Enhancing Study Design and Analysis of MR Imaging Markers Through Measurement Error Modeling.

ABSTRACT:

Background

Measurement error in imaging reduces statistical power and potentially biases parameter estimation, compromising study reliability.

Purpose

To introduce a dual data collection design (reliability and main datasets) to quantify measurement error and apply regression calibration to correct error-prone imaging markers, thereby improving biomarker-outcome estimation, statistical power, and sample size planning.

Study type

Prospective (reliability) and retrospective (regression calibration).

Population

65 healthy volunteers (mean age: 23.2), 60 age and sex matched with 34 epilepsy patients (mean age: 28.7).

Field strength/sequence

3.0 T, MR fingerprinting (MRF) and T1-weighted (T1w) MPRAGE.

Assessment

Three-dimensional brain scan-rescan data

SUBMITTER: Wang X 

PROVIDER: S-EPMC12931679 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature