Loss of White Matter Microstructural Integrity Is Associated with Adverse Neurological Outcome in Tuberous Sclerosis Complex

Rationale and Objectives

Tuberous sclerosis complex (TSC) is a genetic neurocutaneous syndrome in which cognitive and social-behavioral outcomes for patients vary widely in an unpredictable manner. The cause of adverse neurologic outcome remains unclear. The aim of this study was to investigate the hypothesis that disordered white matter and abnormal neural connectivity are associated with adverse neurologic outcomes.

Materials and Methods

Structural and diffusion magnetic resonance imaging was carried out in 40 subjects with TSC (age range, 0.5–25 years; mean age, 7.2 years; median age, 5 years), 12 of whom had autism spectrum disorders (ASD), and in 29 age-matched controls. Tractography of the corpus callosum was used to define a three-dimensional volume of interest. Regional averages of four diffusion scalar parameters of the callosal projections were calculated for each subject. These were the average fractional anisotropy (AFA) and the average mean, radial, and axial diffusivity.

Results

Subjects with TSC had significantly lower AFA and higher average mean, radial, and axial diffusivity values compared to controls. Subjects with TSC and ASD had significantly lower AFA values compared to those without ASD and compared to controls. Subjects with TSC without ASD had similar AFA values compared to controls.

Conclusion

Diffusion tensor scalar parameters provided measures of properties of the three-dimensional callosal projections. In TSC, changes in these parameters may reflect microstructural changes in myelination, axonal integrity, or extracellular environment. Alterations in white matter microstructural properties were associated with TSC, and larger changes were associated with TSC and ASD, thus establishing a relationship between altered white matter microstructural integrity and brain function.

Tuberous sclerosis complex (TSC) is a genetic neurocutaneous syndrome with an estimated incidence of one in 6000 to 10,000. Although some patients with TSC may never show neurologic symptoms affecting their quality of life, epilepsy occurs in 80% to 90% of all patients, close to 45% of patients have mild to profound intellectual disabilities, and autism spectrum disorders (ASD) occur in up to 50% of patients .

The cause of neurologic deficits in patients with TSC is a key unresolved question, and neurologic outcomes remains highly variable and unpredictable. It has been hypothesized that tubers disrupt local cerebral architecture, resulting in impaired brain function. However, no robust conventional magnetic resonance imaging (MRI) measure of tubers correlates consistently with the clinical phenotype or long-term neurologic outcomes , and neither a high tuber load nor tubers in specific locations are necessary or sufficient to predict seizures, cognitive impairment, or autism .

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Materials and methods

Subjects

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Data Acquisition and Analysis

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pk+1=pk+vks p

The new point p k +1 is tested to ensure that it is inside the image boundary and inside the region to be considered for tractography. A mask can be used to ensure that tractography does not step through regions with no white matter. Streamline generation is terminated if points are not validated. Streamline termination criteria related to the FA and angle changes are then checked.

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Fk+1=αFk+(1−α)FA(DK+1) F

(

−

)

(

)

where FA( D k +1 ) is the FA of the tensor D k +1 . The primary eigenvector of the tensor is computed, providing e k +1 . The angle criterion is assessed by accumulating the cosine of trajectory angle changes, :

k+1=βk+(1−β)(∑3j=1ek+1jvjk) k

(

−

)

(

∑

)

The new direction of the streamline is calculated using a combination of the primary eigenvector and tensor deflection, while accounting for the previous direction of the streamline:

vk+1∝γvk+(1−γ)[δ(Dk+1)ϵvk+(1−δ)ek+1] v

∝

(

−

)

[

(

)

(

−

)

]

Propagation of each streamline was terminated if the trajectory FA fell below 0.15 or if the tract trajectory angle exceeded 30°. The trajectories were obtained using the step size parameter s = 0.33 mm, α = 0.5, β = 0.5, γ = 0.5, δ = 0.5, and tensor deflection power ϵ = 2.

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m=∑idipi∑idi,v=∑idi(pi−m)2∑id2i m

∑

(

−

)

∑

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$Figure 1, (a) T1-weighted image, superimposed color-coded representation of tensors, intensity proportional to the fractional anisotropy. Red for left-right, blue for superior-inferior, green for anterior-posterior. A manually drawn two-dimensional region of interest delineates the corpus callosum (CC). (b) Visualization of the color-coded tractography of the CC. (c) Streamline density–weighted image of the CC. Red ( high ) and blue ( low ) colors represent streamline density at each voxel. (d) Out of the midsagittal plane, the streamline density–weighted map follows the trajectories to the cortex.$

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AFA=∑idiFAi∑idivar(AFA)=∑idi(FAi−AFA)2∑id2i, AFA

∑

var

(

AFA

)

∑

(

−

AFA

)

∑

where i is the index of each voxel, d i is the streamline density at voxel i , and FA i is the FA.

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Statistical Analysis

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Results

Patients

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Diffusion Tensor Properties of Projections of the Corpus Callosum

Patients with TSC and controls

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Table 1

P Values Using the Linear Regression Model with the DTI Measure as the Response and Group (Control, TSC, TSC without ASD, TSC with ASD) and Log (Age) as the Predictors

DTI Measure Control vs TSC (All Cases) Control vs TSC without ASD Control vs TSC with ASD TSC without ASD vs TSC with ASD AMD .000652 .022068 .000807 .128267 (NS) ARD .00200 .062096 (NS) .000764 .060672 (NS) AAD .000876 .011224 .005148 .467143 (NS) AFA .0350 .8947 (NS) .0266 .0421

AAD, average axial diffusivity; AFA, average fractional anisotropy; AMD, average mean diffusivity; ARD, average radial diffusivity; ASD, autism spectrum disorder; DTI, diffusion tensor imaging; TSC, tuberous sclerosis complex.

All four DTI measures differed significantly between controls and patients with TSC.

AFA was significantly lower in the subjects with TSC with ASD compared to those without ASD, but no difference was found between patients with TSC without ASD and controls.

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Patients with TSC with and without ASD and controls

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$Figure 2, Graphical displays of the fit linear regression model for (a) average mean diffusivity (AMD), (b) average radial diffusivity (ARD), and (c) average axial diffusivity (AAD). Controls (dotted line) have lower AMD, ARD, and AAD than patients with tuberous sclerosis complex (TSC) with autism spectrum disorders (ASD; solid line ), but this difference reaches significance only for AMD and AAD when controls are compared to patients with TSC without ASD (dashed line) . For average fractional anisotropy (AFA) (d) , controls and patients with TSC without ASD have highly similar values. AFA of the patients with TSC with ASD are significantly lower than controls and patients with TSC without ASD.$

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Callosal volume

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Discussion

Relation between White Matter Microstructure and the Development of Brain Function

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$Figure 3, Illustration of projections of the corpus callosum and average fractional anisotropy (AFA) values: (a) a 5.3-year-old healthy control, AFA = 0.53; (b) a 4.7-year-old patient with tuberous sclerosis complex (TSC) but no autism spectrum disorder (ASD), AFA = 0.54; and (c) a 4.9-year-old patient with TSC and ASD, AFA = 0.34.$

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Table 2

Summary of Published DTI Studies Involving NAWM in TSC

Study n Age (y) ∗ MRI Directions Key Findings † Garaci et al (2004) 18 20 (12–30) 1.5 T 6 MD of perilesional NAWM higher than contralateral NAWM. NAWM of frontal, occipital, and parietal regions and CSO higher MD. Peng et al (2004) 7 0.5–15 1.5 T 6 Lower FA of WM lesions associated with tubers vs contralateral NAWM. Higher MD of CR and SS. Increased λ3 of ILF and SS. Karadag et al 2005 7 2–20 1.5 T 6 Higher MD of tubers vs cortex of controls. Increased MD and lower FA in WM lesions and perilesional WM. No difference in MD and FA of NAWM. Firat et al (2006) 6 9 (3–15) 1.5 T 6 MD of tubers higher than NAWM. MD of NAWM not different from controls. Makki et al (2007) 6 10 (6–15) 1.5 T 6 Higher MD, lower FA in combined NAWM of genu/splenium CC, IC/EC. Greatest increase was in λ2,3 (ie, RD). Arulrajah et al (2009) 23 12 (1–25) 1.5 T 3–18 Increased MD of frontal and pontine NAWM (in subgroup aged 8–12 y), right parietal and occipital NAWM (in subgroup aged > 12 y). Krishnan et al (2010) 10 1.5–25 3 T 35 Lower FA in splenium CC and GCT, lower AD in IC, STG and GCT, increased MD and RD in splenium CC. Simao et al (2010) 12 9 (5–16) 3 T 15 Increased MD, decreased FA, increased RD in genu and splenium CC. Increased MD in IC. DTI measures of genu and splenium CC correlate with tuber volume (not number). This study 40 7 (0.5–25) 3 T 35 Lower FA, higher MD, RD, AD of entire CC in TSC (all) and TSC (with ASD). Lower FA of CC in TSC with ASD vs TSC without ASD. No difference in FA of CC in TSC without ASD.

AD, axial diffusivity; ASD, autism spectrum disorder; CC, corpus callosum; CR, corona radiata; CSO, centrum semiovale; DTI, diffusion tensor imaging; EC, external capsule; FA, fractional anisotropy; GCT, geniculocalcarine tract; IC, internal capsule; ILF, inferior longitudinal fasciculus; MD, mean diffusivity; MRI, magnetic resonance imaging; NAWM, normal-appearing white matter; RD, radial diffusivity; SS, sagittal striatum; STG, superior temporal gyrus; TSC, tuberous sclerosis complex; WM, white matter.

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Streamline Density-Weighted Statistics

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Conclusions

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Acknowledgments

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Loss of White Matter Microstructural Integrity Is Associated with Adverse Neurological Outcome in Tuberous Sclerosis Complex

Rationale and Objectives

Materials and Methods

Results

Conclusion

Materials and methods

Subjects

Data Acquisition and Analysis

Statistical Analysis

Results

Patients

Diffusion Tensor Properties of Projections of the Corpus Callosum

Patients with TSC and controls

Patients with TSC with and without ASD and controls

Callosal volume

Discussion

Relation between White Matter Microstructure and the Development of Brain Function

Streamline Density-Weighted Statistics

Conclusions

Acknowledgments

References

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