Alzheimer's Disease - Modernizing Concept, Biological Diagnosis and Therapy

M. C. Carrillo, H. Hampel

• Publisher: S. Karger
• Year: 2012
• ISBN:
  9783805598033
• Topic: Médecine
• Subtopic: Microbiologie et parasitologie médicales

Expanding knowledge on genetic and epigenetic risk factors is rapidly enhancing our understanding of the complex molecular interactions and systems involved in the pathogenesis of Alzheimer's disease. In this publication, leading experts discuss emerging novel conceptual models of the disease along with advances in the development of surrogate markers that will not only improve the accuracy of diagnostic technologies but also improve the prospects of developing disease-modifying interventions. The novel framework of the disease presented here highlights research on biological markers as well as efforts to validate technologies for early and accurate detection. It also introduces notion of a complex systems dysfunction that extends beyond prevailing ideas derived from the 'amyloid' or 'tau' hypotheses.This outstanding publication provides researchers, clinicians, students and other professionals interested in neurodegenerative disorders with a comprehensive update on current trends and future directions in therapy development, with special focus on advances in clinical trial designs.

Hampel H, Carrillo MC (eds): Alzheimer‘s Disease – Modernizing Concept, Biological Diagnosis and Therapy.
Adv Biol Psychiatry. Basel, Karger, 2012, vol 28, pp 80–114

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MRI- and PET-Based Imaging Markers for the Diagnosis of Alzheimer‘s Disease

Stefan Teipel^a · Reisa A. Sperling^b · Pawel Skudlarski^c · Clifford Jack^d · Harald Hampel^e · Andreas Fellgiebel^f · Karl Herholz^g

^aDepartment of Psychiatry, University of Rostock and DZNE, German Center for Neurodegenerative Diseases, Rostock, Germany;^bCenter for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Massachusetts General Hospital, Harvard Medical School, Boston, Mass.;^cOlin Neuropsychiatry Research Center, Hartford Hospital/IOL, Hartford, Conn.;^dDepartment of Radiology, Mayo Clinic, Rochester, Minn., USA;^eDepartment of Psychiatry, Psychosomatic Medicine and Psychotherapy, Goethe University, Frankfurt a.M.;^fDepartment of Psychiatry, University of Mainz, Mainz, Germany, and ^gUniversity of Manchester, Manchester, UK

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Abstract

Imaging markers of early neurodegeneration play an important role for the definition of predementia and preclinical stages of Alzheimer's disease according to the newly proposed diagnostic consensus criteria. Markers of regional and global brain atrophy in MRI and the detection of cortical metabolic decline and cerebral amyloid deposition using PET are the best established imaging markers for prodromal and clinical Alzheimer's disease to date. Detection of structural and functional cortical disconnection using functional MRI and diffusion tensor imaging add to the diagnostic sensitivity and specificity. Important areas of future research are the application of imaging markers in large multicenter studies, and their implementation in radiological expert systems for diagnosis. Additionally, we need to consider the effect of these new markers on care for patients and counseling of at-risk subjects.

Copyright © 2012 S. Karger AG, Basel

The revised NINCDS-ADRDA criteria for the diagnosis of Alzheimer's disease (AD) [1] propose the use of imaging-derived biomarkers [2, 3] to increase the level of certainty of the diagnosis of dementia of the AD type (clinically highly probable AD) and to identify AD in predementia or even preclinical stages of the disease (http://www.alz.org/research/diagnostic_criteria). The new diagnostic entities of predementia or preclinical AD are intended to serve the early diagnosis in clinical diagnostic studies and the enrichment and stratification of samples for testing effects of potential disease modification in clinical trials of AD [4, 5].

The following three imaging modalities have widely been employed as diagnostic markers or as secondary endpoints in clinical studies on AD: (i) structural MRI, (ii) functional MRI (fMRI), and (iii) PET. As a fourth modality, diffusion tensor imaging (DTI) bridges the gap between brain structure and function. These imaging methods are believed to reflect specific neurobiological changes of disease. Correlations between MRI-based volumetry and neuron numbers in specific brain regions suggest structural MRI as a potential marker of neuronal loss [6]. The blood oxygen level-dependent (BOLD) fMRI signal is primarily a measure of the input and processing of neuronal information within a region [7], opening an avenue to the assessment of intracortical functional connectivity. PET using ¹⁸F-FDG is thought to represent neuronal glucose consumption as the main determinant of neuronal metabolism. Other PET ligands have been designed to bind AD characteristic fibrillar Aß in amyloid plaques in vivo. DTI measures have been shown to reflect the integrity of white matter fiber tracts as the structural basis of functional connectivity. Three core criteria have been postulated for the use of a biological measure as diagnostic marker [4]: (i) applicability, i.e. the test should be non-invasive, widely available, and pose low patient burden, (ii) reliability, both within one center (test-retest reliability) and across centers, and (iii) validity in respect to underlying pathology and clinical outcomes.

The development of imaging biomarkers has entered a new phase with the conduction of large multicenter network studies, such as the North-American Alzheimers Disease Neuroimaging Initiative (ADNI) or the European ADNI (E-ADNI). These and other large-scale national and international multisite networks have allowed experimental markers to enter testing for practicability and multicenter stability along fast acquisition and analysis protocols in large and well-defined clinical cohorts. This renders it desirable to gain an overview about the present state of methodological developments and their potential applications in clinical research and clinical practice. An overview of important imaging markers is given in table 1, further details on these markers with specific emphasis on their potential use as diagnostic markers according to the core criteria of a useful biomarker is given in the following sections.

Structural MRI

In clinical trials, structural MRI markers of AD mainly serve to enrich, define and stratify an at-risk population for trials on potential disease-modifying or -preventive drugs. An academic expert stakeholder workshop convened by the EMEA in London (January 2010) seemed to reach an agreement on the introduction of neuroimaging, particularly structural MRI-derived biomarkers, alone or in combination with CSF candidates, for trial enrichment and enhanced diagnosis of AD at prodromal stages [8].

Structural MRI has already widely been explored in respect to the core criteria of applicability, reliability and validity for a useful biomarker. Structural MRI is noninvasive, can easily be repeated and is relatively widely available. The reliability of volumetric measures obtained from repeated MRI scans is generally high [9, 10]. Less is known about the variability of volumetric measures obtained from different MRI scanners. The variability of manual and automated volumetric measures across 12 different MRI scanners was below 5% in one study [11], the variability of manual volumetric measurement of the hippocampus was only 3.5%. This is in the range of accuracy of manual or automated segmentation protocols tested against simple or complex phantoms in a single-center approach [10], suggesting that multicenter variability, once minimal criteria for scanner quality are met by the participating centers, will not limit the application of structural MRI in clinical trials. The validity of MRI-based markers for the underlying disease pathology has only partly been established. Clinicopathological comparison studies have shown that hippocampus volume obtained ante-mortem accounted for at least 50% of variability in neuron numbers determined during autopsy [12]. The amount of variation explained by MRI- based hippocampus volumetry was above 90% when MRI scans had been obtained postmortem [13]. The relationship of MRI- based atrophy measures to clinical outcome measures of AD such as cognitive decline have also been shown in several studies. The question is still open whether clinical and structural outcomes are closely related in multicenter studies as well.

Table 1. Imaging markers for AD

Marker	Diagnostic use	Comments
Visual rating of hippocampus volume	High correlation with hippocampus volume (R2 ~0.9), diagnostic accuracy for AD vs. controls between 80 and 90%; prediction of AD in MCI not assessed	Useful for diagnostic evaluation at baseline; no use for follow-up
Manual volumetry of hippocampus	Diagnostic accuracy for AD vs. controls between 80 and 90%; prediction of AD in MCI with 70-80% accuracy [17]	Already employed in clinical trials as secondary endpoint, multicenter variability of longitudinal changes needs to be assessed
Automated volumetry of hippocampus	High correlation with manual volumetry (R2 > 0.8). Group discrimination AD vs. controls 83%, MCI vs. controls 73% (post-hoc probability only) [21]	Evaluation in larger multicenter studies has just begun
Manual volumetry of entorhinal cortex	No additional benefit in identifying patients with manifest AD. Accuracy of prediction of AD in MCI increased by a few percent compared to hippocampus volumetry in monocenter studies [24, 294, 295], no additional use in first multicenter studies [28]	Diagnostic use for prognosis of AD in MCI seems to be superior to hippocampus, use as secondary endpoint in RCT appears not superior to hippocampus considering the laborious methodology
Automated measurement of whole brain volume	Diagnostic use only for the rate of change, not the baseline volume, but would require second scan after 1 year before diagnosis can be supported	Already secondary endpoint in clinical trials, but only limited heuristic value due to the global nature of the measurement
Voxel-based morphometry (VBM)	Characteristic pattern of brain atrophy in AD and MCI, but lacks an established statistical model to determine individual risk for a single subject. Combining VBM with regions of interest yields 78% sensitivity and 75% specificity in predicting MCI in healthy subjects, but only post-hoc probability	Combination of...