Abstract
ObjectiveFocal cortical dysplasia (FCD) lesion detection and subtyping remain challenging on conventional MRI. New diffusion models such as the spherical mean technique (SMT) and neurite orientation dispersion and density imaging (NODDI) provide measurements that potentially produce more specific maps of abnormal tissue microstructure. This study aims to assess the SMT and NODDI maps for computational and radiological lesion characterization compared to standard fractional anisotropy (FA) and mean diffusivity (MD).MethodsSMT, NODDI, FA, and MD maps were calculated for 33 pediatric patients with suspected FCD (18 histologically confirmed). Two neuroradiologists scored lesion visibility on clinical images and diffusion maps. Signal profile changes within lesions and homologous regions were quantified using a surface‐based approach. Diffusion parameter changes at multiple cortical depths were statistically compared between FCD type IIa and type IIb.ResultsCompared to fluid‐attenuated inversion recovery (FLAIR) or T1‐weighted imaging, lesions conspicuity on NODDI intracellular volume fraction (ICVF) maps was better/equal/worse in 5/14/14 patients, respectively, while on SMT intra‐neurite volume fraction (INVF) in 3/3/27. Compared to FA or MD, lesion conspicuity on the ICVF was better/equal/worse in 27/4/2, while on the INVF in 20/7/6. Quantitative signal profiling demonstrated significant ICVF and INVF reductions in the lesions, whereas SMT microscopic mean, radial, and axial diffusivities were significantly increased. FCD type IIb exhibited greater changes than FCD type IIa. No changes were detected on FA or MD profiles.SignificanceFCD lesion‐specific signal changes were found in ICVF and INVF but not in FA and MD maps. ICVF and INVF showed greater contrast than FLAIR in some cases and had consistent signal changes specific to FCD, suggesting that they could improve current presurgical pediatric epilepsy imaging protocols and can provide features useful for automated lesion detection.
Highlights
Focal cortical dysplasia (FCD) is a malformation of cortical development, and the most common cause of drug-resistant focal epilepsy in children.[1,2] It is characterized by disrupted tissue organization with the presence of abnormal cells such as dysmorphic neurons and balloon cells.[1]
This is the first study evaluating the ability of multi-compartment diffusion maps based on spherical mean technique (SMT) and neurite orientation dispersion and density imaging (NODDI) models, to delineate and characterize suspected FCD lesions in a significant pediatric population with drugresistant focal epilepsy
This was made possible by recent advances in magnetic resonance imaging (MRI) hardware, such as improved scanner gradient performance, and software, such as multiband imaging sequences[21,22] that reduce the acquisition time of multi-shell diffusion data (~7 minutes) allowing for its incorporation into a clinical pediatric epilepsy protocol
Summary
Focal cortical dysplasia (FCD) is a malformation of cortical development, and the most common cause of drug-resistant focal epilepsy in children.[1,2] It is characterized by disrupted tissue organization with the presence of abnormal cells such as dysmorphic neurons and balloon cells.[1]. The DTI-based metrics FA and MD cannot differentiate between the contributions to signal changes of fiber density/ orientation dispersion and diffusion across intracellular and extracellular compartments.[12,13,14,15] This lack of specificity hampers the neurobiological interpretation and is a confounder in the identification of pathophysiological phenomena in FCD6,15‒17 because similar signal variation can result from pathological changes or normal white matter structure.[18] New diffusion models such as neurite orientation dispersion and density imaging (NODDI)[12] and spherical mean technique (SMT)[13,14] account for orientation dispersion and fiber crossings within different tissue compartments, with the potential to be more specific to microstructural changes in FCD lesions.[15] These multi-compartment models require a greater range of diffusion data, which until recently would have required clinically impractical scan times, for pediatric patients. We aimed to determine whether the diffusion parameters from multi-compartment models demonstrated consistent changes in suspected FCD lesions, to determine
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