Ways toward an early diagnosis in Alzheimer's disease: The Alzheimer's Disease Neuroimaging Initiative (ADNI)

Mueller, Susanne; Weiner, Michael W.; Thal, Leon J.; Petersen, Ronald C.; Jack, Clifford R.; Jagust, William J.; Trojanowski, John Q.; Toga, Arthur W.; Beckett, Laurel A.

doi:10.1016/j.jalz.2005.06.003

Cited by 1,004 publications

(787 citation statements)

References 112 publications

Supporting

Mentioning

753

Contrasting

Unclassified

Order By: Relevance

“…The Alzheimer's Disease Neuroimaging Initiative (ADNI), is a multi-institutional, longitudinal neuroimaging biomarker study of 800 elderly patients comprising 200 elderly controls, 400 patients with prodromal AD or amnestic mild cognitive impairment (MCI), and 200 patients with early stage AD [16]. The planning stages of ADNI gathered some of the foremost experts in quantitative neuroimaging of AD to discuss ways of overcoming the technological hurdles of performing precise vMRI across multiple sites and scanner models [7].…”

Section: The Alzheimer's Disease Neuroimaging Initiativementioning

confidence: 99%

Fully-Automated Volumetric MRI with Normative Ranges: Translation to Clinical Practice

Brewer

2009

Behavioural Neurology

101

View full text Add to dashboard Cite

Abstract.Neurodegenerative disorders, such as Alzheimer's disease (AD), are associated with characteristic patterns of neuropathological spread in the brain. Disease progression is usually accompanied by regional atrophy that can be detected noninvasively using structural magnetic resonance imaging (MRI). A wealth of data has demonstrated the value of quantitative measurements of regional atrophy in AD, suggesting that volumetric MRI (vMRI) may be a useful clinical tool. vMRI provides biological evidence of neurodegenerative disease in patients with cognitive impairment. However, several hurdles impede implementation of vMRI in clinical practice. These include a lack of standardized MRI acquisition protocols, spatial distortions in MRI data, labor-intensive vMRI methods susceptible to interoperator variability, a lack of normative ranges for volume measures, and difficulty integrating vMRI in clinical workflow. Advances in vMRI have resulted from multi-institutional studies of brain imaging, such as the Alzheimer's Disease Neuroimaging Initiative (ADNI), and help address these challenges. New, fully-automated measures of brain structure volumes coupled with large, multi-center studies using standardized MRI protocols now allow the development of age-adjusted normative ranges for vMRI. Such advances are critical for providing physicians a framework for assessing the pattern and degree of regional atrophy in a patient's brain and applying vMRI in clinical practice.

show abstract

Section: The Alzheimer's Disease Neuroimaging Initiativementioning

confidence: 99%

Fully-Automated Volumetric MRI with Normative Ranges: Translation to Clinical Practice

Brewer

2009

Behavioural Neurology

101

View full text Add to dashboard Cite

show abstract

“…A recent study by Rajan et al has shown that impairment in cognition starts almost 18 years before AD dementia could be clinically diagnosed 4. The distinction between memory decline due to the normal course of aging and early stage AD dementia is so ambiguous that the category of mild cognitive impairment (MCI) has been developed to better characterize the earliest signs of AD 5. The MCI category was initially created to identify the early stages of AD and was primarily based on impairment in memory, but with the advances in research made over time, it was noticeable that some patients with MCI remain stable while others progress to AD 6, 7.…”

Section: Introductionmentioning

confidence: 99%

Tau oligomers in cerebrospinal fluid in Alzheimer's disease

Sengupta

Portelius

Hansson

et al. 2017

Ann Clin Transl Neurol

View full text Add to dashboard Cite

ObjectiveWith an increasing incidence of Alzheimer's disease (AD) and neurodegenerative tauopathies, there is an urgent need to develop reliable biomarkers for the diagnosis and monitoring of the disease, such as the recently discovered toxic tau oligomers. Here, we aimed to demonstrate the presence of tau oligomers in the cerebrospinal fluid (CSF) of patients with cognitive deficits, and to determine whether tau oligomers could serve as a potential biomarker for AD.MethodsA multicentric collaborative study involving a double‐blinded analysis with a total of 98 subjects with moderate to severe AD (N = 41), mild AD (N = 31), and nondemented control subjects (N = 26), and two pilot studies of 33 total patients with AD (N = 19) and control (N = 14) subjects were performed. We carried out biochemical assays to measure oligomeric tau from CSF of these patients with various degrees of cognitive impairment as well as cognitively normal controls.ResultsUsing a highly reproducible indirect ELISA method, we found elevated levels of tau oligomers in AD patients compared to age‐matched controls. Western blot analysis confirmed the presence of oligomeric forms of tau in CSF. In addition, the ratio of oligomeric to total tau increased in the order: moderate to severe AD, mild AD, and controls.ConclusionThese assays are suitable for the analysis of human CSF samples. These results here suggest that CSF tau oligomer measurements could be optimized and added to the panel of CSF biomarkers for the accurate and early detection of AD.

show abstract

“…In addition, future methodological developments should be increasingly based on large datasets and multi-centric studies to increase both reproducibility and predictability. Recent data sharing initiatives such as ADNI (Mueller et al 2005), in combination with cloud-computing power, will provide the necessary prerequisites for these developments. We will hopefully see new advances in individual-level classification analysis in order to provide earlier and more accurate diagnoses, better estimation of prognosis, and eventually improve patient care.…”

Section: Discussionmentioning

confidence: 99%

Multivariate Pattern Recognition for Diagnosis and Prognosis in Clinical Neuroimaging: State of the Art, Current Challenges and Future Trends

et al. 2014

View full text Add to dashboard Cite

Many diseases are associated with systematic modifications in brain morphometry and function. These alterations may be subtle, in particular at early stages of the disease progress, and thus not evident by visual inspection alone. Group-level statistical comparisons have dominated neuroimaging studies for many years, proving fascinating insight into brain regions involved in various diseases. However, such group-level results do not warrant diagnostic value for individual patients. Recently, pattern recognition approaches have led to a fundamental shift in paradigm, bringing multivariate analysis and predictive results, notably for the early diagnosis of individual patients. We review the state-of-the-art fundamentals of pattern recognition including feature selection, cross-validation and classification techniques, as well as limitations including inter-individual variation in normal brain anatomy and neurocognitive reserve. We conclude with the discussion of future trends including multi-modal pattern recognition, multi-center approaches with data-sharing and cloud-computing.

show abstract

Ways toward an early diagnosis in Alzheimer's disease: The Alzheimer's Disease Neuroimaging Initiative (ADNI)

Cited by 1,004 publications

References 112 publications

Fully-Automated Volumetric MRI with Normative Ranges: Translation to Clinical Practice

Fully-Automated Volumetric MRI with Normative Ranges: Translation to Clinical Practice

Tau oligomers in cerebrospinal fluid in Alzheimer's disease

Multivariate Pattern Recognition for Diagnosis and Prognosis in Clinical Neuroimaging: State of the Art, Current Challenges and Future Trends

Contact Info

Product

Resources

About