Automated quantitative MRI volumetry reports support diagnostic interpretation in dementia: a multi-rater, clinical accuracy study.

OBJECTIVES: We examined whether providing a quantitative report (QReport) of regional brain volumes improves radiologists' accuracy and confidence in detecting volume loss, and in differentiating Alzheimer's disease (AD) and frontotemporal dementia (FTD), compared with visual assessment alone. METHODS: Our forced-choice multi-rater clinical accuracy study used MRI from 16 AD patients, 14 FTD patients, and 15 healthy controls; age range 52-81. Our QReport was presented to raters with regional grey matter volumes plotted as percentiles against data from a normative population (n = 461). Nine raters with varying radiological experience (3 each: consultants, registrars, 'non-clinical image analysts') assessed each case twice (with and without the QReport). Raters were blinded to clinical and demographic information; they classified scans as 'normal' or 'abnormal' and if 'abnormal' as 'AD' or 'FTD'. RESULTS: The QReport improved sensitivity for detecting volume loss and AD across all raters combined (p = 0.015* and p = 0.002*, respectively). Only the consultant group's accuracy increased significantly when using the QReport (p = 0.02*). Overall, raters' agreement (Cohen's κ) with the 'gold standard' was not significantly affected by the QReport; only the consultant group improved significantly (κs 0.41➔0.55, p = 0.04*). Cronbach's alpha for interrater agreement improved from 0.886 to 0.925, corresponding to an improvement from 'good' to 'excellent'. CONCLUSION: Our QReport referencing single-subject results to normative data alongside visual assessment improved sensitivity, accuracy, and interrater agreement for detecting volume loss. The QReport was most effective in the consultants, suggesting that experience is needed to fully benefit from the additional information provided by quantitative analyses. KEY POINTS: • The use of quantitative report alongside routine visual MRI assessment improves sensitivity and accuracy for detecting volume loss and AD vs visual assessment alone. • Consultant neuroradiologists' assessment accuracy and agreement (kappa scores) significantly improved with the use of quantitative atrophy reports. • First multi-rater radiological clinical evaluation of visual quantitative MRI atrophy report for use as a diagnostic aid in dementia.

Patterns of atrophy in pathologically confirmed dementias: a voxelwise analysis.

OBJECTIVE: Imaging is recommended to support the clinical diagnoses of dementias, yet imaging research studies rarely have pathological confirmation of disease. This study aims to characterise patterns of brain volume loss in six primary pathologies compared with controls and to each other. METHODS: One hundred and eighty-six patients with a clinical diagnosis of dementia and histopathological confirmation of underlying pathology, and 73 healthy controls were included in this study. Voxel-based morphometry, based on ante-mortem T1-weighted MRI, was used to identify cross-sectional group differences in brain volume. RESULTS: Early-onset and late-onset Alzheimer's disease exhibited different patterns of grey matter volume loss, with more extensive temporoparietal involvement in the early-onset group, and more focal medial temporal lobe loss in the late-onset group. The Presenilin-1 group had similar parietal involvement to the early-onset group with localised volume loss in the thalamus, medial temporal lobe and temporal neocortex. Lewy body pathology was associated with less extensive volume loss than the other pathologies, although precentral/postcentral gyri volume was reduced in comparison with other pathological groups. Tau and TDP43A pathologies demonstrated similar patterns of frontotemporal volume loss, although less extensive on the right in the 4-repeat-tau group, with greater parietal involvement in the TDP43A group. The TDP43C group demonstrated greater left anterior-temporal involvement. CONCLUSIONS: Pathologically distinct dementias exhibit characteristic patterns of regional volume loss compared with controls and other dementias. Voxelwise differences identified in these cohorts highlight imaging signatures that may aid in the differentiation of dementia subtypes during life. The results of this study are available for further examination via NeuroVault (http://neurovault.org/collections/ADHMHOPN/).

MRI visual rating scales in the diagnosis of dementia: evaluation in 184 post-mortem confirmed cases.

Accurately distinguishing between different degenerative dementias during life is challenging but increasingly important with the prospect of disease-modifying therapies. Molecular biomarkers of dementia pathology are becoming available, but are not widely used in clinical practice. Conversely, structural neuroimaging is recommended in the evaluation of cognitive impairment. Visual assessment remains the primary method of scan interpretation, but in the absence of a structured approach, diagnostically relevant information may be under-utilized. This definitive, multi-centre study uses post-mortem confirmed cases as the gold standard to: (i) assess the reliability of six visual rating scales; (ii) determine their associated pattern of atrophy; (iii) compare their diagnostic value with expert scan assessment; and (iv) assess the accuracy of a machine learning approach based on multiple rating scales to predict underlying pathology. The study includes T1-weighted images acquired in three European centres from 184 individuals with histopathologically confirmed dementia (101 patients with Alzheimer's disease, 28 patients with dementia with Lewy bodies, 55 patients with frontotemporal lobar degeneration), and scans from 73 healthy controls. Six visual rating scales (medial temporal, posterior, anterior temporal, orbito-frontal, anterior cingulate and fronto-insula) were applied to 257 scans (two raters), and to a subset of 80 scans (three raters). Six experts also provided a diagnosis based on unstructured assessment of the 80-scan subset. The reliability and time taken to apply each scale was evaluated. Voxel-based morphometry was used to explore the relationship between each rating scale and the pattern of grey matter volume loss. Additionally, the performance of each scale to predict dementia pathology both individually and in combination was evaluated using a support vector classifier, which was compared with expert scan assessment to estimate clinical value. Reliability of scan assessment was generally good (intraclass correlation coefficient > 0.7), and average time to apply all six scales was <3 min. There was a very close association between the pattern of grey matter loss and the regions of interest each scale was designed to assess. Using automated classification based on all six rating scales, the accuracy (estimated using the area under the receiver-operator curves) for distinguishing each pathological group from controls ranged from 0.86-0.97; and from one another, 0.75-0.92. These results were substantially better than the accuracy of any single scale, at least as good as expert reads, and comparable to previous studies using molecular biomarkers. Visual rating scores from magnetic resonance images routinely acquired as part of the investigation of dementias, offer a practical, inexpensive means of improving diagnostic accuracy.

Using visual rating to diagnose dementia: a critical evaluation of MRI atrophy scales.

Visual rating scales, developed to assess atrophy in patients with cognitive impairment, offer a cost-effective diagnostic tool that is ideally suited for implementation in clinical practice. By focusing attention on brain regions susceptible to change in dementia and enforcing structured reporting of these findings, visual rating can improve the sensitivity, reliability and diagnostic value of radiological image interpretation. Brain imaging is recommended in all current diagnostic guidelines relating to dementia, and recent guidelines have also recommended the application of medial temporal lobe atrophy rating. Despite these recommendations, and the ease with which rating scales can be applied, there is still relatively low uptake in routine clinical assessments. Careful consideration of atrophy rating scales is needed to verify their diagnostic potential and encourage uptake among clinicians. Determining the added value of combining scores from visual rating in different brain regions may also increase the diagnostic value of these tools.

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.

R47H TREM2 variant increases risk of typical early-onset Alzheimer's disease but not of prion or frontotemporal dementia.

BACKGROUND: Rare TREM2 variants are significant risk factors for Alzheimer's disease (AD). METHODS: We used next generation sequencing of the whole gene (n = 700), exon 2 Sanger sequencing (n = 2634), p.R47H genotyping (n = 3518), and genome wide association study imputation (n = 13,048) to determine whether TREM2 variants are risk factors or phenotypic modifiers in patients with AD (n = 1002), frontotemporal dementia (n = 358), sporadic (n = 2500), and variant (n = 115) Creutzfeldt-Jakob disease (CJD). RESULTS: We confirm only p.R47H as a risk factor for AD (odds ratio or OR = 2.19; 95% confidence interval or CI = 1.04-4.51; P = .03). p.R47H does not significantly alter risk for frontotemporal dementia (OR = 0.81), variant or sporadic CJD (OR = 1.06 95%CI = 0.66-1.69) in our cohorts. Individuals with p.R47H associated AD (n = 12) had significantly earlier symptom onset than individuals with no TREM2 variants (n = 551) (55.2 years vs. 61.7 years, P = .02). We note that heterozygous p.R47H AD is memory led and otherwise indistinguishable from "typical" sporadic AD. CONCLUSION: We find p.R47H is a risk factor for AD, but not frontotemporal dementia or prion disease.