Scheltens, Philip

Abstract Introduction A classification framework for posterior cortical atrophy (PCA) is proposed to improve the uniformity of definition of the syndrome in a variety of research settings. Methods Consensus statements about PCA were developed through a detailed literature review, the formation of an international multidisciplinary working party which convened on four occasions, and a Web‐based quantitative survey regarding symptom frequency and the conceptualization of PCA. Results A three‐level classification framework for PCA is described comprising both syndrome‐ and disease‐level descriptions. Classification level 1 (PCA) defines the core clinical, cognitive, and neuroimaging features and exclusion criteria of the clinico‐radiological syndrome. Classification level 2 (PCA‐pure, PCA‐plus) establishes whether, in addition to the core PCA syndrome, the core features of any other neurodegenerative syndromes are present. Classification level 3 (PCA attributable to AD [PCA‐AD], Lewy body disease [PCA‐LBD], corticobasal degeneration [PCA‐CBD], prion disease [PCA‐prion]) provides a more formal determination of the underlying cause of the PCA syndrome, based on available pathophysiological biomarker evidence. The issue of additional syndrome‐level descriptors is discussed in relation to the challenges of defining stages of syndrome severity and characterizing phenotypic heterogeneity within the PCA spectrum. Discussion There was strong agreement regarding the definition of the core clinico‐radiological syndrome, meaning that the current consensus statement should be regarded as a refinement, development, and extension of previous single‐center PCA criteria rather than any wholesale alteration or redescription of the syndrome. The framework and terminology may facilitate the interpretation of research data across studies, be applicable across a broad range of research scenarios (e.g., behavioral interventions, pharmacological trials), and provide a foundation for future collaborative work.

Abstract During the past decade, a conceptual shift occurred in the field of Alzheimer's disease (AD) considering the disease as a continuum. Thanks to evolving biomarker research and substantial discoveries, it is now possible to identify the disease even at the preclinical stage before the occurrence of the first clinical symptoms. This preclinical stage of AD has become a major research focus as the field postulates that early intervention may offer the best chance of therapeutic success. To date, very little evidence is established on this “silent” stage of the disease. A clarification is needed about the definitions and lexicon, the limits, the natural history, the markers of progression, and the ethical consequence of detecting the disease at this asymptomatic stage. This article is aimed at addressing all the different issues by providing for each of them an updated review of the literature and evidence, with practical recommendations.

AbstractIntroductionThe genetics underlying posterior cortical atrophy (PCA), typically a rare variant of Alzheimer's disease (AD), remain uncertain.MethodsWe genotyped 302 PCA patients from 11 centers, calculated risk at 24 loci for AD/DLB and performed an exploratory genome‐wide association study.ResultsWe confirm that variation in/near APOE/TOMM40 (P = 6 × 10−14) alters PCA risk, but with smaller effect than for typical AD (PCA: odds ratio [OR] = 2.03, typical AD: OR = 2.83, P = .0007). We found evidence for risk in/near CR1 (P = 7 × 10−4), ABCA7 (P = .02) and BIN1 (P = .04). ORs at variants near INPP5D and NME8 did not overlap between PCA and typical AD. Exploratory genome‐wide association studies confirmed APOE and identified three novel loci: rs76854344 near CNTNAP5 (P = 8 × 10−10 OR = 1.9 [1.5–2.3]); rs72907046 near FAM46A (P = 1 × 10−9 OR = 3.2 [2.1–4.9]); and rs2525776 near SEMA3C (P = 1 × 10−8, OR = 3.3 [2.1–5.1]).DiscussionWe provide evidence for genetic risk factors specifically related to PCA. We identify three candidate loci that, if replicated, may provide insights into selective vulnerability and phenotypic diversity in AD.

Abstract Background An international Delphi panel has defined a harmonized protocol (HarP) for the manual segmentation of the hippocampus on MR. The aim of this study is to study the concurrent validity of the HarP toward local protocols, and its major sources of variance. Methods Fourteen tracers segmented 10 Alzheimer's Disease Neuroimaging Initiative (ADNI) cases scanned at 1.5 T and 3T following local protocols, qualified for segmentation based on the HarP through a standard web‐platform and resegmented following the HarP. The five most accurate tracers followed the HarP to segment 15 ADNI cases acquired at three time points on both 1.5 T and 3T. Results The agreement among tracers was relatively low with the local protocols (absolute left/right ICC 0.44/0.43) and much higher with the HarP (absolute left/right ICC 0.88/0.89). On the larger set of 15 cases, the HarP agreement within (left/right ICC range: 0.94/0.95 to 0.99/0.99) and among tracers (left/right ICC range: 0.89/0.90) was very high. The volume variance due to different tracers was 0.9% of the total, comparing favorably to variance due to scanner manufacturer (1.2), atrophy rates (3.5), hemispheric asymmetry (3.7), field strength (4.4), and significantly smaller than the variance due to atrophy (33.5%, P < .001), and physiological variability (49.2%, P < .001). Conclusions The HarP has high measurement stability compared with local segmentation protocols, and good reproducibility within and among human tracers. Hippocampi segmented with the HarP can be used as a reference for the qualification of human tracers and automated segmentation algorithms.

Abstract There is increasing evidence that subjective cognitive decline (SCD) in individuals with unimpaired performance on cognitive tests may represent the first symptomatic manifestation of Alzheimer's disease (AD). The research on SCD in early AD, however, is limited by the absence of common standards. The working group of the Subjective Cognitive Decline Initiative (SCD‐I) addressed this deficiency by reaching consensus on terminology and on a conceptual framework for research on SCD in AD. In this publication, research criteria for SCD in pre‐mild cognitive impairment (MCI) are presented. In addition, a list of core features proposed for reporting in SCD studies is provided, which will enable comparability of research across different settings. Finally, a set of features is presented, which in accordance with current knowledge, increases the likelihood of the presence of preclinical AD in individuals with SCD. This list is referred to as SCD plus .

Abstract Posterior cortical atrophy (PCA) is a clinicoradiologic syndrome characterized by progressive decline in visual processing skills, relatively intact memory and language in the early stages, and atrophy of posterior brain regions. Misdiagnosis of PCA is common, owing not only to its relative rarity and unusual and variable presentation, but also because patients frequently first seek the opinion of an ophthalmologist, who may note normal eye examinations by their usual tests but may not appreciate cortical brain dysfunction. Seeking to raise awareness of the disease, stimulate research, and promote collaboration, a multidisciplinary group of PCA research clinicians formed an international working party, which had its first face‐to‐face meeting on July 13, 2012 in Vancouver, Canada, prior to the Alzheimer's Association International Conference.

Background and purposeThe European Federation of the Neurological Societies (EFNS) guidelines on the use of neuroimaging in the diagnosis and management of dementia are designed to revise and expand previous EFNS recommendations for the diagnosis and management of patients with Alzheimer's disease (AD) and to provide an overview of the evidence for the use of neuroimaging techniques in non‐AD dementias, as well as general recommendations that apply to all types of dementia in clinical practice.MethodsThe task force working group reviewed evidence from original research articles, meta‐analyses and systematic reviews, published before April 2012. The evidence was classified, and consensus recommendations were given and graded according to the EFNS guidance regulations.ResultsStructural imaging, which should be performed at least once in the diagnostic work‐up of patients with cognitive impairment, serves to exclude other potentially treatable diseases, to recognize vascular lesions and to identify specific findings to help distinguish different forms of neurodegenerative types of dementia. Although typical cases of dementia may not benefit from routine functional imaging, these tools are recommended in those cases where diagnosis remains in doubt after clinical and structural imaging work‐up and in particular clinical settings. Amyloid imaging is likely to find clinical utility in several fields, including the stratification of patients with mild cognitive impairment into those with and without underlying AD and the evaluation of atypical AD presentations.ConclusionsA number of recommendations and good practice points are made to improve the diagnosis of AD and other dementias.

BackgroundThe promise of Alzheimer's disease biomarkers has led to their incorporation in new diagnostic criteria and in therapeutic trials; however, significant barriers exist to widespread use. Chief among these is the lack of internationally accepted standards for quantitative metrics. Hippocampal volumetry is the most widely studied quantitative magnetic resonance imaging measure in Alzheimer's disease and thus represents the most rational target for an initial effort at standardization.Methods and ResultsThe authors of this position paper propose a path toward this goal. The steps include the following: (1) Establish and empower an oversight board to manage and assess the effort, (2) adopt the standardized definition of anatomic hippocampal boundaries on magnetic resonance imaging arising from the European Alzheimer's Disease Centers–Alzheimer's Disease Neuroimaging Initiative hippocampal harmonization effort as a reference standard, (3) establish a scientifically appropriate, publicly available reference standard data set based on manual delineation of the hippocampus in an appropriate sample of subjects (Alzheimer's Disease Neuroimaging Initiative), and (4) define minimum technical and prognostic performance metrics for validation of new measurement techniques using the reference standard data set as a benchmark.ConclusionsAlthough manual delineation of the hippocampus is the best available reference standard, practical application of hippocampal volumetry will require automated methods. Our intent was to establish a mechanism for credentialing automated software applications to achieve internationally recognized accuracy and prognostic performance standards that lead to the systematic evaluation and then widespread acceptance and use of hippocampal volumetry. The standardization and assay validation process outlined for hippocampal volumetry was envisioned as a template that could be applied to other imaging biomarkers.