Measurements of medial temporal lobe atrophy for prediction of Alzheimer's disease in subjects with mild cognitive impairment
Open accessAbstract
Our aim was to compare the predictive accuracy of 4 different medial temporal lobe measurements for Alzheimer's disease (AD) in subjects with mild cognitive impairment (MCI). Manual hippocampal measurement, automated atlas-based hippocampal measurement, a visual rating scale (MTA-score), and lateral ventricle measurement were compared. Predictive accuracy for AD 2 years after baseline was assessed by receiver operating characteristics analyses with area under the curve as outcome. Annual cognitive decline was assessed by slope analyses up to 5 years after baseline. Correlations with biomarkers in cerebrospinal fluid (CSF) were investigated. Subjects with MCI were selected from the Development of Screening Guidelines and Clinical Criteria for Predementia AD (DESCRIPA) multicenter study (n = 156) and the single-center VU medical center (n = 172). At follow-up, area under the curve was highest for automated atlas-based hippocampal measurement (0.71) and manual hippocampal measurement (0.71), and lower for MTA-score (0.65) and lateral ventricle (0.60). Slope analysis yielded similar results. Hippocampal measurements correlated with CSF total tau and phosphorylated tau, not with beta-amyloid 1-42. MTA-score and lateral ventricle volume correlated with CSF beta-amyloid 1-42. We can conclude that volumetric hippocampal measurements are the best predictors of AD conversion in subjects with MCI.
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.
Integrity signals
Registry
Cites
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.
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?
Medial temporal lobe atrophy on MRI is considered an early and sensitive marker for AD, and is assumed to reflect underlying neuronal loss in hippocampus and temporal lobe.
“Medial temporal lobe (MTA) atrophy as observed on MRI is considered to be an early and sensitive marker for AD, and is assumed that it reflects underlying neuronal loss in hippocampus and temporal lobe (Clerx et al., 2013; Jack et al., 1997; Duara et al., 2008).”
From T1rho MRI and CSF biomarkers in diagnosis of Alzheimer's disease (2015) · cites this paper as Clerx et al., 2013
The Introduction describes MRI-assessed medial temporal lobe atrophy as an effective aid to early AD diagnosis, and §4.1.1 calls medial temporal neurodegeneration a strong MRI marker of imminent conversion. The paper does not state that the MRI finding reflects neuronal loss in the hippocampus and temporal lobe; §4.1.3 notes that some atrophy measures may reflect more generalized atrophy. (LLM, conf=0.84)
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
Comparison of different MRI brain atrophy rate measures with clinical disease progression in AD
Jack, C. R., Shiung, M. M., Gunter, J. L., O’Brien, P. C., Weigand, S. D., Knopman, D. S., Boeve, B. F., Ivnik, R. J., Smith, G. E., Cha, R. H., et al. (2004) · Neurology · doi:10.1212/01.wnl.0000110315.26026.ef · Cited by 827 · see citing works
Andreasen, N., Hesse, C., Davidsson, P., Minthon, L., Wallin, A., Winblad, B., Vanderstichele, H., Vanmechelen, E., & Blennow, K. (1999) · Archives of Neurology · doi:10.1001/archneur.56.6.673 · Cited by 660 · see citing works
Self-citationBaseline MRI predictors of conversion from MCI to probable AD in the ADNI cohort
Risacher, S., Saykin, A., Wes, J., Shen, L., Firpi, H., & McDonald, B. (2009) · Current Alzheimer Research · doi:10.2174/156720509788929273 · Cited by 538 · see citing works
Jacobs, H. I. L., Van Boxtel, M. P. J., Jolles, J., Verhey, F. R. J., & Uylings, H. B. M. (2012) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2011.06.009 · Cited by 293 · see citing works
Self-citationMRI‐Based Hippocampal Volume Measurements in Epilepsy
Jack, C. R. (1994) · Epilepsia · doi:10.1111/j.1528-1157.1994.tb05986.x · Cited by 224 · see citing works
Grey and white matter changes at different stages of Alzheimer’s disease
Serra, L., Cercignani, M., Lenzi, D., Perri, R., Fadda, L., Caltagirone, C., Macaluso, E., & Bozzali, M. (2010) · Journal of Alzheimer's Disease · doi:10.3233/jad-2010-1223 · Cited by 149 · see citing works
Levy-Cooperman, N., Ramirez, J., Lobaugh, N. J., & Black, S. E. (2008) · Stroke · doi:10.1161/strokeaha.107.498196 · Cited by 52 · see citing works
Flagged first, then by citations
Research works printed but not linked: 5
- Apostolova, L.G., Dinov, I.D., Dutton, R.A., Hayashi, K.M., Toga, A.W., Cummings, J.L., Thompson, P.M., 2006. 3D comparison of hippocampal atrophy in amnestic mild cognitive impairment and Alzheimer's disease [erratum in 2007;130:2474]. Brain 129, 2867e2873.
- Kolen, M.J., Brennan, R.L., 1995. Test Equating: Methods and Practices. Springer, New York.
- Scheltens, P., Leys, D., Barkhof, F., Huglo, D., Weinstein, H.C., Vermersch, P., Kuiper, M., Steinling, M., Wolters, E.C., Valk, J., 1992. Atrophy of medial temporal lobes on MRI in "probable" Alzheimer's disease and normal ageing: diagnostic value and neuropsychological correlates. J. Neurol. Neurosurg. Psychiatry 55, 967e972.
- Smith, S.M., Jenkinson, M., Woolrich, M.W., Beckmann, C.F., Behrens, T.E., Johansen- Berg, H., Bannister, P.R., De Luca, M., Drobnjak, I., Flitney, D.E., Niazy, R.K., Saunders, J., Vickers, J., Zhang, Y., De Stefano, N., Brady, J.M., Matthews, P.M., 2004. Advances in functional and structural MR image analysis and imple- mentation as FSL. Neuroimage 23, S208eS219.
- Zhang, Y., Brady, M., Smith, S., 2001. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans. Med. Imaging 20, 45e57.
Cited by
Sorted by citations
Multi-atlas segmentation of biomedical images: A survey
Iglesias, J. E., & Sabuncu, M. R. (2015) · Medical Image Analysis · doi:10.1016/j.media.2015.06.012 · Cited by 667 · see citing works
Lombardi, G., Crescioli, G., Cavedo, E., Lucenteforte, E., Casazza, G., Bellatorre, A.-G., Lista, C., Costantino, G., Frisoni, G., Virgili, G., et al. (2020) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd009628.pub2 · Cited by 214 · see citing works
Lista, S., Molinuevo, J. L., Cavedo, E., Rami, L., Amouyel, P., Teipel, S. J., Garaci, F., Toschi, N., Habert, M.-O., Blennow, K., et al. (2015) · Journal of Alzheimer's Disease · doi:10.3233/jad-150202 · Cited by 53 · see citing works
Self-citationT1rho MRI and CSF biomarkers in diagnosis of Alzheimer's disease
Haris, M., Yadav, S. K., Rizwan, A., Singh, A., Cai, K., Kaura, D., Wang, E., Davatzikos, C., Trojanowski, J. Q., Melhem, E. R., et al. (2015) · NeuroImage: Clinical · doi:10.1016/j.nicl.2015.02.016 · Cited by 33 · see citing works
- Authors
- Clerx, L., van Rossum, I. A., Burns, L., Knol, D. L., Scheltens, P., Verhey, F., Aalten, P., Lapuerta, P., van de Pol, L., van Schijndel, R., de Jong, R., Barkhof, F., Wolz, R., Rueckert, D., Bocchetta, M., Tsolaki, M., Nobili, F., Wahlund, L.-O., Minthon, L., Frölich, L., Hampel, H., Soininen, H., & Visser, P. J.
- Affiliations
- Maastricht University (NL)
- Bristol-Myers Squibb (United States) (US)
- Amsterdam UMC Location Vrije Universiteit Amsterdam (NL)
- Lexicon Pharmaceuticals (United States) (US)
- Imperial College London (GB)
- Centro San Giovanni di Dio Fatebenefratelli (IT)
- University of Genoa (IT)
- Lund University (SE)
- Heidelberg University (DE)
- Goethe University Frankfurt (DE)
- University of Eastern Finland (FI)
- Corresponding author
- Clerx, Lies
- ORCID
- Venue
- Neurobiology of Aging
- Publisher
- Elsevier BV
- Published
- 2013-08
- Volume
- 34
- Issue
- 8
- Pages
- 2003-2013
- ISSN
- 0197-4580 (ISSN-L)
- OpenAlex
- W1993773381
- Cited by
- 98
- References
- 7
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 8 · 2023: 2 · 2022: 9 · 2021: 12 · 2020: 5 · 2019: 5 · 2018: 6 · 2017: 12 · 2016: 7 · 2015: 19 · 2014: 8 · 2013: 1
- FWCI
- 8.30
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Neurobiology of Aging (publishedVersion)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, other-oa)
- Pure Amsterdam UMC (publishedVersion)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
- VU Research Portal (publishedVersion, other-oa)
- UCL Discovery (University College London) (submittedVersion)
- CINECA IRIS Institutial Research Information System (University of Genoa) (submittedVersion)
- Lund University Publications (Lund University) (submittedVersion)
- INFM-OAR (INFN Catania) (submittedVersion, other-oa)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- Seventh Framework Programme (211696)
- Center for Translational Molecular Medicine (02N-01)
- 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 › Pulmonary and Respiratory Medicine › Cancer-related cognitive impairment studies
- Keywords
- Alzheimer's disease, mild cognitive impairment, medial temporal lobe atrophy, hippocampal volume, lateral ventricle volume, cognitive decline, cerebrospinal fluid biomarkers, tau protein, phosphorylated tau, amyloid-beta 42
- MeSH terms
- Aged, Alzheimer Disease, Atrophy, Cognition, Female, Forecasting, Hippocampus, Humans, Magnetic Resonance Imaging, Male, Peptide Fragments, Biomarkers, Amyloid beta-Peptides, tau Proteins, Disease Progression, Cognitive Dysfunction
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