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Updated: Feb 19, 2026

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
Normal white matter microstructure in women long-term recovered from anorexia nervosa: A diffusion tensor imaging
Lasse Bang1, Øyvind Rø1,2, Tor Endestad3
1Regional Department for Eating Disorders, Division of Mental Health and Addiction, Oslo University Hospital, P.O. Box 4956 Nydalen, Oslo, 0424, Norway.
White matter microstructure alterations in anorexia nervosa (AN) appear reversible after long-term recovery. This study found normal white matter integrity in recovered women, suggesting potential for full recovery of brain structure.
Area of Science:
- Neuroimaging
- Anatomical MRI
- Diffusion Tensor Imaging
Background:
- Anorexia nervosa (AN) is associated with white matter (WM) microstructure alterations.
- The reversibility of these WM changes after recovery from AN remains unclear.
- Existing research on recovered AN patients yields inconsistent findings.
Purpose of the Study:
- To investigate the presence of WM microstructure alterations in women long-term recovered from AN.
- To explore correlations between WM microstructure and clinical characteristics in recovered individuals.
Main Methods:
- Diffusion tensor imaging (DTI) was used to assess WM microstructure.
- Twenty-one women recovered from AN for at least one year were compared to 21 healthy controls.
- Correlational analyses examined relationships between WM metrics and clinical factors.
Main Results:
- No statistically significant differences in WM microstructure were found between recovered AN patients and controls.
- Null findings persisted even with liberal statistical thresholds.
- No significant correlations were observed between WM microstructure and clinical characteristics.
Conclusions:
- WM microstructure appears normal in individuals long-term recovered from AN.
- Findings suggest that WM alterations observed during acute AN are reversible.
- Further research is needed to confirm these findings and understand recovery trajectories.
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