Differential Diagnosis Of Dementia Research Articles

PET CT Brain for the Differential Diagnosis of Dementia -Indian Case Reports

India has been termed as Diabetic hub of the globe. Along with other complications, one of the underestimated complication is cognitive decline and memory loss associated with poor diabetes control. In the Indian context, structural imaging like MRI-Magnetic Resonance imaging is more commonly used in Neurological disorders such as stroke, head injury, Functional imaging of the human brain has been underutilized in the Indian scenario. One such technique is PET CT which has been typically used as a cancer biomarker in India. By virtue of current case study, we propose i) association between poor control of Diabetes and poor cognition ii) role of PET CT brain in differential diagnosis of Dementia. We present two case reports providing strong findings for utilization of PET CT brain in Dementia protocols.

Clinical impact of 18F-FDG-PET among memory clinic patients with uncertain diagnosis

PurposeTo assess the clinical impact and incremental diagnostic value of 18F-fluorodeoxyglucose (FDG-PET) among memory clinic patients with uncertain diagnosis.MethodsThe study population consisted of 277 patients who, despite extensive baseline cognitive assessment, MRI, and CSF analyses, had an uncertain diagnosis of mild cognitive impairment (MCI) (n = 177) or dementia (n = 100). After baseline diagnosis, each patient underwent an FDG-PET, followed by a post-FDG-PET diagnosis formulation. We evaluated (i) the change in diagnosis (baseline vs. post-FDG-PET), (ii) the change in diagnostic accuracy when comparing each baseline and post-FDG-PET diagnosis to a long-term follow-up (3.6 ± 1.8 years) diagnosis used as reference, and (iii) comparative FDG-PET performance testing in MCI and dementia conditions.ResultsFDG-PET led to a change in diagnosis in 86 of 277 (31%) patients, in particular in 57 of 177 (32%) MCI and in 29 of 100 (29%) dementia patients. Diagnostic change was greater than two-fold in the sub-sample of cases with dementia “of unclear etiology” (change in diagnosis in 20 of 32 (63%) patients). In the dementia group, after results of FDG-PET, diagnostic accuracy improved from 77 to 90% in Alzheimer’s disease (AD) and from 85 to 94% in frontotemporal lobar degeneration (FTLD) patients (p < 0.01). FDG-PET performed better in dementia than in MCI (positive likelihood ratios >5 and < 5, respectively).ConclusionWithin a selected clinical population, FDG-PET has a significant clinical impact, both in early and differential diagnosis of uncertain dementia. FDG-PET provides significant incremental value to detect AD and FTLD over a clinical diagnosis of uncertain dementia.

Cognitive tests aid in clinical differentiation of Alzheimer's disease versus Alzheimer's disease with Lewy body disease: Evidence from a pathological study.

Clinical differentiation between Alzheimer's disease (AD) and AD with Lewy body disease (LBD) is relatively imprecise. The current study examined pathologically confirmed group differences in neuropsychological functioning, and the classification ability of specific tests. Fifty-one participants with postmortem diagnoses of AD (n = 34) and AD plus LBD (n = 17) were drawn from the Predictors Study. One-way analyses of variance (ANOVAs) and χ2 analyses examined group differences in neuropsychological performance. Binary logistic regressions examined predictive utility of specific tests for pathological diagnosis. Individuals with AD had better visuoconstruction (P = .006), phonemic fluency (P = .08), and processing speed than AD plus LBD (P = .013). No differences were found in memory, naming, semantic fluency, or set-switching. Processing speed and visuoconstruction predicted pathologic group (P = .03). Processing speed and visuoconstruction predicted postmortem diagnosis of AD versus AD plus LBD. Current results offer guidance in the selection and interpretation of neuropsychological tests to be used in the differential diagnosis of early dementia.

A Machine Learning Approach for the Differential Diagnosis of Alzheimer and Vascular Dementia Fed by MRI Selected Features.

Among dementia-like diseases, Alzheimer disease (AD) and vascular dementia (VD) are two of the most frequent. AD and VD may share multiple neurological symptoms that may lead to controversial diagnoses when using conventional clinical and MRI criteria. Therefore, other approaches are needed to overcome this issue. Machine learning (ML) combined with magnetic resonance imaging (MRI) has been shown to improve the diagnostic accuracy of several neurodegenerative diseases, including dementia. To this end, in this study, we investigated, first, whether different kinds of ML algorithms, combined with advanced MRI features, could be supportive in classifying VD from AD and, second, whether the developed approach might help in predicting the prevalent disease in subjects with an unclear profile of AD or VD. Three ML categories of algorithms were tested: artificial neural network (ANN), support vector machine (SVM), and adaptive neuro-fuzzy inference system (ANFIS). Multiple regional metrics from resting-state fMRI (rs-fMRI) and diffusion tensor imaging (DTI) of 60 subjects (33 AD, 27 VD) were used as input features to train the algorithms and find the best feature pattern to classify VD from AD. We then used the identified VD–AD discriminant feature pattern as input for the most performant ML algorithm to predict the disease prevalence in 15 dementia patients with a “mixed VD–AD dementia” (MXD) clinical profile using their baseline MRI data. ML predictions were compared with the diagnosis evidence from a 3-year clinical follow-up. ANFIS emerged as the most efficient algorithm in discriminating AD from VD, reaching a classification accuracy greater than 84% using a small feature pattern. Moreover, ANFIS showed improved classification accuracy when trained with a multimodal input feature data set (e.g., DTI + rs-fMRI metrics) rather than a unimodal feature data set. When applying the best discriminant pattern to the MXD group, ANFIS achieved a correct prediction rate of 77.33%. Overall, results showed that our approach has a high discriminant power to classify AD and VD profiles. Moreover, the same approach also showed potential in predicting earlier the prevalent underlying disease in dementia patients whose clinical profile is uncertain between AD and VD, therefore suggesting its usefulness in supporting physicians' diagnostic evaluations.

Cholinergic dysfunction, neurodegeneration, and amyloid-beta pathology in neurodegenerative diseases

Cholinergic dysfunction is central in Alzheimer's disease (AD) and dementia with Lewy bodies (DLB). The electroencephalography-based acetylcholine index (EEG-Ach index) has been proposed as a biomarker of cholinergic dysfunction. However, it is unclear how the EEG-Ach index relates to amyloid-beta pathology and neurodegeneration. We investigated the association between the EEG-Ach index and cerebrospinal fluid (CSF) amyloid-beta, CSF total tau, cortical thickness, and hippocampal volume from magnetic resonance imaging (MRI), and cognition. A total of 127 patients with different neurodegenerative diseases were studied. The EEG-Ach index was calculated from quantitative EEG using statistical pattern recognition. The EEG-Ach index was associated with hippocampal volume and cortical thickness in frontal, temporal, and occipital cortices. Cross-sectional sub-analyses based on a small sample suggests that the EEG-Ach index increases the closest to AD dementia, downstream to amyloid-beta pathology, CSF total tau, and hippocampal volume. We conclude that cholinergic dysfunction correlates with atrophy in brain areas important for AD pathogenesis, and this association is more prominent in the dementia stage. These results together with previous studies from this project suggest that the EEG-Ach index may be a useful biomarker for cholinergic dysfunction, with value for differential diagnosis of dementia and monitoring patients at the dementia stage.

Amyloid PET in Dementia Syndromes: A Chinese Multicenter Study.

Cerebral β-amyloid deposits and regional glucose metabolism assessed by PET are used to distinguish between Alzheimer disease (AD) and other dementia syndromes. In the present multicenter study, we estimated the prevalence of β-amyloid deposits on PET imaging in a wide variety of dementia syndromes and mild cognitive impairment (MCI) within a memory clinic population. Methods: Of the 1,193 consecutive patients with cognitive impairment (CI) who received 1 11C-PIB PET or 18F-AV45 PET or both 11C-PIB PET and 18F-AV45 PET, 960 were diagnosed with AD, 36 with frontotemporal dementia (FTD), 5 with dementia with Lewy bodies, 144 with MCI, 29 with vascular dementia, 4 with corticobasal syndrome, and 15 with unclassifiable dementia. Baseline clinical diagnoses were independently established without access to PET imaging results. Apolipoprotein E (ApoE) genotype analysis was performed on CI patients and 231 sex- and age-matched controls. Results: Of the 1,193 CI patients, 860 (72.1%) were amyloid-positive. The prevalence of amyloid positivity in AD and MCI patients was 86.8% (833/960) and 9.7% (14/144), respectively. In FTD patients, the prevalence of β-amyloid deposits was 5.6% (2/36). In the 4 corticobasal syndrome patients, 2 were amyloid-positive. Three of the 5 patients with dementia with Lewy bodies showed amyloid positivity, as did 6 of the 29 vascular dementia (20.7%) patients. The ApoEε4 allele frequency was significantly increased in amyloid-positive CI patients (30.5%) as compared with other amyloid-negative CI patients (14%) or controls (7.3%). Conclusion: Amyloid imaging may potentially be the most helpful parameter for differential diagnosis in dementia, particularly to distinguish between AD and FTD. Amyloid PET can be used in conjunction with the ApoEε4 allele genetic risk test for amyloid deposits.

A new tetra-plex fluorimetric assay for the quantification of cerebrospinal fluid β-amyloid42, total-tau, phospho-tau and α-synuclein in the differential diagnosis of neurodegenerative dementia.

Differential diagnosis of neurodegenerative dementia is currently supported by biomarkers including cerebrospinal fluid (CSF) tests. Among them, CSF total-tau (t-tau), phosphorylated tau (p-tau) and β-amyloid42 (Aβ42) are considered core biomarkers of neurodegeneration. In the present work, we hypothesize that simultaneous assessment of these biomarkers together with CSF α-synuclein (α-syn) will significantly improve the differential diagnostic of Alzheimer's disease and other dementias. To that aim, we characterized the analytical and clinical performance of a new tetra-plex immunoassay that simultaneously quantifies CSF Aβ42, t-tau, p-tau and α-syn in the differential diagnosis of neurodegenerative dementia. Biomarkers' concentrations were measured in neurological controls (n = 38), Alzheimer's disease (n = 35), Creutzfeldt-Jakob disease (n = 37), vascular dementia (n = 28), dementia with Lewy bodies/Parkinson's disease dementia (n = 27) and frontotemporal dementia (n = 34) using the new tetra-plex assay and established single-plex assays. Biomarker's performance was evaluated and diagnostic accuracy in the discrimination of diagnostic groups was determined using partial least squares discriminant analysis. The tetra-plex assay presented accuracies similar to individual single-plex assays with acceptable analytical performance. Significant correlations were observed between tetra-plex and single-plex assays. Using partial least squares discriminant analysis, Alzheimer's disease and Creutzfeldt-Jakob disease were well differentiated, reaching high accuracies in the discrimination from the rest of diagnostic groups. The new tetra-plex assay coupled with multivariate analytical approaches becomes a valuable asset for the differential diagnosis of neurodegenerative dementia and related applications.

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

AimsThe 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.MethodsThe 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.ResultsIntra-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.ConclusionThe 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.

Alpha-synuclein Levels in the Differential Diagnosis of Lewy Bodies Dementia and Other Neurodegenerative Disorders: A Meta-analysis.

Lewy body dementia (LBD) is the second most common type of neurodegenerative dementia after Alzheimer disease (AD). It is characterized by the accumulation of Lewy bodies and Lewy neurites which are composed of aggregated phosphorylated alpha-synuclein, which is a presynaptic neuronal protein genetically and neuropathologically linked to Parkinson disease and to LBD. Alpha-synuclein is thought to contribute to LBD pathogenesis and to linked to disruption of cellular homeostasis and neuronal death, through effects on various intracellular targets, including synaptic function. In the present study, we did a meta-analysis on the reliability of alpha-synuclein levels in the cerebrospinal fluid (CSF) for the discrimination between LBD and other neurodegenerative disorders including AD, Parkinson disease (PD) dementia, progressive supranuclear palsy (PSP), multiple system atrophy (MSA) and frontotemporal dementia (FTD). CSF alpha-synuclein levels were significantly different in LBD compared with AD, but no statistical difference was found between LBD, and dementia in PD, MSA, PSP, and FTD. Alpha-synuclein levels in the CSF can be used for the discrimination between LBD and AD, but not LBD and other neurodegenerative disorders such as dementia in PD, MSA, FTD, and PSP.

Functional Neuroimaging in Psychiatry-Aiding in Diagnosis and Guiding Treatment. What the American Psychiatric Association Does Not Know.

While early efforts in psychiatry were focused on uncovering the neurobiological basis of psychiatric symptoms, they made little progress due to limited ability to observe the living brain. Today, we know a great deal about the workings of the brain; yet, none of this neurobiological awareness has translated into the practice of psychiatry. The categorical system which dominates psychiatric diagnosis and thinking fails to match up to the real world of genetics, sophisticated psychological testing, and neuroimaging. Nevertheless, the American Psychiatric Association (APA) recently published a position paper stating that neuroimaging provided no benefit to the diagnosis and treatment of psychiatric disorders. Using the diagnosis of depression as a model, we illustrate how setting aside the unrealistic expectation of a pathognomonic “fingerprint” for categorical diagnoses, we can avoid missing the biological and, therefore, treatable contributors to psychopathology which can and are visualized using functional neuroimaging. Infection, toxicity, inflammation, gut-brain dysregulation, and traumatic brain injury can all induce psychiatric manifestations which masquerade as depression and other psychiatric disorders. We review these and provide illustrative clinical examples. We further describe situations for which single photon emission computed tomography (SPECT) and positron emission tomography (PET) functional neuroimaging already meet or exceed the criteria set forth by the APA to define a neuroimaging biomarker, including the differential diagnosis of Alzheimer's disease and other dementias, the differential diagnosis of ADHD, and the evaluation of traumatic brain injury. The limitations, both real and perceived, of SPECT and PET functional neuroimaging in the field of psychiatry are also elaborated. An important overarching concept for diagnostic imaging in all its forms, including functional neuroimaging, is that imaging allows a clinician to eliminate possibilities, narrow the differential diagnosis, and tailor the treatment plan. This progression is central to any medical diagnostic process.

Cerebrospinal fluid lipocalin 2 as a novel biomarker for the differential diagnosis of vascular dementia

The clinical diagnosis of vascular dementia (VaD) is based on imaging criteria, and specific biochemical markers are not available. Here, we investigated the potential of cerebrospinal fluid (CSF) lipocalin 2 (LCN2), a secreted glycoprotein that has been suggested as mediating neuronal damage in vascular brain injuries. The study included four independent cohorts with a total n = 472 samples. LCN2 was significantly elevated in VaD compared to controls, Alzheimer’s disease (AD), other neurodegenerative dementias, and cognitively unimpaired patients with cerebrovascular disease. LCN2 discriminated VaD from AD without coexisting VaD with high accuracy. The main findings were consistent over all cohorts. Neuropathology disclosed a high percentage of macrophages linked to subacute infarcts, reactive astrocytes, and damaged blood vessels in multi-infarct dementia when compared to AD. We conclude that CSF LCN2 is a promising candidate biochemical marker in the differential diagnosis of VaD and neurodegenerative dementias.

Evaluating 2-[18F]FDG-PET in differential diagnosis of dementia using a data-driven decision model.

2-[18F]fluoro-2-deoxy-d-glucose positron emission tomography (2-[18F]FDG-PET) has an emerging supportive role in dementia diagnostic as distinctive metabolic patterns are specific for Alzheimer's disease (AD), dementia with Lewy bodies (DLB) and frontotemporal dementia (FTD). Previous studies have demonstrated that a data-driven decision model based on the disease state index (DSI) classifier supports clinicians in the differential diagnosis of dementia by using different combinations of diagnostic tests and biomarkers. Until now, this model has not included 2-[18F]FDG-PET data. The objective of the study was to evaluate 2-[18F]FDG-PET biomarkers combined with commonly used diagnostic tests in the differential diagnosis of dementia using the DSI classifier. We included data from 259 subjects diagnosed with AD, DLB, FTD, vascular dementia (VaD), and subjective cognitive decline from two independent study cohorts. We also evaluated three 2-[18F]FDG-PET biomarkers (anterior vs. posterior index (API-PET), occipital vs. temporal index, and cingulate island sign) to improve the classification accuracy for both FTD and DLB. We found that the addition of 2-[18F]FDG-PET biomarkers to cognitive tests, CSF and MRI biomarkers considerably improved the classification accuracy for all pairwise comparisons of DLB (balanced accuracies: DLB vs. AD from 64% to 77%; DLB vs. FTD from 71% to 92%; and DLB vs. VaD from 71% to 84%). The two 2-[18F]FDG-PET biomarkers, API-PET and occipital vs. temporal index, improved the accuracy for FTD and DLB, especially as compared to AD. Moreover, different combinations of diagnostic tests were valuable to differentiate specific subtypes of dementia. In conclusion, this study demonstrated that the addition of 2-[18F]FDG-PET to commonly used diagnostic tests provided complementary information that may help clinicians in diagnosing patients, particularly for differentiating between patients with FTD, DLB, and AD.

Automated MRI volumetry as a diagnostic tool for Alzheimer's disease: Validation of icobrain dm.

Brain volumes computed from magnetic resonance images have potential for assisting with the diagnosis of individual dementia patients, provided that they have low measurement error and high reliability. In this paper we describe and validate icobrain dm, an automatic tool that segments brain structures that are relevant for differential diagnosis of dementia, such as the hippocampi and cerebral lobes. Experiments were conducted in comparison to the widely used FreeSurfer software. The hippocampus segmentations were compared against manual segmentations, with significantly higher Dice coefficients obtained with icobrain dm (25-75th quantiles: 0.86-0.88) than with FreeSurfer (25-75th quantiles: 0.80-0.83). Other brain structures were also compared against manual delineations, with icobrain dm showing lower volumetric errors overall. Test-retest experiments show that the precision of all measurements is higher for icobrain dm than for FreeSurfer except for the parietal cortex volume. Finally, when comparing volumes obtained from Alzheimer's disease patients against age-matched healthy controls, all measures achieved high diagnostic performance levels when discriminating patients from cognitively healthy controls, with the temporal cortex volume measured by icobrain dm reaching the highest diagnostic performance level (area under the receiver operating characteristic curve=0.99) in this dataset.

A retrospective study on the diagnosis and treatment of dementia in patients referred to the Sagamihara Municipal Medical Center for Dementia for consultation.

In Japan, the Orange Plan was formulated in 2013 to promote community-based integrated care systems, and in 2015, it was revised as the New Orange Plan. Since the introduction of these programmes, adequate research has not been carried out on how these measures affect regional dementia care. The aim of this study was to investigate the state of community-based dementia treatment through a survey of medical consultation pathways, including dementia diagnosis, at the Sagamihara Municipal Medical Center for Dementia. The participants included 1480 patients (585 men, 895 women) who presented for consultation at the Sagamihara Municipal Medical Center for Dementia for a differential diagnosis or treatment of dementia. The relationship between the path leading to medical consultation before pharmacotherapy and post-consultation diagnosis was investigated. Significantly more participants who presented for consultation without a referral were not diagnosed with dementia than diagnosed. Furthermore, among participants referred from a non-psychiatric clinic, significantly more patients were diagnosed with dementia than not. A significant difference was observed in a comparison of facility types and the use or non-use of anti-dementia drugs. Notably, the rate of anti-dementia drug prescriptions was significantly higher in psychiatric hospitals and non-psychiatric clinics. Furthermore, it is possible that approximately 30% of anti-dementia drugs prescribed at each facility were not covered by insurance. Community-based integrated care systems aim to promote collaboration within each region aimed. However, appropriate pharmacotherapy methods for dementia patients have not been adequately communicated to non-specialist physicians and local residents. For this reason, human resource solutions are needed to help medical staff deepen their understanding of dementia so that they can better provide dementia support to patients.

18F-FDG in the differential diagnosis of neurodegenerative dementias

The diagnostic workflow of patients with cognitive decline needs an extensive clinical evaluation. The use of FDG-PET can be helpful because the finding of a rather specific pattern of hypometabolism could point to specific neurodegenerative disorders. In patients with memory impairment and visuo-spatial deficits, FDG-PET may reveal a pattern of temporo-parietal hypometabolism that is associated with Alzheimer’s disease or a more extended area of hypometabolism that spreads to the occipital cortex, as in posterior cortical atrophy indicating signs of neurodegeneration in the associative visual cortex. In the spectrum of fronto-temporal lobe degeneration, FDG-PET is used to support the diagnosis by excluding AD and to identify areas of hypometabolism that are associated with the behavioural variant of FTD or with progressive primary aphasia. When cognitive impairment develops along with parkinsonism, FDG-PET can be used to differentiate among the different forms of disorders, such as dementia with Lewy bodies, progressive supranuclear palsy and cortico-basal degeneration, occurring with different specific pattern of altered metabolism. In this pictorial essay, we present a series of clinical cases in which the use of FDG-PET contributed to the final diagnosis.

A Brief Drawing Task for the Differential Diagnosis of Semantic Dementia.

Semantic dementia (SD) is a subtype of frontotemporal lobe degeneration characterized by semantic loss, with other cognitive functions initially preserved. SD requires differential diagnosis with Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD). Semantic knowledge can be evaluated through different tests; however, most of them depend on language. We describe the development of a brief drawing task that may be helpful for the differential diagnosis of SD. Seventy-two patients, including 32 AD, 19 bvFTD, and 21 SD were asked to draw 12 items with different age of acquisition and familiarity, belonging to four different semantic categories. We employed the drawings of healthy volunteers to build a scoring scheme. Turtle, strawberry, train, and envelope were the items of each category that best discriminated between groups and were selected for the Brief drawing task. The discriminatory power of the Brief drawing task between SD versus AD and bvFTD patients, estimated through the area under the curve was 0.84 (95% CI = 0.72-0.96, p = 0.000007). In a logistic model, the Brief drawing task (p = 0.003) and VOSP "number location" subtest (p = 0.016) were significant predictors of the diagnosis of SD versus AD and bvFTD after adjustment by the main covariates. The Brief drawing task provided clinically useful qualitative information. SD drawings were characterized by loss of the distinctive features, intrusions, tendency to prototype, and answers like "I don't know what this is". The Brief drawing task appears to reveal deficits in semantic knowledge among patients with SD that may assist in the differential diagnosis with other neurodegenerative diseases.

Cerebrospinal fluid biomarkers and cognitive status in differential diagnosis of frontotemporal dementia and Alzheimer's disease.

ObjectiveThis study aimed to determine the most appropriate cognitive and cerebrospinal fluid (CSF) biomarker setting to distinguish frontotemporal dementia (FTD) from Alzheimer’s disease (AD).MethodPatients with FTD, those with AD, and those without dementia were enrolled in this study. CSF amyloid-ß 42 (Aß42), total (t)-tau, and phosphorylated (p)-tau concentrations were determined by enzyme-linked immunosorbent assays. Cognition was evaluated by the Mini-Mental State Examination (MMSE) and its domain scores. The associations of CSF biomarkers with cognitive measures were examined using regression models and the diagnostic value of CSF biomarkers was determined by receiver operating characteristics curves.ResultsCSF Aß42 levels were lower, whereas t-tau/Aß42 and p-tau/Aß42 ratios were higher in patients with AD compared with those with FTD. Some MMSE domain scores were different in FTD and AD, but they did not improve the ability to distinguish between the two pathologies. Poor temporal orientation scores were associated with low Aß42 levels only in patients with FTD. The p-tau/Aß42 ratio reached sufficient levels of sensitivity and specificity to discriminate FTD with primary progressive aphasia from AD.ConclusionsThe ratio of CSF p-tau/Aß42 is a sensitive and specific biomarker for discriminating patients with primary progressive aphasia from those with AD.

Differentiation Between Dementia With Lewy Bodies And Alzheimer's Disease Using Voxel-Based Morphometry Of Structural MRI: A Multicenter Study.

BackgroundThe differential diagnosis of dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD) is particularly important because DLB patients respond better to cholinesterase inhibitors but sometimes exhibit sensitivity to neuroleptics, which may cause worsening of clinical status. Antemortem voxel-based morphometry (VBM) using structural MRI has previously revealed that patients with DLB have normal hippocampal volume, but atrophy in the dorsal mesopontine area.ObjectivesThe aim of this multicenter study was to determine whether VBM of the brain stem in addition to that of medial temporal lobe structures improves the differential diagnosis of AD and DLB.MethodsWe retrospectively chose 624 patients who were clinically diagnosed with either DLB (239 patients) or AD (385 patients) from 10 institutes using different MR scanners with different magnetic field strengths. In all cases, VBM was performed on 3D T1-weighted images. The degree of local atrophy was calculated using Z-score by comparison with a database of normal volumes of interest (VOIs) in medial temporal lobe (MTL) and the dorsal brain stem (DBS). The discrimination of DLB and AD was evaluated using Z-score values in these two VOIs. MRI data from 414 patients were used as the training data set to determine the classification criteria, with the MRI data from the remaining 210 patients used as the test data set.ResultsThe DLB and AD patients did not differ with respect to mean age or Mini-Mental State Examination scores. Z-index scores showed that there was significantly more atrophy in MTL of AD patients, compared to DLB patients and in DBS of DLB patients, compared to AD patients. The discrimination accuracies of VBM were 63.3% in the test data set and 73.4% in the training data set.ConclusionVBM of DBS in addition to that of MTL improves the differentiation of DLB and AD.

The Use of Biomarkers and Genetic Screening to Diagnose Frontotemporal Dementia: Evidence and Clinical Implications.

Within the wide range of neurodegenerative brain diseases, the differential diagnosis of frontotemporal dementia (FTD) frequently poses a challenge. Often, signs and symptoms are not characteristic of the disease and may instead reflect atypical presentations. Consequently, the use of disease biomarkers is of importance to correctly identify the patients. Here, we describe how neuropsychological characteristics, neuroimaging and neurochemical biomarkers and screening for causal gene mutations can be used to differentiate FTD from other neurodegenerative diseases as well as to distinguish between FTD subtypes. Summarizing current evidence, we propose a stepwise approach in the diagnostic evaluation. Clinical consensus criteria that take into account a full neuropsychological examination have relatively good accuracy (sensitivity [se] 75–95%, specificity [sp] 82–95%) to diagnose FTD, although misdiagnosis (mostly AD) is common. Structural brain MRI (se 70–94%, sp 89–99%) and FDG PET (se 47–90%, sp 68–98%) or SPECT (se 36–100%, sp 41–100%) brain scans greatly increase diagnostic accuracy, showing greater involvement of frontal and anterior temporal lobes, with sparing of hippocampi and medial temporal lobes. If these results are inconclusive, we suggest detecting amyloid and tau cerebrospinal fluid (CSF) biomarkers that can indicate the presence of AD with good accuracy (se 74–100%, sp 82–97%). The use of P-tau181 and the Aβ1–42/Aβ1–40 ratio significantly increases the accuracy of correctly identifying FTD vs. AD. Alternatively, an amyloid brain PET scan can be performed to differentiate FTD from AD. When autosomal dominant inheritance is suspected, or in early onset dementia, mutation screening of causal genes is indicated and may also be offered to at-risk family members. We have summarized genotype–phenotype correlations for several genes that are known to cause familial frontotemporal lobar degeneration, which is the neuropathological substrate of FTD. The genes most commonly associated with this disease (C9orf72, MAPT, GRN, TBK1) are discussed, as well as some less frequent ones (CHMP2B, VCP). Several other techniques, such as diffusion tensor imaging, tau PET imaging and measuring serum neurofilament levels, show promise for future implementation as diagnostic biomarkers.

Update on PET in neurodegenerative and neuroinflammatory disorders manifesting on a behavioural level: imaging for differential diagnosis

To give an update on recent findings concerning the use of PET for differential diagnosis in neurodegenerative and neuroinflammatory disorders manifesting on a behavioural level. Although accurate differential diagnosis of dementia can be achieved by imaging disease-specific patterns of cerebral glucose metabolism with [F]fluorodeoxyglucose ([F]FDG)-PET, the diagnostic impact of [F]FDG-PET in primary psychiatric disorders is limited. Amyloid-beta PET provides an incremental value beyond [F]FDG-PET in the differential diagnosis of dementia and was proposed as a biomarker defining the so-called Alzheimer continuum. Recently developed tau-specific tracers might also aid in the diagnostic process (biological definition of Alzheimer's disease together with amyloid-beta). Surpassing the diagnostic accuracy of other techniques, such as MRI, [F]FDG-PET has also gained widespread clinical use for diagnosis and follow-up of paraneoplastic and autoimmune disorders of the central nervous system (CNS) as an important differential diagnosis for rapid progressive dementia and subacute onset of psychiatric syndromes. Molecular neuroimaging with PET is an established method for the differential diagnosis of neurodegenerative and autoimmune CNS disorders manifesting on a behavioural level with significant therapeutic and prognostic impact. Future prospective studies are needed to define the value of tau imaging for diagnosis and prognosis in neurodegenerative disorders.