Diffusion Imaging of Congenital Brain Malformations

Diffusion Imaging of Congenital Brain Malformations

Diffusion Imaging of Congenital Brain Malformations Mike Wahl, MS*,† and Pratik Mukherjee, MD, PhD† Diffusion imaging is a magnetic resonance imaging ...

2MB Sizes 0 Downloads 132 Views

Diffusion Imaging of Congenital Brain Malformations Mike Wahl, MS*,† and Pratik Mukherjee, MD, PhD† Diffusion imaging is a magnetic resonance imaging modality that measures the microscopic molecular motion of water to yield information about brain structure. The technique has been used increasingly in recent years to investigate congenital brain malformations. This article aims to provide a brief overview of diffusion imaging, and to review recent advances in our understanding of congenital brain malformations because of diffusion imaging. The technique has been successfully applied to conditions ranging from rare hindbrain malformations, such as horizontal gaze palsy with progressive scoliosis, to conditions that are undetectable using conventional neuroimaging, such as grapheme-color synesthesia. Though diffusion imaging has already yielded considerable insight into the pathogenesis and clinical features of congenital malformations, recent advances in imaging techniques promise to provide much more extensive knowledge of these conditions in the future. Semin Pediatr Neurol 16:111–119 © 2009 Elsevier Inc. All rights reserved.


ur understanding of congenital brain malformations has been greatly augmented in recent years by the application of diffusion tensor imaging (DTI), a magnetic resonance imaging (MRI) imaging modality that has revolutionized the field of neuroimaging of the white matter. Developed in 1994,1 during the last 15 years the technique has found application in virtually every disorder involving white matter, from schizophrenia to epilepsy to traumatic brain injury. Within the field of pediatric imaging, it has extended our knowledge of congenital malformations significantly beyond what had been attainable through conventional brain imaging. Given the flurry of application of DTI to pediatric brain malformations, now is a useful time to review recent developments. For readers unfamiliar with DTI, we will first briefly review the field of diffusion imaging. We will describe the basic physical concepts behind the technique, discuss common analyses performed with DTI, and introduce more advanced imaging techniques that are now beginning to be used in pediatric neuroimaging. We will then discuss applications of diffusion imaging to several congenital malformations. We begin with rare conditions with well-defined malformations of specific brain regions, including horizontal gaze palsy with progressive scoliosis and pontine tegmental cap dysplasia (PTCD). We then discuss congenital malformations with more diffuse manifes-

From the *Department of Neurology, University of California, San Francisco, CA. †Department of Radiology, University of California, San Francisco, CA. Address reprint requests to Mike Wahl, Department of Neurology, University of California, San Francisco, CA. E-mail: [email protected]

1071-9091/09/$-see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.spen.2009.07.002

tations, including agenesis of the corpus callosum and holoprosencephaly. Finally, we review conditions with subtle anatomic alterations that are not easily seen on conventional imaging, including congenital prosopagnosia and graphemecolor synesthesia. Although the studies discussed are not meant to be an exhaustive review of the published data, they represent the breadth of uses for DTI in pediatric imaging. Finally, we will discuss future directions in the study of congenital malformations with diffusion imaging. More advanced imaging techniques, the combination of DTI with other structural and functional imaging modalities, and the integration of imaging and genetic analysis all promise to provide a detailed picture of the neurobiology of congenital brain malformations.

Diffusion Imaging Large white matter tracts are composed of numerous axons organized in a parallel fashion. As in all tissues, water within these structures diffuses through random molecular motion (Brownian motion), but such motion is partially constrained by densely packed axonal membranes and myelin sheaths. Thus, water will preferentially diffuse along the direction of the axon bundle rather than perpendicular to it. The measurement of this anisotropic diffusion of water forms the basis for diffusion imaging.1,2 Diffusion imaging is performed by acquiring a series of whole-brain MR images in which a magnetic field with a spatial gradient is applied is in a particular direction. The gradient is applied in a combination of pulses such that, if water molecules diffuse along the magnetic gradient, their constituent proton spins become dephased relative to mole111

112 cules that do not diffuse along the gradient. This dephasing causes an attenuation of the magnetic resonance signal as detected by the MRI scanner. The contrast of each image thus represents the degree of diffusion present in a given direction in three-dimensional (3D) space. The information from many images acquired with different spatial gradients is then combined to estimate the 3D profile of water diffusion within each voxel in the brain.3

Diffusion Tensor Imaging DTI approximates this diffusion profile as a 3D Gaussian function, which is visualized as an ellipsoid. This function can be represented mathematically as a symmetric 3 ⫻ 3 matrix, the “Diffusion Tensor.”1,2 From this approximation, two useful pieces of information can be determined. First, the direction of greatest diffusion, or the direction of the major axis of the ellipsoid, estimates the predominant direction of axonal projections within a given voxel. The directional information from neighboring voxels can then be combined to perform DTI fiber tractography, in which 3D white matter pathways are traced through the brain.4-6 Applied to congenital conditions, DTI tractography is a powerful tool to identify the presence of ectopic white matter fibers, or to assess the size and 3D orientation of white matter tracts that may be affected by the condition. Second, the amount of diffusion along the major axis relative to the minor axes, called the fractional anisotropy (FA), provides a quantitative measure of white matter microstructural integrity. Although the precise underlying biological factors that contribute to FA are still unclear, it can be thought of as a composite measure of axonal density, degree of myelination and the directional coherence of axon bundles.7 FA values range from 0 (representing isotropic diffusion) to 1 (representing diffusion entirely in 1 direction). Studies in healthy subjects have shown FA to be a highly reproducible measurement,8 and it has been shown to correlate with cognitive performance in adult9-11 and pediatric populations.12-14 Directional information is commonly combined with FA measurements on FA color maps, in which the color of each voxel represents the predominant diffusion direction, whereas the voxel brightness represents FA value. FA measurements may be also combined with fiber tractography to measure the average FA over an entire white matter tract. This technique provides a useful method for assessing the microstructural integrity of a specific tract. FA measurements thus yield quantitative data that can be used in an effort to correlate radiological information with behavioral and symptomatic metrics. Such quantitative measurements are only beginning to be used to study congenital malformations.

M. Wahl and P. Mukherjee single high-gradient field strength in many independent directions.16-19 These techniques are able to achieve high angular resolution measurements of the diffusion profile, at the cost of spatial resolution. This high angular resolution allows the Gaussian assumption to be relaxed, yielding a modelindependent description of the diffusion profile. Diffusion spectrum imaging and q-ball imaging methods are thus able to reconstruct multiple fiber directions within a single voxel, allowing for the successful reconstruction of axon fiber bundles that cross on a subvoxel scale. This advance is particularly useful when performing tractography in regions of complex white matter architecture, in which fibers merge or cross. Although these methods are not commonly used for pediatric imaging, they are likely to find increasing application in the future.

Applications to Congenital Malformations Horizontal Gaze Palsy With Progressive Scoliosis Horizontal gaze palsy with progressive scoliosis (HGPPS) is a rare autosomal recessive disorder characterized by congenital absence of normal horizontal eye movements and progressive scoliosis through childhood and adolescence, with no other associated neurological or behavioral abnormalities. It has been found to be associated with a number of mutations in the ROBO3 gene, thought to be critical for hindbrain midline axon crossing.19 Conventional neuroimaging findings of HGPPS include hypoplastic cerebellar peduncles and pons, as well as anterior and posterior clefts of the medulla and pons.20 DTI and tractography studies have demonstrated a lack of the normal decussation of superior cerebellar peduncles and an absence of normal pontine crossing fibers21 (Figs 1A and B). In addition, the corticospinal descending tracts do not decussate, and instead are found to project ipislaterally22 (Figs 1C and D). Corpora callosa appear normal (Fig 1D), suggesting that the midline crossing defect is limited to hindbrain structures. In one study, these findings are supported by functional MRI (fMRI) and neurophysiology studies showing only ipsilateral cortical activation from a motor task, contrasting with the contralateral activation seen in control subjects.21 These DTI findings are consistent with the known function of the gene implicated in HGPPS (ROBO3) in hindbrain midline axon crossing. Thus, the imaging findings, coupled with the gene discovery, present a coherent picture of the pathogenesis of HGPPS.

Pontine Tegmental Cap Dysplasia Advanced Diffusion Imaging Methods Newer methods yield more detailed information about the diffusion profile of water in white matter. Diffusion spectrum imaging acquires images over multiple gradient magnetic field strengths,15 whereas q-ball imaging acquires images at a

PTCD is a novel brainstem malformation first described using both conventional MRI and DTI.23,24 On conventional imaging, many findings are evident, including hypoplasia of the ventral pons, a dorsal vault projecting from the tegmentum into the fourth ventricle (Fig 2C), partial absence of the

Diffusion imaging of congenital brain malformations


Figure 1 DTI of horizontal gaze palsy with progressive scoliosis. (A) and (B) show DTI color maps of the middle and superior pons, respectively, and demonstrate the absence of normal decussating pontine fibers (A) and superior cerebellar peduncles (B) in HGPPS compared with control subjects. Red arrows indicate the MCP (A) and SCP (B), whereas yellow arrows indicate normal decussating fibers in control subjects. Bottom panel displays fiber tractography of corticospinal tracts (C,D) and corpus callosum (E) in an HGPPS subject, demonstrating the lack of corticospinal tract decussation despite callosum structure. For all images, color depicts the predominant fiber direction, with blue denoting superior-inferior, green denoting anterior-posterior, and red denoting left-right fiber orientation. Figures reprinted with permission from Sicotte NL, et al21 and Haller S, et al.22 (Color version of this figure is available online.)

middle cerebellar peduncles, shortening of the isthmus of the mesencephalon, and alterations to the shape and size of both superior and inferior cerebellar peduncles. Clinical findings include consistent involvement of cranial nerves, with acoustic nerve involvement in all patients, and variable involvement of facial and trigeminal nerves. Swallowing is impaired in most patients, and cerebellar motor symptoms are commonly found. Many patients with PTCD have significant developmental delay, and callosal hypoplasia has been noted in some patients, suggesting supratentorial involvement in at least some cases.24 The genetic basis for PTCD is still unknown; analysis of axonal guidance genes

NTN1 and DCC in PTCD failed to identify any pathogenic mutations.23 DTI tractography has extended the neuroradiological picture of PTCD by revealing both an absence of normal decussating pontocerebellar fibers and an ectopic transverse fiber tract occupying the region of the dorsal vault seen on conventional imaging23,24 (Figs 2A and B). These DTI findings are highly suggestive of PTCD being either a primary disorder of axonal navigation or disorder of pontine neuronal migration. The location of the ectopic fiber invites specific testable hypotheses to explain its presence (Fig 2D), which in turn indicate specific candidate genes that may be causative

M. Wahl and P. Mukherjee


Figure 2 DTI of pontine tegmental cap dysplasia. (A,B) Comparison of normal (left) and PTCD (right) pontine crossing structures, both on DTI color maps (A) and with DTI tractography (B). Both maps clearly show the absence of normal ventral decussating fibers, and the presence of an ectopic dorsal fiber bundle crossing the midline. Numbers in (A) indicate pontine structures: 1 ⫽ corticospinal tract, 2 ⫽ pontocerebellar fibers, 3 ⫽ medial lemniscus, 4 ⫽ ectopic transverse fiber bundle. (C) Midline sagittal MR image showing characteristic pontine “cap” (black arrow). (D) Possible mechanisms for the formation of the ectopic dorsal fiber bundle, due to either defects in axon guidance or neuronal migration of pontine gray neurons (green), produced in rhombic lip (blue circles) and sending axonal projections to the MCP (pink oval). Top diagram shows normal migration pattern, whereas bottom 3 demonstrate possible growth and guidance defects. Reprinted with permission from Barth PG, et al23 and Jissendi-Tchofo P, et al.24 (Color version of this figure is available online.)

of PTCD.24 Thus, DTI has added valuable information regarding the mechanism behind PTCD, although the exact cause is still unknown.

Agenesis of the Corpus Callosum Agenesis of the corpus callosum (AgCC) is a congenital brain malformation with a frequency of about 1 in 4000 individuals. It is characterized by a partial or complete absence of callosal fibers, and accompanied by a spectrum of neuropsychological deficits, including many deficits falling within the autistic spectrum.25 AgCC is commonly associated with other brain malformations, such as polymicrogyria or cortical and subcortical heterotopias, although cases of AgCC in the absence of other malformations (“isolated” AgCC) are not uncommon.26 Even among individuals with isolated AgCC, there is a wide variation in the severity of the condition, ranging from minor social impairment to significant developmental delay;27 the cause of such variability is still unclear. Several diffusion imaging studies have examined various neuroanatomical aspects of AgCC.

Early efforts focused on the Probst bundles, which are aberrant intrahemispheric white matter tracts thought to arise from misdirected callosal axons. These studies used DTI tractography to establish an anteroposterior direction of the Probst bundles, and revealed that fibers are at least partially topographically organized within the Probst bundle.28-30 However, these studies were limited by scan quality and image resolution, and were unable to provide more detailed information on the origin and destination of axons that compose the Probst bundles. Recent analysis using q-ball tractography, a more advanced technique that can resolve multiple tracts within a single voxel (see Diffusion Imaging section), suggests that many axons within the Probst bundles actually project to subcortical regions (unpublished data). Although these results are still preliminary, they raise the possibility that the fibers comprising the Probst bundle are not simply corticocortical projections rerouted from the corpus callosum, but represent axons that are aberrantly signaled to project to subcortical regions. Other study has focused on the callosal connectivity of

Diffusion imaging of congenital brain malformations individuals with partial AgCC (pAgCC). Although the callosal fragments that are characteristic of pAgCC are visible on conventional imaging, the connectivity of axons crossing through the fragments was unknown before the advent of DTI. Two alternative hypotheses have been proposed regarding the mechanism of development of these callosal fragments. The first is that the fragments are the result of arrested development of a normal callosum: the callosum develops along its normal trajectory until growth is terminated by some developmental insult. Another hypothesis is that the callosal fragments represent a more plastic process, in which axons pass through the fragment in a manner distinct from that seen in normal callosal development. This process would lead to callosal fragments with connectivity patterns not seen in normal callosa. An early study30 examined 5 subjects with pAgCC, and identified consistently anteriorly located callosal fragments

115 with anterior frontal connectivity, supporting the hypothesis of arrested development along a rostrocaudal axis. However, the study also observed an aberrant interhemispheric fiber, termed the “asymmetric sigmoid bundle,” projecting from the right anterior frontal lobe to right occipitoparietal lobes. Because normal corpora callosa are composed entirely of connections between homologous cortical areas (homotopic connections), the connections between nonhomologous areas (heterotopic connections) constitute a novel fiber absent from the normal callosa, suggesting that a more plastic process forms the callosal fragments. A more recent study used q-ball tractography to analyze the callosal connectivity of 6 individuals with pAgCC.31 Connectivity was varied between subjects, including fibers projecting to all major cortical areas. Also, a number of distinct heterotopic interhemispheric connections were found, generalizing the “asymmetric sigmoid bundle” finding to include

Figure 3 Q-ball tractography of partial callosal agenesis subjects. All homotopic and heterotopic segmented tracts are shown on both axial (top) and midline sagittal (bottom) projections. Fibers are colored according to the origin and termination of their projections: homotopic anterior frontal, posterior frontal, and occipitotemporal fibers are colored blue, orange, and green, respectively, whereas heterotopic fibers are colored red, yellow, pink, and purple. Reprinted with permission from Wahl M, et al.31 (Color version of this figure is available online.)

116 heterotopic projections between many different regions (Fig 3). Crucially, the connectivity observed through a given callosal fragment was not observed to correlate with the position of that fragment relative to the location of a normal corpus callosum. Thus, fragments of a similar size and location were found to have drastically different connectivity. This finding strongly suggests that the development of pAgCC is a plastic process, and not the arrested development of a normal callosum. A quantitative DTI study of AgCC has also been performed.32 The authors hypothesized that alterations to the cingulum bundle in AgCC might account for the different symptoms seen in individuals with AgCC compared with “split-brain” patients, specifically observed deficits in executive function and emotional control. DTI tractography was performed on the ventral cingulum bundle (VCB) of 12 subjects with AgCC, along with 12 matched controls. The fractional anisotropy of the entire tract was computed for each subject, and a group comparison was performed between experimental and control cohorts. To complement the DTI measurements, the volume of the VCB was also measured using T1-weighted structural MRI images. The authors found reduced FA specific to the right VCB, along with bilateral reductions in the tract volume. These results may provide an anatomical explanation for some symptoms seen in AgCC that cannot be explained by the lack of a corpus callosum. Thus, absence of callosal fibers in AgCC may simply be the most obvious manifestation of a more widespread white matter disorder.

Holoprosencephaly Holoprosencephaly is a congenital neurodevelopmental disorder characterized by defective forebrain development, specifically the partial or complete failure of the forebrain to divide into left and right hemispheric structures.33 The severity of the disorder depends primarily on the degree of hemispheric division, with lobar, semilobar, and alobar representing increasingly severe phenotypes. Clinical characteristics vary widely, but include facial dysmorphism, mental retardation, athetoid movements, epilepsy, and endocrine disorders.34 Although considerable effort has been put into characterizing holoprosencephaly based on markers evident on conventional imaging (eg, gyral and sulcal patterns34), the use of DTI to probe white matter structure has recently gained appreciation as a potentially beneficial area of investigation. One study performed DTI on 13 patients with holoprosencephaly, and focused specifically on characterizing white matter tracts in the brainstem.35 In the 2 patients with alobar holoprosencephaly (the most severe form), corticospinal tracts were found to be absent bilaterally, whereas patients with semilobar type demonstrated intact corticospinal tracts. In addition, the size of both corticospinal tracts and middle cerebellar peduncles was estimated based on DTI color images. The sizes of both tracts were found to be strongly anticorrelated with the degree of forebrain malformation, and correlated with patients’ score on a neurodevelopmental as-

M. Wahl and P. Mukherjee sessment. These findings helped to establish that mesencephalic structures are commonly involved in holoprosencephaly. More significantly, these results provide an imaging-based biomarker of anatomic and developmental severity that has the potential to be a useful prognostic tool. An additional case report examined using DTI tractography the cortical and subcortical connectivity of a patient with semilobar holoprosencephaly.36 Several altered white matter structures were noted, including fused fronto-occipital fasciculi, dysplastic fornices, and a posterior commissural white matter bundle in the expected location of the splenium. It is unclear if these structures are commonly present in holoprosencephaly, and more extensive investigation of the condition could yield a more complete picture about the white matter neuroanatomy associated with holoprosencephaly.

Malformations Not Evident With Conventional Imaging Finally, we consider two examples of disorders in which conventional imaging fails to reveal anatomic abnormalities on an individual basis, although some evidence of subtle alterations may be evident when subjects are grouped and compared with healthy controls. In such cases, DTI has the potential to greatly improve our understanding of the condition by identifying its underlying structural basis in the absence of gross anatomical evidence of malformation. Congenital prosopagnosia is characterized by a selective inability to recognize faces, with normal vision and intelligence.37 Conventional structural imaging revealed a volume reduction in the anterior fusiform gyrus associated with the condition,38 but functional imaging studies failed to demonstrate significantly altered cortical activity in relevant face recognition areas.39 These results suggest that prosopagnosia may be a result of a structural connectivity deficit. To test this hypothesis, DTI tractography was performed on 6 subjects with congenital prosopagnosia, and the 2 major tracts passing through the fusiform region, the inferior longitudinal fasciculus (ILF) and inferior fronto-occipital fasciculus (IFO) were reconstructed37 (Figs 4A-D). The average FA of the tracts were then compared with those of matched healthy controls, and found to be significantly reduced bilaterally in both ILF and IFO. In addition, an assumption-free whole-brain analysis was performed, in which the FA of prosopagnosia subjects was compared with that of controls on a voxel-by-voxel basis. This analysis revealed FA reduction in regions along the trajectory of the ILF and IFO in the regions of the anterior fusiform gyrus, supporting the findings of the tract-based FA measurements (Fig 4E). These results strongly suggest that the structural basis for prosopagnosia resides in disruption in the organization of specific white matter tracts. Finally, we consider the condition of grapheme-color synesthesia, in which letters evoke the perception of specific colors, that is, seeing the letter “D” produces the sensation of “red.” Although not strictly considered a brain malformation, because the condition does not interfere with normal brain

Diffusion imaging of congenital brain malformations


Figure 4 DTI tractography of congenital prosopagnosia. (A-D) Fiber tractography of ILF (A,C) and IFO (B,D) for prosopagnosia subjects (red) and controls (blue). FA measurements of both tracts were found to be significantly lower in prosopagnosia subjects, despite the normal appearance of the tractography results. (E) Whole-brain voxelwise comparison of FA measurements reveals reduced microstructural organization in white matter adjacent to the fusiform gyrus bilaterally in prosopagnosia subjects compared with controls (brightness indicates significance of group differences in FA at each voxel). Reprinted with permission from Thomas C, et al.37 (Color version of figure is available online.)

function and may be viewed as a positive attribute, it has been extensively studied with conventional imaging, fMRI, and DTI, and offers insight into normal and altered brain connectivity. A recent study of grapheme-color synesthesia employed both DTI and fMRI modalities.40 The DTI analysis used a method for comparing FA measurements between cohorts in an assumption-free manner, called tract-based spatial statistics.41 Briefly, the method works by constructing a skeleton of the white matter core for each subject and projecting FA measurements onto that skeleton. Each skeleton is then

transformed to a common template, and voxelwise comparisons are then made between experimental and control cohorts. Using this technique, the authors found a region of higher FA adjacent to the right inferior temporal cortex, as well as regions in left parietal and bilateral frontal cortex (Fig 5). Interestingly, the fMRI analysis of cortical activity during synesthetic experience showed a large region in the right inferior temporal cortex, adjacent to the white matter with higher FA that was significantly more active in synesthetes than in controls.

Figure 5 DTI and fMRI of grapheme-color synesthesia. A skeleton of the white matter structure was created for subjects with grapheme-color synesthesia and matched control subjects (green). Regions in which the FA values were significantly higher in synesthetes are indicated in yellow, and include white matter adjacent to the right inferior temporal cortex. fMRI revealed increased cortical activation during synesthetic experience localized to an adjacent area in the inferior temporal cortex (blue, shown on axial slice). Reprinted with permission from Rouw R, et al.40 (Color version of figure is available online.)

M. Wahl and P. Mukherjee

118 These findings are further supported by an observed association between the particular type of synesthesia and FA measurements. Grapheme-color synesthetes can be classified as “projectors,” who see synesthetic color in the external world, or “associators,” who are limited to an internal perception of synesthetic color. FA measurements in the right temporal lobe were significantly correlated with the degree of self-reported projection or association, with subjects with higher FA being more likely to be associators (r2 ⫽ 0.548, P ⫽ 0.009). Taken together, these results are highly suggestive of the fact that increased connectivity in right temporal cortex forms the anatomic basis for grapheme-color synesthetic experience.

Discussion DTI Applications Can Be Classified DTI has found numerous applications in the study of congenital brain malformations, from gross structural dysmorphisms to conditions that appear virtually normal on conventional imaging. On the basis of studies presented in this review, we can group the uses of DTI into 4 distinct categories. First, gross white matter alterations can be classified by visual inspection of DTI color maps. This process is similar to qualitative analysis of conventional scans, and simply uses the additional information provided by directional and FA information. Examples include the observation of the absence of decussating hindbrain axonal fibers in HGPPS, and the observation of corticospinal tract absence in alobar holoprosencephaly. This visual inspection can be seen as a firstorder analysis to identify gross white matter alterations in congenital malformations, and as a potentially useful diagnostic tool. Second, DTI tractography can be performed to characterize aberrant white matter structures, or to establish the absence of specific white matter tracts. Examples include the tracking of the ectopic dorsal pontine fiber tract in PTCD, and the identification of aberrant heterotopic callosal projections in partial AgCC. Findings based on DTI tractography can be useful in elucidating possible mechanisms underlying white matter dysgenesis. Third, case-control studies can be performed in which FA or white matter volume measurements are performed and compared between experimental and control cohorts. Examples include FA analysis of the cingulum bundle in AgCC, and tract-based FA measurements of ILF and IFO in prosopagnosia. Because FA measurements based on tractography have been demonstrated to be highly reproducible across subjects, these studies are an effective way of exploring the organization of a specific white matter tract based on an a priori hypothesis. Furthermore, these quantitative measurements can be correlated with behavioral metrics to establish a link between specific structural deficits and behavioral characteristics. As our clinical and anatomical understanding of congenital malformations progress in tandem, these correla-

tions between structure and behavior are likely to become more prevalent. Finally, whole-brain assumption-free analyses of white matter microstructure can be performed using voxelwise comparisons of DTI measurements. Examples include the voxel-by-voxel FA comparison performed in prosopagnosia, and the tract-based spatial statistics method used in synesthesia. These methods are perhaps the most powerful probe of white matter organization, and have the ability to identify alterations in unanticipated regions. However, such methods require that subjects’ scans are registered to a standard brain atlas before voxelwise comparisons can be performed. If brain alterations are subtle or absent on conventional imaging such registration is possible. However, malformations with more pervasive anatomic alterations, such as AgCC or holoprosencephaly, are difficult to accurately register to a control brain template. Until progress is made in creating brain atlases specific to these conditions, DTI analyses are limited to hypothesis-driven investigations of specific white matter tracts or regions.

Future Directions A number of advances in imaging acquisition and analysis are likely to drive further developments in this field in the future. Diffusion imaging at high magnetic field strengths42 yields high spatial resolution and angular resolution diffusion measurements that are capable of tracking complex white matter architecture in great detail. The increasing integration of DTI with functional imaging modalities (magnetoencephalography or fMRI) yields valuable information about the relationship between brain structure and function in normal and pathologic states. Finally, work to establish direct links between features found on neuroimaging and genotypes associated with a particular disorder promises to yield considerable insight into the genetic and molecular mechanisms of congenital brain malformations.43 As much as diffusion imaging has aided research in the past few years, the most beneficial era of imaging congenital brain malformations may be yet to come.

References 1. Basser PJ, Mattiello J, Le Bihan D: Estimation of the effective selfdiffusion-tensor from the NMR spin echo. J Magn Reson B 103:247254, 1994 2. Pierpaoli C, Jezzard P, Basser PJ, et al: Diffusion tensor MR imaging of the human brain. Radiology 201:637-648, 1996 3. Mori S, Zhang J: Principles of diffusion tensor imaging and its applications to basic neuroscience research. Neuron 51:527-539, 2006 4. Conturo TE, Lori NF, Cull TS, et al: Tracking neuronal fiber pathways in the living human brain. Proc Natl Acad Sci U S A 96:10422-10427, 1999 5. Mori S, Kaufmann WE, Pearlson GD, et al: Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Ann Neurol 45:265-269, 1999 6. Wakana S, Jiang H, Nagae-Poetscher LM, et al: Fiber tract-based atlas of human white matter anatomy. Radiology 230:77-87, 2004 7. Beaulieu C: The basis of anisotropic water diffusion in the nervous system—A technical review. NMR Biomed 15:435-455, 2002 8. Wakana S, Caprihan A, Panzenboeck MM, et al: Reproducibility of quantitative tractography methods applied to cerebral white matter. Neuroimage 36:630-644, 2007

Diffusion imaging of congenital brain malformations 9. Charlton RA, Barrick TR, McIntyre DJ: White matter damage on diffusion tensor imaging correlates with age-related cognitive decline. Neurology 66:217-222, 2006 10. Niogi SN, Mukherjee P, Ghajar J, et al: Extent of microstructural white matter integrity in postconcussive syndrome correlates with impaired cognitive reaction time: A 3T diffusion tensor imaging study of mild traumatic brain injury. AJNR Am J Neuroradiol 29:967-973, 2008 11. Salo R, Nordahl TE, Buonocore MH, et al: Cognitive control and white matter callosal microstructure in methamphetamine-dependent subjects: A diffusion tensor imaging study. Biol Psychiatry 65:122-128, 2009 12. Schmithorst VJ, Wilke M, Dardzniski BJ, et al: Cognitive functions correlated with white matter architecture in a normal pediatric population: A diffusion tensor MRI study. Hum Brain Mapp 26:139-147, 2005 13. Skranes J, Vangberg TR, Kulseng S: Clinical findings and white matter abnormalities seen on diffusion tensor imaging in adolescents with very low birth weight. Brain 130:654-666, 2007 14. Wozniak JR, Krach L, Mueller BA, et al: Neurocognitive and neuroimaging correlates of pediatric traumatic brain injury: A diffusion tensor imaging (DTI) study. Arch Clin Neuropsychol 22:555-568, 2007 15. Weeden VJ, Hagmann P, Tseng WY, et al: Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging. Magn Reson Med 54:1377-1386, 2005 16. Tuch DS, Reese TG, Wiegell MR, et al: Diffusion MRI of complex neural architecture. Neuron 40:885-895, 2003 17. Tuch DS: Q-ball imaging. Magn Reson Med 52:1358-1372, 2004 18. Hess CP, Mukherjee P: Visualizing white matter pathways in the living human brain: Diffusion tensor imaging and beyond. Neuroimaging Clin N Am 17:407-426, 2007 19. Jen JC, Chan WM, Bosley TM, et al: Mutations in a human ROBO gene disrupt hindbrain axon pathway crossing and morphogenesis. Science 304:1509-1513, 2004 20. Rossi A, Catala M, Biancheri R, et al: MR imaging of brain-stem hypoplasia in horizontal gaze palsy with progressive scoliosis. AJNR Am J Neuroradiol 25:1046-1048, 2004 21. Sicotte NL, Salamon G, Shattuck DW, et al: Diffusion tensor MRI shows abnormal brainstem crossing fibers associated with ROBO3 mutations. Neurology 67:519-521, 2006 22. Haller S, Wetzel SG, Lutschg J: Functional MRI, DTI and neurophysiology in horizontal gaze palsy with progressive scoliosis. Neuroradiology 50:453-459, 2008 23. Barth PG, Majoie CB, Caan MW, et al: Pontine tegmental cap dysplasia: A novel brain malformation with a defect in axonal guidance. Brain 130:2258-2266, 2007 24. Jissendi-Tchofo P, Doherty D, McGillivray G, et al: Pontine tegmental cap dysplasia: MR imaging and diffusion tensor imaging features of impaired axonal navigation. AJNR Am J Neuroradiol 30:113-119, 2009 25. Badaruddin DH, Andrews GL, Bolte S, et al: Social and behavioral problems of children with agenesis of the corpus callosum. Child Psychiatry Hum Dev 38:287-302, 2007 26. Hetts SW, Sherr EH, Chao SD, et al: Anomalies of the corpus callosum:








33. 34.


36. 37.



40. 41.



An MR analysis of the phenotypic spectrum of associated malformations. AJR Am J Roentgenol 187:1343-1348, 2006 Paul LK, Brown WS, Adolphs R, et al: Agenesis of the corpus callosum: Genetic, developmental and functional aspects of connectivity. Nat Rev Neurosci 8:287-299, 2007 Lee SK, Mori S, Kim DJ, et al: Diffusion tensor MR imaging visualizes the altered hemispheric fiber connection in callosal dysgenesis. AJNR Am J Neuroradiol 25:25-28, 2004 Utsunomiya H, Yamashita S, Takano K, et al: Arrangement of fiber tracts forming Probst bundle in complete callosal agenesis: Report of two cases with an evaluation by diffusion tensor tractography. Acta Radiol 47:1063-1066, 2006 Tovar-Moll F, Moll J, de Oliveira-Souza R, et al: Neuroplasticity in human callosal dysgenesis: A diffusion tensor imaging study. Cereb Cortex 17:531-541, 2007 Wahl M, Strominger Z, Jeremy RJ, et al: Variability of homotopic and heterotopic callosal connectivity in partial agenesis of the corpus callosum: A 3T diffusion tensor imaging and Q-ball tractography study. AJNR Am J Neuroradiol 30:292-289, 2009 Nakata Y, Barkovich AJ, Wahl M, et al: Diffusion abnormalities and reduced volume of the ventral cingulum bundle in agenesis of the corpus callosum: A 3T imaging study. AJNR Am J Neuroradiol 30: 1142-1148, 2009 Simon EM, Barkovich AJ: Holoprosencephaly: New concepts. Magn Reson Imaging Clin N Am 9:149-164, 2001 Barkovich AJ, Simon EM, Clegg NJ, et al: Analysis of the cerebral cortex in holoprosencephaly with attention to the Sylvian fissures. AJNR Am J Neuroradiol 23:143-150, 2002 Albayram S, Melhem ER, Mori S, et al: Holoprosencephaly in children: Diffusion tensor MR imaging of white matter tracts of the brainsteminitial experience. Radiology 223:645-651, 2002 Rollins N: Semilobar holoprosencephaly seen with diffusion tensor imaging and fiber tracking. AJNR Am J Neuroradiol 26:2148-2152, 2005 Thomas C, Galia A, Humphreys K, et al: Reduced structural connectivity in ventral visual cortex in congenital prosopagnosia. Nat Neurosci 12:29-31, 2009 Berhmann M, Avidan G, Gao F, et al: Structural imaging reveals anatomical variations in inferotemporal cortex in congenital prosopagnosia. Cereb Cortex 17:2354-2363, 2007 Avidan G, Hasson U, Malach R, et al: Detailed exploration of facerelated processing in congenital prosopagnosia: 2. Functional neuroimaging findings. J Cogn Neurosci 17:1150-1167, 2005 Rouw R, Scholte SH: Increased structural connectivity in graphemecolor synesthesia. Nat Neurosci 10:792-797, 2007 Smith SM, Jenkinson M, Johansen-Berg H, et al: Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31:1487-1505, 2006 Mukherjee P, Hess CP, Xu D, et al: Development and initial evaluation of 7-T q-ball imaging of the human brain. Magn Reson Imaging 26:171180, 2008 Kempf L, Nicodemus KK, Kolachana B, et al: Functional polymorphisms in PRODH are associated with risk and protection for schizophrenia and fronto-striatal structure and function. PLoS Genet 4:e1000252, 2008