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1.
Int J Dev Neurosci ; 82(2): 146-158, 2022 Apr.
Article in English | MEDLINE | ID: mdl-34969179

ABSTRACT

Moyamoya disease (MMD) is a rare, progressive cerebrovascular disorder, with an unknown aetiology and pathogenesis. It is characterized by steno-occlusive changes at the terminal portion of the internal carotid artery (ICA), which is accompanied by variable development of the basal collaterals called moyamoya vessels. In this study, we investigate the potential for structural T1 magnetic resonance imaging (MRI) to help characterize MMD clinically, with the help of regionally distributed relative signal intensities (RRSIs) and volumes (RRVs). These RRSIs and RRVs provide the ability to characterize aspects of regional brain development and represent an extension to existing automated biomarker extraction technologies. This study included 269 MRI examinations from MMD patients and 993 MRI examinations from neurotypical controls, with regional biomarkers compared between groups with the area under the receiver operating characteristic curve (AUC). Results demonstrate abnormal presentation of RRSIs and RRVs in the insula (15- to 20-year old cohort, left AUC: 0.74, right AUC: 0.71) and the lateral orbitofrontal region (5- to 10-year old cohort, left AUC: 0.67; 15-20 year cohort, left AUC: 0.62, right AUC: 0.65). Results indicate that RRSIs and RRVs may help in characterizing brain development, assist in the assessment of the presentation of the brains of children with MMD and help overcome standardization challenges in multiprotocol clinical MRI. Further investigation of the potential for RRSIs and RRVs in clinical imaging is warranted and supported through the release of open-source software.


Subject(s)
Moyamoya Disease , Adolescent , Adult , Brain/diagnostic imaging , Brain/pathology , Cerebral Cortex/pathology , Child , Child, Preschool , Humans , Magnetic Resonance Imaging/methods , Moyamoya Disease/diagnostic imaging , Moyamoya Disease/pathology , ROC Curve , Young Adult
2.
Int J Dev Neurosci ; 81(8): 698-705, 2021 Dec.
Article in English | MEDLINE | ID: mdl-34370351

ABSTRACT

Moyamoya disease (MMD) is a progressive cerebrovascular disorder, with an unknown pathogenesis and aetiology. MMD is characterized by steno-occlusive changes at the terminal portion of the internal carotid artery (ICA), which is accompanied by variable development of the basal collaterals, also known as moyamoya vessels. Patients with MMD show variable patterns of brain damage and may experience recurrent multiple transient ischaemic attacks, intracranial bleeding and cerebral infarction. In this study, we investigate the potential for structural T1 magnetic resonance imaging (MRI) to help characterize abnormal cortical development in MMD clinically, with an analysis of both average and variability of regional cortical thicknesses. This study also included a machine learning analysis to assess the predictive capacity of the cortical thickness abnormalities observed in this research. This study included 993 MRI examinations from neurotypical controls and 269 MRI examinations from MMD patients. Results demonstrate abnormal cortical presentation of the insula, caudate, postcentral, precuneus and cingulate regions, in agreement with previous literature cortical thickness findings as well as alternative methods such as functional MRI (fMRI) and digital angiography. To the best of our knowledge, this is the first manuscript to report cortical thickness abnormalities in the middle temporal visual area in MMD and the first study to report on cortical thickness variability abnormalities in MMD.


Subject(s)
Cerebral Cortex/diagnostic imaging , Moyamoya Disease/diagnostic imaging , Adolescent , Child , Child, Preschool , Humans , Infant , Infant, Newborn , Machine Learning , Magnetic Resonance Imaging , Retrospective Studies , Young Adult
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