Frontotemporal Dementia MRI Clustering Analysis of 400 Patients

A research dataset of structural magnetic resonance imaging (MRI) data from 400 patients diagnosed with various frontotemporal dementia clinical syndromes. The data was used for a clustering ensemble analysis to investigate syndromic heterogeneity, with results suggesting a three-cluster solution offered the most clinically meaningful separation. The dataset was authored by Neha Singh-Reilly and last updated on 2026-05-05.

Use Cases

• Replicate the clustering ensemble analysis based on MRI-derived principal components described in the study.
• Investigate the relationship between clinical FTD syndromes and structural brain atrophy patterns mentioned in the results.
• Validate the three-axis heterogeneity model (frontal, temporal, midbrain/subcortical) proposed in the discussion using the underlying data.

Strengths

• Includes data from 400 patients with clinical FTD diagnoses, providing a substantial sample size for analysis.
• MRI data was processed using w-scoring relative to cognitively unimpaired individuals and principal component analysis.
• Clustering analysis evaluated multiple solutions (K=2, 3, or 4) to determine the most clinically meaningful separation.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for specific modeling tasks.
• The dataset is small (137.9 KB), suggesting it may contain summary or processed results rather than raw image data.

Provenance

Source

figshare, author Neha Singh-Reilly.

Collection Method

Data-driven clustering analysis of structural MRI data from patients with clinical FTD diagnoses.

Freshness

Last updated 2026-05-05 07:23:13; freshness should be verified.