Brief Computer‐Based Information Processing Measures are Linked to White Matter Integrity in Pediatric‐Onset Multiple Sclerosis. Issue 1 (4th October 2018)

• Record Type: Journal Article
• Authors: Bartlett, Elizabeth; Shaw, Michael; Schwarz, Colleen; Feinberg, Charles; DeLorenzo, Christine; Krupp, Lauren B.; Charvet, Leigh E.
• Is Part Of: Journal of neuroimaging. Volume 29:Issue 1(2019)
• Page Start: 140
• Page End: 150
• Publication Date: 2018-10-04
• Subjects: Pediatric‐onset multiple sclerosis -- cognition -- information processing speed -- BICAMS -- diffusion tensor imaging; Diagnostic imaging -- Periodicals; Nervous system -- Diseases -- Diagnosis -- Periodicals; Imagerie pour le diagnostic -- Périodiques; Système nerveux -- Maladies -- Diagnostic -- Périodiques; Imagerie médicale; Neuroimagerie; Neurologie; Système nerveux; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.804754
• DOI: 10.1111/jon.12566
• Languages: English
• ISSNs: 1051-2284

Abstract

ABSTRACT: BACKGROUND AND PURPOSE: Pediatric‐onset multiple sclerosis (POMS) is a demyelinating disorder with unique clinical challenges. A brief computer‐administered cognitive screening battery measuring processing speed (Cogstate) and the Brief International Cognitive Assessment in MS (BICAMS) detect cognitive impairment in POMS. The neuroanatomic correlates of these deficits are incompletely understood. The purpose of this study is to define the neuroanatomic underpinnings of deficits identified with cognitive screening batteries in POMS. METHODS: Participants with POMS and age‐matched healthy controls (HCs) were screened with Cogstate and BICAMS. Diffusion tensor imaging assessed region‐wise and tractography‐based fractional anisotropy (FA). RESULTS: The POMS ( n = 15) and HC ( n = 21) groups were matched on age (mean ages 17.9 ± 3.2 vs. 17.8 ± 3.3 years, respectively) and on an estimate of general intellectual functioning. The Cogstate composite revealed significant slowing in POMS relative to HCs ( P = .004), but the BICAMS composite did not significantly distinguish the groups ( P = .10). The Cogstate composite showed moderate‐to‐strong correlations with regional FA ( r = –.67 to –.82) and significantly associated with uncinate fasciculus FA following multiple comparisons correction ( P = .002) in POMS. However, the BICAMS composite measure showed only weak‐to‐moderate correlations with FA in POMS ( r = –.19 to –.57), with none surviving multiple comparisons correction. CONCLUSIONS: Computer‐administered measures of cognitive processing are particularly sensitive in POMS and are closely linked to white matter FA.