Examination of Frontal and Parietal Tectocortical Attention Pathways in Spina Bifida Meningomyelocele Using Probabilistic Diffusion Tractography

Abstract

Abnormalities of the midbrain tectum are common but variable malformations in spina bifida meningomyelocele (SBM) and have been linked to neuropsychological deficits in attention orienting. The degree to which variations in tectum structure influence white matter (WM) connectivity to cortical regions is unknown. To assess the relationship of tectal structure and connectivity to frontal and parietal cortical regions, probabilistic diffusion tractography was performed on 106 individuals (80 SBM, 26 typically developing [TD]) to isolate anterior versus posterior tectocortical WM pathways. Results showed that those with SBM exhibited significantly reduced tectal volume, along with decreased fractional anisotropy (FA) in posterior but not anterior tectocortical WM pathways when compared with TD individuals. The group with SBM also showed greater within-subject discrepancies between frontal and parietal WM integrity compared with the TD group. Of those with SBM, qualitative classification of tectal beaking based on radiological review was associated with increased axial diffusivity across both anterior and posterior tectocortical pathways, relative to individuals with SBM and a normal appearing tectum. These results support previous volumetric findings of greater impairment to posterior versus anterior brain regions in SBM, and quantifiably relate tectal volume, tectocortical WM integrity, and tectal malformations in this population.

Postshunt lateral ventricular volume, white matter integrity, and intellectual outcomes in spina bifida and hydrocephalus

“…39 In the present study, we extended these findings by associating the integrity of these pathways with lateral ventricular volume and with clinical factors related to shunt revisions. We also assessed whether DTI metrics, ventricular volume, and shunt revisions were related to IQ scores in individuals having SBH.…”

“…We also observed that the 2 groups did not differ in FA along the frontal pathways. 39 Although our previous study did not assess the relationship between DTI metrics and ventricular volume, we hypothesized that the decrease in WM integrity was due to mechanical stretching forces during ventricular expansion in hydrocephalus. These forces spared the anterior regions but strongly affected posterior pathways.…”

“…All procedures for MRI acquisition, processing, and analyses have been described in detail by Williams et al 39 Briefly, T1-weighted scans were acquired on a Philips 3.0-T Intera system with the following parameters: slice thickness 1.5 mm; TR/TE 6.5-6.7/3.04-3.14 msec; flip angle 8°; square FOV 24 cm 3 ; acquisition matrix 256 × 256; in-plane pixel dimensions (x, y) 0.94, 0.94; and NEX 2. The DTI images were acquired using a single-shot spinecho diffusion-sensitized echo-planar imaging sequence with the balanced Icosa21-encoding scheme with the following DTI parameters: 44 slices total; square FOV 24 cm 3 ; acquisition matrix 256 × 256; slice thickness 3 mm; TR/TE 6100/84 msec; b value 1000 sec/mm 2 .…”

“…Maps for FA, AD (l 1 ), and RD ([l 2 + l 3 ]/2) were then isolated for further tractography processing and analysis. 9,33,34 Procedures for labeling midbrain seed regions and deriving DTI metrics using probabilistic tractography have been described in detail in Williams et al 39 Briefly, the left and right divisions of the midbrain tectum were manually defined for each participant by a single rater (V.J.W.) blinded to the diagnosis.…”

Covert Orienting in Three Etiologies of Congenital Hydrocephalus: The Effect of Midbrain and Posterior Fossa Dysmorphology

“…We instead 272 A, Treble-Barna et al (54) 19 (51) 2(5) 16 (43) 28 (76) 9(24) 0 (0) 25 (37) 7(10) 36 (53) 40 (59) 8(12) 20 (29) 3(4) 60 (88) 5 (7) 0(0) 3(4) 62 (91) 3 (4) 0 (0) 68 (100) SBM-no tectal beaking 7(41) 10 (59) 3(30) 1(10) 6(60) 9(90) 1(10) 0(0) 4(23) 3 (18) 10 (59) 8 (47) 2(12) 7(41) 4 (24) 13 (77) focused on simple, obvious visual distinctions of present versus absent. The validity of this coding scheme is demonstrated by its sensitivity to differences in connectivity using diffusion tensor imaging (DTI) in a recent study on a different cohort (Williams et al, 2013). MRI abnormalities by etiology group are presented in Table 3.…”