Quantitative Fiber Tracking Analysis of the Optic Radiation Correlated with Visual Performance in Premature Newborns

Imaging

Thirty-six premature infants were scanned with MR imaging. Our institution's review board approved this study, and we obtained parental consent for each neonate. Imaging was performed at 1.5T scanner (GE Medical Systems, Waukesha, Wis) with a custom-made high-sensitivity neonatal head coil integrated into an MR-compatible incubator.¹⁸ The signal-to-noise ratio within the white matter on diffusion-weighted images was approximately 35, and the signal-to-noise ratio within white matter on the echo-planar images without diffusion weighting was approximately 65. At time of MR imaging, the infants ranged in age from 29 to 41 weeks of gestational age (GA) with a mean age of 34.5 weeks of GA. The infants were born at an average of 28.4 weeks of GA (range, 20.3–33.1 weeks’ GA) and were scanned an average of 6.1 weeks after birth (range, 0.7–17 weeks). Neonates did not have severe periventricular white matter abnormalities on conventional T1- and T2-weighted images. With use of the grading system described previously,⁶ 21 neonates had no periventricular white matter abnormalities, 9 neonates had minimal abnormalities, 4 had mild abnormalities, and 2 had moderate abnormalities. Three neonates had mild ventriculomegaly, and the remaining 33 neonates had no ventriculomegaly.

Diffusion tensor images were acquired with a 4.8-minute single-shot echo-planar sequence. Imaging parameters were TR, 7 s; TE, 100 ms; 256 × 128 matrix; 1.4 × 1.4 mm in-plane resolution; 3-mm-thick contiguous sections; 360- to 180-mm FOV; 167-kHz bandwidth; and 3 acquisition averages. Diffusion weighting gradients were applied in 6 noncolinear directions at b = 600 s/mm² in addition to a b = 0 s/mm² volume. A 2D 10th order nonlinear registration algorithm was used to correct for motion.^19,20 Diffusion-weighted volumes were adjusted to correct for motion with the b = 0 s/mm² volume used as a reference.

Before calculation of the diffusion tensor, a set of smoothed diffusion-weighted images was produced by averaging a 3 × 3 voxel in-plane neighborhood. The diffusion tensor and associated diffusion metrics were calculated for each voxel from the smoothed and unsmoothed diffusion-weighted images.²¹ The smoothed diffusion metric maps were used for region-of-interest placement and DTI fiber tracking. To reduce partial volume averaging, we used the unsmoothed diffusion metric maps for tract-specific measurements.

Fiber Tracking and Quantification

We performed DTI fiber tracking and tract-specific quantification using software written with Interactive Data Language (ITT Visual Solutions, Boulder, Colo). The fiber tracking algorithm was based on the deterministic fiber tracking by the continuous assignment method.²² The algorithm operates under the assumption that the primary eigenvector indicates the orientation of axonal bundles and follows the primary eigenvector from voxel to voxel in 3D. Fiber trajectories of the optic radiation are launched from a region of interest drawn on a plane anterior to the trigone of the lateral ventricle (Fig 1A). The starting region of interest spans multiple axial sections and was designed to include the entire white matter within and surrounding the optic radiation. DTI fiber tracks were initiated from 27 equally spaced starting points arranged in a 3 × 3 × 3 grid within each voxel of the starting region. The fiber trajectories followed the primary eigenvector from voxel to voxel and were stopped when turning an unphysical angle of greater than 50° between 2 voxels or exiting the white matter as indicated by fractional anisotropy (FA) less than 0.05. Fiber trajectories passing through a second region of interest drawn in a plane posterior to the lateral ventricle (Fig 1A) were retained as the delineated optic radiation. The second region of interest spans multiple axial sections containing the lateral ventricle and was designed to encompass the entire region of white matter that the optic radiation may pass through anterior to the visual cortex.

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Fig 1.

DTI fiber tracking and segmentation. A, DTI fiber tracks (red) were launched from a starting region of interest (green mesh) in a plane adjacent to the trigone of the lateral ventricle. Fiber tracks were filtered with a second region of interest (blue mesh) in a plane posterior to the lateral ventricle. B, The average fiber track (yellow) was constructed by averaging coordinates from each of the delineated optic radiation fiber tracks (red). C, The average fiber track was divided into 7-mm segments. Each voxel within the delineated optic radiation is assigned to the closest segment. Different segments are shown with various colors. D, Each discrete 7-mm segment is assigned to either the anterior, middle, or posterior anatomic segment of the optic radiation. The background image in each panel is an echo-planar image without diffusion weighting.

To examine the spatial heterogeneity of the optic radiation's microstructure, we segmented the delineated tracts into 3 anatomic regions. It is expected that diffusion metrics vary along the tract because of varying white matter geometry and architecture. The anterior region was defined as the portion of the optic radiation anterior to the lateral ventricle and closest to the thalamus. The middle region was adjacent to the lateral ventricle, and the posterior region was posterior to the ventricle and closest to the primary visual cortex. The steps in segmenting the delineated tract are shown in Fig 1. The first step (Fig 1B) in segmentation was to generate an average streamline or fiber track to characterize the position and curvature of the overall white matter tract. The average fiber track was calculated by averaging the coordinates of each step along each fiber trajectory. The second segmentation step (Fig 1C) was to divide the average fiber track into 7-mm-long segments starting with the lateral geniculate nucleus. Each fiber trajectory was then segmented such that each coordinate along the trajectory was assigned to the closest 7-mm segment. The final step (Fig 1D) involved a user manually assigning each of the 7-mm discrete segments to either the anterior, middle, or posterior anatomic segments.

Measurements of diffusion metrics including FA, eigenvalues (λ₁, λ₂, λ₃), and directionally averaged diffusivity (D_av) within the optic radiation were made on the basis of the voxels containing DTI fiber tracks. Transverse diffusivity, λ_⊥, is the mean of the second and third eigenvalues and indicates diffusivity perpendicular to axonal bundles. Tract-specific measurements were a weighted average with the number of fiber trajectories passing through a voxel comprising the weight for the voxel's DTI metric. Voxels with fewer fiber trajectories were assumed to include other unrelated white matter tracts and contribute less to the measurement. Voxels in the core of the white matter tract with many fiber trajectories contribute to most of the diffusion parameter measurements. Left- and right-sided optic radiation measurements within a patient were averaged. Measurements were taken from the entire optic radiation in addition to the anterior, middle, and posterior segments of the white matter tract.

Visual Function Examination

Each neonate was tested within 24 hours of MR imaging by the same child neurologist to assess visual function. The examiner was blinded to MR imaging results. The visual examination was performed when the neonate was in a maximally awake state with eyes open and limbs moving spontaneously. The neurologist's face was used as a target to test the infant's visual fixation and tracking ability once for a minimum of 2 consecutive minutes. Visual fixation tracking tests the integrity of the visual system, and test scores normally improve with increasing age.²³ The neonate's performance was scored from worst to best on a scale from 1 to 5. A score of 5 indicated stable fixation and complete following, a score of 4 indicated stable fixation and incomplete following, a score of 3 indicated stable fixation and rare following, a score of 2 indicated transient fixation and random eye movement, and a score of 1 indicated no fixation and random eye movements.

Tract-Specific Diffusion Metrics

Diffusion metrics were measured within the anterior, middle, and posterior segments of the optic radiation (Fig 3). FA within each anatomic segment significantly increased with age at an average rate of 6 × 10⁻³ (∼ 3%) per week (P < .0001, Fig 3A). The rate of increase of FA with age was not significantly different among the 3 anatomic segments. FA within the 3 anatomic segments was significantly distinct (P < .0001, Wilcoxon signed-rank with Bonferroni correction), with the anterior segment exhibiting the highest FA and the posterior segment exhibiting the lowest FA.

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Fig 3.

Tract-specific diffusion metrics. Plots show diffusion metrics (FA, D_av, λ₁, and λ_⊥) within the anterior (red), middle (blue), and posterior (green) segments of the optic radiation.

The diffusivity metrics also exhibited correlations with age and anatomic segment. D_av decreased at an average rate of −17 × 10⁻⁶ mm²/s per week (P < .0003). The primary eigenvalue, λ₁, decreased at an average rate of −10 × 10⁻⁶ mm²/s per week (P < .02). Transverse diffusivity, λ_⊥, decreased with age at a rate of −21 × 10⁻⁶ mm²/s per week (P < .0001). The rates of decrease between anatomic segments were not significantly different, and average rates for D_av, λ₁, and λ_⊥ are reported. The anterior segment of the optic radiation had significantly lower D_av, λ₁, and λ_⊥ compared with the middle and posterior segments (P < .005, Wicoxon signed rank with Bonferroni correction). The middle and posterior segments were not significantly differentiated by D_av, λ₁, or λ_⊥ measurements.

Diffusion Metrics and Functional Testing

The correlation between visual fixation performance and whole-tract diffusion metrics was analyzed while controlling for the effects of age with a multivariable regression. Optic radiation FA increased significantly with visual fixation score (P < .006) independent of GA (Fig 4). This relationship is most noticeable in the 2 infants older than 39 weeks of GA who exhibited poor visual fixation scores (3 and 4) and low FA for their age. Although D_av, λ₁, and λ_⊥ trended toward lower values with increased visual fixation score, the relationship did not reach significance.

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Fig 4.

Relationship between visual fixation score, FA, and age. FA within the optic radiation increases with GA. The symbols are colored to indicate each neonate's visual fixation score on a scale from 1 to 5. Neonates with higher visual fixation scores demonstrated better visual fixation and tracking behavior. The visual fixation score correlated significantly with FA, independent of age. This relationship between visual fixation score and FA is evident within the set of neonates older than 39 weeks’ GA. Two neonates older than 39 weeks’ GA with abnormally poor visual examination performance also displayed abnormally low FA.