Can neuroimaging measures differentiate the disease course of anorexia nervosa? A systematic review

Can neuroimaging measures differentiate the disease course of anorexia nervosa? A systematic review

Anorexia nervosa (AN) entails many uncertainties regarding the clinical outcome, due to large heterogeneity in the disease course. AN is associated with global decrease in brain volumes and altered brain functioning during acute illness. However, it is unclear whether structural and functional brain...

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Bibliographic Details
Published in:Journal of psychiatric research Vol. 163; pp. 337 - 349
Main Authors: Bracké, Katrien F.M., Steegers, Cathelijne P.M., van der Harst, Tess, Dremmen, Marjolein H.G., Vernooij, Meike W., White, Tonya J.H., Dieleman, Gwen C.
Format: Journal Article
Language:English
Published: England Elsevier Ltd 01-07-2023
Subjects:
Anorexia nervosa
Anorexia Nervosa - pathology
Brain
Disease course
Disease Progression
Gray Matter - pathology
Humans
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
Neuroimaging
Prediction
Prognosis
Neuroimaging
Prognosis
Anorexia nervosa
Magnetic resonance imaging
Disease course
Prediction
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Summary:Anorexia nervosa (AN) entails many uncertainties regarding the clinical outcome, due to large heterogeneity in the disease course. AN is associated with global decrease in brain volumes and altered brain functioning during acute illness. However, it is unclear whether structural and functional brain alterations can predict clinical outcome. We aimed to systematically review the predictive value of volumetric and functional brain outcome measures of structural and functional brain magnetic resonance imaging (MRI) on the disease course of AN. Four databases (Embase, Medline, Psycinfo, and Cochrane Central Register) were systematically searched. A total of 15 studies (structural MRI: n = 6, functional MRI: n = 9) were reviewed. In total 464 unique AN patients, and 328 controls were included. Follow-up time ranged between 1 and 43 months. Structural neuroimaging studies showed that lower brain volumes of the cerebellum, subcortical grey matter, and cortical white matter at admission predicted a worse clinical outcome. A smaller increase of the anterior cingulate cortex volume in the early phase of the disease predicted a worse clinical outcome. Lower overall gyrification, and a higher clustering coefficient predicted a worse clinical outcome. Functional MRI studies showed that frontal, parietal and temporal activity during task-based algorithms predicted follow-up body mass index, although results were bidirectional possibly due to the large heterogeneity in methodological approaches. Neuroimaging measures may predict the clinical outcome of AN. However, there is a lack of replication studies. Future studies are needed to validate the prognostic utility of neuroimaging measures in AN patients, and should harmonize demographic, clinical and neuroimaging features in order to enhance comparability.
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ISSN:0022-3956
1879-1379
DOI:10.1016/j.jpsychires.2023.05.059