Magnetic resonance imaging pattern recognition in childhood bilateral basal ganglia disorders

Shekeeb S Mohammad; Rajeshwar Reddy Angiti; Andrew Biggin; Hugo Morales-Briceño; Robert Goetti; Belen Perez-Dueñas; Allison Gregory; Penelope Hogarth; Joanne Ng; Apostolos Papandreou; Kaustuv Bhattacharya; Shamima Rahman; Kristina Prelog; Richard I Webster; Evangeline Wassmer; Susan Hayflick; John Livingston; Manju Kurian; W Kling Chong; Russell C Dale; Basal Ganglia MRI Study Group

doi:10.1093/braincomms/fcaa178

Magnetic resonance imaging pattern recognition in childhood bilateral basal ganglia disorders

Brain Commun. 2020 Oct 26;2(2):fcaa178. doi: 10.1093/braincomms/fcaa178. eCollection 2020.

Authors

Shekeeb S Mohammad^{1

2

3}, Rajeshwar Reddy Angiti^{4

5}, Andrew Biggin³, Hugo Morales-Briceño⁶, Robert Goetti⁷, Belen Perez-Dueñas⁸, Allison Gregory⁹, Penelope Hogarth⁹, Joanne Ng¹⁰, Apostolos Papandreou¹⁰, Kaustuv Bhattacharya¹¹, Shamima Rahman¹², Kristina Prelog⁷, Richard I Webster², Evangeline Wassmer¹³, Susan Hayflick⁹, John Livingston¹⁴, Manju Kurian¹⁰, W Kling Chong¹⁵, Russell C Dale^{1

2

3}; Basal Ganglia MRI Study Group

Affiliations

¹ Kids Neuroscience Centre, The Children's Hospital at Westmead, Westmead, NSW 2145, Australia.
² TY Nelson Department of Neurology and Neurosurgery, The Children's Hospital at Westmead, Sydney, Australia.
³ The Children's hospital at Westmead Clinical School, Faculty of Medicine, University of Sydney, Sydney, NSW 2145, Australia.
⁴ Newborn and Peadiatric Emergency Transport Service (NETS), Bankstown, NSW, Australia.
⁵ Department of Neonatology, Liverpool Hospital, Liverpool, NSW, Australia.
⁶ Movement Disorders Unit, Neurology Department, Westmead Hospital, Westmead, NSW 2145, Australia.
⁷ Medical Imaging, The Children's Hospital at Westmead and Sydney Medical School, University of Sydney, Sydney, Australia.
⁸ Paediatric Neurology Department, Hospital Vall d'Hebrón Universitat Autónoma de Barcelona, Vall d'Hebron Research Institute Barcelona, Barcelona, Spain.
⁹ Department of Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR, USA.
¹⁰ Molecular Neurosciences, Developmental Neurosciences, UCL-Institute of Child Health, London, UK.
¹¹ Western Sydney Genomics Program, The Children's Hospital at Westmead and Sydney Medical School, University of Sydney, Sydney, Australia.
¹² Mitochondrial Research Group, Genetics and Genomic Medicine, Institute of Child Health, University College London and Metabolic Unit, Great Ormond Street Hospital, London, UK.
¹³ Department of Paediatric Neurology, Birmingham Children's Hospital, Birmingham, UK.
¹⁴ Department of Paediatric Neurology, Leeds Teaching Hospitals Trust, University of Leeds, UK.
¹⁵ Department of Radiology, Great Ormond Street Hospital, London, UK.

Abstract

Bilateral basal ganglia abnormalities on MRI are observed in a wide variety of childhood disorders. MRI pattern recognition can enable rationalization of investigations and also complement clinical and molecular findings, particularly confirming genomic findings and also enabling new gene discovery. A pattern recognition approach in children with bilateral basal ganglia abnormalities on brain MRI was undertaken in this international multicentre cohort study. Three hundred and five MRI scans belonging to 201 children with 34 different disorders were rated using a standard radiological scoring proforma. In addition, literature review on MRI patterns was undertaken in these 34 disorders and 59 additional disorders reported with bilateral basal ganglia MRI abnormalities. Cluster analysis on first MRI findings from the study cohort grouped them into four clusters: Cluster 1-T₂-weighted hyperintensities in the putamen; Cluster 2-T₂-weighted hyperintensities or increased MRI susceptibility in the globus pallidus; Cluster 3-T₂-weighted hyperintensities in the globus pallidus, brainstem and cerebellum with diffusion restriction; Cluster 4-T₁-weighted hyperintensities in the basal ganglia. The 34 diagnostic categories included in this study showed dominant clustering in one of the above four clusters. Inflammatory disorders grouped together in Cluster 1. Mitochondrial and other neurometabolic disorders were distributed across clusters 1, 2 and 3, according to lesions dominantly affecting the striatum (Cluster 1: glutaric aciduria type 1, propionic acidaemia, 3-methylglutaconic aciduria with deafness, encephalopathy and Leigh-like syndrome and thiamine responsive basal ganglia disease associated with SLC19A3), pallidum (Cluster 2: methylmalonic acidaemia, Kearns Sayre syndrome, pyruvate dehydrogenase complex deficiency and succinic semialdehyde dehydrogenase deficiency) or pallidum, brainstem and cerebellum (Cluster 3: vigabatrin toxicity, Krabbe disease). The Cluster 4 pattern was exemplified by distinct T₁-weighted hyperintensities in the basal ganglia and other brain regions in genetically determined hypermanganesemia due to SLC39A14 and SLC30A10. Within the clusters, distinctive basal ganglia MRI patterns were noted in acquired disorders such as cerebral palsy due to hypoxic ischaemic encephalopathy in full-term babies, kernicterus and vigabatrin toxicity and in rare genetic disorders such as 3-methylglutaconic aciduria with deafness, encephalopathy and Leigh-like syndrome, thiamine responsive basal ganglia disease, pantothenate kinase-associated neurodegeneration, TUBB4A and hypermanganesemia. Integrated findings from the study cohort and literature review were used to propose a diagnostic algorithm to approach bilateral basal ganglia abnormalities on MRI. After integrating clinical summaries and MRI findings from the literature review, we developed a prototypic decision-making electronic tool to be tested using further cohorts and clinical practice.

Keywords: MRI; basal ganglia; pattern recognition; striatal necrosis; striatum.

Abstract

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