Voxel-based analysis of R2* maps in the healthy human brain

Patrice Péran, Gisela Hagberg, Giacomo Luccichenti, Andrea Cherubini, Valentina Brainovich, Pierre Celsis, Carlo Caltagirone, Umberto Sabatini

Research output: Contribution to journalArticlepeer-review


Purpose: To develop a voxel-based analysis of an R2* map of healthy human brain that is automatic, reproducible, and realizable in a single examination on a 3T MR imager. Such a tool could be useful to measure iron accumulation in neurodegenerative diseases. Materials and Methods: In all, 18 healthy subjects underwent MR imaging at a field strength of 3T: 1) six consecutive T2*-weighted gradient-echo volumes were acquired using a segmented echo-planar imaging sequence and 2) a conventional dual-echo turbo spin echo sequence was also applied to acquire T2-weighted images. Images were realigned and spatial correction was performed using a template brain dataset with SPM2. For each subject we performed a voxel-by-voxel nonlinear least-squares fitting of the data acquired at the six echo times to obtain a monoexponential signal decay curve. The reproducibility and sensitivity to age variation were assessed by voxel-based analysis. Results: The reproducibility tests in whole brain analysis showed little R2* variation. Furthermore, the statistical analysis, performed on each brain voxel, revealed a significant positive correlation between age and MR values located in regions where a slow and constant age-related iron deposition is known. Conclusion: Our method, combining data acquisition and data processing, demonstrates the feasibility of voxel-based analysis on an R2* map and affords a high degree of sensitivity and good reproducibility while maintaining high spatial resolution.

Original languageEnglish
Pages (from-to)1413-1420
Number of pages8
JournalJournal of Magnetic Resonance Imaging
Issue number6
Publication statusPublished - Dec 2007


  • Brain
  • R2*
  • Voxel based analysis

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology


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