Although the diagnosis of dementia still is primarily based on clinical criteria, neuroimaging is playing an increasingly important role. This is in large part due to advances in techniques that can assist with discriminating between different syndromes. Magnetic resonance imaging remains at the core of differential diagnosis, with specific patterns of cortical and subcortical changes having diagnostic significance. Recent developments in molecular PET imaging techniques have opened the door for not only antemortem but early, even preclinical, diagnosis of underlying pathology. This is vital, as treatment trials are underway for pharmacological agents with specific molecular targets, and numerous failed trials suggest that earlier treatment is needed. This article provides an overview of classic neuroimaging findings as well as new and cutting-edge research techniques that assist with clinical diagnosis of a range of dementia syndromes, with an emphasis on studies using pathologically proven cases.

Background

Myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD) and pediatric-onset multiple sclerosis (POMS) share clinical and magnetic resonance imaging (MRI) features but differ in prognosis and management. Early POMS diagnosis is essential to avoid disability accumulation. Central vein sign (CVS), paramagnetic rim lesions (PRLs), and central core lesions (CCLs) are susceptibility-based imaging (SbI)-related signs understudied in pediatric populations that may help discerning POMS from MOGAD.

Methods

T2-FLAIR and SbI (three-dimensional echoplanar imaging (3D-EPI)/susceptibility-weighted imaging (SWI) or similar) were acquired on 1.5T/3T scanners. Two readers assessed CVS-positive rate (%CVS+), and their average score was used to build a receiver operator curve (ROC) assessing the ability to discriminate disease type. PRLs and CCLs were identified using a consensual approach.

Results

The %CVS+ distinguished 26 POMS cases (mean age 13.7 years, 63% females, median EDSS 1.5) from 14 MOGAD cases (10.8 years, 35% females, EDSS 1.0) with ROC = 1, p < 0.0001, (cutoff 41%). PRLs were only detectable in POMS participants (mean 2.1±2.3, range 1-10), discriminating the two conditions with a sensitivity of 69% and a specificity of 100%. CCLs were more sensitive (81%) but less specific (71.43%).

Conclusion

The %CVS+ and PRLs are highly specific markers of POMS. After proper validation on larger multicenter cohorts, consideration should be given to including such imaging markers for diagnosing POMS at disease onset.

Diffusion imaging is very useful for the diagnosis of sporadic Creutzfeldt-Jakob disease, but it has limitations in tracking disease progression as mean diffusivity changes non-linearly across the disease course. We previously showed that mean diffusivity changes across the disease course follow a quasi J-shaped curve, characterized by decreased values in earlier phases and increasing values later in the disease course. Understanding how MRI metrics change over-time, as well as their correlations with clinical deficits are crucial steps in developing radiological biomarkers for trials. Specifically, as mean diffusivity does not change linearly and atrophy mainly occurs in later stages, neither alone is likely to be a sufficient biomarker throughout the disease course. We therefore developed a model combining mean diffusivity and Volume loss (MRI Disease-Staging) to take into account mean diffusivity's non-linearity. We then assessed the associations between clinical outcomes and mean diffusivity alone, Volume alone and finally MRI Disease-Staging. In 37 sporadic Creutzfeldt-Jakob disease subjects and 30 age- and sex-matched healthy controls, high angular resolution diffusion and high-resolution T1 imaging was performed cross-sectionally to compute z-scores for mean diffusivity (MD) and Volume. Average MD and Volume were extracted from 41 GM volume of interest (VOI) per hemisphere, within the images registered to the Montreal Neurological Institute (MNI) space. Each subject's volume of interest was classified as either "involved" or "not involved" using a statistical threshold of ± 2 standard deviation (SD) for mean diffusivity changes and/or -2 SD for Volume. Volumes of interest were MRI Disease-Staged as: 0 = no abnormalities; 1 = decreased mean diffusivity only; 2 = decreased mean diffusivity and Volume; 3 = normal ("pseudo-normalized") mean diffusivity, reduced Volume; 4 = increased mean diffusivity, reduced Volume. We correlated Volume, MD and MRI Disease-Staging with several clinical outcomes (scales, score and symptoms) using 4 major regions of interest (Total, Cortical, Subcortical and Cerebellar gray matter) or smaller regions pre-specified based on known neuroanatomical correlates. Volume and MD z-scores correlated inversely with each other in all four major ROIs (cortical, subcortical, cerebellar and total) highlighting that ROIs with lower Volumes had higher MD and vice-versa. Regarding correlations with symptoms and scores, higher MD correlated with worse Mini-Mental State Examination and Barthel scores in cortical and cerebellar gray matter, but subjects with cortical sensory deficits showed lower MD in the primary sensory cortex. Volume loss correlated with lower Mini-Mental State Examination, Barthel scores and pyramidal signs. Interestingly, for both Volume and MD, changes within the cerebellar ROI showed strong correlations with both MMSE and Barthel. Supporting using a combination of MD and Volume to track sCJD progression, MRI Disease-Staging showed correlations with more clinical outcomes than Volume or MD alone, specifically with Mini-Mental State Examination, Barthel score, pyramidal signs, higher cortical sensory deficits, as well as executive and visual-spatial deficits. Additionally, when subjects in the cohort were subdivided into tertiles based on their Barthel scores and their percentile of disease duration/course ("Time-Ratio"), subjects in the lowest (most impaired) Barthel tertile showed a much greater proportion of more advanced MRI Disease-Stages than the those in the highest tertile. Similarly, subjects in the last Time-Ratio tertile (last tertile of disease) showed a much greater proportion of more advanced MRI Disease-Stages than the earliest tertile. Therefore, in later disease stages, as measured by time or Barthel, there is overall more Volume loss and increasing MD. A combined multiparametric quantitative MRI Disease-Staging is a useful tool to track sporadic Creutzfeldt-Jakob- disease progression radiologically.

Objective

Rates of worsening and evolution to secondary progressive multiple sclerosis (MS) may be substantially lower in actively treated patients compared to natural history studies from the pretreatment era. Nonetheless, in our recently reported prospective cohort, more than half of patients with relapsing MS accumulated significant new disability by the 10th year of follow-up. Notably, "no evidence of disease activity" at 2 years did not predict long-term stability. Here, we determined to what extent clinical relapses and radiographic evidence of disease activity contribute to long-term disability accumulation.

Methods

Disability progression was defined as an increase in Expanded Disability Status Scale (EDSS) of 1.5, 1.0, or 0.5 (or greater) from baseline EDSS = 0, 1.0-5.0, and 5.5 or higher, respectively, assessed from baseline to year 5 (±1 year) and sustained to year 10 (±1 year). Longitudinal analysis of relative brain volume loss used a linear mixed model with sex, age, disease duration, and HLA-DRB1*15:01 as covariates.

Results

Relapses were associated with a transient increase in disability over 1-year intervals (p = 0.012) but not with confirmed disability progression (p = 0.551). Relative brain volume declined at a greater rate among individuals with disability progression compared to those who remained stable (p < 0.05).

Interpretation

Long-term worsening is common in relapsing MS patients, is largely independent of relapse activity, and is associated with accelerated brain atrophy. We propose the term silent progression to describe the insidious disability that accrues in many patients who satisfy traditional criteria for relapsing-remitting MS. Ann Neurol 2019;85:653-666.

Objective

A major challenge in multiple sclerosis (MS) research is the understanding of silent progression and Progressive MS. Using a novel method to accurately capture upper cervical cord area from legacy brain MRI scans we aimed to study the role of spinal cord and brain atrophy for silent progression and conversion to secondary progressive disease (SPMS).

Methods

From a single-center observational study, all RRMS (n = 360) and SPMS (n = 47) patients and 80 matched controls were evaluated. RRMS patient subsets who converted to SPMS (n = 54) or silently progressed (n = 159), respectively, during the 12-year observation period were compared to clinically matched RRMS patients remaining RRMS (n = 54) or stable (n = 147), respectively. From brain MRI, we assessed the value of brain and spinal cord measures to predict silent progression and SPMS conversion.

Results

Patients who developed SPMS showed faster cord atrophy rates (-2.19%/yr) at least 4 years before conversion compared to their RRMS matches (-0.88%/yr, p < 0.001). Spinal cord atrophy rates decelerated after conversion (-1.63%/yr, p = 0.010) towards those of SPMS patients from study entry (-1.04%). Each 1% faster spinal cord atrophy rate was associated with 69% (p < 0.0001) and 53% (p < 0.0001) shorter time to silent progression and SPMS conversion, respectively.

Interpretation

Silent progression and conversion to secondary progressive disease are predominantly related to cervical cord atrophy. This atrophy is often present from the earliest disease stages and predicts the speed of silent progression and conversion to Progressive MS. Diagnosis of SPMS is rather a late recognition of this neurodegenerative process than a distinct disease phase. ANN NEUROL 2022;91:268-281.

White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process.