The problematic nature of the Alzheimer’s disease does not allow physicians to determine whether or not a person has it, although it is relatively easy to see if they have dementia. Alzheimer’s Association (2017) states that “diagnosing Alzheimer’s requires careful medical evaluation” (para. 2). However, recent researches demonstrate a lot of possibilities to diagnose Alzheimer’s disease via different approaches and methods (Liu et al., 2013; Guzmán-Martinez, Farías and Maccioni, 2013; Blennow et al., 2015; Ramírez et al., 2013).
In this paper, the focus is on an article by Sabri et al. (2015) that provides an overview of Florbetaben PET imaging that detects amyloid beta plaques in patients potentially who have Alzheimer’s disease. This diagnosing tool is a pivotal histopathology, which allows assessing the connections between florbetaben and β-amyloid through “comparing whole-brain visual reads and quantitative analysis with the final neuropathological diagnoses of β-amyloid in the brain” (p. 965).
The test is valid because of its ability to precisely differentiate between whether or not a patient is suffering Alzheimer’s disease; due to the test focus on measuring only the samples of subjects were confirmed to have passed away because of Alzheimer’s, it allows extraordinary precision. However, the authors state that there is a flaw in this test, which is a result of researching only the post-mortem samples; this could increase the probability of PET output becoming biased. The sensitivity of this test is yet to be discovered because the research is currently in development; the same applies to this test’s specificity, which does not allow it to be implemented in field activity yet. Therefore, because of the developers’ inability to apply the procedures in practice, there is no certainty in the test’s predictive value. However, the research goes on without stopping, so future publications may include field implementations, which will allow estimating sensitivity, specificity, and predictive value.
Due to the nature of this test, a high-quality equipment and sample materials are required, thus rendering the procedure expensive; furthermore, the families of participants that donated their bodies to post-mortem sampling must receive reimbursements in various forms. Moreover, to allow the best precision of results, costly procedures may be required each time the test is to be implemented, and there is no certainty that there will be no need for future post-mortem sampling.
“Another advantage of this direct regional assessment of PET and histopathology was to allow the analysis of the ability of florbetaben to bind to diffuse and neuritic plaques. Although there is growing evidence that all β-amyloid deposits add to the course of AD, and the National Institute on Aging – Alzheimer’s Association NIA-AA guidelines added nonneuritic β-amyloid deposition in form of modified Thal stages to the neuropathological assessment of AD, the binding of β-amyloid imaging agents to diffuse plaques is controversial and not well studied” (p. 969). This demonstrates that the guidelines for this test were developed by an organization that focuses on Alzheimer’s disease-related issues; therefore, they are implemented with taking recommendations of a professional team into account. This means that the guidelines were developed by reaching a consensus, which was achieved by the developers working in collaboration with an organization that supported their researches and causes. The guidelines are functioning as a method of forming a more unbiased nature of the test allowing for more precise results and eliminating any possible contamination of the results.
References
Alzheimer’s Association (2017). Diagnosis of Alzheimer’s disease and dementia. Web.
Blennow, K., Dubois, B., Fagan, A. M., Lewczuk, P., de Leon, M. J., & Hampel, H. (2015). Clinical utility of cerebrospinal fluid biomarkers in the diagnosis of early Alzheimer’s disease. Alzheimer’s & Dementia, 11(1), 58-69.
Guzmán-Martinez, L., Farías, G. A., & Maccioni, R. B. (2013). Tau oligomers as potential targets for Alzheimer’s diagnosis and novel drugs. Frontiers in Neurology, 4. Web.
Liu, S., Song, Y., Cai, W., Pujol, S., Kikinis, R., Wang, X., & Feng, D. (2013). Multifold Bayesian kernelization in Alzheimer’s diagnosis. Medical Image Computing and Computer‑Assisted Intervention, 16(2), 303-310.
Ramírez, J., Górriz, J. M., Salas-Gonzalez, D., Romero, A., López, M., Álvarez, I., & Gómez-Río, M. (2013). Computer-aided diagnosis of Alzheimer’s type dementia combining support vector machines and discriminant set of features. Information Sciences, 237(1), 59-72.
Sabri, O., Sabbagh, M. N., Seibyl, J., Barthel, H., Akatsu, H., Ouchi, Y., … Schulz-Schaeffer, W. J. (2015). Florbetaben PET imaging to detect amyloid beta plaques in Alzheimer’s disease: Phase 3 study. Alzheimer’s & Dementia, 11(8), 964-974.