Tensor-valued diffusion MRI differentiates cortex and white matter in malformations of cortical development associated with epilepsy

Objective: Delineation of malformations of cortical development (MCD) is central in presurgical evaluation of drug-resistant epilepsy. Delineation using magnetic resonance imaging (MRI) can be ambiguous, however, because the conventional T1- and T2-weighted contrasts depend strongly on myelin for differentiation of cortical tissue and white matter. Variations in myelin content within both cortex and white matter may cause MCD findings on MRI to change size, become undetectable, or disagree with histopathology. The novel tensor-valued diffusion MRI (dMRI) technique maps microscopic diffusion anisotropy, which is sensitive to axons rather than myelin. This work investigated whether tensor-valued dMRI may improve differentiation of cortex and white matter in the delineation of MCD. Methods: Tensor-valued dMRI was performed on a 7 T MRI scanner in 13 MCD patients (age = 32 ± 13 years) featuring periventricular heterotopia, subcortical heterotopia, focal cortical dysplasia, and polymicrogyria. Data analysis yielded maps of microscopic anisotropy that were compared with T1-weighted and T2-fluid-attenuated inversion recovery images and with the fractional anisotropy from diffusion tensor imaging. Results: Maps of microscopic anisotropy revealed large white matter-like regions within MCD that were uniformly cortex-like in the conventional MRI contrasts. These regions were seen particularly in the deep white matter parts of subcortical heterotopias and near the gray-white boundaries of focal cortical dysplasias and polymicrogyrias. Significance: By being sensitive to axons rather than myelin, mapping of microscopic anisotropy may yield a more robust differentiation of cortex and white matter and improve MCD delineation in presurgical evaluation of epilepsy.


| INTRODUCTION
Malformations of cortical development (MCD) are important causes of drug-resistant epilepsy, a condition that affects millions worldwide and is associated with significant morbidity and mortality. 1 MCD comprise a diverse group of gray matter lesions related to developmental disruption of neuronal proliferation, migration, and organization. Disrupted neuronal migration from the ventricular and subventricular zones to the cortical plate results in misplacement of cortical tissue close to the ventricles (periventricular heterotopia [PH]) or within white matter (subcortical heterotopia [SH]). Disrupted neuronal organization within the cerebral cortex manifests as abnormal cortical layering, for example, on the local level in focal cortical dysplasia (FCD) or across whole gyri in polymicrogyria (PMG). 2 MCD may have intrinsic epileptogenic activity and produce medically refractory seizures that are most effectively treated through surgical resection.
Delineation of cortical abnormalities with magnetic resonance imaging (MRI) is central in presurgical evaluation of epilepsy and to the odds of achieving seizure freedom. 3,4 However, the delineation of MCD can be ambiguous with conventional MRI, because the T 1 -and T 2weighted contrasts depend on myelin for differentiation of cortex and white matter. In the normal adult brain, a low myelin content makes cortex hypointense to white matter on T 1weighted images and hyperintense to white matter on T 2 -weighted images. 5 The myelin content changes during maturation, [5][6][7] however, and may be altered in pathologies such as MCD. 8,9 Consequently, variations in myelin content within both cortex and adjacent white matter may cause MCD findings on T 1 -and T 2 -weighted images to change size, become undetectable or indicate "pseudothickening" of the cerebral cortex in disagreement with histopathology. 6,8,10 On T 2 -weighted images, differentiation of cortex and white matter is additionally complicated by iron content, which is typically higher in gray matter and may counteract the myelin-based contrast in some cortical regions. [11][12][13] Thus, a more robust delineation of MCD in presurgical evaluation of epilepsy requires an imaging contrast that can differentiate cortex and white matter based on a feature other than myelin.
Diffusion MRI (dMRI) probes tissue microstructure by the diffusive motion of water molecules. The technique is sensitive to the anisotropic diffusion induced by elongated structures such as axons. 14 The diffusion anisotropy from axons is not strongly dependent on myelin, 15,16 wherefore using dMRI to differentiate cortex and white matter based on axonal content may be a more robust alternative to T 1 -and T 2 -weighted contrasts. Diffusion anisotropy has historically been quantified by the fractional anisotropy (FA) from diffusion tensor imaging. However, differentiation of cortex and white matter based on the FA is ambiguous, because the FA reflects diffusion anisotropy on the macroscopic voxel level. Thus, a low FA does not necessarily reflect a low axonal content but could also reflect a lower orientation coherence of axons. 17 The novel "tensor-valued" dMRI technique overcomes this limitation by performing diffusion encoding in multiple directions simultaneously. [18][19][20][21][22][23] Acquiring data with different shapes of the "b-tensor" yields independent information that isolates the influence of the microscopic diffusion anisotropy. Previous studies have suggested that microscopic anisotropy can be estimated from data acquired with conventional encodings only. 24 However, results from data acquired with multiple shapes of the b-tensor have shown such measures to be highly inaccurate. [25][26][27][28] Fortunately, tensor-valued dMRI is both fast and available on common clinical platforms (https://github.com/filip-szczepankiewicz/fwf_seq_resources). 29,30 By providing an axon-sensitive measure through the microscopic anisotropy, tensor-valued dMRI may be a promising tool for differentiation of cortex and white matter in conditions affecting myelin such as MCD.
This study examined 13 patients with MCD on a 7 T MRI scanner using tensor-valued dMRI as well as T 1 -weighted and T 2 -fluid-attenuated inversion recovery (FLAIR) sequences. We hypothesize that mapping microscopic anisotropy with tensor-valued dMRI may improve MCD delineation by enabling differentiation of cortex and white matter based on a voxel's axonal content rather than its myelin content.
The resulting patient population consisted of 13 subjects, eight females and five males, with a mean ± standard deviation age of 32 ± 13 years at the date of examination. See Table S1 for an overview of patient characteristics.
The study was approved by the Swedish Ethical Review Authority, and all subjects gave written informed consent according to recommendations of the Declaration of Helsinki.

| MRI acquisition
Whole-brain MRI data were acquired on an actively shielded 7 T Achieva (Philips) equipped with a dual-channel transmit and 32-channel receive head coil (Nova Medical). For increased field homogeneity, dielectric pads were used during image acquisition. dMRI data were acquired using a prototype diffusion-weighted spin-echo sequence 29 for b-values up to 2.0 ms/μm 2 using both linear and spherical shapes of the b-tensor. 20 The spatial resolution was 2 × 2 × 4 mm 3 . See Table S2 for a detailed description of the diffusion sequence. T 1weighted images were acquired using a three-dimensional (3D) turbo-field echo sequence with repetition time = 8 milliseconds, echo time = 2.8 milliseconds, flip angle = 7°, and 0.6mm isotropic voxel dimensions. T 2 -FLAIR images were acquired using a 3D spin-echo sequence 31 with repetition time = 6000 milliseconds, echo time = 390 milliseconds, flip angle = 55°, and a spatial resolution of 0.69 × 0.69 × 1.4 mm 3 (reconstructed to 0.69 × 0.69 × 0.7 mm 3 ). The acquisition times for the T 1 -weighted and T 2 -FLAIR sequences were 11:46 and 10:00 minutes, respectively.

| MRI postprocessing and analysis
The dMRI data were corrected for eddy currents and subject motion using ElastiX with extrapolated target volumes, 32 and subsequently smoothed using a 3D Gaussian kernel with a standard deviation of 0.42 times the voxel dimensions. The q-space trajectory imaging model 23 was fitted to the data voxel-by-voxel using linear regression with heteroscedasticity correction to yield a metric of the microscopic anisotropy (microscopic diffusion anisotropy [MK A ]) 22 together with the conventional FA. All postprocessing and model fitting of dMRI data was performed using MATLAB (R2015b, MathWorks) together with the multidimensional dMRI toolbox, 33 available at https://github.com/markus-nilsson/md-dmri. The T 1 -weighted and T 2 -FLAIR images were bias field-corrected using FMRIB Software Library FAST. For the purpose of visualization and region of interest (ROI) definition, the diffusion parameter maps and the T 2 -FLAIR images were coregistered to the T 1 -weighted images using ElastiX and rigid-body transformations. To improve performance, the T 1weighted images were downsampled to 1.5-mm isotropic voxel dimensions before coregistration.

| Comparison of MRI contrasts in MCD
Two approaches were used to investigate whether mapping microscopic anisotropy by the MK A may improve the differentiation of cortex and white matter in the delineation of MCD. First, we compared the appearance of the MCD in the MK A maps with that in the conventional MRI contrasts (T 1 -weighted, T 2 -FLAIR, and FA). Second, we compared the image intensity distributions of the MCD between the different contrasts. For each lesion and each contrast, we quantified the percentage of voxels classified as "cortex-like" or "white matter-like." This classification utilized information drawn from normal-appearing cortex and white matter. Details of the procedure are given below.

| Regions of interest
As a basis for all investigations, ROIs were placed in MCD and in normal-appearing tissue. For all patients, suspected MCD were localized and delineated with ROIs in the T 1 -weighted images. The delineation aimed to include cortical abnormalities but to exclude associated white matter, even if suspected pathological. Thus, with the exception of blurred gray-white boundaries in FCD, only tissue that was isointense with cortex was included. For very large lesions, including some PMG and SH, the ROIs were limited to representative parts. For one PMG patient, three ROIs subdivided one large lesion into three separate parts that engaged different gyri and featured different morphological characteristics. The reviewing was performed by B.L. together with I.M.B.-B., a senior neuroradiologist. Normal brain tissue was defined on the T 1 -weighted images by placing ROIs in normal-appearing cortex and its adjacent white matter on the contralateral side to each lesion in each patient.
All ROI definition was performed in the coregistered T 1 -weighted downsampled image space. However, the dMRI data featured some geometric distortions from the EPI readout. To minimize the influence of partial volume effects from such distortions, as well as from the lower native resolution of the dMRI data, the lesion ROIs were drawn with a margin of one to two voxels. Furthermore, each ROI was carefully inspected in the dMRI data using the nondiffusion-weighted images. Voxels with cerebrospinal fluid contamination were removed and, when necessary, the dMRI images were manually translated in 3D space.

| Intensity distributions and differentiation of cortex and white matter
Intensity distributions were extracted from each ROI in each contrast. Average distributions were obtained for normal brain tissue and for each of the different MCD types by averaging the distributions between ROIs.
Optimal intensity thresholds for differentiation of cortex and white matter were obtained for each contrast through a receiver operating characteristic (ROC) analysis on the average distributions from normal brain tissue. Using these thresholds, contrast-specific classifications were obtained for each lesion voxel as either cortex-like or white matter-like.
The T 1 -weighted and T 2 -FLAIR intensities were normalized, for each ROI, by division with the mean intensity within a reference ROI in the same subject. For T 1 -weighted intensities, the lesion ROIs were referenced to the adjacent normal-appearing white matter and the normal brain tissue ROIs were referenced to the normal white matter ROI (corresponding to each location). For T 2 -FLAIR intensities, all ROIs were referenced to the relatively homogeneous anterior corona radiata.

| Data accessibility
The data that support the findings of this study-metadata, thumbnail images, and extracted parameter values-are available from the corresponding author upon request.

| Statistical methods
The ROC analysis was performed with the perfcurve function in MATLAB.

| MCD localization
A total of 25 different lesions were delineated among the 13 patients ( Table 1). The lesions represented each of the four different MCD types referred to in the introduction. An overview of typical manifestations for these MCD on structural MRI is shown in Figure 1. PH typically manifests as nodular masses of cortical tissue localized alongside the ventricular border or protruding into the ventricles. SH manifests as more irregular (curvilinear) patches of cortical tissue that are located mainly within deep white matter but that are often contiguous with the cerebral cortex. FCD resides within the cerebral cortex and has subtle manifestations, including a blurred gray-white boundary or apparent cortical thickening. Finally, PMG manifests as (often large) stretches of cerebral cortex with microscopic gyration.

| Comparison of MRI contrasts in normal brain tissue
Imaging results from the normal brain are exemplified in Figure 2. All MRI contrasts appeared to enable differentiation of normal cortex and white matter. The T 1 -weighted image was darker in gray matter (including both the cerebral cortex and deep gray matter) than in white matter, and the T 2 -FLAIR image featured the opposite pattern. Dividing the T 1 -weighted image with the (coregistered) T 2 -FLAIR image yielded a strong contrast that could plausibly reflect myelin, as suggested by Glasser et al, 34 featuring the highest intensities in major white matter tracts such as the corpus callosum and the internal capsule. As for the dMRI contrasts, both the FA map and the MK A map were dark in gray matter and bright in white matter, although they exhibited notable differences. The MK A map was homogeneously bright in white matter, whereas the FA map featured darker areas in regions known to have crossing fibers. Conversely, the FA map was homogeneously dark in gray matter, whereas the MK A map featured brighter gray matter regions, for example, in the lateral thalamus and in the medial putamen. The example illustrates the ambiguity in the FA due to the influence of orientation coherence. In white matter, variation in orientation coherence causes variation in FA even when diffusion anisotropy is uniformly high at the microscopic level (MK A ). In gray matter, a low orientation coherence causes a uniformly low FA even when diffusion anisotropy varies at the microscopic level (MK A ).

| Comparison of MRI contrasts in MCD
Imaging results from the lesions are shown in Figure 3 (PH and SH) and  Table 1. In the T 1 -weighted images that were used to delineate the lesions, the lesions appeared uniformly cortex-like. Brighter areas with intensities similar to that of white matter were seen only in the blurred gray-white boundaries of the FCD (present in all FCD). The lesions appeared mainly cortex-like also in the T 2 -FLAIR images. However, white matter-like intensities were seen in some PMG (Table 1, lesions 11:1, 11:3, and 12:1), including a region where the T 1 -weighted image indicated severe cortical thickening (Figure 4, row 3). In the FA maps, all lesions were dark and similar to nearby cortex, although brighter areas were seen near the lesion border in two PMG lesions (Figure 4). In the MK A maps, the lesions appeared more heterogeneous than in the other contrasts. In particular, the MK A varied between dark and cortex-like to bright and white matter-like, both within and between different lesions. In PH, the MK A was always cortex-like. In SH, the MK A was cortex-like in the parts that were contiguous with the cerebral cortex but white matter-like in the parts located within deep white matter. These bright MK A regions were seen in all but three of the eight SH lesions (where the extension into white matter was small or absent, Table 1, lesions 5:5, 6:2, and 4:4). In FCD, the MK A was generally cortex-like, although white matter-like regions that overlapped the (T 1weighted) blurred gray-white boundaries were seen in two cases (Figure 4, row 2 and Table  1, lesion 7:1). The PMG lesions were the most heterogeneous in MK A . Two lesions were near exclusively cortex-like (Table 1, lesions 11:2 and 11:3), one lesion was near exclusively white matter-like (Table 1, lesion 12:1), and two lesions showed white matter-like parts next to cortex-like parts (Figure 4, rows 3-4), including the region of apparent cortical thickening.
Average intensity distributions in each contrast are shown in Figure 5A for normal brain tissue and for the different MCD types. The ROC-derived thresholds for differentiation of normal cortex and white matter (dashed lines) divide the MCD distributions between voxels classified as cortex-like and white matter-like (percentages indicated in the figure). Figure 5B (white matter-like voxels in red), and the white matter-like percentage (WM%) for each individual lesion is listed in Table 1. In T 1 -weighted intensities, which were used for ROI definition, the overlap between normal cortex and white matter was minimal ( Figure 5A, area under the curve [AUC] = 0.98) and the MCD distributions were primarily within the cortex range (WM% between 2% and 7%). For T 2 -FLAIR, the overlap between normal cortex and white matter was larger (AUC = 0.84). The distributions were primarily within the cortex range for PH, SH, and FCD (WM% between 6% and 21%). However, as exemplified in Figure 5B, T 2 -FLAIR indicated a substantial portion of white matter-like voxels in PMG (WM% = 59%), reflecting a high WM% in three of the five lesions (Table 1). For FA, the overlap between normal cortex and white matter was similar to that of T 1 -weighted intensities (AUC = 0.97). The range of FA values was markedly wider in white matter than in the cortex. All MCD types featured similar distributions that resembled that of the normal cortex but shifted toward slightly higher FA values. As a result, a portion of voxels within the white matter range of FA were present in all MCD (WM% between 16% and 23%) and were often found near the lesion borders ( Figure 5B). For MK A , the overlap between normal cortex and white matter was small, although somewhat larger than in T 1 -weighted intensities and in FA (AUC = 0.95). Both cortex and white matter exhibited wider ranges of values in MK A compared with the range of values in FA. The MCD distributions were considerably more heterogeneous in the MK A than in the other contrasts. The distribution was primarily within the cortex range for PH (WM% = 13%). However, substantial portions of voxels far into the white matter range were seen in SH, FCD, and PMG (WM% between 30% and 45%).

| DISCUSSION
Tensor-valued dMRI yielded information on MCD independent from that obtained with conventional MRI contrasts. Lesions that appeared uniformly cortex-like in conventional MRI were revealed to feature white matter-like regions in maps of microscopic diffusion anisotropy (Figures 3-5, Table 1). Conventional MRI includes T 1 -and T 2 -weighted sequences, which are sensitive to myelin 5 and iron, 11 and FA from diffusion tensor imaging, which is sensitive to coherently ordered axons. 14,17 The observed variation in microscopic anisotropy within and between MCD thus shows that some aspect of the microstructure can vary without affecting these conventional contrast mechanisms.
We argue that the observed variation in microscopic anisotropy within MCD is consistent with a variation in axonal content. In normal brain, microscopic anisotropy is low in cortex and high in white matter (Figure 2). [26][27][28]35,36 This is consistent with axons but not dendrites as a cause of microscopic anisotropy, because the combined density of axons and dendrites (neurites) is similar in cortex and white matter. 28,37,38 If axons and dendrites contributed equally to the microscopic diffusion anisotropy, the difference between cortex and white matter would be small. Even across normal gray matter regions, the variation in microscopic anisotropy appears related to a variation in axonal content. 28 Here, higher MK A was seen in the lateral thalamus, which is myelin-rich, 39 and in the medial putamen, which is near the passage of striatopallidal fibers (Figure 2). 40 In MCD, the observed variation in microscopic anisotropy is consistent with variations in axonal content expected from previous findings. For example, we found low MK A in PH where the neural connectivity is limited, 41 as well as in the dysplastic cortex of FCD and PMG where the neuronal density is reduced. 42,43 Conversely, we found high MK A in the white matter-embedded parts of SH, consistent with fiber-tracking findings of tracts passing through heterotopias located within white matter. 44 We also found high MK A in parts of FCD and PMG lesions located close to white matter ( Figure 5B), which we interpret as subcortical white matter with myelin pathology, which can appear isointense with cortex in conventional MRI contrasts. 8 Sensitivity to a voxel's axonal content rather than its myelin content should allow a more robust differentiation of cortex and white matter. The T 1 -weighted and T 2 -weighted MRI contrasts provide a clear gray-white boundary in the normal adult brain. 5 However, depending on the state of myelination within both cortical and noncortical tissue, the boundary may blur, exaggerate, or underestimate the cortex's true extent. [6][7][8]10 This complicates not only the clinical delineation of lesions but also the neuroscientific evaluation of cortical thickness, for example, during maturation. 7 T 2 -weighted images may be less confounded by myelin content 8 but may confound cortex and white matter also based on iron content. Here, T 2 -FLAIR indicated a high WM% in PMG similar to MK A ( Figure 5A). However, the two contrasts disagreed on individual lesions (for example, Table 1, lesions 11:3 and 13:1, and Figure 5B, row two), indicating that the T 2 -FLAIR finding represents a different effect. That effect could plausibly be iron content, seeing that the lesions with high WM% values were close to the motor and auditory regions ( Table 1, lesions 11:1 and 12:1, and lesion 11:3, respectively), where iron concentrations are relatively high 45 and where T 2weighted hypointensities have been demonstrated also in healthy subjects. 12,13 The FA is sensitive to axonal content 14 but, as illustrated in Figure 2, it provides a cloudy picture that is difficult to interpret by its dependence on orientation coherence. Here, the FA indicated higher white matter-like percentages in MCD than in normal cortex ( Figure 5A) and FA maps were bright at the borders of high-MK A areas in PMG (Figures 4 and 5B). However, the FA also showed tissue as homogeneous and dominantly cortex-like, where the MK A showed considerable heterogeneity (Figures 3-5). As these conventional contrasts are unreliable in complex tissue with unknown myelin content, tensor-valued dMRI may become an important tool for tissue differentiation and for the evaluation of cortical thickness.
A more robust tool for differentiation of cortex and white matter would likely improve MCD delineation in presurgical evaluation of epilepsy. For surgery to achieve seizure freedom with minimal neurological sequelae, presurgical evaluation aims to delineate the "epileptogenic zone," which is defined as the volume of cortical tissue that initiates or could initiate seizures. 45 Recognizing tissue as white matter rather than cortex could result in a decrease of the planned resection volume and thereby a decreased risk of sequelae. For example, subcortical white matter may be spared in FCD and PMG ( Figure 4). 8,10 In large and often deep lesions such as SH (Figure 3), one may also prioritize the cortex-like parts for invasive investigations such as intracranial video-electroencephalographic recordings. 4 Conversely, recognizing tissue as cortex rather than white matter could result in an increase of the planned resection volume and thereby an increased probability of seizure freedom. Examples of cortex resembling white matter in conventional MRI contrasts include cases with high myelin content, 7 high iron content, 12,13 and other unknown mechanisms. 6 We identified four main limitations of this study. First, the gradient waveforms used to generate spherical b-tensors were not compensated for concomitant gradients, because the approach to generate compensated waveforms was not available at the start of this study. This is expected to bias the MK A . 47 A positive bias was revealed by comparing the MK A values obtained here, across the normal brain, with values obtained previously. 28 A positive bias in MK A has also been reported from previous data acquired with the 7-T MRI scanner used in the present study. 29 However, the bias appeared spatially homogeneous and unlikely to have influenced the contrast, for example, between MCD and adjacent normal brain tissue. Second, we acknowledge that our results may be affected by partial volume effects. The dMRI data were affected by EPI-related geometric distortions, which are more pronounced on 7-T MRI, 29 and the voxel size of 2 × 2 × 4 mm 3 was large compared with the size of the cerebral cortex and some MCD. Although steps were taken to address this issue, partial volume effects may still have contributed to, for example, the relatively large percentage of high FA in some PH lesions (which are small, Table 1). Additionally, some voxels with suspected sensitivity encoding-related artifacts were observed within lesions close to the edge of the brain (Figure 3, red arrows). Our main finding of high-MK A regions within MCD should be robust to these limitations, however, as these were present in many subjects and often large enough to involve multiple slices in the dMRI data's native resolution. Third, microscopic anisotropy estimates may be biased by perturbations in T 2relaxation values between intra-and extracellular environments as, for example, in white matter lesions. 28 Here, high MK A was observed in the (T 1 -weighted) blurred gray-white boundaries of two of the four FCD lesions (Table 1). Both FCD lesions without high MK A exhibited high mean diffusivity, which could indicate extracellular edema with long T 2 -relaxation values that dominate the signal from anisotropic structures. 28 The importance of accounting for T 2 -relaxation as in, for example, our recent work, 26 in the context of MCD should be explored in future studies. Fourth, the gradient waveforms used to generate linear and spherical b-tensors differed with respect to time-dependent diffusion encoding, which may positively bias the MK A . 48 However, multiple studies have shown negligible diffusion time dependence in the human brain for the long encoding times used with clinical MRI scanners. 28,49,50 In conclusion, mapping microscopic diffusion anisotropy revealed white matter-like regions within MCD that appeared cortex-like in conventional MRI. The results suggest that by reflecting axonal content rather than myelin content, microscopic anisotropy allows a more robust differentiation of cortex and white matter and improves MCD delineation. There are no technical barriers to performing tensor-valued dMRI. Techniques for mapping microscopic anisotropy are available at common clinical MRI systems 29 and can be performed in just 3 minutes. 30 Thus, tensor-valued dMRI has the potential to become an important tool for tissue differentiation in conditions that affect myelin and to benefit presurgical evaluation of epilepsy. Future studies should investigate the validity of microscopic anisotropy as a marker of axonal content in MCD. Such studies should address limitations of the current study and use larger sample sizes and correlations with histopathology. Future studies should also explore the technique's potential for identifying "MRI-negative" lesions in drug-resistant epilepsy 3 and compare its performance with a combination of conventional MRI contrasts, for example, through a machine learning approach. 51

Supplementary Material
Refer to Web version on PubMed Central for supplementary material.

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Delineation of MCD on MRI is central in presurgical evaluation of drugresistant epilepsy • Conventional T 1 -and T 2 -weighted contrasts may confound cortex with white matter when myelin content is altered

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The novel tensor-valued dMRI technique maps microscopic diffusion anisotropy, which is sensitive to axons rather than myelin • Maps of microscopic anisotropy revealed white matter-like tissue in MCD that was cortex-like in conventional MRI contrasts • Tensor-valued dMRI may improve differentiation of cortex and white matter and the delineation of MCD in presurgical evaluation of epilepsy Typical manifestations of malformations of cortical development (MCD). On structural magnetic resonance imaging, periventricular heterotopia (PH) is characterized by cortical tissue misplaced near the ventricles, subcortical heterotopia (SH) by cortical tissue misplaced within deep white matter but often contiguous with the cerebral cortex, focal cortical dysplasia (FCD) by patches in the cerebral cortex with a blurred gray-white boundary, and polymicrogyria (PMG) by stretches of cerebral cortex with microscopic gyration. The color difference between MCD and normal cortex is for emphasis only Imaging results from the normal brain. Magnified regions highlight different gray matter structures: the cerebral cortex (a), the putamen (b), the head of the caudate nucleus (c), and the thalamus (d). The T 1 -weighted image was darker in gray matter than in white matter, with lowest intensities in the cerebral cortex and in the head of the caudate nucleus followed by the putamen. The T 2 -fluid-attenuated inversion recovery (FLAIR) image featured a similar but opposite pattern. The image obtained as the ratio between the T 1 -weighted and the T 2 -FLAIR images featured a sharp contrast that emphasized myelin-rich regions such as the corpus callosum and the internal capsule (arrows). Both the fractional anisotropy (FA) map and the microscopic diffusion anisotropy (MK A ) map were dark in gray matter and bright in white matter. However, the FA was comparatively low in the anterior corona radiata (arrow), and the MK A revealed higher levels of microscopic anisotropy in the lateral thalamus and in the medial putamen (arrows). All contrasts were coregistered to the T 1weighted image space. The T 1 -weighted and T 2 -FLAIR intensities are in arbitrary units, and the FA and MK A are dimensionless Imaging results from periventricular heterotopia (PH) and subcortical heterotopia (SH). In the T 1 -weighted, T 2 -fluid-attenuated inversion recovery (FLAIR), and fractional anisotropy (FA) contrasts, the PH and the SH appeared uniform, with intensities similar to nearby cortex. In the microscopic diffusion anisotropy (MK A ) maps, the lesions were more heterogeneous. Dark and cortex-like MK A was seen in the PH and in the parts of the SH that were contiguous with the cerebral cortex. Bright and white matter-like MK A was seen in the parts of SH located within deep white matter (yellow arrows). The red arrows point out suspected sensitivity encoding-related artifacts in some voxels near the edge of the brain that resulted in an apparent high MK A . All contrasts were coregistered to the T 1 -weighted image space. The T 1 -weighted and T 2 -FLAIR intensities are in arbitrary units, and the FA and MK A are dimensionless Imaging results from focal cortical dysplasia (FCD) and polymicrogyria (PMG). In the T 1weighted, T 2 -fluid-attenuated inversion recovery (FLAIR) and fractional anisotropy (FA) contrasts, the FCD and the PMG appeared uniform, with intensities similar to nearby cortex. Exceptions were blurred gray-white boundaries in FCD, a hypointense T 2 -FLAIR in one PMG where the T 1 -weighted image indicated apparent cortical thickening, and a bright FA close to the PMG borders (blue arrows). In the microscopic diffusion anisotropy (MK A ) maps, both FCD and PMG exhibited mixed cortex-like and white matter-like parts. Dark and cortex-like MK A was seen in most parts of FCD and in different parts of PMG, including the most superficial region in row 3 and the posterior gyrus in row 4. Bright and white matterlike MK A was seen in the blurred gray-white boundary of some FCD, including in row 2, and in different parts of PMG, including the region of apparent cortical thickening in row 3 and the anterior gyrus in row 4 (yellow arrows). All contrasts were coregistered to the T 1weighted image space. The T 1 -weighted and T 2 -FLAIR intensities are in arbitrary units, and the FA and MK A are dimensionless  Percentages of lesion voxels classified as white matter-like