Medial temporal lobe atrophy ratings in a large 75-year-old population-based cohort: gender-corrected and education-corrected normative data

Prestroke Cognitive Impairment: Frequency and Association With Premorbid Neuropsychiatric, Functional, and Neuroimaging Features

BACKGROUND

Some patients with stroke have prestroke cognitive impairment (pre-SCI), but its etiology is not clear. The aim of this cross-sectional study was to assess the frequency of pre-SCI and its association with premorbid neuropsychiatric, functional, and neuroimaging features.

METHODS

Patients hospitalized in stroke unit with an informant who could complete IQCODE (Informant Questionnaire for Cognitive Decline in the Elderly) were included. Pre-SCI was diagnosed if the IQCODE score was >3.3. Prestroke assessment also included NPI-Q (Neuropsychiatric Inventory Questionnaire), the basic Activities of Daily Living and Instrumental Activities of Daily Living scales, and the Clinical Dementia Rating scale. A multivariate logistic regression model was used to evaluate the association of pre-SCI with age, sex, education, arterial hypertension, atrial fibrillation, white matter lesions, cerebral microbleeds, and pathological medial temporal lobe atrophy.

RESULTS

IQCODE was available in 474 of 520 patients (91.2%; 45% women; mean age 75.5±13.3 years). Pre-SCI had a prevalence of 32.5% and was associated with prestroke NPI-Q (pre-SCI absent versus present, 1.7±2.3 versus 5.5±4.9; P<0.001), Activities of Daily Living scale (0.3±0.8 versus 1.8±1.9; P<0.001), Instrumental Activities of Daily Living scale (0.6±1.3 versus 3.8±4.0; P<0.001), and Clinical Dementia Rating scale score (0.7±1.7 versus 7.2±6.2; P<0.001). In the 271 patients with a magnetic resonance imaging available, the multivariate logistic regression showed that age (odds ratio [OR], 1.05 [95% CI, 1.62-9.73]), white matter lesions (OR, 1.26 [95% CI, 1.003-1.58]), and a pathological medial temporal lobe atrophy score (OR, 3.97 [95% CI, 1.62-9.73]) were independently associated with pre-SCI. In the 218 patients with ischemic stroke, white matter lesions (OR, 1.34 [95% CI, 1.04-1.72]) and medial temporal lobe atrophy (OR, 3.56 [95% CI, 1.38-9.19]), but not age, were associated with pre-SCI.

CONCLUSIONS

One-third of patients admitted to a stroke unit have pre-SCI that is associated with preexisting neuropsychiatric symptoms and functional performance. White matter lesions and medial temporal lobe atrophy are associated with pre-SCI, suggesting that both small vessel disease and neurodegeneration might be involved in its etiology.

Automated Scoring of Alzheimer's Disease Atrophy Scale with Subtype Classification Using Deep Learning-Based T1-Weighted Magnetic Resonance Image Segmentation

Background

Application of visual scoring scales for regional atrophy in Alzheimer's disease (AD) in clinical settings is limited by their high time cost and low intra/inter-rater agreement.

Objective

To provide automated atrophy scoring using objective volume driven from deep-learning segmentation methods for AD subtype classification using magnetic resonance imaging (MRI).

Methods

We enrolled 3,959 participants (1,732 cognitively normal [CN], 1594 with mild cognitive impairment [MCI], and 633 with AD). The occupancy indices for each regional volume were calculated by dividing each volume by the size of the lateral and inferior ventricular volumes. MR images from 355 participants (119 CN, 119 MCI, and 117 AD) from three different centers were used for validation. Two neuroradiologists performed visual assessments of the medial temporal, posterior, and global cortical atrophy scores in the frontal lobe using T1-weighted MR images. Images were also analyzed using the deep learning-based segmentation software, Neurophet AQUA. Cutoff values for the three scores were determined using the data distribution according to age. The scoring results were compared for consistency and reliability.

Results

Four volumetric-driven scoring results showed a high correlation with the visual scoring results for AD, MCI, and CN. The overall agreement with human raters was weak-to-moderate for atrophy scoring in CN participants, and good-to-almost perfect in AD and MCI participants. AD subtyping by automated scores also showed usefulness as a research tool.

Conclusions

Determining AD subtypes using automated atrophy scoring for late-MCI and AD could be useful in clinical settings or multicenter studies with large datasets.

The role of visual rating and automated brain volumetry in early detection and differential diagnosis of Alzheimer's disease

BACKGROUND

Medial temporal lobe atrophy (MTA) is a diagnostic marker for mild cognitive impairment (MCI) and Alzheimer's disease (AD), but the accuracy of quantitative MTA (QMTA) in diagnosing early AD is unclear. This study aimed to investigate the accuracy of QMTA and its related components (inferior lateral ventricle [ILV] and hippocampus) with MTA in the early diagnosis of MCI and AD.

METHODS

This study included four groups: normal (NC), MCI stable (MCIs), MCI converted to AD (MCIs), and mild AD (M-AD) groups. Magnetic resonance image analysis software was used to quantify the hippocampus, ILV, and QMTA. MTA was rated by two experienced neurologists. Receiver operating characteristic area under the curve (AUC) analysis was performed to compare their capability in differentiating AD from NC and MCI, and optimal thresholds were determined using the Youden index.

RESULTS

QMTA distinguished M-AD from NC and MCI with higher diagnostic accuracy than MTA, hippocampus, and ILV (AUCNC = 0.976, AUCMCI = 0.836, AUCMCIs = 0.894, AUCMCIc = 0.730). The diagnostic accuracy of QMTA was superior to that of MTA, the hippocampus, and ILV in differentiating MCI from AD. The diagnostic accuracy of QMTA was found to remain the best across age, sex, and pathological subgroups analyzed. The sensitivity (92.45%) and specificity (90.64%) were higher in this study when a cutoff value of 0.635 was chosen for QMTA.

CONCLUSIONS

QMTA may be a better choice than the MTA scale or the associated quantitative components alone in identifying AD patients and MCI individuals with higher progression risk.

Towards validation in clinical routine: a comparative analysis of visual MTA ratings versus the automated ratio between inferior lateral ventricle and hippocampal volumes in Alzheimer's disease diagnosis

PURPOSE

To assess the performance of the inferior lateral ventricle (ILV) to hippocampal (Hip) volume ratio on brain MRI, for Alzheimer's disease (AD) diagnostics, comparing it to individual automated ILV and hippocampal volumes, and visual medial temporal lobe atrophy (MTA) consensus ratings.

METHODS

One-hundred-twelve subjects (mean age ± SD, 66.85 ± 13.64 years) with varying degrees of cognitive decline underwent MRI using a Philips Ingenia 3T. The MTA scale by Scheltens, rated on coronal 3D T1-weighted images, was determined by three experienced radiologists, blinded to diagnosis and sex. Automated volumetry was computed by icobrain dm (v. 5.10) for total, left, right hippocampal, and ILV volumes. The ILV/Hip ratio, defined as the percentage ratio between ILV and hippocampal volumes, was calculated and compared against a normative reference population (n = 1903). Inter-rater agreement, association, classification accuracy, and clinical interpretability on patient level were reported.

RESULTS

Visual MTA scores showed excellent inter-rater agreement. Ordinal logistic regression and correlation analyses demonstrated robust associations between automated brain segmentations and visual MTA ratings, with the ILV/Hip ratio consistently outperforming individual hippocampal and ILV volumes. Pairwise classification accuracy showed good performance without statistically significant differences between the ILV/Hip ratio and visual MTA across disease stages, indicating potential interchangeability. Comparison to the normative population and clinical interpretability assessments showed commensurability in classifying MTA "severity" between visual MTA and ILV/Hip ratio measurements.

CONCLUSION

The ILV/Hip ratio shows the highest correlation to visual MTA, in comparison to automated individual ILV and hippocampal volumes, offering standardized measures for diagnostic support in different stages of cognitive decline.

Associations of carotid artery flow parameters with MRI markers of cerebral small vessel disease and patterns of brain atrophy

OBJECTIVES

A growing body of evidence links age related brain pathologies to systemic vascular processes. We aimed to study the prevalence and interrelations between magnetic resonance imaging (MRI) markers of cerebral small vessel disease and patterns of brain atrophy, and their association to carotid duplex ultrasound flow parameters.

MATERIALS AND METHODS

We investigated a population based randomised cohort of older adults (n=391) aged 70-87, part of the Swedish Good Aging in Skåne Study. Peak systolic and end diastolic velocities of the carotid arteries were measured by ultrasound, and resistivity- and pulsatility indexes were calculated. Subjects with increased peak systolic velocity indicating carotid stenosis were excluded from analysis. Nine MRI findings were rated by visual scales: white matter changes, pontine white matter changes, microbleeds, lacunar infarctions, medial temporal lobe atrophy, global cortical atrophy, parietal atrophy, precuneus atrophy and central atrophy.

RESULTS

MRI pathologies were found in 80% of subjects. Mean end diastolic velocity in common carotid arteries was inversely associated with white matter hyperintensities (OR=0.92; p=0.004), parietal lobe atrophy (OR=0.94; p=0.039), global cortical atrophy (OR=0.90; p=0.013), precuneus atrophy (OR=0.94; p=0.022), "number of CSV pathologies" (β=-0.07; p<0.001) and "MRI-burden score" (β=-0.11; p<0.001), after adjustment for age and sex. The latter three were also associated with pulsatility and resistivity indexes.

CONCLUSIONS

Low carotid end diastolic velocity, as well as increased carotid resistivity and pulsatility, were associated with signs of cerebral small vessel disease and patterns of brain atrophy, indicating a vascular component in the process of brain aging.

Combination of Cerebral Computed Tomography and Simplified Cardiac Arrest Hospital Prognosis (sCAHP) Score for Predicting Neurological Recovery in Cardiac Arrest Survivors

Background

Cerebral computed tomography (CT) and various severity scoring systems have been developed for the early prediction of the neurological outcomes of cardiac arrest survivors. However, few studies have combined these approaches. Therefore, we evaluated the value of the combination of cerebral CT and severity score for neuroprognostication.

Methods

This single-center, retrospective observational study included consecutive patients surviving nontraumatic cardiac arrest (January 2016 and December 2020). Gray-to-white ratio (GWR), third and fourth ventricle characteristics, and medial temporal lobe atrophy scores were evaluated on noncontrast cerebral CT. Simplified cardiac arrest hospital prognosis (sCAHP) score was calculated for severity assessment. The associations between the CT characteristics, sCAHP score and neurological outcomes were analyzed.

Results

This study enrolled 559 patients. Of them, 194 (34.7%) were discharged with favorable neurological outcomes. Patients with favorable neurological outcome had a higher GWR (1.37 vs 1.25, p < 0.001), area of fourth ventricle (461 vs 413 mm 2 , p < 0.001), anteroposterior diameter of fourth ventricle (0.95 vs 0.86 cm , p < 0.001) and a lower sCAHP score (146 vs 190, p < 0.001) than those with poor recovery. Patients with higher sCAHP score had lower GWR (p trend < 0.001), area of fourth ventricle (p trend = 0.019) and anteroposterior diameter of fourth ventricle (p trend = 0.014). The predictive ability by using area under receiver operating characteristic curve (AUC) for the combination of sCAHP score and GWR was significantly higher than that calculated for sCAHP (0.86 vs 0.76, p < 0.001) or GWR (0.86 vs 0.81, p = 0.001) alone.

Conclusions

The combination of GWR and sCAHP score can be used to effectively predict the neurological outcomes of cardiac arrest survivors and thus ensure timely intervention for those at high risk of poor recovery.

Corneal Nerve and Brain Imaging in Mild Cognitive Impairment and Dementia

Background:

Visual rating of medial temporal lobe atrophy (MTA) is an accepted structural neuroimaging marker of Alzheimer’s disease. Corneal confocal microscopy (CCM) is a non-invasive ophthalmic technique that detects neuronal loss in peripheral and central neurodegenerative disorders.

Objective:

To determine the diagnostic accuracy of CCM for mild cognitive impairment (MCI) and dementia compared to medial temporal lobe atrophy (MTA) rating on MRI.

Methods:

Subjects aged 60–85 with no cognitive impairment (NCI), MCI, and dementia based on the ICD-10 criteria were recruited. Subjects underwent cognitive screening, CCM, and MTA rating on MRI.

Results:

182 subjects with NCI (n = 36), MCI (n = 80), and dementia (n = 66), including AD (n = 19, 28.8%), VaD (n = 13, 19.7%), and mixed AD (n = 34, 51.5%) were studied. CCM showed a progressive reduction in corneal nerve fiber density (CNFD, fibers/mm²) (32.0±7.5 versus 24.5±9.6 and 20.8±9.3, p < 0.0001), branch density (CNBD, branches/mm²) (90.9±46.5 versus 59.3±35.7 and 53.9±38.7, p < 0.0001), and fiber length (CNFL, mm/mm²) (22.9±6.1 versus 17.2±6.5 and 15.8±7.4, p < 0.0001) in subjects with MCI and dementia compared to NCI. The area under the ROC curve (95% CI) for the diagnostic accuracy of CNFD, CNBD, CNFL compared to MTA-right and MTA-left for MCI was 78% (67–90%), 82% (72–92%), 86% (77–95%) versus 53% (36–69%) and 40% (25–55%), respectively, and for dementia it was 85% (76–94%), 84% (75–93%), 85% (76–94%) versus 86% (76–96%) and 82% (72–92%), respectively.

Conclusion:

The diagnostic accuracy of CCM, a non-invasive ophthalmic biomarker of neurodegeneration, was high and comparable with MTA rating for dementia but was superior to MTA rating for MCI.

Incidental findings of typical iNPH imaging signs in asymptomatic subjects with subclinical cognitive decline

Background

The etiology of idiopathic normal pressure hydrocephalus (iNPH) remains unclear. Little is known about the pre-symptomatic stage. This study aimed to investigate the association of neuropsychological data with iNPH-characteristic imaging changes compared to normal imaging and unspecific atrophy in a healthy population.

Methods

We extracted data from the community-dwelling Austrian Stroke Prevention Family Study (ASPS-Fam) database (2006–2010). All subjects underwent a baseline and identical follow-up examination after 3–5 years with MR imaging and an extensive neuropsychological test battery (Trail Making Test B, short physical performance balance, walking speed, memory, visuo-practical skills, composite scores of executive function and g-factor). We categorized the subjects into “iNPH”-associated, non-specific “atrophy,” and “normal” based on the rating of different radiological cerebrospinal fluid (CSF) space parameters. We noted how the categories developed over time. We assessed the association of the image categories with the neuropsychological data, different demographic, and lifestyle parameters (age, sex, education, alcohol intake, arterial hypertension, hypercholesterolemia), and the extent of white matter hyperintensities. We investigated whether neuropsychological data associated with the image categories were independent from other parameters as confounders.

Results

One hundred and thirteen subjects, aged 50–70 years, were examined. The imaging category “iNPH” was only present at follow-up. A third of subjects with “atrophy” at baseline changed to the category “iNPH” at follow-up. More white matter hyperintensities (WMH) were present in later “iNPH” subjects. Subjects with “iNPH” performed worse than “normal” subjects on executive function (p = 0.0118), memory (p = 0.0109), and Trail Making Test B (TMT-B. p < 0.0001). Education, alcohol intake, diabetes, arterial hypertension, and hypercholesterolemia had no effect. Age, number of females, and the extent of white matter hyperintensities were higher in “iNPH” than in “normal” subjects but did not significantly confound the neuropsychological results.

Conclusions

Apparent asymptomatic subjects with “iNPH” imaging characteristics presented with subclinical cognitive decline and showed worse executive function, memory, and TMT-B results than “normal” subjects. WMH seem to play a role in the etiology before ventriculomegaly. Clinical screening of individuals with incidental iNPH-characteristic imaging and conspicuous results sof these neurocognitive tests needs further validation.

Factors Associated with Cognitive Outcomes After First-Ever Ischemic Stroke: The Impact of Small Vessel Disease Burden and Neurodegeneration

BACKGROUND

Differences exist regarding post-stroke cognitive outcomes.

OBJECTIVE

The aim of this study investigates the potential factors associated with post-stroke cognitive performance and trajectories.

METHODS

We performed a prospective cohort study using serial monitoring of cognitive function over a 1-year period after a first-ever ischemic stroke. Small vessel disease (SVD) burden and hippocampal atrophy (HA) were evaluated using the modified cerebral small vessel disease scores (mCSVD) and medial temporal atrophy score (MTA) scores. A generalized estimating equation (GEE) model and a group-based trajectory model (GBTM) was used to analyze the potential factors associated with post-stroke cognitive outcomes.

RESULTS

A total of 112 patients were enrolled. The GEE model showed that all patients, regardless of initial cognitive performance, had a tendency to show an increase in the Montreal Cognitive Assessment over time. The cognitive performance was better in male patients with higher education levels (p = 0.046 and p <  0.001, respectively), but tended to be worse in patients with higher SVD burden and HA. The GBTM model grouped patients into low, intermediate, and high performance (LP, IP, and HP) after stroke. A higher SVD burden, rather than HA and initial stroke severity and location, independently predicted a higher odds of poor post-stroke cognitive trajectory (being in the LP group) after stroke (adjusted odds ratio 2.74, 95%CI 1.09-6.86).

CONCLUSION

In patients with first-ever mild stroke, cognitive improvement over time was evident. The detrimental impact of the SVD burden may outweigh the effect of HA or acute stroke insult on the post-stroke cognitive trajectory during the 1-year follow-up.

Validity and reliability of the medial temporal lobe atrophy scale in a memory clinic population

Background

Visual rating of medial temporal lobe atrophy (MTA) is often performed in conjunction with dementia workup. Most prior studies involved patients with known or probable Alzheimer’s disease (AD). This study investigated the validity and reliability of MTA in a memory clinic population.

Methods

MTA was rated in 752 MRI examinations, of which 105 were performed in cognitively healthy participants (CH), 184 in participants with subjective cognitive impairment, 249 in subjects with mild cognitive impairment, and 214 in patients with dementia, including AD, subcortical vascular dementia and mixed dementia. Hippocampal volumes, measured manually or using FreeSurfer, were available in the majority of cases. Intra- and interrater reliability was tested using Cohen’s weighted kappa. Correlation between MTA and quantitative hippocampal measurements was ascertained with Spearman’s rank correlation coefficient. Moreover, diagnostic ability of MTA was assessed with receiver operating characteristic (ROC) analysis and suitable, age-dependent MTA thresholds were determined.

Results

Rater agreement was moderate to substantial. MTA correlation with quantitative volumetric methods ranged from -0.20 (p< 0.05) to -0.68 (p < 0.001) depending on the quantitative method used. Both MTA and FreeSurfer are able to distinguish dementia subgroups from CH. Suggested age-dependent MTA thresholds are 1 for the age group below 75 years and 1.5 for the age group 75 years and older.

Conclusions

MTA can be considered a valid marker of medial temporal lobe atrophy and may thus be valuable in the assessment of patients with cognitive impairment, even in a heterogeneous patient population.

The neuroimaging of neurodegenerative and vascular disease in the secondary prevention of cognitive decline

Structural brain changes indicative of dementia occur up to 20 years before the onset of clinical symptoms. Efforts to modify the disease process after the onset of cognitive symptoms have been unsuccessful in recent years. Thus, future trials must begin during the preclinical phases of the disease before symptom onset. Age related cognitive decline is often the result of two coexisting brain pathologies: Alzheimer’s disease (amyloid, tau, and neurodegeneration) and vascular disease. This review article highlights some of the common neuroimaging techniques used to visualize the accumulation of neurodegenerative and vascular pathologies during the preclinical stages of dementia such as structural magnetic resonance imaging, positron emission tomography, and white matter hyperintensities. We also describe some emerging neuroimaging techniques such as arterial spin labeling, diffusion tensor imaging, and quantitative susceptibility mapping. Recent literature suggests that structural imaging may be the most sensitive and cost-effective marker to detect cognitive decline, while molecular positron emission tomography is primarily useful for detecting disease specific pathology later in the disease process. Currently, the presence of vascular disease on magnetic resonance imaging provides a potential target for optimizing vascular risk reduction strategies, and the presence of vascular disease may be useful when combined with molecular and metabolic markers of neurodegeneration for identifying the risk of cognitive impairment.

Visual rating versus volumetry of regional brain atrophy and longitudinal changes over a 5-year period in an elderly population

INTRODUCTION

The purpose of our study was to compare visual rating and volumetry of brain atrophy in an elderly population over a 5-year period and compare findings with cognitive test results.

MATERIALS AND METHODS

Two hundred and one subjects were examined with magnetic resonance imaging (MRI) of the brain. Visual rating and volumetry were performed in all subjects at ages 75 and 80. Cognitive function at both time points was assessed with the Mini-Mental State Examination (MMSE) and Trail Making Tests A and B (TMT-A and TMT-B). Changes in visual rating and volumetry were compared with changes in cognitive test.

RESULTS

A correlation was found between visual rating of medial temporal lobe atrophy (MTA) and hippocampal volumetry at both time points (rs = -.42 and rs = -.49, p < .001, respectively). The correlation between visual rating of posterior atrophy (PA); frontal atrophy (F-GCA) and volumetry of these brain regions was significant only at age 80 (rs = -.16, p = .02 for PA and rpb = .19, p = .006 for F-GCA). Visual rating showed only a minimal progression of regional atrophy at age 80, whereas volumetry showed 2%-5% decrease in volume depending on brain region. Performance in the MMSE, TMT-A, and TMT-B was virtually unchanged between ages 75 and 80.

CONCLUSION

We found a mild age-associated decrease in regional brain volumes in this healthy cohort with well-preserved cognitive functions. Visual assessment may not be sufficient for detecting mild progression of brain atrophy due to normal aging, whereas volumetry is more sensitive to capture these subtle changes.

Clinical and MRI Predictors of Conversion From Mild Behavioural Impairment to Dementia

OBJECTIVE

As an analogy with mild cognitive impairment (MCI), the mild behavioral impairment (MBI) construct has been proposed as a diagnostic label for those presenting late-onset behavioral symptoms. To date, however, the clinical, cognitive, and structural imaging features associated with an increased risk of conversion from MBI to dementia are poorly understood.

METHODS

We retrospectively analyzed the cognitive performance and structural brain MRI of 113 subjects, with a clinical follow-up of at least 4 years available. Subjects were randomly assigned to a Group A (56 subjects; age: 65.4 ± 7.9 years, 15 females, MMSE score: 28.4 ± 2.3)) or to a Group B (57 subjects, age: 66.6 ± 6.4, 17 females, MMSE score: 28.0 ± 1.4). In the Group A, cognitive and structural variables were compared between converters (at 4 years) and nonconverters and then verified in the Group B group.

RESULTS

In the Group A, 14 patients converted to behavioral-variant of frontotemporal dementia (bv-FTD) and 4 to Alzheimer's Disease (AD). Converters presented at baseline lower executive function scores and total Theory of Mind (ToM scores), as well as more severe focal frontal atrophy. In the Group B, 13 subjects converted to bv-FTD and none to AD. The combination of the variables identified in the Group A significantly (p <0.001) discriminated between converters and nonconverters in the Group B with a sensitivity of 0.615 and a specificity of 1 (total accuracy 91.22%).

CONCLUSION

The combined presence of executive deficit, impaired ToM, and presence of isolated frontal atrophy was associated with risk of progression from MBI to a clinically evident neurodegenerative condition, mainly bv-FTD, over a 4-year period.

Medial temporal atrophy in preclinical dementia: Visual and automated assessment during six year follow-up

•

Visual MTA ratings can detect longitudinal changes in preclinical dementia patients.

•

Medial temporal atrophy rate is greater in individuals with an AD biomarker profile.

•

Visual MTA ratings provide a robust alternative to automated measures.

Medial temporal lobe (MTL) atrophy is an important morphological marker of many dementias and is closely related to cognitive decline. In this study we aimed to characterize longitudinal progression of MTL atrophy in 93 individuals with subjective cognitive decline and mild cognitive impairment followed up over six years, and to assess if clinical rating scales are able to detect these changes. All MRI images were visually rated according to Scheltens’ scale of medial temporal atrophy (MTA) by two neuroradiologists and AVRA, a software for automated MTA ratings. The images were also segmented using FreeSurfer’s longitudinal pipeline in order to compare the MTA ratings to volumes of the hippocampi and inferior lateral ventricles. We found that MTL atrophy rates increased with CSF biomarker abnormality, used to define preclinical stages of Alzheimer’s Disease. Both AVRA’s and the radiologists’ MTA ratings showed similar longitudinal trends as the subcortical volumes, suggesting that visual rating scales provide a valid alternative to automatic segmentations. Our results further showed that it took more than 8 years on average for individuals with mild cognitive impairment, and an Alzheimer’s disease biomarker profile, to increase the MTA score by one. This suggests that discrete MTA ratings are too coarse for tracking individual MTL atrophy in short time spans. While the MTA scores from each radiologist showed strong correlations to subcortical volumes, the inter-rater agreement was low. We conclude that the main limitation of quantifying MTL atrophy with visual ratings in clinics is the subjectiveness of the assessment.

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.

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.

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.