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This article focuses on the prospects and ethics of using neuroimaging to predict Alzheimer’s disease (AD). It is motivated by consideration of the historical roles of science in medicine and society, and considerations specifically contemporary of capabilities in imaging and aging, and the benefits and hope they bring. A general consensus is that combinations of imaging methods will ultimately be most fruitful in predicting disease. Their roll-out into translational practice will not be free of complexity, however, as culture and values differ in terms of what defines benefit and risk, who will benefit and who is at risk, what methods must be in place to assure the maximum safety, comfort, and protection of subjects and patients, and educational and policy needs. Proactive planning for the ethical and societal implications of predicting diseases of the aging brain is critical and will benefit all stakeholders— researchers, patients and families, health care providers, and policy makers.
The progressive deficits characterizing dementia in Alzheimer’s disease (AD) ultimately destroy judgment and communication abilities. The deficits are particularly difficult to detect in early stages,1 and true confirmation of this form of neurodegenerative disease is elusive without postmortem histological examination of the brain for neuronal loss, neurofibrillary tangles, and senile plaques. A consequence of the subtlety of these changes is that diagnostic criteria are conservative and diagnosis is delayed until there is significant functional disability (Diagnostic Statistical Manual IV, 1994). Given the late age of onset of AD and a growing elderly American population, the public health burden of this disease is significant. Estimates of the prevalence of Americans suffering from the condition today vary between 1.5 and 4 million, with projections increasing steadily through 2050.2,3 Despite recent therapeutic advances, available treatments at present are aimed primarily at slowing progression of the disease rather than halting it completely or reversing its progression.
Imaging is one among a few tests, such as genetic markers, cerebrospinal fluid, and demographic risk factors that may predict AD. Original genetic studies in the early 1990s, for example, associated one gene that encodes apolipoprotein E with the disease. APOE is a plasma protein that binds and transports cholesterol.4 The presence of the type 4 allele (estimated to occur in about 25% of the AD population)5 is widely viewed as a risk factor. However, many individuals affected by AD do not have the allele, and others who do inherit it do not manifest AD. The development of imaging biomarkers and a discussion of accompanying ethical challenges are the focus of the present article.
Neuroimaging techniques are poised to transform the process of diagnosis, prediction, and clinical management of AD and related dementias. The role of magnetic resonance imaging (MRI) and positron emission tomography (PET) in the diagnosis of dementia and investigation of cognitive impairment has been discussed at length by Knopman et al.6 and Albert et al.7 (www.alz.org/Research/Papers/Imaging_consensus_report.pdf). Currently, neuroimaging essentially serves the purpose of excluding alternate potential etiologies for cognitive dysfunction. For the future, there are three particularly important roles that neuroimaging may play: (1) increasing the sensitivity and specificity in diagnosing AD; (2) predicting who is likely to develop AD in the nondemented population; and (3) replacing clinical outcome measures in therapeutic trials (i.e., surrogate measures that have no direct relationship to a patient’s clinical state but are presumed to substitute for a clinically important measure). With respect to diagnosis, current accuracy is already highly sensitive and specific as compared to the neuropathological standard. In contrast, there is much work needed to predict who will develop AD in the nondemented population. As a surrogate outcome measure in studies evaluating new treatments, neuroimaging has great potential to reduce the length and cost of clinical trials because it can be collected long before current clinical outcome measures are available. The 5-year public-private Alzheimer’s disease neuroimaging initiative (ADNI) is an example of ongoing validation trial toward this goal8 (http://www.loni.ucla.edu/ADNI).
Although brain imaging is not currently applied in a clinical context for diagnosing AD except as a means of ruling out other causes of dementia, such as strokes or tumors, it has been widely accepted that benefits would accrue to patients and individuals at risk with improved assessment of brain integrity; structural and functional imaging are likely candidates since they may provide more direct information than inferences based on behavior, genetics, or other systemic indicators, such as CSF metabolites.9 As described in this volume and elsewhere, early detection of the disease has been a major focus of a variety of neuroimaging techniques, including fMRI, structural MRI, and PET. Recently, these techniques have also been found to be useful in monitoring cognitive and pathological progression of the disease, as well as monitoring response to clinical intervention and treatment.10–14
With each new technique comes the burden of validation against current standards for diagnosis and disease state monitoring. The consensus report on the use of MRI and PET for Clinical Diagnosis of Dementia7 provides guidelines based on the state-of-the-art and scientific research. This consensus report was developed to extend the current clinical standards as described by the American Academy of Neurology Guidelines6 for the use of neuroimaging in clinical diagnosis. With each new application of a technique, there are ethical implications that must be addressed. To complement the other articles in this volume, the editorial board invited us to report on our examination of these implications. To do so, we explored them systematically according to five major themes:
Our discovery and recommendations follow.
As described previously5 for genetic testing, the potential value of predicting AD must be considered in the context of the meaning of the disease for those affected and those around them. Unintended consequences and counseling further emerged as key areas under this theme.
A number of areas on which predictive imaging will have an impact may face unintended consequences. They are:
In the current health care system in the United States:
Because people live in a cognitively centered world, any information that raises questions about cognitive status of an individual may stigmatize that individual:
We recognized that in spite of any stigma, some people will have psychological solace from the biologic information.
Testing might exacerbate existing disparities, largely through access.
A great deal of expertise will be required of clinical providers who offer predictive imaging services. In this respect, a cohort of specialists may emerge especially since, recalling counseling in the history of genetic testing, guidelines fell away as primary care providers could not possibly keep up with demand.
Any discussion of the ethical issues at play for screening imaging for AD must take into account two important facts. The first is that treatments for AD currently have limited effectiveness and the disease is fatal. The second is that even the best imaging test will be prone to some degree of false positive and false negative results. The ethical issues pertaining to which clinical populations should be tested will depend largely on whether or not a definitive treatment becomes available. The screening of certain populations and the accompanying ethical issues will vary depending on whether such a treatment is effective at stemming the progression of AD or can actually reverse the pathologic changes and cure patients. Similarly, there will be a separate set of ethical questions if a treatment is developed that can prevent the disease from occurring when given to presymptomatic subjects. With these important caveats in mind we consider four specific scenarios for clinical screening as follows:
The scenario to screen asymptomatic individuals with risk factors, such as family history, ApoE genotype, older age, or some combination of these variables, analyses represents the most typical of the cost-benefit analyses made by physicians considering testing a patient for a particular disease. Many patients and their families in this scenario may find it useful, in terms of planning for the future, to know with some certainty that the cognitive loss they are already suffering is due to AD. At the level of intervention, a physician might encourage or limit treatment, such as with a cholinesterase inhibitor, especially for an AD patient with limited means or multiple other medical conditions that can be treated more effectively. However:
A great deal of variability exists among consumers in the desire to be tested. This variability will exist as long as treatments are lacking, but will likely diminish as treatments become available. In light of this, and for this scenario as well as the others described above:
We further note that the greater predictive power combined with the growing number of people with AD might be the brick that breaks the back of the current health care system.
Efforts to improve the quality of imaging technologies are ongoing in a variety of domains, notably by increasing the availability of techniques and comfortable, well-validated clinical applications.
The information contributed by neuroimaging techniques must improve in a manner that justifies its cost by increasing sensitivity and specificity of differential diagnosis for decision making.
Normative measures generated from one gender, ethnic, or age group may not generalize to all.
Unless an imaging biomarker has been tested to assess whether it is associated with later change through prospective longitudinal studies, it should be used with extreme caution.
Findings of possible clinical significance are detected in the brain both in clinical workup and in research. Previous studies of incidence suggest that the rate of occurrence of such findings is about 1–2% in the general population24 and the data suggest that it may be substantially higher in older cohorts.25
Although predictive neuroimaging has not yet reached its potential utility, we recognize future therapeutic benefits and procedures.
Neuroimaging research in AD raises a number of important well-known challenges in the domain of research ethics. These include issues such as informed consent, confidentiality, and privacy. The potential translation of neuroimaging research to clinical care intersects with a broader and significant number of potential ethical, legal, and social issues. In particular, it will yield sensitive personal information that will have to be handled with utmost ethical care. National and international laws and guidelines for research need to be carefully considered in the research design and recruitment phases of research given the current negative risk-benefit trade-off for individual AD volunteers often recruited from the pool of vulnerable volunteers (e.g., mentally disabled persons as alluded to in the Common Rule; Federal Policy for the Protection of Human Subjects; 45 CFR 46). Autonomy, cognitive privacy, and cultural sensitivity are of paramount importance. As stated in the Belmont Report, any participation of vulnerable volunteers, including patients with AD, should be based on the needs of science and for improving clinical care.
Many people suffering from AD remain capable of understanding and deciding whether they want to participate in a specific research project.
Additional ethical complexity is created when volunteers cannot directly give informed consent either because they are declared legally incompetent in matters of research participation or lack the capacity to consent.
When a volunteer has written specific advanced directives27–29 for research participation, such as a research living will, guidance is available about prior autonomous wishes. These may be wishes, such as the willingness to participate in minimal risk research only or not to participate in research involving scanners. The pure autonomy standard, that is, precedence of previously expressed autonomous judgments, should apply.
The absence of advanced directives for research is the likely case for most prospective research subjects. In the absence of specific directives:
Large neuroimaging consortia studying AD have created data banks that require specific security and deidentification measures.
To date, FDG-PET has been approved by the Centers for Medicare and Medicaid Services to help distinguish AD from frontotemporal dementia. However, no neuroimaging procedure is currently used to rule-in, that is, definitively diagnose AD. The predictive power of neuroimaging remains to be proven despite positive impressions fueled hopes for technology transfer and commercialization and marketing practices.
History predicts that the process of rolling out newtechnology, such as imaging, for an application such as detecting neurodegenerative disease, happens on a continuum. With off-label uses already in existence and active information dissemination throughout the media, Internet, and other sources, the full introduction of the technology can be anticipated. Working to maximize the generalizability of results is imperative. In the context of education and policy, therefore, four major considerations are key: the content of education, education about research, driving forces in utilization, and professional responsibility.
Key factors for education about the predicting AD with imaging are:
The group recognized the importance of K-12 science education as first priority for education about science in our society. Beyond this:
Many of the groups that represent cores for education also represent major driving forces in technology transfer and utilization.
The goal of predictive neuroimaging is to improve upon the human condition in neurodegenerative disease by providing reliable information about treatment outcome, rate of decline, and possibly therapeutic benefit to slowor even halt its relentless progression. These worthy goals are challenged by the still relatively immature state of the technology. Past events in the history of neuroscience and clinical medicine have taught us that such challenges must further take into consideration how culture and values differ in terms of what defines benefit and risk, and who will benefit and who is at risk. Methods must be set in place to assure not only maximum safety, comfort, and protection of subjects and patients, but also the educational and policy needs of all stakeholders.
We explored many issues here, resolved some, and left others open. Clearly, we also left many completely untouched. Overall, we conclude that as ethical paths are followed right alongside the development of powerful imaging tools, the future will hold ever-greater promise for AD patients and their families.
This article is based on the results of a workshop held at Stanford University on May 16, 2006, that was independent of, but coincident with, the meeting at the New York Academy of Sciences on which this issue of the Annals is based. The specific themes described here were addressed in plenary sessions and in working groups comprising individuals from a diverse range of disciplines including bioethics, neuroscience, law, health policy, and education. This written product was prepared by the authors and refined based on feedback of participants by way of web-based open commentary and follow-up conference calls as needed. It does not reflect consensus or majority and minority opinions; rather it represents the issues, possible solutions or recommendations, and remaining ethical questions that participants felt were at the current heart of the state of the art in predictive imaging. The authors acknowledge the participation both of presenters and attendees. Presenters were: Susan Bookheimer (Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles), Neil Buckholtz (National Institute of Aging, NIH), Henry T. (Hank) Greely (School of Law and Center for Biomedical Ethics, Stanford University), William Jagust (School of Public Health, University of California, San Francisco), Claudia Kawas (Department of Neurology and Neurobiology and Behavior, University of California, Irvine), Howard Rosen (Department of Neurology University of California, Berkeley). Invited participants were: Bruce Arnow (Department of Psychiatry and Behavioral Sciences, Stanford University), Laurence Baker (Health Research and Policy, Stanford University), Mildred Cho (Center for Biomedical Ethics, Stanford University), LaVera Crawley (Center for Biomedical Ethics, Stanford University), Ann Davidson (Stakeholder), Elizabeth Edgerly (Alzheimer’s Association, Northern California and Northern Nevada), William Fisher (Alzheimer’s Association, Northern California and Northern Nevada), Gary Glover (Department of Radiology, Stanford University), Victor Henderson (Department of Health Research and Policy, Stanford University), Agnieszka Jaworska (Department of Philosophy, Stanford University), Frank Longo (Department of Neurology and Neurological Sciences, Stanford University) David Magnus (Center for Biomedical Ethics, Stanford University), Micki Miller (Stakeholder) Ruth O’Hara (Department of Psychiatry and Behavioral Sciences, Stanford University), Peter B. Reiner (Department of Psychiatry and Brain Research Centre, University of British Columbia), David Salmon, Department of Neurosciences, University of California, San Diego), Navah Statman (National Alliance for the Mentally Ill), Joy Taylor (Department of Psychiatry and Behavioral Sciences, Stanford University), Tony Wyss-Coray (Department of Neurology and Neurological Sciences, Stanford University), Jerome Yesavage (Department of Psychiatry and Behavioral Science, Stanford University). The work was supported by NIH/NINDS RO1 045831. Sponsorship of the workshop was also provided by the Mental Illness Research Education and Clinical Center (MIRREC) Palo Alto VA Healthcare System. The authors gratefully acknowledge Karen Renschler and Vivian Chin for conference and editorial assistance.