Enzyme Replacement Therapy for CLN2 Disease: MRI Volumetry Shows Significantly Slower Volume Loss Compared with a Natural History Cohort.
AJNR Am J Neuroradiol
; 2024 Oct 24.
Article
en En
| MEDLINE
| ID: mdl-38977290
ABSTRACT
BACKGROUND AND PURPOSE:
Neuronal ceroid lipofuscinoses are a group of neurodegenerative disorders. Recently, enzyme replacement therapy (ERT) was approved for neuronal ceroid lipofuscinosis type 2 (CLN2), a subtype of neuronal ceroid lipofuscinoses. The aim of this study was to quantify brain volume loss in CLN2 disease in patients on ERT in comparison with a natural history cohort using MRI. MATERIALS ANDMETHODS:
Nineteen (14 female, 5 male) patients with CLN2 disease at 1 UK center were studied using serial 3D T1-weighted MRI (follow-up time, 1-9 years). Brain segmentation was performed using FreeSurfer. Volume measurements for supratentorial gray and white matter, deep gray matter (basal ganglia/thalami), the lateral ventricles, and cerebellar gray and white matter were recorded. The volume change with time was analyzed using a linear mixed-effects model excluding scans before treatment onset. Comparison was made with a published natural history cohort of 12 patients (8 female, 4 male), which was re-analyzed using the same method.RESULTS:
Brain volume loss of all segmented brain regions was much slower in treated patients compared with the natural history cohort. For example, supratentorial gray matter volume in treated patients decreased by a mean of 3% (SD, 0.74%) (P < .001) annually compared with an annual volume loss of a mean of 16.8% (SD, 1.5%) (P < .001) in the natural history cohort.CONCLUSIONS:
Our treatment cohort showed a significantly slower rate of brain parenchymal volume loss compared with a natural history cohort in several anatomic regions. Our results complement prior clinical data that found a positive response to ERT. We demonstrate that automated MRI volumetry is a sensitive tool to monitor treatment response in children with CLN2 disease.
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Colección:
01-internacional
Banco de datos:
MEDLINE
Idioma:
En
Revista:
AJNR Am J Neuroradiol
Año:
2024
Tipo del documento:
Article