Author
Karl Herholz
Other affiliations: German Center for Neurodegenerative Diseases, Max Planck Society, University of Cologne
Bio: Karl Herholz is an academic researcher from University of Manchester. The author has contributed to research in topics: Positron emission tomography & Dementia. The author has an hindex of 89, co-authored 347 publications receiving 24281 citations. Previous affiliations of Karl Herholz include German Center for Neurodegenerative Diseases & Max Planck Society.
Papers published on a yearly basis
Papers
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TL;DR: The current status of the technique and recommendations on the measurement of [18F]-FDG uptake for tumour response monitoring from a consensus meeting of the EORTC PET study group held in Brussels in February 1998 and confirmed at a subsequent meeting in March 1999 are summarized.
1,641 citations
TL;DR: A new diagnostic indicator of FDG PET scan abnormality, based on age-adjusted t statistics and an automated voxel-based procedure, is presented and validated in a large data set comprising 110 normal controls and 395 patients with probable Alzheimer's disease (AD) that were studied in eight participating centers as discussed by the authors.
764 citations
New York University1, Nathan Kline Institute for Psychiatric Research2, University of Manchester3, University of Florence4, Ludwig Maximilian University of Munich5, University of Milan6, University of Arizona7, Dresden University of Technology8, University of Cologne9, Helmholtz-Zentrum Dresden-Rossendorf10, University of Washington11
TL;DR: Standardized automated analysis of 18F-FDG PET scans may provide an objective and sensitive support to the clinical diagnosis in early dementia.
Abstract: This multicenter study examined 18 F-FDG PET measures in the differential diagnosis of Alzheimer’s disease (AD), frontotemporal dementia (FTD), and dementia wit hL ewy bodies (DLB) from normal aging and from each other and the relation of disease-specific patterns to mild cognitive impairment (MCI). Methods: We examined the 18 F-FDG PET scans of 548 subjects, including 110 healthy elderly individuals (‘‘normals’’ or NLs), 114 MCI, 199 AD, 98 FTD, and 27 DLB patients, collected at 7 participating centers. Individual PET scans wereZ scored using automated voxelbased comparison with generation of disease-specific patterns of cortical and hippocampal 18 F-FDG uptake that were then applied to characterize MCI. Results: Standardized diseasespecific PET patterns were developed that correctly classified 95% AD, 92% DLB, 94% FTD, and 94% NL. MCI patients showed primarily posterior cingulate cortex and hippocampal hypometabolism (81%), whereas neocortical abnormalities varied according to neuropsychological profiles. An AD PET pattern was observed in 79% MCI with deficits in multiple cognitive domains and 31% amnesic MCI. 18F-FDG PET heterogeneity in MCI with nonmemory deficits ranged from absent hypometabolism to FTD and DLB PET patterns. Conclusion: Standardized automated analysis of 18 F-FDG PET scans may provide an objective and
651 citations
Goethe University Frankfurt1, GE Healthcare2, Federal Institute for Drugs and Medical Devices3, University of Rostock4, Center for Drug Evaluation and Research5, University of Manchester6, Trinity College, Dublin7, University of Bonn8, Ludwig Maximilian University of Munich9, Food and Drug Administration10, University of Gothenburg11
TL;DR: There is an urgent need for collaboration between academic institutions, industry and regulatory organizations for the establishment of standards and networks for the identification and qualification of biological marker candidates.
Abstract: Advances in therapeutic strategies for Alzheimer's disease that lead to even small delays in onset and progression of the condition would significantly reduce the global burden of the disease To effectively test compounds for Alzheimer's disease and bring therapy to individuals as early as possible there is an urgent need for collaboration between academic institutions, industry and regulatory organizations for the establishment of standards and networks for the identification and qualification of biological marker candidates Biomarkers are needed to monitor drug safety, to identify individuals who are most likely to respond to specific treatments, to stratify presymptomatic patients and to quantify the benefits of treatments Biomarkers that achieve these characteristics should enable objective business decisions in portfolio management and facilitate regulatory approval of new therapies
616 citations
TL;DR: The shell region of the right nucleus accumbens is chosen as target for deep brain stimulation (DBS) in a pilot-series of four patients with severe obsessive-compulsive- and anxiety-disorders, with significant reduction in severity of symptoms.
535 citations
Cited by
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Johns Hopkins University1, Johns Hopkins University School of Medicine2, Mayo Clinic3, McGill University4, Harvard University5, University of California, Irvine6, University of Pittsburgh7, Columbia University Medical Center8, Eli Lilly and Company9, Washington University in St. Louis10, UCL Institute of Neurology11, VU University Medical Center12, Alzheimer's Association13, Northwestern University14, National Institutes of Health15
TL;DR: The workgroup sought to ensure that the revised criteria would be flexible enough to be used by both general healthcare providers without access to neuropsychological testing, advanced imaging, and cerebrospinal fluid measures, and specialized investigators involved in research or in clinical trial studies who would have these tools available.
Abstract: The National Institute on Aging and the Alzheimer's Association charged a workgroup with the task of revising the 1984 criteria for Alzheimer's disease (AD) dementia. The workgroup sought to ensure that the revised criteria would be flexible enough to be used by both general healthcare providers without access to neuropsychological testing, advanced imaging, and cerebrospinal fluid measures, and specialized investigators involved in research or in clinical trial studies who would have these tools available. We present criteria for all-cause dementia and for AD dementia. We retained the general framework of probable AD dementia from the 1984 criteria. On the basis of the past 27 years of experience, we made several changes in the clinical criteria for the diagnosis. We also retained the term possible AD dementia, but redefined it in a manner more focused than before. Biomarker evidence was also integrated into the diagnostic formulations for probable and possible AD dementia for use in research settings. The core clinical criteria for AD dementia will continue to be the cornerstone of the diagnosis in clinical practice, but biomarker evidence is expected to enhance the pathophysiological specificity of the diagnosis of AD dementia. Much work lies ahead for validating the biomarker diagnosis of AD dementia.
13,710 citations
9,362 citations
TL;DR: Past observations are synthesized to provide strong evidence that the default network is a specific, anatomically defined brain system preferentially active when individuals are not focused on the external environment, and for understanding mental disorders including autism, schizophrenia, and Alzheimer's disease.
Abstract: Thirty years of brain imaging research has converged to define the brain’s default network—a novel and only recently appreciated brain system that participates in internal modes of cognition Here we synthesize past observations to provide strong evidence that the default network is a specific, anatomically defined brain system preferentially active when individuals are not focused on the external environment Analysis of connectional anatomy in the monkey supports the presence of an interconnected brain system Providing insight into function, the default network is active when individuals are engaged in internally focused tasks including autobiographical memory retrieval, envisioning the future, and conceiving the perspectives of others Probing the functional anatomy of the network in detail reveals that it is best understood as multiple interacting subsystems The medial temporal lobe subsystem provides information from prior experiences in the form of memories and associations that are the building blocks of mental simulation The medial prefrontal subsystem facilitates the flexible use of this information during the construction of self-relevant mental simulations These two subsystems converge on important nodes of integration including the posterior cingulate cortex The implications of these functional and anatomical observations are discussed in relation to possible adaptive roles of the default network for using past experiences to plan for the future, navigate social interactions, and maximize the utility of moments when we are not otherwise engaged by the external world We conclude by discussing the relevance of the default network for understanding mental disorders including autism, schizophrenia, and Alzheimer’s disease
8,448 citations
TL;DR: These guidelines supersede the prior 2007 guidelines and 2009 updates and support the overarching concept of stroke systems of care and detail aspects of stroke care from patient recognition; emergency medical services activation, transport, and triage; through the initial hours in the emergency department and stroke unit.
Abstract: Background and Purpose—The authors present an overview of the current evidence and management recommendations for evaluation and treatment of adults with acute ischemic stroke. The intended audienc...
7,214 citations
TL;DR: The standard nonparametric randomization and permutation testing ideas are developed at an accessible level, using practical examples from functional neuroimaging, and the extensions for multiple comparisons described.
Abstract: Requiring only minimal assumptions for validity, nonparametric permutation testing provides a flexible and intuitive methodology for the statistical analysis of data from functional neuroimaging experiments, at some computational expense. Introduced into the functional neuroimaging literature by Holmes et al. ([1996]: J Cereb Blood Flow Metab 16:7-22), the permutation approach readily accounts for the multiple comparisons problem implicit in the standard voxel-by-voxel hypothesis testing framework. When the appropriate assumptions hold, the nonparametric permutation approach gives results similar to those obtained from a comparable Statistical Parametric Mapping approach using a general linear model with multiple comparisons corrections derived from random field theory. For analyses with low degrees of freedom, such as single subject PET/SPECT experiments or multi-subject PET/SPECT or fMRI designs assessed for population effects, the nonparametric approach employing a locally pooled (smoothed) variance estimate can outperform the comparable Statistical Parametric Mapping approach. Thus, these nonparametric techniques can be used to verify the validity of less computationally expensive parametric approaches. Although the theory and relative advantages of permutation approaches have been discussed by various authors, there has been no accessible explication of the method, and no freely distributed software implementing it. Consequently, there have been few practical applications of the technique. This article, and the accompanying MATLAB software, attempts to address these issues. The standard nonparametric randomization and permutation testing ideas are developed at an accessible level, using practical examples from functional neuroimaging, and the extensions for multiple comparisons described. Three worked examples from PET and fMRI are presented, with discussion, and comparisons with standard parametric approaches made where appropriate. Practical considerations are given throughout, and relevant statistical concepts are expounded in appendices.
5,777 citations