CoChat
Sign Up
Cited by 958Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatmentsMedical Imaging Techniques and Applications

11C PiB and structural MRI provide complementary information in imaging of Alzheimer's disease and amnestic mild cognitive impairment

Open access
Jack, Clifford R., Lowe, Val J., Senjem, Matthew L., Weigand, Stephen D., Kemp, Bradley J., Shiung, Maria M., Knopman, David S., Boeve, Bradley F. +3 more·2008·Brain
DOI 10.1093/brain/awm336PMC PMC2730157
Open this paper in CoChat — free accountOpen PDF

Abstract

To date, most diagnostic imaging comparisons between amyloid labelling ligands and other imaging modalities have been between the use of amyloid labelling ligand (11)C Pittsburgh Compound B (PiB) and FDG-PET. Our objectives were to compare cognitive performance and diagnostic group-wise discrimination between cognitively normal, amnestic mild cognitive impairment (MCI) and Alzheimer's disease subjects with MRI-based measures of hippocampal volume and PiB retention, and secondly to evaluate the topographic distribution of PiB retention and grey matter loss using 3D voxel-wise methods. Twenty cognitively normal, 17 amnestic MCI and 8 probable Alzheimer's disease subjects were imaged with both MRI and PiB. PiB retention was quantified as the ratio of uptake in cortical to cerebellar regions of interest (ROIs) 40-60 min post-injection. A global cortical PiB retention summary measure was derived from six cortical ROIs. Statistical parametric mapping (SPM) and voxel-based morphometry (VBM) were used to evaluate PiB retention and grey matter loss on a 3D voxel-wise basis. Alzheimer's disease subjects had high global cortical PiB retention and low hippocampal volume; most cognitively normal subjects had low PiB retention and high hippocampal volume; and on average amnestic MCI subjects were intermediate on both PiB and hippocampal volume. A target-to-cerebellar ratio of 1.5 was used to designate subjects with high or low PiB cortical retention. All Alzheimer's disease subjects fell above this ratio, as did 6 out of 20 cognitively normal subjects and 9 out of 17 MCI subjects, indicating bi-modal PiB retention in the latter two groups. Interestingly, we found no consistent differences in learning and memory performance between high versus low PiB cognitively normal or amnestic MCI subjects. The SPM/VBM voxel-wise comparisons of Alzheimer's disease versus cognitively normal subjects provided complementary information in that clear and meaningful similarities and differences in topographical distribution of amyloid deposition and grey matter loss were shown. The frontal lobes had high PiB retention with little grey matter loss, anteromedial temporal areas had low PiB retention with significant grey matter loss, whereas lateral temporoparietal association cortex displayed both significant PiB retention and grey matter loss. A voxel-wise SPM conjunction analysis revealed that subjects with high PiB retention shared a common PiB retention topographical pattern regardless of clinical category, and this matched that of amyloid plaque distribution from autopsy studies of Alzheimer's disease. Both global cortical PiB retention and hippocampal volumes demonstrated significant correlation in the expected direction with cognitive testing performance; however, correlations were stronger with MRI than PiB. Pair-wise inter-group diagnostic separation was significant for all group-wise pairs for both PiB and hippocampal volume with the exception of the comparison of cognitively normal versus amnestic MCI, which was not significant for PiB. PiB and MRI provided complementary information such that clinical diagnostic classification using both methods was superior to using either in isolation.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/brain/awm336

Cites

17 of 17 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • A similar proportion of individuals clinically diagnosed as AD dementia have normal amyloid PET or CSF Aβ42 studies.

    “and a similar proportion has normal amyloid PET or CSF Aβ42 studies [53–62].”

    From NIA‐AA Research Framework: Toward a biological definition of Alzheimer's disease (2018) · cites this paper as [55]

    The Introduction says nearly all clinically diagnosed AD subjects show PiB retention, which leaves open a small minority with normal amyloid PET findings. The Discussion reports that all eight AD subjects in this study had high PiB retention. The paper does not establish a ‘similar proportion’ with normal findings or report a proportion with normal CSF Aβ42. (LLM, conf=0.80)

    Experimental — accuracy not yet measured

  • PIB uptake and CSF Aβ42 are reliable surrogate markers of amyloid plaque pathology in living subjects.

    “A preponderance of evidence supports the interpretation that PIB uptake and CSF Aβ42 are reliable surrogate markers of amyloid plaque pathology in living subjects (15-19).”

    From Human ApoE isoforms differentially regulate brain amyloid-β peptide clearance (2011) · cites this paper as [16]

    The Introduction (page unavailable) describes PiB as an in vivo amyloid-plaque tracer whose binding corresponds to plaque distribution. It also reports an inverse correlation between cortical PiB uptake and CSF Aβ42, but does not establish that CSF Aβ42 is itself a reliable surrogate for plaque pathology. The Discussion (page unavailable) calls PiB an accurate marker of brain fibrillar amyloid a current expectation. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

  • A similar proportion of cognitively unimpaired elderly persons has abnormal amyloid biomarkers.

    “and a similar proportion has abnormal amyloid biomarkers [33,53–55,60,70–73].”

    From NIA‐AA Research Framework: Toward a biological definition of Alzheimer's disease (2018) · cites this paper as [55]

  • Elevated CSF P-tau, with a mean level of 31 pg/mL, is seen in FTD owing to a genetic variant in the MAPT gene.

    “It was reported that elevated levels of CSF P-tau, with a mean level of 31 pg/mL, is seen in FTD owing to a genetic variant in the MAPT gene,46 which produces the protein product tau.”

    From Association of Cognitive and Behavioral Features Between Adults With Tuberous Sclerosis and Frontotemporal Dementia (2020) · cites this paper as [46]

    The Introduction discusses CSF amyloid beta 42 and PiB binding in frontotemporal dementia, but not CSF P-tau levels in FTD. Searches for the reported 31 pg/mL mean and for MAPT-related FTD found no passage addressing either point in our copy. (LLM, conf=0.75)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 70

  1. Archer H, Edison P, Brooks DJ, Barnes J, Frost C, Yeatman T, et al. Amyloid load and cerebral atrophy in Alzheimer's disease: an 11C-PIB positron emission tomography study. Ann Neurol 2006; 60: 145-7.
  2. Ashburner J, Friston KJ. Voxel-based morphometry-the methods. Neuroimage 2000; 11: 805-21.
  3. Ashburner J, Friston KJ. Unified Segmentation. Neruoimage 2005; 26: 839-851.
  4. Bacskai BJ, Frosch MP, Freeman SH, Raymond SB, Augustinack JC, Johnson KA, et al., Molecular imaging with Pittsburgh Compound B confirmed at autopsy: a case report. Arch Neurol 2007; 64: 431-4. doi:10.1001/archneur.64.3.431. · DOI
  5. Baron JC, Chetelat G, Desgranges B, Perchey G, Landeau B, de la Sayette V, et al. In vivo mapping of gray matter loss with voxel-based morphometry in mild Alzheimer's disease. Neuroimage 2001; 14: 298-309.
  6. Blomquist G, Ringheim A, Extrada S, Hoglund U, Frandberg P, Nylen G. Influx and net accumulation of PIB compared with CBF in a rhesus monkey. EJNM 2005; 32: S263.
  7. Bobinski M, de Leon MJ, Wegiel J, Desanti S, Convit A, Saint Louis LA, et al. The histological validation of post mortem magnetic resonance imaging-determined hippocampal volume in Alzheimer's disease. Neuroscience 2000; 95: 721-5.
  8. Chetelat G, Desgranges B, de la Sayette V, Viader F, Eustache F, Baron C-J. Mapping gray matter loss with voxel-based morphometry in mild cognitive impairment. Brain Imaging 2002; 13: 1939.
  9. Christie RH, Bacskai BJ, Zipfel WR, Williams RM, Kajdasz ST, Webb WW, et al. Growth arrest of individual senile plques in a model of Alzheimer's disease observed by in vivo multiphoton microscopy. J Neurosci 2001; 21: 858-64.
  10. Csernansky JG, Hamstra J, Wang L, McKeel D, Price JL, Gado MH, et al. Correlations between antemortem hippocampal volume and postmor- tem neuropathology in AD subject. Alzheimer Dis Assoc Disord 2004; 18: 190-5.
  11. Engler H, Forsberg A, Almkvist O, Blomquist G, Larsson E, Savitcheva I, et al. Two-year follow-up of amyloid deposition in patients with Alzheimer's disease. Brain 2006; 129: 2856-66. doi:10.1093/brain/ awl178. · DOI
  12. Fagan AM, Mintun MA, Mach RH, Lee SY, Dence CS, Shah AR, et al. Inverse relation between in vivo amyloid imaging load and cerebrospinal fluid Abeta42 in humans. Ann Neurol 2006; 59: 512-9.
  13. Forsberg A, Engler H, Almkvist O, Blomquist G, Hagman G, Wall A, et al. PET imaging of amyloid deposition in patients with mild cognitive impairment. Neurobiol Aging 2007, in press.
  14. Fox NC, Warrington EK, Freeborough PA, Hartikainen P, Kennedy AM, Stevens JM, et al. Presymptomatic hippocampal atrophy in Alzheimer's disease. A longitudinal MRI study. Brain 1996; 119: 2001-7.
  15. Frisoni GB, Testa C, Zorzan A, Sabattoli F, Beltramello A, Soininen H, et al. Detection of gray matter loss in mild Alzheimer's disese with voxel-based morphometry. J Neurol Neurosurg Psychiatry 2002; 73: 657-64.
  16. Genovese CR, Lazar NA, Nichols TE. Thresholding of statistical maps in functional neuroimaging using the false discovery rate. Neuroimage 2002; 15: 772-86.
  17. Gosche KM, Mortimer JA, Smith CD, Markesbery WR, Snowdon DA. Hippocampal volume as an index of Alzheimer neuropathology: findings from the Nun Study. Neurology 2002; 58: 1476-82.
  18. Green M, Kaye JA, Ball MJ. The Oregon Brain Aging Study. Neurology 2000; 54: 105-13.
  19. Harrell FE. Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis. New York: Springer- Verlag; 2001; 1-568.
  20. Hyman B, Marzloff K, Arriagada PV. The lack of accumulation of senile plaques or amyloid burden in Alzheimer's disease suggests a dynamic balance between amyloid deposition and resolution. J Neuropathol Exp Neurol 1993; 52: 594-600.
  21. Jack CR Jr, Petersen RC, O'Brien PC. MR-based hippocampal volumetry in the diagnosis of Alzheimer's disease. Neurology 1992; 42: 183-8.
  22. Jack CR Jr, Petersen RC, Xu Y, O'Brien PC, Smith GE, Ivnik RJ, et al. The rate of medial temporal lobe atrophy in typical aging and Alzheimer's disease. Neurology 1998; 51: 993-9.
  23. Jack CR Jr, Petersen RC, Xu YC, Waring SC, O'Brien PC, Tangalos EG, et al. Medial temporal atrophy on MRI in normal aging and very mild Alzheimer's disease. Neurology 1997; 49: 786-94.
  24. Jack CR Jr, Shiung MM, Weignad SD, O'Brien PC, Gunter JL, Boever BF, et al. Brain atrophy rates predict subsequent clinical conversion in normal elderly and amnestic MCI. Neurology 2005; 65: 1227-31.
  25. Jack CR Jr, Dickson DW, Parisi JE, Xu YC, Cha RH, O'Brien PC, et al. Antemortem MRI findings correlate with hippocampal neuropathology in typical aging and dementia. Neurology 2002; 58: 750-7.
  26. Kaye JA, Swihart T, Howieson D, Dame A. Volume loss of the hippocampus and temporal lobe in healthy elderly persons destined to develop dementia. Neurology 1997; 48: 1297-04.
  27. Kemppainen NM, Aalto S, Wilson IA, Nagren K, Helin S, Bruck A, et al. Voxel-based analysis of PET amyloid ligand [11C]PIB uptake in Alzheimer disease. Neurology 2006; 67: 1575-80. doi:10.1212/01.wnl. 0000240117.55680. · DOI
  28. Kemppainen NM, Aalto S, Wilson IA, Nagren K, Helin S, Bruck A, et al. PET amyloid ligand [11C]PIB uptake is increased in mild cognitive impairment. Neurology 2007; 68: 1603-6. doi:10.1212/01.wnl. 0000260969.94695. · DOI
  29. Killiany RJ, Hyman BT, Gomez-Isla T, Moss MB, Kikinis R, Jolesz F, et al. MRI measures of entorhinal cortex vs hippocampus in preclinical AD. Neurology 2002; 58: 1188-96.
  30. Kinniany RJ, Moss MB, Albert MS, Sandor T, Tieman J, Jolesz F. Temporal lobe regions on magnetic resonance imaging identify patients with early Alzheimer's disease. Arch Neurol 1993; 50: 949-54.
  31. Klunk WE, Engler H, Nordberg A, Wang Y, G B, P HD, et al. Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound-B. Ann Neurol 2004; 55: 306-19.
  32. Knopman DS, Parisi JE, Salviati A. Neuropathology of cognitively normal elderly. J Neuropathol Exp Neurol 2003; 62: 1087-95.
  33. Kokmen E, Smith GE, Petersen RC, Tangalos E, Ivnik RC. The short test of mental status: correlations with standardized psychometric testing. Arch Neurol 1991; 48: 725-8.
  34. Laakso MP, Soininen H, Partanen K, Lehtovirta M, Hallikainen M, Hanninen T, et al. MRI of the hippocampus in Alzheimer's disease: sensitivity, specificity, and analysis of the incorrectly classified subjects. Neurobiol Aging 1998; 19: 23-31.
  35. Lopresti BJ, Klunk WE, CMathis CA, Hoge JA, Ziolko SK, Lu X, et al. Simplified quantification of Pittsburgh compound B amyloid imaging PET studies: a comparative analysis. J Nucl Med 2005; 46: 1959-72.
  36. Mathis CA, Wang Y, Holt DP, Huang GF, Debnath ML, Klunk WE. Synthesis and evaluation of 11C-labeled 6-substituted 2-arylbenzothia- zoles as amyloid imaging agents. J Med Chem 2003; 46: 2740-54.
  37. McCullagh P. Regression models for ordinal data. J R Stat S Ser B (Methodol) 1980; 42: 109-42.
  38. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer's disease: report of the NINCDS- ADRDA work group under the auspices of Department of Health and Human Services Task Force on Alzheimer's disease. Neurology 1984; 34: 939-44.
  39. Meltzer C, Kinahan PE, Greer PJ, Nichols TE, Comtat C, Cantwell MN, et al. Comparative evaluation of MR-based partial-volume correc- tion schemes for PET. J Nucl Med 1999; 40: 2053-65.
  40. Mintun MA, LaRossa GN, Sheline YI, Dence CS, Lee SY, Mach RH, et al. [11C]PIB in a nondemented population: Potential antecedent marker of Alzheimer disease. Neurology 2006; 67: 446-52. doi:10.1212/01.wnl. 0000228230.26044. · DOI
  41. Morris JC. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology 1993; 43: 2412-14.
  42. Nichols TE, Brett M, Andersson JLR, Wager T, Poline J-B. Valid conjunction inference with the minimum statistic. Neuroimage 2005; 25: 653-60.
  43. O'Brien PC, Dyck PJ. Procedures for setting normal values. Neurology 1995; 45: 17-23.
  44. Petersen RC. Normal aging, mild cognitive impairment, and early Alzheimer's disease. The Neurologist 1995; 1: 326-344.
  45. Petersen RC, Doody RS, Kurz A, Hohs R, Morris JC, Rabins PV, et al. Current concepts in mild cognitive impairment. Arch Neurol 2001; 58: 1985-92.
  46. Petersen RC, Kokmen E, Tangalos E, Ivnik RJ, Kurland LT. Mayo Clinic Alzheimer's Disease Patient Registry. Aging 1990; 2: 408-415.
  47. Petersen RC, Smith GE, Ivnik RJ, Tangalos EG, Schaid DJ, Thibodeau SN, et al. Apolipoprotein E status as a predictor of the development of Alzheimer's disease in memory impaired individuals. JAMA 1995; 273: 1274-78.
  48. Pike KE, Savage G, Villemagne VL, Ng S, Moss SA, Maruff P, et al. Beta- amyloid imaging and memory in non-demented individuals: evidence for preclinical Alzheimer's disease. Brain 2007; 130: 2837-44.
  49. Price JC, Klunk WE, Lopristi BJ, Lu X, Hoge JA, Ziolko SK, et al. Kinetic modeling of amyloid binding in humans using PET imaging and Pittsburgh Compound-B. J Cereb Blood Flow Metab 2005; 25: 1528-47.
  50. Price JL, Morris JC. Tangles and plaques in nondemented aging and ''preclinical'' Alzheimer's disease. Ann Neurol 1999; 45: 358-68.
  51. Rabinovici GD, Furst AJ, O'Neil JP, Racine CA, Mormino EC, Baker SL, et al. 11C-PIB PET imaging in Alzheimer disease and frontotemporal lobar degeneration. Neurology 2007; 68: 1205-12. doi:10.1212/01.wnl. 0000259035.98480.ed. · DOI
  52. Riley KP, Snowdon DA, Markesbery WR. Alzheimer's neurofibrillary pathology and the spectrum of cognitive function: findigns from the Nun Study. Ann Neurol 2002; 51: 567-77.
  53. Rombouts SA, Barkhof F, Witter MP, Scheltens P. Unbiased whole-brain analysis of gray matter loss in Alzheimer's disease. Neurosci Lett 2000; 285: 231-3.
  54. Rowe CC, Ng S, Ackermann U, Gong SJ, Pike K, Savage G, et al. Imaging {beta}-amyloid burden in aging and dementia. Neurology 2007; 68: 1718-25. doi:10.1212/01.wnl.0000261919.22630.ea. · DOI
  55. Schmitt FA, Davis DG, Wekstein D. ''Preclinical'' AD revisted: neuro- pathology of cognitively normal older adults. Neurology 2000; 55: 370-6.
  56. Senjem ML, Gunter JL, Shiung MM, Petersen RC, Jack CR Jr. Comparison of different methodological implementations of voxel- based morphometry in neurodegenerative disease. Neuroimage 2005; 26: 600-8.
  57. Silbert LC, Quinn JF, Moore MM, Corbridge E, Ball MJ, Murdoch G, et al. Changes in premorbid brain volume predict Alzheimer's disease pathology. Neurology 2003; 61: 487-92.
  58. Small GW, Kepe V, Ercoli LM, Siddarth P, Bookheimer SY, Miller KJ, et al. PET of brain amyloid and Tau in mild cognitive impairment. N Engl J Med 2006; 355: 2652-63.
  59. Snowdon DA, Greiner LH, Mortimer JA, Riley KP, Greiner PA, Markesbery WR. Brain infarction and the clinical expression of Alzheimer's disease, The Nun Study. JAMA 1997; 277: 813-7.
  60. Sun FT, Schriber RA, Greenia JM, He J, Gitcho A, Jagust WJ. Automated templeate-based PET region of interest analyses in the aging brain. Neuroimage 2007; 34: 608-17.
  61. Tang-Wai DF, Knopman DS, Geda YE, Edland SD, Smith GE, Ivnik RJ, et al. Comparison of Short Test of Mental Status and Mini Mental State Examination in mild cognitive impairment. Arch Neurol 2003; 60: 1777-81.
  62. Terry RD, Masliah E, Salmon DP, Butters N, DeTeresa R, Hill R, et al. Physical basis of cognitive alterations in Alzheimer's disease: synapse loss is the major correlate of cognitive impairment. Ann Neurol 1991; 30: 572-80.
  63. Thal DR, Rub U, Orantes M, Braak H. Phases of Ab-deposition in the human brain and its relevance for the development of AS. Neurology 2002; 58: 1791-800.
  64. Troncoso JC, Martin LJ, Del Forno G, Kawas CH. Neuropathology in controls and demented subjects from the Baltimore Longitudinal Study of Aging. Neurobiol Aging 1996; 17: 365-71.
  65. Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, et al. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single- subject brain. Neuroimage 2002; 15: 273-89.
  66. Verhoeff NP, Wilson AA, Takeshita S, Trop L, Hussey D, Singh K, et al. In-vivo imaging of Alzheimer disese beta=amyloid with (11C)SB-13 PET. Am J Geriatr Psychiatry 2004; 12: 584-95.
  67. Visser PJ, Scheltens P, Verhey FRJ, Schmand B, Launer LJ, Jolles J, et al. Medial temporal lobe atrophy and memory dysfunction as predictors for dementia in subjects with mild cognitive impairment. J Neurol 1999; 246: 477-85.
  68. White L, Small BJ, Petrovitch H, Ross GW, Masaki K, Abbott RD, et al. Recent clinical-pathologic research on the causes of dementia in late life: update from the Honolulu-Asia Aging Study. J Geriatr Psychiatr Neurol 2005; 18: 224-7.
  69. Whitwell JL, Shiung MM, Przybelski SA, Weigand SD, Knopman DS, Boeve BF, et al. MRI patterns of atrophy associated with progression to AD in amnestic mild cognitive impairment. Neurology 2007a; in press.
  70. Whitwell JL, Weigand SD, Shiung MM, F BB, Ferman TJ, Smith GE, et al. Focal atrophy in dementia with Lewy bodies on MRI: a distinct pattern from Alzheimer's disease. Brain 2007b; 130: 708-19.

Cited by

Sorted by citations

Authors
Jack, C. R., Lowe, V. J., Senjem, M. L., Weigand, S. D., Kemp, B. J., Shiung, M. M., Knopman, D. S., Boeve, B. F., Klunk, W. E., Mathis, C. A., & Petersen, R. C.
Affiliations
Mayo Clinic (US)
ORCID
Venue
Brain
Publisher
Oxford University Press (OUP)
Published
2008-02-07
Volume
131
Issue
3
Pages
665-680
ISSN
  • 0006-8950 (ISSN-L)
  • 1460-2156
DOI
10.1093/brain/awm336
PMC
PMC2730157
OpenAlex
W2148079076
Cited by
958
References
17
Citations by year
2026: 17 · 2025: 25 · 2024: 32 · 2023: 32 · 2022: 48 · 2021: 57 · 2020: 46 · 2019: 57 · 2018: 44 · 2017: 49 · 2016: 49 · 2015: 49 · 2014: 72 · 2013: 83 · 2012: 76
FWCI
52.00
Type
journal article
Language
en
Open access
Licence
cc-by-nc
Locations
  • Brain (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • Mayo Foundation for Medical Education and Research (AG16574)
  • National Institutes of Health (AG11378, AG06786, R01 AG11378, AG16574)
  • National Institute on Aging (R01AG11378, P50‐AG16574, U01AG06786, AG 16574, U01AG006786, R01AG011378, AG-11378, P50AG016574)
  • National Center for Research Resources (C06RR018898)
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
Keywords
11C-Pittsburgh compound B, amyloid PET, Alzheimer's disease, amnestic mild cognitive impairment, hippocampal volume, gray matter loss, voxel-based morphometry, statistical parametric mapping, cognitive performance, learning and memory, multimodal neuroimaging, FDG-PET comparison
MeSH terms
Aged, Alzheimer Disease, Amnesia, Aniline Compounds, Brain Mapping, Carbon Radioisotopes, Cognition Disorders, Diagnosis, Differential, Female, Hippocampus, Humans, Longitudinal Studies, Magnetic Resonance Imaging, Male, Middle Aged, Neuropsychological Tests, Thiazoles, Positron-Emission Tomography

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review