FDG-PET improves accuracy in distinguishing frontotemporal dementia and Alzheimer's disease.

Distinguishing Alzheimer's disease (AD) and frontotemporal dementia (FTD) currently relies on a clinical history and examination, but positron emission tomography with [(18)F] fluorodeoxyglucose (FDG-PET) shows different patterns of hypometabolism in these disorders that might aid differential diagnosis. Six dementia experts with variable FDG-PET experience made independent, forced choice, diagnostic decisions in 45 patients with pathologically confirmed AD (n = 31) or FTD (n = 14) using five separate methods: (1) review of clinical summaries, (2) a diagnostic checklist alone, (3) summary and checklist, (4) transaxial FDG-PET scans and (5) FDG-PET stereotactic surface projection (SSP) metabolic and statistical maps. In addition, we evaluated the effect of the sequential review of a clinical summary followed by SSP. Visual interpretation of SSP images was superior to clinical assessment and had the best inter-rater reliability (mean kappa = 0.78) and diagnostic accuracy (89.6%). It also had the highest specificity (97.6%) and sensitivity (86%), and positive likelihood ratio for FTD (36.5). The addition of FDG-PET to clinical summaries increased diagnostic accuracy and confidence for both AD and FTD. It was particularly helpful when raters were uncertain in their clinical diagnosis. Visual interpretation of FDG-PET after brief training is more reliable and accurate in distinguishing FTD from AD than clinical methods alone. FDG-PET adds important information that appropriately increases diagnostic confidence, even among experienced dementia specialists.

Cognitive, affective, and psychiatric features of Parkinson's disease.

Nonmotor symptoms, including cognitive deterioration and dementia, depression and apathy, and psychosis, are common in Parkinson's disease. Their presence is associated with a tremendous burden for the patient and family members. This article reviews the pathophysiololgy, risks, impact, major features, diagnosis, and treatment of these symptoms in Parkinson's disease.

Temporoparietal hypometabolism in frontotemporal lobar degeneration and associated imaging diagnostic errors.

OBJECTIVE: To evaluate the cause of diagnostic errors in the visual interpretation of positron emission tomographic scans with fludeoxyglucose F 18 (FDG-PET) in patients with frontotemporal lobar degeneration (FTLD) and patients with Alzheimer disease (AD). DESIGN: Twelve trained raters unaware of clinical and autopsy information independently reviewed FDG-PET scans and provided their diagnostic impression and confidence of either FTLD or AD. Six of these raters also recorded whether metabolism appeared normal or abnormal in 5 predefined brain regions in each hemisphere-frontal cortex, anterior cingulate cortex, anterior temporal cortex, temporoparietal cortex, and posterior cingulate cortex. Results were compared with neuropathological diagnoses. SETTING: Academic medical centers. PATIENTS: Forty-five patients with pathologically confirmed FTLD (n=14) or AD (n=31). RESULTS: Raters had a high degree of diagnostic accuracy in the interpretation of FDG-PET scans; however, raters consistently found some scans more difficult to interpret than others. Unanimity of diagnosis among the raters was more frequent in patients with AD (27 of 31 patients [87%]) than in patients with FTLD (7 of 14 patients [50%]) (P=.02). Disagreements in interpretation of scans in patients with FTLD largely occurred when there was temporoparietal hypometabolism, which was present in 7 of the 14 FTLD scans and 6 of the 7 scans lacking unanimity. Hypometabolism of anterior cingulate and anterior temporal regions had higher specificities and positive likelihood ratios for FTLD than temporoparietal hypometabolism had for AD. CONCLUSIONS: Temporoparietal hypometabolism in FTLD is common and may cause inaccurate interpretation of FDG-PET scans. An interpretation paradigm that focuses on the absence of hypometabolism in regions typically affected in AD before considering FTLD is likely to misclassify a significant portion of FTLD scans. Anterior cingulate and/or anterior temporal hypometabolism indicates a high likelihood of FTLD, even when temporoparietal hypometabolism is present. Ultimately, the accurate interpretation of FDG-PET scans in patients with dementia cannot rest on the presence or absence of a single region of hypometabolism but rather must take into account the relative hypometabolism of all brain regions.

Validation of consensus panel diagnosis in dementia.

BACKGROUND: The clinical diagnosis of dementing diseases largely depends on the subjective interpretation of patient symptoms. Consensus panels are frequently used in research to determine diagnoses when definitive pathologic findings are unavailable. Nevertheless, research on group decision making indicates that many factors can adversely affect panel performance. OBJECTIVE: To determine conditions that improve consensus panel diagnosis. DESIGN: Comparison of neuropathologic diagnoses with individual and consensus panel diagnoses based on clinical scenarios only, fludeoxyglucose F 18 positron emission tomography images only, and scenarios plus images. SETTING: Expert and trainee individual and consensus panel deliberations using a modified Delphi method in a pilot research study of the diagnostic utility of fludeoxyglucose F 18 positron emission tomography. PATIENTS: Forty-five patients with pathologically confirmed Alzheimer disease or frontotemporal dementia. MAIN OUTCOME MEASURES: Statistical measures of diagnostic accuracy, agreement, and confidence for individual raters and panelists before and after consensus deliberations. RESULTS: The consensus protocol using trainees and experts surpassed the accuracy of individual expert diagnoses when clinical information elicited diverse judgments. In these situations, consensus was 3.5 times more likely to produce positive rather than negative changes in the accuracy and diagnostic certainty of individual panelists. A rule that forced group consensus was at least as accurate as majority and unanimity rules. CONCLUSIONS: Using a modified Delphi protocol to arrive at a consensus diagnosis is a reasonable substitute for pathologic information. This protocol improves diagnostic accuracy and certainty when panelist judgments differ and is easily adapted to other research and clinical settings while avoiding the potential pitfalls of group decision making.

Heredity, genes, and headache.

It is well recognized that headache, and especially migraine, runs in families. Recent studies into the heritability of primary headache subtypes, migraine, cluster and tension headache, and conditions in which headache is a prominent feature, such as the mitochondrial disease, mitochondrial encephalopathy, lactic acidosis, and strokelike episodes, and the arteriopathy, cerebral autosomal-dominant arteriopathy with subcortical infarctions and leukoencephalopathy, are improving our understanding of the genetic contribution to headache. Studies of the rare familial hemiplegic migraine are leading to advances in understanding the pathophysiological mechanisms of the more common migraine types. Current knowledge of hereditary and genetic features of headache subtypes is reviewed and the implications for understanding the pathophysiology of migraine are discussed.

A comparison of classification methods for differentiating fronto-temporal dementia from Alzheimer's disease using FDG-PET imaging.

Flurodeoxyglucose positron emission tomography (FDG-PET) is being explored to determine its ability to differentiate between a diagnosis of Alzheimer's disease (AD) and fronto-temporal dementia (FTD). We have examined statistical discrimination procedures to help achieve this purpose and compared the results to visual ratings of FDG-PET images. The methods are applied to a data set of 48 subjects with autopsy confirmed diagnoses of AD or FTD (these subjects come from a multi-centre collaborative study funded by the National Alzheimer's Coordinating Center). FDG-PET images are composed of thousands of voxels (volume elements) so one is left with a situation where there are vastly more variables than subjects. Therefore, it is necessary to perform a data reduction before a statistical procedure can be applied. Approaches using both the entire image and summary statistics calculated on a number of volumes of interest (VOI) are examined. We performed the data reduction techniques of principal components analysis (PCA) and partial least-squares (PLS) on the entire image and then used linear discriminant analysis (LDA), quadratic (QDA) or logistic regression (LR) to classify subjects as having AD or FTD. Some of these methods achieve diagnostic accuracy (as assessed by leave-one-out cross-validation) that is similar to visual ratings by expert raters. Methods using PLS appear to be more successful. Averaging or using VOI data may also be helpful.