Will PET Amyloid Imaging Lead to Overdiagnosis of Alzheimer Dementia?

Alzheimer disease (AD), a progressive neurodegenerative disease that causes dementia, affects millions of elderly Americans and represents a growing problem with the aging of the population. There has been an increasing effort for improved and earlier diagnosis for AD. Several newly developed radiolabeled compounds targeting β-amyloid plaques, one of the major pathologic biomarkers of AD, have recently become available for clinical use. These radiopharmaceuticals allow for in vivo noninvasive visualization of abnormal β-amyloid deposits in the brain using positron emission tomography (PET). Amyloid PET imaging has demonstrated high sensitivity for pathologic cerebral amyloid deposition in multiple studies. Principal drawbacks to this new diagnostic test are declining specificity in older age groups and uncertain clinical role given lack of disease-modifying therapy for AD. Although there is strong evidence for the utility of amyloid PET in certain situations, detailed in a set of guidelines for appropriate use from the Alzheimer’s Association and the Society of Nuclear Medicine and Molecular Imaging, the question of overdiagnosis, the diagnosis of a disease that would result in neither symptoms nor deaths, using this new medical tool needs to be carefully considered in light of efforts to secure reimbursement for the new technology that is already widely available for use as a clinical tool.

Scope of Alzheimer Epidemic

Dementia is the decline of neuropsychological function, affecting one or more cognitive domains including memory, reasoning, judgment, visuospatial abilities, language, or behavior, of sufficient severity that it interferes with one’s usual activities. Causes of dementia include Alzheimer disease (AD), diffuse Lewy body disease (DLB), frontotemporal lobar dementia (FTLD), vascular dementia, and structural causes such as normal pressure hydrocephalus (NPH), among others; with few exceptions, such as early treatment of NPH, these remain progressive irreversible diseases.

AD is the most common type of dementia, responsible for approximately 50%–60% of cases and is thought to affect 5.2 million Americans including >200,000 under the age of 65 years . By the year 2050, the prevalence of AD in the United States is estimated to be 13.8 million . From those 5 million over the age of 65 years, AD causes 600,000 deaths, comprising 32% of all older adult deaths in the United States, which is expected to grow to 1.6 million deaths in 2050, or 43% of all older adult deaths in the United States . Although the rates of dementia vary between countries , this trend also appears to be global with an estimated 1%–2% of people who will be living with AD by the year 2050 . Despite the relatively high incidence, it is estimated that only half of all cases are diagnosed . With under-recognition and underdiagnosis currently widespread, there are concerted efforts to improve early diagnosis underway.

Continued growth of the AD population will directly translate into a heavier economic and societal burden. Specifically, in the United States for 2014, total care costs for dementia patients aged >65 years old were estimated to be $214 billion . Additional unpaid care costs by family members were valued at $220 billion . Although already high, these costs are thought to underestimate the total actual costs of dementia and AD . Therefore, AD represents an increasingly common and debilitating disease with subsequent heavy financial and societal burden on a global scale. It is no surprise that there is great demand for a predictive test from patients and physicians alike . However, the push for diagnosis at earlier milder stages of disease, where clinical presentations of various syndromes are often overlapping, also pushes the limits of current clinical testing and diagnostic imaging modalities, dominated by structural magnetic resonance imaging (MRI) and fluorine 18 radioisotope label [F-18] fluorodeoxyglucose (FDG) positron emission tomography (PET; Fig 1 ). There are concerns that a newly developed technology, PET targeting cerebral β-amyloid will result in additional overdiagnosis of AD , defined as the diagnosis of a disease that would result in neither symptoms nor deaths, particularly as no effective therapy has yet been developed . The merits of screening for dementia have been reviewed elsewhere ; this review will evaluate the possible effects of amyloid PET on overdiagnosis in AD in the current clinical environment.

Advantages and Disadvantages of Making or Excluding a Diagnosis of AD

Although there are currently no disease-modifying effective therapies for neurodegenerative causes of dementia, there is a growing interest in early diagnosis. First, early diagnosis allows earlier discussion of prognosis, which can affect life planning. Early diagnosis guides the selection of the modestly effective therapies available, as well as the exclusion of therapies targeted for other diseases, avoiding unnecessary side effects. Finally, although still hypothetical at this time, it is believed that any therapy developed in the future would be most efficacious only if administered early in the course of disease, before the onset of irreversible synaptic and neural destruction; future development of a disease-modifying therapy would dramatically change the clinical role for amyloid PET and other tests for early diagnosis.

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Current Status of Tests for AD

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Amyloid PET

Radiotracer Development

Get Radiology Tree app to read full this article<

Imaging Performance of Amyloid PET

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Role of Amyloid PET in Setting of Other Tests

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Conclusion

Get Radiology Tree app to read full this article<

References

• 1. 2014 Alzheimer’s disease facts and figures. Alzheimers Dement 2014; 10: pp. e47-e92.

• 2. Querfurth H.W., LaFerla F.M.: Alzheimer’s disease. N Engl J Med 2010; 362: pp. 329-344.

• 3. Weuve J., Hebert L.E., Scherr P.A., et. al.: Prevalence of Alzheimer disease in US states. Epidemiology 2015; 26: pp. e4-e6.

• 4. Ferri C.P., Prince M., Brayne C., et. al.: Global prevalence of dementia: a Delphi consensus study. Lancet 2005; 366: pp. 2112-2117.

• 5. Brookmeyer R., Johnson E., Ziegler-Graham K., et. al.: Forecasting the global burden of Alzheimer’s disease. Alzheimers Dement 2007; 3: pp. 186-191.

• 6. World Alzheimer report 2011: the benefits of early diagnosis and intervention. 2011.

• 7. Colucci L., Bosco M., Fasanaro A.M., et. al.: Alzheimer’s disease costs: what we know and what we should take into account. J Alzheimers Dis 2014; 42: pp. 1311-1324.

• 8. van den Dungen P., van Kuijk L., van Marwijk H., et. al.: Preferences regarding disclosure of a diagnosis of dementia: a systematic review. Int Psychogeriatr 2014; 26: pp. 1603-1618.

• 9. Brunet M.: Targets for dementia diagnoses will lead to overdiagnosis. BMJ 2014; 348: pp. g2224.

• 10. O’Brien J.T., Burns A.: Clinical practice with anti-dementia drugs: a revised (second) consensus statement from the British Association for Psychopharmacology. J Psychopharmacol 2011; 25: pp. 997-1019.

• 11. Le Couteur D.G., Doust J., Creasey H., et. al.: Political drive to screen for pre-dementia: not evidence based and ignores the harms of diagnosis. BMJ 2013; 347: pp. f5125.

• 12. Caligiuri M.P., Rockwell E., Jeste D.V.: Extrapyramidal side effects in patients with Alzheimer’s disease treated with low-dose neuroleptic medication. Am J Geriatr Psychiatry 1998; 6: pp. 75-82.

• 13. Wicklund S., Wright M.: Donepezil-induced mania. J Neuropsychiatry Clin Neurosci 2012; 24: pp. E27.

• 14. Pratt R.D., Perdomo C.A., Surick I.W., et. al.: Donepezil: tolerability and safety in Alzheimer’s disease. Int J Clin Pract 2002; 56: pp. 710-717.

• 15. Welch H.G.: Overdiagnosis and mammography screening. BMJ 2009; 339: pp. b1425.

• 16. Welch H.G., Black W.C.: Overdiagnosis in cancer. J Natl Cancer Inst 2010; 102: pp. 605-613.

• 17. Ahn H.S., Kim H.J., Welch H.G.: Korea’s thyroid-cancer “epidemic”—screening and overdiagnosis. N Engl J Med 2014; 371: pp. 1765-1767.

• 18. Hiltunen M., van Groen T., Jolkkonen J.: Functional roles of amyloid-beta protein precursor and amyloid-beta peptides: evidence from experimental studies. J Alzheimers Dis 2009; 18: pp. 401-412.

• 19. Holtzman D.M., Morris J.C., Goate A.M.: Alzheimer’s disease: the challenge of the second century. Sci Transl Med 2011; 3: pp. 77sr1.

• 20. Holtzman D.M., Goate A., Kelly J., et. al.: Mapping the road forward in Alzheimer’s disease. Sci Transl Med 2011; 3: pp. 114ps48.

• 21. Arriagada P.V., Growdon J.H., Hedley-Whyte E.T., et. al.: Neurofibrillary tangles but not senile plaques parallel duration and severity of Alzheimer’s disease. Neurology 1992; 42: pp. 631-639.

• 22. Beach T.G., Monsell S.E., Phillips L.E., et. al.: Accuracy of the clinical diagnosis of Alzheimer disease at National Institute on Aging Alzheimer Disease Centers, 2005–2010. J Neuropathol Exp Neurol 2012; 71: pp. 266-273.

• 23. Albert M.S., DeKosky S.T., Dickson D., et. al.: The diagnosis of mild cognitive impairment due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 2011; 7: pp. 270-279.

• 24. Shaw L.M., Vanderstichele H., Knapik-Czajka M., et. al.: Cerebrospinal fluid biomarker signature in Alzheimer’s disease neuroimaging initiative subjects. Ann Neurol 2009; 65: pp. 403-413.

• 25. Vemuri P., Wiste H.J., Weigand S.D., et. al.: MRI and CSF biomarkers in normal, MCI, and AD subjects: diagnostic discrimination and cognitive correlations. Neurology 2009; 73: pp. 287-293.

• 26. Zwan M., van Harten A., Ossenkoppele R., et. al.: Concordance between cerebrospinal fluid biomarkers and [11C]PIB PET in a memory clinic cohort. J Alzheimers Dis 2014; 41: pp. 801-807.

• 27. Zetterberg H., Lautner R., Skillback T., et. al.: CSF in Alzheimer’s disease. Adv Clin Chem 2014; 65: pp. 143-172.

• 28. Mattsson N., Insel P.S., Donohue M., et. al.: Independent information from cerebrospinal fluid amyloid-beta and florbetapir imaging in Alzheimer’s disease. Brain 2015; 138: pp. 772-783.

• 29. Prestia A., Caroli A., Herholz K., et. al.: Diagnostic accuracy of markers for prodromal Alzheimer’s disease in independent clinical series. Alzheimers Dement 2013; 9: pp. 677-686.

• 30. Dickerson B.C., Bakkour A., Salat D.H., et. al.: The cortical signature of Alzheimer’s disease: regionally specific cortical thinning relates to symptom severity in very mild to mild AD dementia and is detectable in asymptomatic amyloid-positive individuals. Cereb Cortex 2009; 19: pp. 497-510.

• 31. Misra C., Fan Y., Davatzikos C.: Baseline and longitudinal patterns of brain atrophy in MCI patients, and their use in prediction of short-term conversion to AD: results from ADNI. NeuroImage 2009; 44: pp. 1415-1422.

• 32. de Flores R., La Joie R., Landeau B., et. al.: Effects of age and Alzheimer’s disease on hippocampal subfields: Comparison between manual and freesurfer volumetry. Hum Brain Mapp 2015; 36: pp. 463-474.

• 33. Frisoni G.B., Jack C.R., Bocchetta M., et. al.: The EADC-ADNI Harmonized Protocol for manual hippocampal segmentation on magnetic resonance: Evidence of validity. Alzheimers Dement 2014;

• 34. Mulder E.R., de Jong R.A., Knol D.L., et. al.: Hippocampal volume change measurement: quantitative assessment of the reproducibility of expert manual outlining and the automated methods FreeSurfer and FIRST. NeuroImage 2014; 92: pp. 169-181.

• 35. Yushkevich P.A., Pluta J.B., Wang H., et. al.: Automated volumetry and regional thickness analysis of hippocampal subfields and medial temporal cortical structures in mild cognitive impairment. Hum Brain Mapp 2015; 36: pp. 258-287.

• 36. Douaud G., Menke R.A., Gass A., et. al.: Brain microstructure reveals early abnormalities more than two years prior to clinical progression from mild cognitive impairment to Alzheimer’s disease. J Neurosci 2013; 33: pp. 2147-2155.

• 37. Hanseeuw B.J., Van Leemput K., Kavec M., et. al.: Mild cognitive impairment: differential atrophy in the hippocampal subfields. AJNR Am J Neuroradiol 2011; 32: pp. 1658-1661.

• 38. Tosun D., Joshi S., Weiner M.W.: Alzheimer’s disease neuroimaging I. Neuroimaging predictors of brain amyloidosis in mild cognitive impairment. Ann Neurol 2013; 74: pp. 188-198.

• 39. Vos S.J., van Rossum I.A., Verhey F., et. al.: Prediction of Alzheimer disease in subjects with amnestic and nonamnestic MCI. Neurology 2013; 80: pp. 1124-1132.

• 40. Hedden T., Oh H., Younger A.P., et. al.: Meta-analysis of amyloid-cognition relations in cognitively normal older adults. Neurology 2013; 80: pp. 1341-1348.

• 41. Friedland R.P., Jagust W.J., Huesman R.H., et. al.: Regional cerebral glucose transport and utilization in Alzheimer’s disease. Neurology 1989; 39: pp. 1427-1434.

• 42. Bohnen N.I., Djang D.S., Herholz K., et. al.: Effectiveness and safety of 18F-FDG PET in the evaluation of dementia: a review of the recent literature. J Nucl Med 2012; 53: pp. 59-71.

• 43. Newberg A.B., Arnold S.E., Wintering N., et. al.: Initial clinical comparison of 18F-florbetapir and 18F-FDG PET in patients with Alzheimer disease and controls. J Nucl Med 2012; 53: pp. 902-907.

• 44. Klunk W.E., Engler H., Nordberg A., et. al.: Imaging brain amyloid in Alzheimer’s disease with Pittsburgh compound-B. Ann Neurol 2004; 55: pp. 306-319.

• 45. Mathis C.A., Mason N.S., Lopresti B.J., et. al.: Development of positron emission tomography beta-amyloid plaque imaging agents. Semin Nucl Med 2012; 42: pp. 423-432.

• 46. Wong D.F., Rosenberg P.B., Zhou Y., et. al.: In vivo imaging of amyloid deposition in Alzheimer disease using the radioligand 18F-AV-45 (florbetapir [corrected] F 18). J Nucl Med 2010; 51: pp. 913-920.

• 47. Wolk D.A., Grachev I.D., Buckley C., et. al.: Association between in vivo fluorine 18-labeled flutemetamol amyloid positron emission tomography imaging and in vivo cerebral cortical histopathology. Arch Neurol 2011; 68: pp. 1398-1403.

• 48. Villemagne V.L., Ong K., Mulligan R.S., et. al.: Amyloid imaging with (18)F-florbetaben in Alzheimer disease and other dementias. J Nucl Med 2011; 52: pp. 1210-1217.

• 49. Landau S.M., Thomas B.A., Thurfjell L., et. al.: Amyloid PET imaging in Alzheimer’s disease: a comparison of three radiotracers. Eur J Nucl Med Mol Imaging 2014; 41: pp. 1398-1407.

• 50. Landau S.M., Breault C., Joshi A.D., et. al.: Amyloid-beta imaging with Pittsburgh compound B and florbetapir: comparing radiotracers and quantification methods. J Nucl Med 2013; 54: pp. 70-77.

• 51. Rowe C.C., Pejoska S., Mulligan R.S., et. al.: Head-to-head comparison of 11C-PiB and 18F-AZD4694 (NAV4694) for beta-amyloid imaging in aging and dementia. J Nucl Med 2013; 54: pp. 880-886.

• 52. Jack C.R., Wiste H.J., Lesnick T.G., et. al.: Brain beta-amyloid load approaches a plateau. Neurology 2013; 80: pp. 890-896.

• 53. Clark C.M., Schneider J.A., Bedell B.J., et. al.: Use of florbetapir-PET for imaging beta-amyloid pathology. JAMA 2011; 305: pp. 275-283.

• 54. Clark C.M., Pontecorvo M.J., Beach T.G., et. al.: Cerebral PET with florbetapir compared with neuropathology at autopsy for detection of neuritic amyloid-beta plaques: a prospective cohort study. Lancet Neurol 2012; 11: pp. 669-678.

• 55. Rabinovici G.D., Furst A.J., O’Neil J.P., et. al.: 11C-PIB PET imaging in Alzheimer disease and frontotemporal lobar degeneration. Neurology 2007; 68: pp. 1205-1212.

• 56. Vandenberghe R., Adamczuk K., Dupont P., et. al.: Amyloid PET in clinical practice: Its place in the multidimensional space of Alzheimer’s disease. Neuroimage Clin 2013; 2: pp. 497-511.

• 57. Riley K.P., Snowdon D.A., Markesbery W.R.: Alzheimer’s neurofibrillary pathology and the spectrum of cognitive function: findings from the Nun Study. Anna Neurol 2002; 51: pp. 567-577.

• 58. Zhang S., Smailagic N., Hyde C., et. al.: (11)C-PIB-PET for the early diagnosis of Alzheimer’s disease dementia and other dementias in people with mild cognitive impairment (MCI). Cochrane Database Syst Rev 2014; 7: pp. CD010386.

• 59. Rowe C.C., Ellis K.A., Rimajova M., et. al.: Amyloid imaging results from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging. Neurobiol Aging 2010; 31: pp. 1275-1283.

• 60. Aizenstein H.J., Nebes R.D., Saxton J.A., et. al.: Frequent amyloid deposition without significant cognitive impairment among the elderly. Arch Neurol 2008; 65: pp. 1509-1517.

• 61. Jha S.: Overdiagnosis versus overtreatment: a false dichotomy. Radiology 2014; 270: pp. 628.

• 62. Javitt M.C.: Section editor’s notebook: breast cancer screening and overdiagnosis unmasked. AJR Am J Roentgenol 2014; 202: pp. 259-261.

• 63. Shokouhi S., Claassen D., Kang H., et. al.: Longitudinal progression of cognitive decline correlates with changes in the spatial pattern of brain 18F-FDG PET. J Nucl Med 2013; 54: pp. 1564-1569.

• 64. Kadir A., Almkvist O., Forsberg A., et. al.: Dynamic changes in PET amyloid and FDG imaging at different stages of Alzheimer’s disease. Neurobiol Aging 2012; 33: pp. 198.e1-198.e14.

• 65. Rowe C.C., Bourgeat P., Ellis K.A., et. al.: Predicting Alzheimer disease with beta-amyloid imaging: results from the Australian imaging, biomarkers, and lifestyle study of ageing. Ann Neurol 2013; 74: pp. 905-913.

• 66. Rabinovici G.D., Rosen H.J., Alkalay A., et. al.: Amyloid vs FDG-PET in the differential diagnosis of AD and FTLD. Neurology 2011; 77: pp. 2034-2042.

• 67. Johnson K.A., Minoshima S., Bohnen N.I., et. al.: Appropriate use criteria for amyloid PET: a report of the Amyloid Imaging Task Force, the Society of Nuclear Medicine and Molecular Imaging, and the Alzheimer’s Association. J Nucl Med 2013; 54: pp. 476-490.

• 68. Jacques L, Jensen TS, Rollins J, et al. Beta amyloid positron emission tomography in dementia and neurodegenerative disease (CAG-00431N). In: Services CfMaM ed. 2013.

• 69. Florbetapir (F-18) Assessment Report: EMA committee for medicinal products for human use.2013.European Medicines Agency

• 70. Florbetaben (F-18) Assessment Report: EMA committee for medicinal products for human use.2014.European Medicines Agency

• 71. Flutemetamol (F-18) Assessment Report: EMA committee for medicinal products for human use.2014.European Medicines Agency