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Record W4413370556 · doi:10.1080/23279095.2025.2546951

High‑Resolution T2 MRI Volumetry of Medial Temporal Lobe Subregions Predicts Cognitive Decline Across the Alzheimer’s Disease Continuum

2025· article· en· W4413370556 on OpenAlexaboutno aff
Mehrdad Mozafar, Sahba Shahbazi, Mohammad Amir Amirian, Kosar Shekari, Neshat Sepahvand, Melika Esmaeili, AmirAbbas Amini, Shayan Shakeri, Hanieh Mirhosseini, Mahsa Mayeli

Bibliographic record

VenueApplied Neuropsychology Adult · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersNational Institute of Biomedical Imaging and BioengineeringNational Institutes of HealthGenentechIXICOUniversity of California, Los AngelesServierNorthern California Institute for Research and EducationDoD Alzheimer's Disease Neuroimaging InitiativeRush UniversityBerlin-Brandenburg School for Regenerative TherapiesPfizerNovartis Pharmaceuticals CorporationEisai IncorporatedMedpaceUniversity of PennsylvaniaRocheEli Lilly and CompanyGE HealthcareBioClinicaNational Institute on AgingAlzheimer's AssociationMerckU.S. Department of Defense
KeywordsTemporal lobeCognitive declineNeuroscienceCognitionDiseaseHigh resolutionPsychologyMedicinePathologyDementiaGeographyRemote sensing

Abstract

fetched live from OpenAlex

Atrophy of medial temporal lobe (MTL) subregions is an early biomarker of Alzheimer’s disease (AD). This study aimed to examine the relationship between MTL subregion volumes and cognitive performance in patients across the AD continuum. We analyzed data from 276 participants using the Alzheimer’s Disease Neuroimaging Initiative (ADNI), including 74 cognitively normal (CN), 110 subjective memory complaints (SMC), 37 early mild cognitive impairment (EMCI), 35 late mild cognitive impairment (LMCI), and 20 AD participants. MTL subregions volumes were measusing high-resolution T2-weighted MRI, and analyses were adjusted for age, education, APOE ε4 status, and intracranial volume (ICV). Significant atrophy in regions such as the cornu ammonis (CA), dentate gyrus (DG), subiculum (SUB), entorhinal cortex (ERC), and Brodmann area 35 (BA35) was found in AD participants compared with other groups. In AD, poorer Alzheimer’s Disease Assessment Scale - Cognitive Subscale 13 (ADAS-13) performance was associated with reduced CA, DG, BA35, and parahippocampal cortex (PHC) volumes. In LMCI, lower Mini-Mental State Examination (MMSE) scores were associated with atrophy in CA and SUB. Diminished Montreal Cognitive Assessment (MoCA) scores were linked to reduced ERC volumes in CN, as well as with atrophy in BA35, ERC and CA subfields among AD patients. In LMCI, poorer Trail Making Test, Part B performance (i.e., longer completion time) was related to smaller Brodmann area 36 (BA36), collateral sulcus (CS), and PHC subregion volumes, whereas in the AD, it was related to BA36 only. Poorer immediate memory recall in AD was associated with atrophy in CA, DG, while in early stages of MCI, poorer verbal learning scores correlated with atrophy in the CA, DG, BA35, SUB, and CS regions. Moreover, diminished Logical Memory Delayed Recall was associated with atrophy in the CA, BA35, and PHC subfields among AD subjects. These findings support the value of atrophy in MTL subregions as potential imaging markers for detecting and monitoring cognitive decline across the AD continuum.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.880

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.338
Teacher spread0.322 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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