Automated morphometric magnetic resonance imaging analysis for the detection of periventricular nodular heterotopia

Abstract

SUMMARYPurpose: To describe a novel magnetic resonance imaging (MRI) postprocessing technique for the detection of periventricular nodular heterotopia (PNH) and to evaluate its diagnostic value. The method is a further development of voxel-based morphometric analysis with focus on a region of interest around the lateral ventricles to increase the sensitivity and specificity for automated detection of abnormally located gray matter in this area. Methods: T 1 -weighted MRI volume data sets were normalized and segmented in statistical parametric mapping (SPM 5 software), and the distribution of gray matter was compared to a normal database. As a new approach, individual masks derived from segmentation of the lateral ventricles were used to restrict the search for ectopic gray matter to the periventricular area. PNH were automatically detected by localizing the maximum deviation from the normal database in this area, provided that the z-score exceeded a certain threshold. The optimal z-score threshold for maximum sensitivity and specificity was determined by a receiver operating characteristic (ROC) curve analysis. The method was applied in 40 patients with PNH and 400 controls. Key Findings: PNH were detected in 37 of 40 patients, and false positives were found in 34 of 400 controls, amounting to 92.5% sensitivity and 91.5% specificity. In 17 of the patients in whom PNH could be identified, these lesions had been overlooked in the past, and in 8 patients even in the high-resolution MRI subsequently used for postprocessing. Significance: The results suggest that automated morphometric MRI analysis with focus on ectopic gray matter in the periventricular areas facilitates the evaluation of MRI data and increases the sensitivity for the detection of PNH.

Computational analysis in epilepsy neuroimaging: A survey of features and methods

“…These techniques can be adapted to identify other malformations, such as subcortical band heterotopia (“double cortex” syndrome) ( Huppertz et al, 2008 ) or periventricular heterotopia, where ventricle masks are used to look for abnormal gray matter outlining the ventricles (92.5% sensitivity and 91.5% specificity) ( Pascher et al, 2013 ). In addition, these methods have been sensitive to detecting co-occurring neoplasia with focal cortical dysplasia (87% sensitivity) ( Bruggemann et al, 2007 ).…”

Periventricular white matter abnormalities and restricted repetitive behavior in autism spectrum disorder

“…This may be due to limitations in MRI-visibility of many malformations ( Colombo et al, 2009 ). Although malformations such as tuberous sclerosis are grossly apparent on visual review, others can be visually elusive, such as periventricular heterotopia and focal cortical dysplasia ( Bernasconi et al, 2011 , Pascher et al, 2013 ). Periventricular heterotopia detection is improved with quantitative MRI methods.…”

“…Periventricular heterotopia detection is improved with quantitative MRI methods. In people with epilepsy, 46% of heterotopias detected with quantitative MRI were previously overlooked on conventional visual analysis ( Pascher et al, 2013 ).…”

Quantitative assessment of corpus callosum morphology in periventricular nodular heterotopia

“…The method we used for quantification of heterotopic grey matter nodules is freely available, and provides an alternative approach to a recently published technique (Pascher, Kroll et al 2013). As noted in the results section, labelling was occasionally incomplete in severe cases.…”