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Dive into the research topics where Marilyn S. Albert is active.

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Featured researches published by Marilyn S. Albert.


Neurology | 1998

Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria.

David Neary; J. S. Snowden; L. Gustafson; U. Passant; D. Stuss; S. Black; M. Freedman; Andrew Kertesz; P. H. Robert; Marilyn S. Albert; K. Boone; Bruce L. Miller; Jeffrey L. Cummings; D. F. Benson

Objective: To improve clinical recognition and provide research diagnostic criteria for three clinical syndromes associated with frontotemporal lobar degeneration. Methods: Consensus criteria for the three prototypic syndromes-frontotemporal dementia, progressive nonfluent aphasia, and semantic dementia-were developed by members of an international workshop on frontotemporal lobar degeneration. These criteria build on earlier published clinical diagnostic guidelines for frontotemporal dementia produced by some of the workshop members. Results: The consensus criteria specify core and supportive features for each of the three prototypic clinical syndromes and provide broad inclusion and exclusion criteria for the generic entity of frontotemporal lobar degeneration. The criteria are presented in lists, and operational definitions for features are provided in the text. Conclusions: The criteria ought to provide the foundation for research work into the neuropsychology, neuropathology, genetics, molecular biology, and epidemiology of these important clinical disorders that account for a substantial proportion of cases of primary degenerative dementia occurring before the age of 65 years.


Neuron | 2002

Whole Brain Segmentation: Automated Labeling of Neuroanatomical Structures in the Human Brain

Bruce Fischl; David H. Salat; Evelina Busa; Marilyn S. Albert; Megan E. Dieterich; Christian Haselgrove; Andre van der Kouwe; Ronald J. Killiany; David N. Kennedy; Shuna Klaveness; Albert Montillo; Nikos Makris; Bruce R. Rosen; Anders M. Dale

We present a technique for automatically assigning a neuroanatomical label to each voxel in an MRI volume based on probabilistic information automatically estimated from a manually labeled training set. In contrast to existing segmentation procedures that only label a small number of tissue classes, the current method assigns one of 37 labels to each voxel, including left and right caudate, putamen, pallidum, thalamus, lateral ventricles, hippocampus, and amygdala. The classification technique employs a registration procedure that is robust to anatomical variability, including the ventricular enlargement typically associated with neurological diseases and aging. The technique is shown to be comparable in accuracy to manual labeling, and of sufficient sensitivity to robustly detect changes in the volume of noncortical structures that presage the onset of probable Alzheimers disease.


NeuroImage | 2006

An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

Rahul S. Desikan; Florent Ségonne; Bruce Fischl; Brian T. Quinn; Bradford C. Dickerson; Deborah Blacker; Randy L. Buckner; Anders M. Dale; R. Paul Maguire; Bradley T. Hyman; Marilyn S. Albert; Ronald J. Killiany

In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment.


Journal of Internal Medicine | 2004

Mild cognitive impairment : beyond controversies, towards a consensus : report of the International Working Group on Mild Cognitive Impairment

Bengt Winblad; K. Palmer; Miia Kivipelto; Vesna Jelic; Laura Fratiglioni; L.-O. Wahlund; Agneta Nordberg; Lars Bäckman; Marilyn S. Albert; Ove Almkvist; Hiroyuki Arai; Hans Basun; Kaj Blennow; M. J. de Leon; Charles DeCarli; T. Erkinjuntti; Ezio Giacobini; Caroline Graff; John Hardy; Clifford R. Jack; Anthony F. Jorm; Karen Ritchie; C. M. van Duijn; Pieter Jelle Visser; R. C. Petersen

The First Key Symposium was held in Stockholm, Sweden, 2–5 September 2003. The aim of the symposium was to integrate clinical and epidemiological perspectives on the topic of Mild Cognitive Impairment (MCI). A multidisciplinary, international group of experts discussed the current status and future directions of MCI, with regard to clinical presentation, cognitive and functional assessment, and the role of neuroimaging, biomarkers and genetics. Agreement on new perspectives, as well as recommendations for management and future research were discussed by the international working group. The specific recommendations for the general MCI criteria include the following: (i) the person is neither normal nor demented; (ii) there is evidence of cognitive deterioration shown by either objectively measured decline over time and/or subjective report of decline by self and/or informant in conjunction with objective cognitive deficits; and (iii) activities of daily living are preserved and complex instrumental functions are either intact or minimally impaired.


Journal of Magnetic Resonance Imaging | 2008

The Alzheimer's Disease Neuroimaging Initiative (ADNI): MRI methods

Clifford R. Jack; Matt A. Bernstein; Nick C. Fox; Paul M. Thompson; Gene E. Alexander; Danielle Harvey; Bret Borowski; Paula J. Britson; Jennifer L. Whitwell; Chadwick P. Ward; Anders M. Dale; Joel P. Felmlee; Jeffrey L. Gunter; Derek L. G. Hill; Ronald J. Killiany; Norbert Schuff; Sabrina Fox-Bosetti; Chen Lin; Colin Studholme; Charles DeCarli; Gunnar Krueger; Heidi A. Ward; Gregory J. Metzger; Katherine T. Scott; Richard Philip Mallozzi; Daniel James Blezek; Joshua R. Levy; Josef Phillip Debbins; Adam S. Fleisher; Marilyn S. Albert

The Alzheimers Disease Neuroimaging Initiative (ADNI) is a longitudinal multisite observational study of healthy elders, mild cognitive impairment (MCI), and Alzheimers disease. Magnetic resonance imaging (MRI), (18F)‐fluorodeoxyglucose positron emission tomography (FDG PET), urine serum, and cerebrospinal fluid (CSF) biomarkers, as well as clinical/psychometric assessments are acquiredat multiple time points. All data will be cross‐linked and made available to the general scientific community. The purpose of this report is to describe the MRI methods employed in ADNI. The ADNI MRI core established specifications thatguided protocol development. A major effort was devoted toevaluating 3D T1‐weighted sequences for morphometric analyses. Several options for this sequence were optimized for the relevant manufacturer platforms and then compared in a reduced‐scale clinical trial. The protocol selected for the ADNI study includes: back‐to‐back 3D magnetization prepared rapid gradient echo (MP‐RAGE) scans; B1‐calibration scans when applicable; and an axial proton density‐T2 dual contrast (i.e., echo) fast spin echo/turbo spin echo (FSE/TSE) for pathology detection. ADNI MRI methods seek to maximize scientific utility while minimizing the burden placed on participants. The approach taken in ADNI to standardization across sites and platforms of the MRI protocol, postacquisition corrections, and phantom‐based monitoring of all scanners could be used as a model for other multisite trials. J. Magn. Reson. Imaging 2008.


NeuroImage | 2006

Reliability of MRI-derived measurements of human cerebral cortical thickness: the effects of field strength, scanner upgrade and manufacturer.

Xiao Han; Jorge Jovicich; David H. Salat; Andre van der Kouwe; Brian T. Quinn; Silvester Czanner; Evelina Busa; Jenni Pacheco; Marilyn S. Albert; Ronald J. Killiany; Paul Maguire; Diana Rosas; Nikos Makris; Anders M. Dale; Bradford C. Dickerson; Bruce Fischl

In vivo MRI-derived measurements of human cerebral cortex thickness are providing novel insights into normal and abnormal neuroanatomy, but little is known about their reliability. We investigated how the reliability of cortical thickness measurements is affected by MRI instrument-related factors, including scanner field strength, manufacturer, upgrade and pulse sequence. Several data processing factors were also studied. Two test-retest data sets were analyzed: 1) 15 healthy older subjects scanned four times at 2-week intervals on three scanners; 2) 5 subjects scanned before and after a major scanner upgrade. Within-scanner variability of global cortical thickness measurements was <0.03 mm, and the point-wise standard deviation of measurement error was approximately 0.12 mm. Variability was 0.15 mm and 0.17 mm in average, respectively, for cross-scanner (Siemens/GE) and cross-field strength (1.5 T/3 T) comparisons. Scanner upgrade did not increase variability nor introduce bias. Measurements across field strength, however, were slightly biased (thicker at 3 T). The number of (single vs. multiple averaged) acquisitions had a negligible effect on reliability, but the use of a different pulse sequence had a larger impact, as did different parameters employed in data processing. Sample size estimates indicate that regional cortical thickness difference of 0.2 mm between two different groups could be identified with as few as 7 subjects per group, and a difference of 0.1 mm could be detected with 26 subjects per group. These results demonstrate that MRI-derived cortical thickness measures are highly reliable when MRI instrument and data processing factors are controlled but that it is important to consider these factors in the design of multi-site or longitudinal studies, such as clinical drug trials.


Alzheimers & Dementia | 2011

Introduction to the recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease.

Clifford R. Jack; Marilyn S. Albert; David S. Knopman; Guy M. McKhann; Reisa A. Sperling; Maria C. Carrillo; Bill Thies; Creighton H. Phelps

Criteria for the clinical diagnosis of Alzheimers disease (AD) were established in 1984. A broad consensus now exists that these criteria should be revised to incorporate state‐of‐the‐art scientific knowledge.


Annals of Neurology | 2000

Use of structural magnetic resonance imaging to predict who will get Alzheimer's disease

Ronald J. Killiany; Teresa Gomez-Isla; Mark B. Moss; Ron Kikinis; Tamas Sandor; Ferenc A. Jolesz; Rudolph E. Tanzi; Kenneth J. Jones; Bradley T. Hyman; Marilyn S. Albert

We used magnetic resonance imaging (MRI) measurements to determine whether persons in the prodromal phase of Alzheimers disease (AD) could be accurately identified before they developed clinically diagnosed dementia. Normal subjects (n = 24) and those with mild memory difficulty (n = 79) received an MRI scan at baseline and were then followed annually for 3 years to determine which individuals subsequently met clinical criteria for AD. Patients with mild AD at baseline were also evaluated (n = 16). Nineteen of the 79 subjects with mild memory difficulty “converted” to a diagnosis of probable AD after 3 years of follow‐up. Baseline MRI measures of the entorhinal cortex, the banks of the superior temporal sulcus, and the anterior cingulate were most useful in discriminating the status of the subjects on follow‐up examination. The accuracy of discrimination was related to the clinical similarity between groups. One hundred percent (100%) of normal subjects and patients with mild AD could be discriminated from one another based on these MRI measures. When the normals were compared with the individuals with memory impairments who ultimately developed AD (the converters), the accuracy of discrimination was 93%, based on the MRI measures at baseline (sensitivity = 0.95; specificity = 0.90). The discrimination of the normal subjects and the individuals with mild memory problems who did not progress to the point where they met clinical criteria for probable AD over the 3 years of follow‐up (the “questionables”) was 85% and the discrimination of the questionables and converters was 75%. The apolipoprotein E genotype did not improve the accuracy of discrimination. The specific regions selected for each of these discriminations provides information concerning the hierarchical fashion in which the pathology of AD may affect the brain during its prodromal phase. Ann Neurol 2000;47:430–439.


Neurology | 2005

Increased hippocampal activation in mild cognitive impairment compared to normal aging and AD

Bradford C. Dickerson; David H. Salat; Douglas N. Greve; Elizabeth F. Chua; Erin Rand-Giovannetti; Dorene M. Rentz; Lars Bertram; Kristina Mullin; Rudolph E. Tanzi; Deborah Blacker; Marilyn S. Albert; Reisa A. Sperling

Objective: To use fMRI to investigate whether hippocampal and entorhinal activation during learning is altered in the earliest phase of mild cognitive impairment (MCI). Methods: Three groups of older individuals were studied: 10 cognitively intact controls, 9 individuals at the mild end of the spectrum of MCI, and 10 patients with probable Alzheimer disease (AD). Subjects performed a face-name associative encoding task during fMRI scanning, and were tested for recognition of stimuli afterward. Data were analyzed using a functional-anatomic method in which medial temporal lobe (MTL) regions of interest were identified from each individuals structural MRI, and fMRI activation was quantified within each region. Results: Significantly greater hippocampal activation was present in the MCI group compared to controls; there were no differences between these two groups in hippocampal or entorhinal volumes. In contrast, the AD group showed hippocampal and entorhinal hypoactivation and atrophy in comparison to controls. The subjects with MCI performed similarly to controls on the fMRI recognition memory task; patients with AD exhibited poorer performance. Across all 29 subjects, greater mean entorhinal activation was found in the subgroup of 13 carriers of the APOE ε4 allele than in the 16 noncarriers. Conclusions: The authors hypothesize that there is a phase of increased medial temporal lobe activation early in the course of prodromal Alzheimer disease followed by a subsequent decrease as the disease progresses.


The Journal of Neuroscience | 2006

Alterations in Memory Networks in Mild Cognitive Impairment and Alzheimer's Disease: An Independent Component Analysis

Kim A. Celone; Vince D. Calhoun; Bradford C. Dickerson; Alireza Atri; Elizabeth F. Chua; Saul L. Miller; Kristina M. DePeau; Doreen M. Rentz; Dennis J. Selkoe; Deborah Blacker; Marilyn S. Albert; Reisa A. Sperling

Memory function is likely subserved by multiple distributed neural networks, which are disrupted by the pathophysiological process of Alzheimers disease (AD). In this study, we used multivariate analytic techniques to investigate memory-related functional magnetic resonance imaging (fMRI) activity in 52 individuals across the continuum of normal aging, mild cognitive impairment (MCI), and mild AD. Independent component analyses revealed specific memory-related networks that activated or deactivated during an associative memory paradigm. Across all subjects, hippocampal activation and parietal deactivation demonstrated a strong reciprocal relationship. Furthermore, we found evidence of a nonlinear trajectory of fMRI activation across the continuum of impairment. Less impaired MCI subjects showed paradoxical hyperactivation in the hippocampus compared with controls, whereas more impaired MCI subjects demonstrated significant hypoactivation, similar to the levels observed in the mild AD subjects. We found a remarkably parallel curve in the pattern of memory-related deactivation in medial and lateral parietal regions with greater deactivation in less-impaired MCI and loss of deactivation in more impaired MCI and mild AD subjects. Interestingly, the failure of deactivation in these regions was also associated with increased positive activity in a neocortical attentional network in MCI and AD. Our findings suggest that loss of functional integrity of the hippocampal-based memory systems is directly related to alterations of neural activity in parietal regions seen over the course of MCI and AD. These data may also provide functional evidence of the interaction between neocortical and medial temporal lobe pathology in early AD.

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Yaakov Stern

Columbia University Medical Center

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Jason Brandt

Johns Hopkins University School of Medicine

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Susumu Mori

Johns Hopkins University School of Medicine

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Nikolaos Scarmeas

National and Kapodistrian University of Athens

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Anja Soldan

Johns Hopkins University

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Abhay Moghekar

Johns Hopkins University

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