. Reson. Imaging 2010;31:1311–1322. © 2010 Wiley-Liss, Inc.

Lesion Explorer: a comprehensive segmentation and parcellation package to obtain regional volumetrics for subcortical hyperintensities and intracranial tissue

Subcortical hyperintensities (SH) are a commonly observed phenomenon on MRI of the aging brain (Kertesz et al., 1988). Conflicting behavioral, cognitive and pathological associations reported in the literature underline the need to develop an intracranial volumetric analysis technique to elucidate pathophysiological origins of SH in Alzheimer's disease (AD), vascular cognitive impairment (VCI) and normal aging (De Leeuw et al., 2001; Mayer and Kier, 1991; Pantoni and Garcia, 1997; Sachdev et al., 2008). The challenge is to develop processing tools that effectively and reliably quantify subcortical small vessel disease in the context of brain tissue compartments. Segmentation and brain region parcellation should account for SH subtypes which are often classified as: periventricular (pvSH) and deep white (dwSH), incidental white matter disease or lacunar infarcts and Virchow-Robin spaces. Lesion Explorer (LE) was developed as the final component of a comprehensive volumetric segmentation and parcellation image processing stream built upon previously published methods (Dade et al., 2004; Kovacevic et al., 2002). Inter-rater and inter-method reliability was accomplished both globally and regionally. Volumetric analysis showed high inter-rater reliability both globally (ICC=.99) and regionally (ICC=.98). Pixel-wise spatial congruence was also high (SI=.97). Whole brain pvSH volumes yielded high inter-rater reliability (ICC=.99). Volumetric analysis against an alternative kNN segmentation revealed high inter-method reliability (ICC=.97). Comparison with visual rating scales showed high significant correlations (ARWMC: r=.86; CHIPS: r=.87). The pipeline yields a comprehensive and reliable individualized volumetric profile for subcortical vasculopathy that includes regionalized (26 brain regions) measures for: GM, WM, sCSF, vCSF, lacunar and non-lacunar pvSH and dwSH.

Small vessel versus large vessel vascular dementia: risk factors and MRI findings

OBJECTIVE

The aim of this study was a cross-sectional comparison of clinical and MRI characteristics and risk factor profiles between patients with small vessel disease (lacunae and white matter hyperintensities) and large vessel disease (large territorial or strategical infarcts) in a large cohort of VaD patients.

METHODS

Patients with VaD (NINDS-AIREN) were included in a large multicenter treatment trial (the VantagE study). All patients were examined by a neurologist and interviewed about their medical history. Based on MRI, patients were classified as having large vessel VaD, small vessel VaD, or a combination. Other MRI characteristics included white matter hyperintensities (WMH), medial temporal lobe atrophy (MTA) and general cortical atrophy.

RESULTS

Of the 706 patients, 522 (74 %) had small vessel disease, 126 (18 %) had large vessel disease and 58 (8 %) had both. Patients with small vessel disease were older and less educated, and showed more cortical and medial temporal lobe atrophy than patients with large vessel disease. The most prevalent vascular risk factors (hypertension, diabetes and smoking) were equally distributed between the different types of VaD. However, patients with large vessel disease had more hypercholesterolemia and cardiac risk factors compared to patients with small vessel disease.

CONCLUSION

Cerebrovascular disease underlying VaD consists in the majority of small vessel disease and in about one fifth of large vessel disease. This study demonstrates heterogeneity between these two groups with regard to risk factor profile and atrophy scores on MRI.

Anterior-medial thalamic lesions in dementia: frequent, and volume dependently associated with sudden cognitive decline

BACKGROUND

The anterior-medial thalamus (AMT), which is associated with memory processing, is severely affected by Alzheimer's disease pathology and, when damaged, can be the sole cause of dementia.

OBJECTIVE

To assess the frequency of magnetic resonance imaging (MRI) hyperintensities affecting the AMT, and their relationship with sudden cognitive decline.

METHODS

205 consecutive participants from a university cognitive neurology clinic underwent clinical evaluation, neuropsychological testing and quantitative MRI.

RESULTS

AMT hyperintensities >5 mm3 occurred in 0 of 34 normal controls but were found in 5 of 30 (17%) participants with cognitive impairment with no dementia (CIND), 9 of 109 (8%) patients with probable Alzheimer's disease, 7 of 17 (41%) with mixed disease and 8 of 15 (53%) with probable vascular dementia (VaD). AMT hyperintensities occurred more often in participants with stepwise decline than in those with slow progression (chi2 = 31.7; p<0.001). Of the 29 people with AMT hyperintensities, those with slow progression had smaller medial temporal width (p<0.001) and smaller anterior-medial thalamic hyperintensities (p<0.001). In a logistic regression model, both variables were significant, and the pattern of decline was correctly classified in 86% of the sample (Cox and Snell R2 = 0.56; p<0.001). Those with AMT hyperintensities >55 mm3 were likely to have stepwise decline in cognitive function regardless of medial temporal lobe width; in contrast, those with smaller AMT hyperintensities showed a stepwise decline only in the absence of medial temporal lobe atrophy. All patients with VaD had left-sided AMT hyperintensities, whereas those with CIND had right-sided AMT hyperintensities.

CONCLUSIONS

AMT hyperintensities >55 mm3 probably result in symptomatic decline, whereas smaller lesions may go unrecognised by clinicians and radiologists. Only half of those with AMT hyperintensities had diagnoses of VaD or mixed disease; the other AMT hyperintensities occurred in patients diagnosed with Alzheimer's disease or CIND. These silent hyperintensities may nevertheless contribute to cognitive dysfunction. AMT hyperintensities may represent a major and under-recognised contributor to cognitive impairment.

Neuroradiological findings in vascular dementia

INTRODUCTION

There are multiple diagnostic criteria for vascular dementia (VaD) that may define different populations. Utilizing the criteria of the National Institute of Neurological Disorders and Stroke and Association Internationale pour la Recherche et l'Enseignement en Neurosciences (NINDS-AIREN) has provided improved consistency in the diagnosis of VaD. The criteria include a table listing brain imaging lesions associated with VaD.

METHODS

The different neuroradiological aspects of the criteria are reviewed based on the imaging data from an ongoing large-scale clinical trial testing a new treatment for VaD. The NINDS-AIREN criteria were applied by a centralized imaging rater to determine eligibility for enrollment in 1,202 patients using brain CT or MRI.

RESULTS

Based on the above data set, the neuroradiological features that are associated with VaD and that can result from cerebral small-vessel disease with extensive leukoencephalopathy or lacunae (basal ganglia or frontal white matter), or may be the consequence of single strategically located infarcts or multiple infarcts in large-vessel territories, are illustrated. These features may also be the consequence of global cerebral hypoperfusion, intracerebral hemorrhage, or other mechanisms such as genetically determined arteriopathies.

CONCLUSION

Neuroimaging confirmation of cerebrovascular disease in VaD provides information about the topography and severity of vascular lesions. Neuroimaging may also assist with the differential diagnosis of dementia associated with normal pressure hydrocephalus, chronic subdural hematoma, arteriovenous malformation or tumoral diseases.

Imaging dementing illnesses

Dementia is an impairment of mental ability representing a decline from that level previously reached by the individual. It is usually of insidious onset, associated with neurologic changes, and results in the inability to appropriately interact with one's environment. Dementias may be static, progressive, or reversible, and have many etiologies. One percent of the population above age 40 suffers from dementia and this figure rises to 7% above age 80 and 50% above age 90. Forty-five percent of dementias are due to Alzheimer disease (AD) followed closely by vascular dementia. A stage along the way to dementia is mild cognitive impairment (MCI). There are various definitions but the simplest ones refer to a person who has some memory problems but can continue to live independently. A more specific description refers to deficits in two or more areas of cognition >1.5 SD below mean for the individuals age and education. Although previously considered a part of normal aging, a recent study has shown MCI to be a precursor of Alzheimer disease (1). In a cohort of nuns and priests studied annually until they developed MCI or dementia and died. 180 brains in this study have already been autopsied (37 MCI, 60 with no impairment, 53 with dementia). Pathologists measured theamount of AD pathology and cerebral infarcts. Of 37 with MCI, more than half had AD by pathology, 1/3 had infarcts (5 with both) and 14 did not have either pathology. One third of the 180 with average age of 85 had no cognitive decline! Since this study showed MCI patients to have Alzheimer disease pathology in their brains, recognition of MCI clinically is important for institution of therapy, although there has not yet been an effective therapy developed.

Comparison of fluid-attenuated inversion recovery and T2-weighted magnetic resonance images in dogs and cats with suspected brain disease

To compare fluid-attenuated inversion recovery (FLAIR) and T2-weighted magnetic resonance (MR) imaging in small animal patients with suspected brain disease, paired sets of FLAIR and T2-weighted MR images of 116 dogs and cats were reviewed separately without any patient information. Images were rated as normal or abnormal using a five-point scale, and the distribution, signal intensity, and anatomic location of abnormalities were recorded. In 60 animals, both FLAIR and T2-weighted images were normal. In 50 animals, the same abnormalities were identified in both FLAIR and T2-weighted images. Overall, very good agreement was found between FLAIR and T2-weighted MR images (kappa = 0.88). FLAIR images had abnormalities that were not recognized in the corresponding T2-weighted images in six of 116 examinations (5%). In four of these, the abnormalities in FLAIR images were thought to represent pathology, including granulomatous meningoencephalitis in one dog, postictal edema in one dog, and undiagnosed lesions in two dogs. In the remaining two examinations, the abnormalities in FLAIR images were probably artifacts. No examples were found of intracranial abnormalities in T2-weighted images that were not visible in FLAIR images. In this study, acquiring FLAIR images in addition to T2-weighted images resulted in detection of otherwise occult abnormalities in relatively few patients.

Pathological aging of the brain: an overview

The number of elderly people is increasing rapidly and, therefore, an increase in neurodegenerative and cerebrovascular disorders causing dementia is expected. Alzheimer disease (AD) is the most common cause of dementia. Vascular dementia, dementia with Lewy bodies, and frontotemporal dementia are the most frequent causes after AD, but a large proportion of patients have a combination of degenerative and vascular brain pathology. Characteristic magnetic resonance (MR) imaging findings can contribute to the identification of different diseases causing dementia. The MR imaging protocol should include axial T2-weighted images (T2-WI), axial fluid-attenuated inversion recovery (FLAIR) or proton density-weighted images, and axial gradient-echo T2*-weighted images, for the detection of cerebrovascular pathology. Structural neuroimaging in dementia is focused on detection of brain atrophy, especially in the medial temporal lobe, for which coronal high resolution T1-weighted images perpendicular to the long axis of the temporal lobe are extremely important. Single photon emission computed tomography and positron emission tomography may have added value in the diagnosis of dementia and may become more important in the future, due to the development of radioligands for in vivo detection of AD pathology. New functional MR techniques and serial volumetric imaging studies to identify subtle brain abnormalities may also provide surrogate markers for pathologic processes that occur in diseases causing dementia and, in conjunction with clinical evaluation, may enable a more rigorous and early diagnosis, approaching the accuracy of neuropathology.