Data quality in diffusion tensor imaging studies of the preterm brain: a systematic review

Area of Science:

• Neonatal neuroimaging
• Developmental neuroscience
• Medical physics

Background:

• Diffusion tensor imaging (DTI) is vital for assessing preterm infant brain development and injury.
• Reliable DTI data is essential for accurate evaluation of neurodevelopmental outcomes.
• Standardized methodologies are needed to ensure data integrity in DTI studies.

Purpose of the Study:

• To systematically review the literature on DTI acquisition and processing methods in preterm infants.
• To identify variations and inconsistencies in DTI methodology within published studies.
• To assess the quality and completeness of reporting for DTI parameters.

Main Methods:

• A comprehensive literature search was conducted across Embase, Medline, Web of Science, and Cochrane databases.
• Studies published between 2003 and 2013 focusing on DTI in preterm infants were included.
• Keywords included prematurity, neuroimaging, brain, and diffusion tensor imaging.

Main Results:

• 74 DTI studies in preterm infants met the inclusion criteria, revealing significant variability in acquisition and processing.
• Incomplete reporting of DTI settings was common, with only 26% using neonatal hardware.
• Quality control measures like artifact correction and data exclusion were often unreported (45% and 24%, respectively).

Conclusions:

• Current DTI acquisition and processing methods in preterm infant studies are inconsistently reported and highly variable.
• Many studies do not adhere to optimal standards, potentially compromising the reliability of findings.
• Standardization and complete reporting of DTI methodology are urgently needed.