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J Neuroimaging. 2019 Nov;29(6):750-759. doi: 10.1111/jon.12653. Epub 2019 Jul 14.

Resting-State fMRI Networks in Children with Tuberous Sclerosis Complex.

Author information

1
Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA.
2
Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, MA.
3
Department of Radiology, Radio-oncology and Nuclear Medicine, University of Montreal and CHU Sainte-Justine, Montreal, QC, Canada.
4
Department of Neuroscience, Brown University, Providence, RI.
5
Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA.
6
Department of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH.
7
Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH.
8
Department of Neurology, University of Alabama at Birmingham, Birmingham, AL.
9
Department of Pediatrics, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX.
10
Division of Pediatric Neurology, University of California at Los Angeles Mattel Children's Hospital, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA.
11
Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA.
12
Translational Neuroscience Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA.
13
F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Harvard University, Boston, MA.
14
Division of Neuroradiology, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA.

Abstract

BACKGROUND AND PURPOSE:

There are no published studies examining resting state networks (RSNs) and their relationship with neurodevelopmental metrics in tuberous sclerosis complex (TSC). We aimed to identify major resting-state functional magnetic resonance imaging (rs-fMRI) networks in infants with TSC and correlate network analyses with neurodevelopmental assessments, autism diagnosis, and seizure history.

METHODS:

Rs-fMRI data from 34 infants with TSC, sedated with propofol during the scan, were analyzed to identify auditory, motor, and visual RSNs. We examined the correlations between auditory, motor, and visual RSNs at approximately 11.5 months, neurodevelopmental outcome at approximately 18.5 months, and diagnosis of autism spectrum disorders at approximately 36 months of age.

RESULTS:

RSNs were obtained in 76.5% (26/34) of infants. We observed significant negative correlations between auditory RSN and auditory comprehension test scores (p = .038; r = -.435), as well as significant positive correlations between motor RSN and gross motor skills test scores (p = .023; r = .564). Significant positive correlations between motor RSNs and gross motor skills (p = .012; r = .754) were observed in TSC infants without autism, but not in TSC infants with autism, which could suggest altered motor processing. There were no significant differences in RSNs according to seizure history.

CONCLUSIONS:

Negative correlation between auditory RSN, as well as positive correlation between motor RSN and developmental outcome measures might reflect different brain mechanisms and, when identified, may be helpful in predicting later function. A larger study of TSC patients with a healthy control group is needed before auditory and motor RSNs could be considered as neurodevelopmental outcome biomarkers.

KEYWORDS:

Autism spectrum disorders; propofol; resting state functional resonance imaging; resting state networks; tuberous sclerosis complex

PMID:
31304656
DOI:
10.1111/jon.12653

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