MRI Visual Ratings of Brain Atrophy and White Matter Hyperintensities across the Spectrum of Cognitive Decline Are Differently Affected by Age and Diagnosis

The Effect of Spinal Cord Injury on Beta-Amyloid Plaque Pathology in TgCRND8 Mouse Model of Alzheimer's Disease

BACKGROUND

The accumulation and aggregation of Aβ as amyloid plaques, the hallmark pathology of the Alzheimer's disease, has been found in other neurological disorders, such as traumatic brain injury. The axonal injury may contribute to the formation of Aβ plaques. Studies to date have focused on the brain, with no investigations of spinal cord, although brain and cord share the same cellular components.

OBJECTIVE

We utilized a spinal cord transection model to examine whether spinal cord injury acutely induced the onset or promote the progression of Aβ plaque 3 days after injury in TgCRND8 transgenic model of AD.

METHODS

Spinal cord transection was performed in TgCRND8 mice and its littermate control wild type mice at the age of 3 and 20 months. Immunohistochemical reactions/ELISA assay were used to determine the extent of axonal damage and occurrence/alteration of Aβ plaques or levels of Aβ at different ages in the spinal cord of TgCRND8 mice.

RESULTS

After injury, widespread axonal pathology indicated by intra-axonal co-accumulations of APP and its product, Aβ, was observed in perilesional region of the spinal cord in the TgCRND8 mice at the age of 3 and 20 months, as compared to age-matched non-TgCRND8 mice. However, no Aβ plaques were found in the TgCRND8 mice at the age of 3 months. The 20-month-old TgCRND8 mice with established amyloidosis in spinal cord had a reduction rather than increase in plaque burden at the lesion site compared to the tissue adjacent to the injured area and corresponding area in sham mice following spinal cord transection. The lesion site of spinal cord area was occupied by CD68 positive macrophages/ activated microglia in injured mice compared to sham animals. These results indicate that spinal cord injury does not induce the acute onset and progression of Aβ plaque deposition in the spinal cord of TgCRND8 mice. Conversely, it induces the regression of Aβ plaque deposition in TgCRND8 mice.

CONCLUSION

The findings underscore the dependence of traumatic axonal injury in governing acute Aβ plaque formation and provide evidence that Aβ plaque pathology may not play a role in secondary injury cascades following spinal cord injury.

Circulating metabolites are associated with brain atrophy and white matter hyperintensities

Introduction

Our aim was to study whether systemic metabolites are associated with magnetic resonance imaging (MRI) measures of brain and hippocampal atrophy and white matter hyperintensities (WMH).

Methods

We studied associations of 143 plasma‐based metabolites with MRI measures of brain and hippocampal atrophy and WMH in three independent cohorts (n = 3962). We meta‐analyzed the results of linear regression analyses to determine the association of metabolites with MRI measures.

Results

Higher glucose levels and lower levels of three small high density lipoprotein (HDL) particles were associated with brain atrophy. Higher glucose levels were associated with WMH.

Discussion

Glucose levels were associated with brain atrophy and WMH, and small HDL particle levels were associated with brain atrophy. Circulating metabolites may aid in developing future intervention trials.

The Parietal Atrophy Score on Brain Magnetic Resonance Imaging is a Reliable Visual Scale

Aims

The purpose of the study was to evaluate the reliability of our new visual scale for a quick atrophy assessment of parietal lobes on brain Magnetic Resonance Imaging (MRI) among different professionals. A good agreement would justify its use for differential diagnosis of neurodegenerative dementias, especially early-onset Alzheimer’s Disease (AD), in clinical settings.

Methods

The visual scale named the Parietal Atrophy Score (PAS) is based on a semi-quantitative assessment ranging from 0 (no atrophy) to 2 (prominent atrophy) in three parietal structures (sulcus cingularis posterior, precuneus, parietal gyri) on T1-weighted MRI coronal slices through the whole parietal lobes. We used kappa statistics to evaluate intra-rater and inter-rater agreement among four raters who independently scored parietal atrophy using PAS. Rater 1 was a neuroanatomist (JM), rater 2 was an expert in MRI acquisition and analysis (II), rater 3 was a medical student (OP) and rater 4 was a neurologist (DS) who evaluated parietal atrophy twice in a 3-month interval to assess intra-rater agreement. All raters evaluated the same 50 parietal lobes on brain MRI of 25 cognitively normal individuals with even distribution across all atrophy degrees from none to prominent according to the neurologist’s rating.

Results

Intra-rater agreement was almost perfect with the kappa value of 0.90. Inter-rater agreement was moderate to substantial with kappa values ranging from 0.43-0.86.

Conclusion

The Parietal Atrophy Score is the reliable visual scale among raters of different professions for a quick evaluation of parietal lobes on brain MRI within 1-2 minutes. We believe it could be used as an adjunct measure in differential diagnosis of dementias, especially early-onset AD.

Reporting frequency of radiology findings increases after introducing visual rating scales in the primary care diagnostic work up of subjective and mild cognitive impairment

Objectives

Study the effect of introducing a template for radiological reporting of non-enhanced computed tomography (NECT) in the primary care diagnostic work up of cognitive impairment using visual rating scales (VRS).

Methods

Radiology reports were assessed regarding compliance with a contextual report template and the reporting of the parameters medial temporal lobe atrophy (MTA), white matter changes (WMC), global cortical atrophy (GCA), and width of lateral ventricles (WLV) using established VRS in two age-matched groups examined with NECT before (n = 111) and after (n = 125) the introduction of contextual reporting at our department. True positive rate (TPR) and true negative rate (TNR) before and after were compared.

Results

We observed a significant increase in the percentage of radiology reports with mentioning of MTA from 29 to 76% (p < 0.001), WMC from 69 to 86% (p < 0.01), and GCA from 54 to 82% (p < 0.001). We observed a significant increase in the percentages of reports where all of the parameters were mentioned, from 6 to 29% (p < 0.001). There was a significant increase in TPR from 10 to 55% for MTA.

Conclusion

This study suggests that contextual radiological assessment using VRS could increase the reporting frequency of radiology findings in the diagnostic work up of cognitive impairment but compliance with templates may be difficult to endorse.

Key Points

• Introducing visual rating scales in clinical practice increases the reporting frequency of MTA, WMC, and GCA in the diagnostic work up of subjective and mild cognitive impairment.

• Introducing visual rating scales has an effect on the true positive rate of reported MTA.

• Compliance with contextual radiology templates remains low when use of the template is not enforced by the department leadership.

ATN classification and clinical progression in subjective cognitive decline: The SCIENCe project

Objective

To investigate the relationship between the ATN classification system (amyloid, tau, neurodegeneration) and risk of dementia and cognitive decline in individuals with subjective cognitive decline (SCD).

Methods

We classified 693 participants with SCD (60 ± 9 years, 41% women, Mini-Mental State Examination score 28 ± 2) from the Amsterdam Dementia Cohort and Subjective Cognitive Impairment Cohort (SCIENCe) project according to the ATN model, as determined by amyloid PET or CSF β-amyloid (A), CSF p-tau (T), and MRI-based medial temporal lobe atrophy (N). All underwent extensive neuropsychological assessment. For 342 participants, follow-up was available (3 ± 2 years). As a control population, we included 124 participants without SCD.

Results

Fifty-six (n = 385) participants had normal Alzheimer disease (AD) biomarkers (A–T–N–), 27% (n = 186) had non-AD pathologic change (A–T–N+, A–T+N–, A–T+N+), 18% (n = 122) fell within the Alzheimer continuum (A+T–N–, A+T–N+, A+T+N–, A+T+N+). ATN profiles were unevenly distributed, with A–T+N+, A+T–N+, and A+T+N+ containing very few participants. Cox regression showed that compared to A–T–N–, participants in A+ profiles had a higher risk of dementia with a dose–response pattern for number of biomarkers affected. Linear mixed models showed participants in A+ profiles showed a steeper decline on tests addressing memory, attention, language, and executive functions. In the control group, there was no association between ATN and cognition.

Conclusions

Among individuals presenting with SCD at a memory clinic, those with a biomarker profile A–T+N+, A+T–N–, A+T+N–, and A+T+N+ were at increased risk of dementia, and showed steeper cognitive decline compared to A–T–N– individuals. These results suggest a future where biomarker results could be used for individualized risk profiling in cognitively normal individuals presenting at a memory clinic.

Early Cognitive Impairment after Minor Stroke: Associated Factors and Functional Outcome

OBJECTIVES

Evaluation of cognitive status is not performed routinely in the acute stroke setting. This study aimed to evaluate the frequency of early cognitive impairment in patients with minor ischemic stroke, analyze the factors associated with early cognitive impairment, and assess functional outcomes.

METHODS

In this prospective study, 112 consecutive patients with acute minor ischemic stroke were enrolled. Neuroimages were assessed for semiquantitative evaluation of brain atrophy and small vessel disease (SVD) markers. Cognitive performance was measured within 5 days of onset using Montreal Cognitive Assessment (MoCA) scores. Functional outcome analyses were adjusted for demographic variables, premorbid cognitive status, education level, vascular risk factors, neuroimaging characteristics, stroke severity, and MoCA scores.

RESULTS

The median MoCA score was 22, and 63% of patients had cognitive impairment. Factors independently associated with cognitive impairment were education (odds ratios [OR], .79; confidence intervals [CI], .63-.99), smoking (OR, .26; 95%CI, .073-.89), and temporal horn atrophy (OR, 4.73; 95% CI, 1.66-13.49). Factors independently associated with poor functional outcome were total MoCA score (OR, .78; 95%CI, .62-.95) and the sum of 4 MoCA subscores (visuospatial/executive, attention, language, and orientation; OR, .72; 95%CI, .53-.92). The cutoff value of the sum of 4 MoCA subscores for predicting poor outcome was 13 points with 76.5% sensitivity and 81.1% specificity.

CONCLUSIONS

Early cognitive impairment was common after minor ischemic stroke and was associated with preexisting temporal horn atrophy but not SVD markers. The sum of 4 MoCA subscores was useful in predicting the functional outcome.

Retinal sublayer defect is independently associated with the severity of hypertensive white matter hyperintensity

PURPOSE

To investigate the association of specific retinal sublayer thicknesses on optical coherence tomography (OCT) imaging with brain magnetic resonance imaging (MRI) markers using the Fazekas scale in hypertensive white matter hyperintensity (WMH) subjects.

METHODS

Eighty-eight participants (32 healthy controls and 56 hypertensive white matter hyperintensity subjects) underwent retinal imaging using the OCT and MRI. A custom-built algorithm was used to measure the thicknesses of the retinal nerve fiber layer (RNFL) and ganglion cell layer and inner plexiform layer (GCIP). Focal markers for white matter hyperintensities were assessed on MRI and graded using the Fazekas visual rating.

RESULTS

Hypertensive WMH showed significantly reduced (p < .05) RNFL and GCIP layers when compared to healthy controls, respectively. A significant correlation was found between the RNFL (ρ = -.246, p < .001) and GCIP (ρ = -.338, p < .001) of the total participants and the Fazekas score, respectively. Statistical differences were still significant (p < .05) when correlations were adjusted for intereye correlation, age, hypertension, smoking, body mass index, and diabetes. Among the cases of hypertensive WMH, higher Fazekas scores were significantly associated (p < .05) with the thinning of both the RNFL and GCIP layers after adjustment of age and other risk factors.

CONCLUSIONS

Retinal degeneration in the RNFL and GCIP was independently associated with focal lesions in the white matter of the brain and deteriorates with the severity of the lesions. We suggest that imaging and measurement of the retinal sublayers using the OCT may provide evidence on neurodegeneration in WMH.

The A/T/N model applied through imaging biomarkers in a memory clinic

PURPOSE

The A/T/N model is a research framework proposed to investigate Alzheimer's disease (AD) pathological bases (i.e., amyloidosis A, neurofibrillary tangles T, and neurodegeneration N). The application of this system on clinical populations is still limited. The aim of the study is to evaluate the topography of T distribution by 18F-flortaucipir PET in relation to A and N and to describe the A/T/N status through imaging biomarkers in memory clinic patients.

METHODS

Eighty-one patients with subjective and objective cognitive impairment were classified as A+/A- and N+/N- through amyloid PET and structural MRI. Tau deposition was compared across A/N subgroups at voxel level. T status was defined through a global cut point based on A/N subgroups and subjects were categorized following the A/T/N model.

RESULTS

A+N+ and A+N- subgroups showed higher tau burden compared to A-N- group, with A+N- showing significant deposition limited to the medial and lateral temporal regions. Global cut point discriminated A+N+ and A+N- from A-N- subjects. On A/T/N classification, 23% of patients showed a negative biomarker profile, 58% fell within the Alzheimer's continuum, and 19% of the sample was characterized by non-AD pathologic change.

CONCLUSION

Medial and lateral temporal regions represent a site of significant tau accumulation in A+ subjects and possibly a useful marker of early clinical changes. This is the first study in which the A/T/N model is applied using 18F-flortaucipir PET in a memory clinic population. The majority of patients showed a profile consistent with the Alzheimer's continuum, while a minor percentage showed a profile suggestive of possible other neurodegenerative diseases. These results support the applicability of the A/T/N model in clinical practice.

Applying the ATN scheme in a memory clinic population: The ABIDE project

OBJECTIVE

To apply the ATN scheme to memory clinic patients, to assess whether it discriminates patient populations with specific features.

METHODS

We included 305 memory clinic patients (33% subjective cognitive decline [SCD]: 60 ± 9 years, 61% M; 19% mild cognitive impairment [MCI]: 68 ± 9 years, 68% M; 48% dementia: 66 ± 10 years, 58% M) classified for positivity (±) of amyloid (A) ([¹⁸F]Florbetaben PET), tau (T) (CSF p-tau), and neurodegeneration (N) (medial temporal lobe atrophy). We assessed ATN profiles' demographic, clinical, and cognitive features at baseline, and cognitive decline over time.

RESULTS

The proportion of A+T+N+ patients increased with syndrome severity (from 1% in SCD to 14% in MCI and 35% in dementia), while the opposite was true for A-T-N- (from 48% to 19% and 6%). Compared to A-T-N-, patients with the Alzheimer disease profiles (A+T+N- and A+T+N+) were older (both p < 0.05) and had a higher prevalence of APOE ε4 (both p < 0.05) and lower Mini-Mental State Examination (MMSE) (both p < 0.05), memory (both p < 0.05), and visuospatial abilities (both p < 0.05) at baseline. Non-Alzheimer profiles A-T-N+ and A-T+N+ showed more severe white matter hyperintensities (both p < 0.05) and worse language performance (both p < 0.05) than A-T-N-. A linear mixed model showed faster decline on MMSE over time in A+T+N- and A+T+N+ (p = 0.059 and p < 0.001 vs A-T-N-), attributable mainly to patients without dementia.

CONCLUSIONS

The ATN scheme identified different biomarker profiles with overlapping baseline features and patterns of cognitive decline. The large number of profiles, which may have different implications in patients with vs without dementia, poses a challenge to the application of the ATN scheme.

Medial temporal lobe atrophy and posterior atrophy scales normative values

OBJECTIVES

The medial temporal lobe atrophy (MTA) and the posterior atrophy (PA) scales allow to assess the degree hippocampal and parietal atrophy from magnetic resonance imaging (MRI) scans. Despite reliable, easy and widespread employment, appropriate normative values are still missing. We aim to provide norms for the Italian population.

METHODS

Two independent raters assigned the highest MTA and PA score between hemispheres, based on 3D T1-weighted MRI of 936 Italian Brain Normative Archive subjects (age: mean ± SD: 50.2 ± 14.7, range: 20-84; MMSE>26 or CDR = 0). The inter-rater agreement was assessed with the absolute intraclass correlation coefficient (aICC). We assessed the association between MTA and PA scores and sociodemographic features and APOE status, and normative data were established by age decade based on percentile distributions.

RESULTS

Raters agreed in 90% of cases for MTA (aICC = 0.86; 95% CI = 0.69-0.98) and in 86% for PA (aICC = 0.82; 95% CI = 0.58-0.98). For both rating scales, score distribution was skewed, with MTA = 0 in 38% of the population and PA = 0 in 52%, while a score ≥ 2 was only observed in 12% for MTA and in 10% for PA. Median denoted overall hippocampal (MTA: median = 1, IQR = 0-1) and parietal (PA: median = 0, IQR = 0-1) integrity. The 90th percentile of the age-specific distributions increased from 1 (at age 20-59) for both scales, to 2 for PA over age 60, and up to 4 for MTA over age 80. Gender, education and APOE status did not significantly affect the percentile distributions in the whole sample, nor in the subset over age 60.

CONCLUSIONS

Our normative data for the MTA and PA scales are consistent with previous studies and overcome their main limitations (in particular uneven representation of ages and missing percentile distributions), defining the age-specific norms to be considered for proper brain atrophy assessment.

Neuropsychological impact of white matter hyperintensities in older adults without dementia

The purpose of this study was to determine (a) if simple clinical judgements of white matter hyperintensities (WMH) on imaging are associated with measurable cognitive impacts in otherwise cognitively normal older adults, (b) if neuropsychological measures can predict those with WMH, and (c) the frequency of low cognitive scores in those with WMH on a battery of measures. Forty-four individuals judged free of other cognitive disorders despite moderate to extensive WMH were compared with 50 individuals matched on age (mean of 83), education (college educated), and gender (predominantly female). Data was obtained from the National Alzheimer's Coordinating Center database. The group with at least moderate WMH had lower scores on the Trail Making Test A, verbal fluency, and digit span. A component score derived from these measures was a significant predictor of the presence of WMH, though only correctly classified 68% of participants. Even in individuals free from other suspected conditions, clinically judged moderate to extensive WMH was associated with cognitive weaknesses for processing speed, working memory, and executive functioning. This shows that a relatively simple judgment of WMH burden is meaningfully associated with worse cognition. Implications and future directions for are discussed.

White matter hyperintensities are related to pain intensity in an outpatient memory clinic population: preliminary findings

Background: The association between pain and dementia is complicated and may depend on underlying brain pathology. It was hypothesized that both medial temporal atrophy (MTA) and global cortical atrophy (GCA) predicted no/mild pain, while white matter hyperintensities (WMH) predicted moderate/severe pain.

Objectives: To study the association between pain intensity and measures of brain pathology, more specifically MTA, GCA, and WMH.

Methods: In total, 115 consecutive patients visiting an outpatient memory clinic were included. In total, diagnoses included dementia (N=70), mild cognitive impairment (N=30), and subjective cognitive impairment (N=15). Without administering stimuli, pain intensity was assessed with the Brief Pain Inventory. MTA, GCA, and WMH were measured with a MRI visual rating scale. Logistic regression analyses to examine the relationship between WMH, MTA, GCA, and self-reported pain intensity (no/mild pain versus moderate/severe pain) were adjusted for confounders.

Results: Mean age of the patients was 81 years (IQR: 78–85, 53% female). Moderate/severe pain was reported by 23.5% and associated with greater WMH (OR =3.34, 95% CI =1.01–10.97, p=0.047), but not MTA or GCA.

Conclusions: In contrast to the present results, earlier studies have reported either a positive or negative relationship between pain and brain volume. It is suggested that the presence of dementia may explain the absence of a relationship between pain and brain volume. WMH is positively related with pain in an older memory outpatient population. Considering the small sample size, our findings should be interpreted with caution. Hence, our conclusions are preliminary findings, warranting future replication.

AVRA: Automatic visual ratings of atrophy from MRI images using recurrent convolutional neural networks

Quantifying the degree of atrophy is done clinically by neuroradiologists following established visual rating scales. For these assessments to be reliable the rater requires substantial training and experience, and even then the rating agreement between two radiologists is not perfect. We have developed a model we call AVRA (Automatic Visual Ratings of Atrophy) based on machine learning methods and trained on 2350 visual ratings made by an experienced neuroradiologist. It provides fast and automatic ratings for Scheltens' scale of medial temporal atrophy (MTA), the frontal subscale of Pasquier's Global Cortical Atrophy (GCA-F) scale, and Koedam's scale of Posterior Atrophy (PA). We demonstrate substantial inter-rater agreement between AVRA's and a neuroradiologist ratings with Cohen's weighted kappa values of κw = 0.74/0.72 (MTA left/right), κw = 0.62 (GCA-F) and κw = 0.74 (PA). We conclude that automatic visual ratings of atrophy can potentially have great scientific value, and aim to present AVRA as a freely available toolbox.

Multiple Visual Rating Scales Based on Structural MRI and a Novel Prediction Model Combining Visual Rating Scales and Age Stratification in the Diagnosis of Alzheimer's Disease in the Chinese Population

Objective: To explore the value of multiple visual rating scales based on structural MRI in the diagnosis of Alzheimer's disease (AD) in the Chinese population.

Materials and Methods: One hundred patients with AD and 100 age- and gender- matched cognitively normal controls were enrolled in this study. All the participants underwent neuropsychological tests and a structural MRI scan of the brain, among them, 42 AD cases and 47 cognitively normal controls also underwent 3D-T1 weighted sequence used for the analysis of voxel-based morphometry (VBM). The AD cases were divided into mild and moderate–severe groups according to the mini-mental state examination. Each participant was evaluated by two trained radiologists who were blind to the clinical information, according to the six visual rating scales, including for medial temporal lobe atrophy (MTA), posterior atrophy (PA), anterior temporal (AT), orbitofrontal (OF) cortex, anterior cingulate (AC), and fronto-insula (FI). Finally, we estimated the relationship between the visual rating scales and the volume of corresponding brain regions, using correlation analysis, and evaluated the specificity and sensitivity of every single scale and combination of multiple scales in the diagnosis of AD, using a receiver operating characteristic (ROC) curve and establishing a logistic regression model.

Results: The optimal cutoff of all six visual rating scales for distinguishing AD cases from normal controls was 1.5. Using automated classification based on all six rating scales, the accuracy for distinguishing AD cases from healthy controls ranged from 0.68 to 0.80 (for mild AD) and 0.77–0.90 (for moderate–severe AD), respectively. A diagnostic prediction model with a combination of MTA and OF results was made as follows: Score = B_MTA(score) + B_OF(score) −1.58 (age < 65 years); Score = B_MTA(score) + B_OF(score) −4.09 (age ≥65 years). The model was superior to any single visual rating scale in the diagnosis of mild AD (P < 0.05).

Conclusion: Each of the six visual rating scales could be applied to the diagnosis of moderate-severe AD alone in the Chinese population. A prediction model of the combined usage of MTA, OF, and age stratification for the early diagnosis of AD was preliminarily established.

Structural imaging findings on non-enhanced computed tomography are severely underreported in the primary care diagnostic work-up of subjective cognitive decline

Purpose

The purpose of this study was to investigate how structural imaging findings of medial temporal lobe atrophy (MTA), posterior cortical atrophy (PCA), global cortical atrophy (GCA), white matter changes (WMC), and Evans’ index/width of lateral ventricles (EI/WLV) are reported in the primary care diagnostic work-up of patients with subjective cognitive decline or mild cognitive impairment.

Methods

We included 197 patients referred to a non-enhanced computed tomography (NECT) as part of the diagnostic work-up. We compared the frequencies of reported findings in radiology reports written by neuroradiologists and general radiologists with actual pathological findings in a second view done by a single neuroradiologist using the MTA, PCA, GCA, WMC, and EI/WLV visual rating scales. Structural findings were also compared to cognitive tests.

Results

We found that MTA and PCA were clearly underreported by both neuroradiologists and general radiologists. The presence of GCA and WMC was also underreported among general radiologists. Only MTA showed a clear association with cognitive test results.

Conclusions

We believe that the use of visual rating scales should be put into clinical practice to increase the yield of clinical NECT exams in the investigation of cognitive impairment. Special emphasis should be put on reporting MTA.

Cognitive Profiles and Atrophy Ratings on MRI in Senior Patients With Mild Cognitive Impairment

In this cross-sectional study, we sought to describe cognitive and neuroimaging profiles of Memory clinic patients with Mild Cognitive Impairment (MCI). 51 MCI patients and 51 controls, matched on age, sex, and socio-economic status (SES), were assessed with an extensive neuropsychological test battery that included a measure of intelligence (General Ability Index, "GAI," from WAIS-IV), and structural magnetic resonance imaging (MRI). MCI subtypes were determined after inclusion, and z-scores normalized to our control group were generated for each cognitive domain in each MCI participant. MR-images were scored by visual rating scales. MCI patients performed significantly worse than controls on 23 of 31 cognitive measures (Bonferroni corrected p = 0.001), and on 8 of 31 measures after covarying for intelligence (GAI). Compared to nonamnestic MCI patients, amnestic MCI patients had lower test results in 13 of 31 measures, and 5 of 31 measures after co-varying for GAI. Compared to controls, the MCI patients had greater atrophy on Schelten's Medial temporal lobe atrophy score (MTA), especially in those with amnestic MCI. The only structure-function correlation that remained significant after correction for multiple comparisons was the MTA-long delay recall domain. Intelligence operationalized as GAI appears to be an important moderator of the neuropsychological outcomes. Atrophy of the medial temporal lobe, based on MTA scores, may be a sensitive biomarker for the functional episodic memory deficits associated with MCI.

Evaluating combinations of diagnostic tests to discriminate different dementia types

Introduction

We studied, using a data-driven approach, how different combinations of diagnostic tests contribute to the differential diagnosis of dementia.

Methods

In this multicenter study, we included 356 patients with Alzheimer's disease, 87 frontotemporal dementia, 61 dementia with Lewy bodies, 38 vascular dementia, and 302 controls. We used a classifier to assess accuracy for individual performance and combinations of cognitive tests, cerebrospinal fluid biomarkers, and automated magnetic resonance imaging features for pairwise differentiation between dementia types.

Results

Cognitive tests had good performance in separating any type of dementia from controls. Cerebrospinal fluid optimally contributed to identifying Alzheimer's disease, whereas magnetic resonance imaging features aided in separating vascular dementia, dementia with Lewy bodies, and frontotemporal dementia. Combining diagnostic tests increased the accuracy, with balanced accuracies ranging from 78% to 97%.

Discussion

Different diagnostic tests have their distinct roles in differential diagnostics of dementias. Our results indicate that combining different diagnostic tests may increase the accuracy further.

Distinct patterns of brain atrophy in Genetic Frontotemporal Dementia Initiative (GENFI) cohort revealed by visual rating scales

Background

In patients with frontotemporal dementia, it has been shown that brain atrophy occurs earliest in the anterior cingulate, insula and frontal lobes. We used visual rating scales to investigate whether identifying atrophy in these areas may be helpful in distinguishing symptomatic patients carrying different causal mutations in the microtubule-associated protein tau (MAPT), progranulin (GRN) and chromosome 9 open reading frame (C9ORF72) genes. We also analysed asymptomatic carriers to see whether it was possible to visually identify brain atrophy before the appearance of symptoms.

Methods

Magnetic resonance imaging of 343 subjects (63 symptomatic mutation carriers, 132 presymptomatic mutation carriers and 148 control subjects) from the Genetic Frontotemporal Dementia Initiative study were analysed by two trained raters using a protocol of six visual rating scales that identified atrophy in key regions of the brain (orbitofrontal, anterior cingulate, frontoinsula, anterior and medial temporal lobes and posterior cortical areas).

Results

Intra- and interrater agreement were greater than 0.73 for all the scales. Voxel-based morphometric analysis demonstrated a strong correlation between the visual rating scale scores and grey matter atrophy in the same region for each of the scales. Typical patterns of atrophy were identified: symmetric anterior and medial temporal lobe involvement for MAPT, asymmetric frontal and parietal loss for GRN, and a more widespread pattern for C9ORF72. Presymptomatic MAPT carriers showed greater atrophy in the medial temporal region than control subjects, but the visual rating scales could not identify presymptomatic atrophy in GRN or C9ORF72 carriers.

Conclusions

These simple-to-use and reproducible scales may be useful tools in the clinical setting for the discrimination of different mutations of frontotemporal dementia, and they may even help to identify atrophy prior to onset in those with MAPT mutations.

Data-Driven Differential Diagnosis of Dementia Using Multiclass Disease State Index Classifier

Clinical decision support systems (CDSSs) hold potential for the differential diagnosis of neurodegenerative diseases. We developed a novel CDSS, the PredictND tool, designed for differential diagnosis of different types of dementia. It combines information obtained from multiple diagnostic tests such as neuropsychological tests, MRI and cerebrospinal fluid samples. Here we evaluated how the classifier used in it performs in differentiating between controls with subjective cognitive decline, dementia due to Alzheimer's disease, vascular dementia, frontotemporal lobar degeneration and dementia with Lewy bodies. We used the multiclass Disease State Index classifier, which is the classifier used by the PredictND tool, to differentiate between controls and patients with the four different types of dementia. The multiclass Disease State Index classifier is an extension of a previously developed two-class Disease State Index classifier. As the two-class Disease State Index classifier, the multiclass Disease State Index classifier also offers a visualization of its decision making process, which makes it especially suitable for medical decision support where interpretability of the results is highly important. A subset of the Amsterdam Dementia cohort, consisting of 504 patients (age 65 ± 8 years, 44% females) with data from neuropsychological tests, cerebrospinal fluid samples and both automatic and visual MRI quantifications, was used for the evaluation. The Disease State Index classifier was highly accurate in separating the five classes from each other (balanced accuracy 82.3%). Accuracy was highest for vascular dementia and lowest for dementia with Lewy bodies. For the 50% of patients for which the classifier was most confident on the classification the balanced accuracy was 93.6%. Data-driven CDSSs can be of aid in differential diagnosis in clinical practice. The decision support system tested in this study was highly accurate in separating the different dementias and controls from each other. In addition to the predicted class, it also provides a confidence measure for the classification.

Shades of white: diffusion properties of T1- and FLAIR-defined white matter signal abnormalities differ in stages from cognitively normal to dementia

The underlying pathology of white matter signal abnormalities (WMSAs) is heterogeneous and may vary dependent on the magnetic resonance imaging contrast used to define them. We investigated differences in white matter diffusivity as an indicator for white matter integrity underlying WMSA based on T1-weighted and fluid-attenuated inversion recovery (FLAIR) imaging contrast. In addition, we investigated which white matter region of interest (ROI) could predict clinical diagnosis best using diffusion metrics. One hundred three older individuals with varying cognitive impairment levels were included and underwent neuroimaging. Diffusion metrics were extracted from WMSA areas based on T1 and FLAIR contrast and from their overlapping areas, the border surrounding the WMSA and the normal-appearing white matter (NAWM). Regional diffusivity differences were calculated with linear mixed effects models. Multinomial logistic regression determined which ROI diffusion values classified individuals best into clinically defined diagnostic groups. T1-based WMSA showed lower white matter integrity compared to FLAIR WMSA-defined regions. Diffusion values of NAWM predicted diagnostic group best compared to other ROI's. To conclude, T1- or FLAIR-defined WMSA provides distinct information on the underlying white matter integrity associated with cognitive decline. Importantly, not the "diseased" but the NAWM is a potentially sensitive indicator for cognitive brain health status.

Amsterdam Dementia Cohort: Performing Research to Optimize Care

The Alzheimer center of the VU University Medical Center opened in 2000 and was initiated to combine both patient care and research. Together, to date, all patients forming the Amsterdam Dementia Cohort number almost 6,000 individuals. In this cohort profile, we provide an overview of the results produced based on the Amsterdam Dementia Cohort. We describe the main results over the years in each of these research lines: 1) early diagnosis, 2) heterogeneity, and 3) vascular factors. Among the most important research efforts that have also impacted patients' lives and/or the research field, we count the development of novel, easy to use diagnostic measures such as visual rating scales for MRI and the Amsterdam IADL Questionnaire, insight in different subgroups of AD, and findings on incidence and clinical sequelae of microbleeds. Finally, we describe in the outlook how our research endeavors have improved the lives of our patients.

Retinal thickness correlates with parietal cortical atrophy in early-onset Alzheimer's disease and controls

Introduction

The retina may reflect Alzheimer's disease (AD) neuropathological changes and is easily visualized with optical coherence tomography (OCT). Retinal thickness decrease has been correlated to AD, however, without information on amyloid status. We correlated retinal (layer) thickness to AD biomarkers in amyloid-positive early-onset AD (EOAD) patients and amyloid-negative controls.

Methods

We measured macular thickness and peripapillary retinal nerve fiber layer thickness with OCT in 15 EOAD patients and 15 controls and correlated retinal thickness to visual rating scores for atrophy on magnetic resonance imaging.

Results

Total macular thickness correlated to parietal cortical atrophy in both groups (Spearman ρ -0.603, P = .001). Macular and peripapillary retinal nerve fiber layer thicknesses were not significantly decreased in EOAD compared to controls.

Discussion

Retinal thickness does not discriminate EOAD from controls but is correlated to parietal cortical atrophy in both groups. These findings may suggest reflection of cerebral cortical changes in the retina, independent of amyloid.

MRI-assessed atrophy subtypes in Alzheimer's disease and the cognitive reserve hypothesis

BACKGROUND/AIMS

MRI assessment of the brain has demonstrated four different patterns of atrophy in patients with Alzheimer's disease dementia (AD): typical AD, limbic-predominant AD, hippocampal-sparing AD, and a subtype with minimal atrophy, previously referred to as no-atrophy AD. The aim of the present study was to identify and describe the differences between these four AD subtypes in a longitudinal memory-clinic study.

METHODS

The medial temporal lobes, the frontal regions, and the posterior regions were assessed with MRI visual rating scales to categorize 123 patients with mild AD according to ICD-10 and NINCDS-ADRDA criteria and the clinical dementia rating scale (CDR) into atrophy subtypes. Demographic data, neuropsychological measures, cerebrospinal-fluid biomarkers, and progression rate of dementia at two-year follow-up were compared between the groups.

RESULTS

Typical AD was found in 59 patients (48%); 29 (24%) patients had limbic-predominant AD; 19 (15%) had hippocampal-sparing AD; and 16 (13%) belonged to the group with minimal atrophy. No differences were found regarding cognitive test results or progression rates between the different subtypes. Using adjusted logistic regression analysis, we found that the patients in the minimal-atrophy group were less educated, had a lower baseline CDR sum of boxes score, and had higher levels of amyloid β in the cerebrospinal fluid.

CONCLUSION

Previous results concerning the prevalence and the similar phenotypic expressions of the four AD subtypes were confirmed. The main finding was that patients with minimal atrophy as assessed by MRI had less education than the other AD subtypes and that this could support the cognitive reserve hypothesis and, at least in part, explain the lower degree of atrophy in this group. Patients with less formal education might present with clinically typical AD symptoms before they have positive biomarkers of AD and this finding might challenge suggested biomarker-based criteria for AD.