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braini0202 Brain (1997), 120, 271–281 Disproportion of cerebral surface areas and volumes in cerebral dysgenesis MRI-based evidence for connectional abnormalities S. M. Sisodiya and S. L. Free Epilepsy Research Group, Institute of Neurology, National Hospital for Neurology and Neurosurgery, and National Society for Epilepsy, London, UK Correspondence to: Dr S. M. Sisodiya, Department of Clinical Neurology, Radcliffe Infirmary, Woodstock Road, Oxford OX2 6HE, UK Summary In the normal adult human brain, there are quantitative relationships between a surface area measure of the grey matter and the volume of hemispheric grey matter, the volume of the hemispheric subcortical matter and the cross-sectional area of the corpus callosum as revealed by analysis of high resolution MRI data. These relationships reflect structural order in, and biological features of, normal human cerebral hemispheres. Cerebral dysgenesis (CD) is associated with disruption of the normal organization of the hemispheres to a greater or lesser extent and is often manifest as refractory epilepsy. We have examined structural proportions and their disruption in the brains of patients with epilepsy and CD. We found that structural measures were abnormal in 60% of patients with CD, with abnormalities in 64% of hemispheres that, on visual inspection alone, appeared completely normal. We showed that the disruptions found are compatible with expected histopathology in cases where histopathology may be predictable, and that extensive abnormalities may be due to abnormal patterns of connections within the hemispheres. In some cases, it may be possible to predict histopathology on the basis of quantitative analyses of high resolution MRI data, when such prediction is not possible on visual inspection alone. Keywords: brain measurement; cerebral dysgenesis; surface area; connectivity Abbreviations: CCA 5 corpus callosal cross-sectional area; CD 5 cerebral dysgenesis; EA 5 extra subcortical matter surface area; ECC 5 EA:CCA ratio; EGM 5 EA:GMV ratio; ESM 5 EA:SMV ratio; GM 5 grey matter; GMV 5 GM volume; SM 5 subcortical matter; SMA 5 SM surface area; SMV 5 SM volume Introduction The development and organization of the vast number of neurons (Braendgaard et al., 1990) and synapses (Cherniak, 1990) in the human brain is governed by a comparatively minute amount of genetic information, suggesting that general rules must exist for the establishment of cerebral structure, almost certainly with environmental influence producing local modulation (Purves et al., 1992). General rules are reflected in quantitative measures of normal cerebral structure: the mean number of neurons per unit volume and per unit surface area is relatively constant (Haug, 1987; Braendgaard et al., 1990); the variation in neocortical thickness is limited, both within and between species (Welker, 1990; Rakic, 1995); the proportions of neurons allocated to specific functional groups, e.g. projectional or nonprojectional, are relatively constant (Rockel et al., 1980; Winfield et al., 1980). The existence © Oxford University Press 1997 of general rules is highlighted by the finding that single gene defects can result in dramatic, extensive and histologically homogeneous structural disorder in human development (Reiner et al., 1993). Because of these rules, useful macroscopic parameters of cerebral structure exist (Hofman 1985, 1991; Haug, 1987; Filipek et al., 1994; Sisodiya et al., 1995, 1996). Also, reliable determination of cortical surface area or volume might provide a means of estimating total (Mountcastle, 1978), regional and functionspecific neuronal numbers in normal brains. A knowledge of the number of neurons, and the proportion allocated to a certain laminar or functional group, would be of importance in the further investigation of normal cortical organization and its disruption. The availability and usefulness of such information would be enhanced if it could be gathered in vivo. 272 S. M. Sisodiya and S. L. Free Fig. 1 Schematic drawing of the derivation of EA. The corrugated circle represents the real SM surface in cross-section; the plain circle encompasses the same area but is unfolded; the difference in the perimeters of the two regions is the extra length (area in three dimensions) generated by the folding of the surface of the SM. This extra area is termed EA, and is defined by: EA 5 SMA – 4kπ(3SMV/4π)2/3 where SMA is the measured SM surface area and SMV the measured SM volume, and k is a constant converting volume to voxel number (for details, see Sisodiya et al., 1996). MRI allows quantitative data on human cerebral structure to be acquired in vivo: it permits the study of macroscopic cerebral parameters, such as volumes and surface areas. Using MRI, we have examined cerebral surface areas and volumes in normal adult human brains and shown that a number of quantitative relationships do indeed exist between various parameters, reflecting general organizational rules (Sisodiya et al., 1996). Thus, in the normal brain, total hemispheric grey matter volume and (inner) grey matter surface area correlate linearly, implying that variation in the range of cortical thickness across normal subjects is limited, and reflecting the histological finding of a relatively constant mean neuronal surface density. In addition, the corpus callosum cross-sectional area, a measure of the number of fibres passing through it (Aboitiz et al., 1992), also correlates with a surface area measure of the grey matter, supporting the suggestion that a fixed proportion of neurons belong to a given functional class. Whilst all previously published data on cortical areas concern the free surfaces (grey–CSF interfaces; e.g. Schlaug et al., 1995), usually of post-mortem brains (Blinkov and Glezer, 1968; Henery and Mayhew, 1989), the inner surface (grey–white matter boundary) can be defined with greater precision globally on MRI. This inner surface is also the surface of the subcortical matter (SM, defined as the subcortical white matter and subcortical nuclei excluding the caudate) and is created by the spatial dominance of projectional (extracortical) fibres; these may form intergyral arcuate (or ‘U’) fibres or fibres travelling further afield. Such projectional fibres are most plentiful in the walls and at the crowns of gyri and least numerous in the depths of the sulci (Welker, 1990). The variable EA, defined as a measure of the extra surface area generated by the folding of the SM surface (see Fig. 1), may also be taken as an estimate of the surface area of the white matter cores of gyri, that is the area of SM directly overlain by cortical grey matter in gyral crowns and walls rather than in sulcal depths (Sisodiya et al., 1996). Folding in normal brains is necessitated by the number of projectional axons and the amount of neuropil (intracortical synapses, dendrites and axons) covering a limited volume of white matter (Prothero and Sundsten, 1984; Ruppin et al., 1993). EA is thus a better average measure of projectional (afferent and efferent) axon numbers and neuropil quantity than is the total SM area (SMA); EA may be considered to be more biologically relevant. Abnormal organization of the cortex defines cerebral cortical dysgenesis (CD) and may occur at any level, from the synaptic to the macroscopic (Becker, 1991; Sarnat, 1992; Raymond et al., 1995). The nomenclature of dysgenesis is not yet universally agreed; we use the system proposed by Raymond et al. (1995), based on the appearance of dysgenesis as seen on routine inspection of high-resolution MRI. We propose that in dysgenesis quantitative measures and normal proportions of cerebral structure might be altered and that examination of quantitative parameters in brains with dysgenesis might shed light, in vivo, on the nature, distribution and extent of the dysgenetic process. Based on the outcome from surgery, it has been proposed that in human CD, structural abnormalities may extend beyond the visualized boundaries of a lesion (Taylor et al., 1971; Awad et al., 1991; Andermann, 1994). It has subsequently been shown that there is indeed both local lesional extension (Palmini et al., 1995) and distant alteration in cerebral structure (Sisodiya et al., 1995) in cerebrum appearing normal on inspection. It has been suggested that abnormalities spatially removed from a lesion may be due to abnormal connectivity associated with apparently focal dysgenesis, given evidence from animal experiments (Goldman-Rakic, 1980; Rakic, 1988; Loopuijt et al., 1995) and the high degree of connectivity in the normal human brain (Cherniak, 1990). Abnormal connectivity has been considered in dysgenesis directly using MRI through the analysis of developmental anomalies of the corpus callosum, known to be associated with the presence of abnormal cerebral structure (Friede, 1975; Barkovich and Norman, 1988) and function (Hynd et al., 1995). In this report, we develop previously reported parameters of cerebral structure further and examine their use in investigating structural disturbances in vivo in patients with CD. Specifically, we attempt (i) to determine if there is disruption of surface structural measures in CD; (ii) to correlate any changes with known or presumed histopathology; (iii) to look for further evidence that CD may extend beyond visualized abnormalities and (iv) to Cerebral surface areas and volumes in cerebral dysgenesis 273 Table 1 Patient clinical and neuroimaging data Patient no./sex/ age at scan (years)/ age at seizure onset MRI diagnosis Seizure types 1/F/36/24 years 2/M/17/8 years 3/F/35/21 years 4/M/18/1 month 5/F/36/6 months 6/M/23/12 years 7/F/15/10 years 8/F/18/5 years 9/F/34/23 years 10/F/29/2 years 11/F/27/17 years 12/F/18/13 months R frontoparietal polymicrogyria Extensive R occipital dysgenesis (Fig. 2) Extensive R CH gyral abnormality, polymicrogyria R medial occipital and R lateral parietal clefts (partial thickness) L frontal medial and lateral gyral abnormality, L frontal SEH Hypothalamic hamartoma Bilateral posterior macrogyria (Fig. 4) L occipitotemporal macrogyria Bilateral full thickness clefts Bilateral SEH and R posterior localised macrogyria Bilateral small parietal subcortical heterotopic nodules Agenesis of corpus callosum and R temporal, anterior parietal CD, full thickness cleft, bilateral SEH (Fig. 3) Bilateral SEH (occipital and temporal horns; diffuse) R parietal macrogyria L occipital, posterior parieto-temporal full thickness cleft Bilateral subependymal heterotopia, parietal full thickness clefts Agenesis of corpus callosum Bilateral subcortical band heterotopia, frontal Bilateral subcortical band heterotopia. R posterior parieto-temporal full thickness cleft L hemisensory, SGS 1–2/month CPS, tonic extension L leg; SGS once only SPS, L hemisensory; no CPS for 10 years; no SGS L arm aura then SGS, 3/month Dropping head, raising arms, falling down; no SGS Gelastic seizures; drop attacks SPS; drop attacks; rare SGS CPS; visual aura; no SGS Focal motor, L arm; no SGS CPS with buzzing; no SGS L arm focal motor seizures CPS with jerking of all limbs; no SGS 13/F/31/17 years 14/F/28/12 years 15/F/15/10 months 16/M/26/18 months 17/F/23/15 years 18/M/29/12 years 19/M/33/18 months 20/M/27/26 years CPS; three SGS only Nightly SGS SPS (aura); CPS. R focal motor; no SGS CPS; myoclonic jerks; four SGS only CPS only with hypothermia R focal motor and two SGS Absences; 2–3 GS/year CPS; no SGS CH 5 cerebral hemisphere; CPS 5 complex partial seizure; SPS 5 simple partial seizure; GS 5 generalized seizures; SGS 5 secondary generalized seizures; SEH 5 subependymal heterotopia. examine the possibility that such extension is associated with abnormalities of interneuronal connections. Methods Subjects Thirty-three neurologically normal volunteers, 11 female and 22 male, were scanned using MRI. Their age range was 19–52 years. All gave informed consent for the scanning procedure; scanning was approved by the ethics committee of the National Hospital for Neurology and Neurosurgery. Twenty patients, with definite CD identified on routine visual inspection of MRI scans by an experienced neuroradiologist, were selected because the grey–white interface on postprocessing was of a certain degree of complexity and was neither thicker than normal nor blurred (see below in ‘Area measurements’). All patients attended clinics at the National Hospital or the Chalfont Centre for Epilepsy. Patient details are given in Table 1. There was no significant difference between the ages of the controls and the ages of the patients (Mann–Whitney, two-tailed, P . 0.2). Imaging, segmentation and block analysis The imaging and segmentation protocols have been described in detail previously (Sisodiya et al., 1995). Briefly, all subjects were scanned using sagittal T1-weighted, coronal T1-weighted volumetric, axial T2-weighted and axial proton density sequences. All images had been reviewed by an experienced neuroradiologist who specifically examined for subtle dysgenesis. In no case was there any evidence of either dysgenesis other than that reported in Table 1, or of gliosis on T2-weighted imaging. On each coronal image for each subject, the cortical grey matter (GM) and SM were isolated using a dedicated image processing workstation (Allegro, ISG Technologies, Toronto, Canada) and these regions-ofinterest reconstructed into three-dimensional images. The volumes of the hemispheric GM and SM (GMV and SMV) reconstructions were automatically calculated. The symmetry and regional distributions of GMV and SMV in these reconstructions were also assessed (see Sisodiya et al., 1995). In essence, the method quantifies the amount of cortical grey matter or subcortical matter within prescribed proportions (blocks each extending one-tenth of the anterior–posterior axis) of each individual hemisphere. Eighty measures are thus generated (10 GMV and 10 SMV per hemisphere, 20 individual block ratios of GMV:SMV, 10 ratios each of GMV and SMV in a block in the left hemisphere compared with the volume in the homologous block in the right hemisphere). Normal ranges, lying ,3 SDs from each of these 80 means from the 33 control subjects, can identify and locate abnormalities of the distribution of a particular tissue within the hemispheres. None of the 33 control subjects had more than one abnormal value out of the total of eighty. On this basis, the presence of more than one abnormal variable (of 80 in total) in a particular subject was considered abnormal; this finding has previously been given a biological interpretation (Sisodiya et al.,1995). 274 S. M. Sisodiya and S. L. Free Area measurements The surface area of the SM reconstructions (SMA) and the cross-sectional area of the corpus callosum (CCA) were obtained as summarized below and described in full detail elsewhere (Sisodiya et al., 1996). SM surface area The surface area of a reconstruction was defined as the number of voxels in its surface contour. For the SM, this contour is effectively the grey–white interface, except for the small region where the SM surface is formed by the corpus callosum, where the contour is not overlain by GM. This surrogate measure is only valid under certain circumstances. The method is model-based and therefore not unbiased (Mayhew, 1992): orientation of the brain in the scanner could alter the final voxel count obtained. In practice, however, because of the complexity of the SM surface, which is highly convoluted in three dimensions, the actual measured effect of deliberately altering intrascanner orientation in a limited number of brains is small with respect to biological variation and the effect of segmentation. This finding of orientation-independence can be applied to other brains without formal testing, provided that the SM surface complexity is similar. The surface complexity was measured by estimation of its fractal dimension (Mandelbrot, 1982), and for controls falls within a very narrow range (right SM surface 2.27–2.31; left SM surface 2.28–2.31; Free et al., 1996). The selection of subjects for this study was limited to those in whom the fractal dimension lay within the normal range. Voxel counting also estimates surface area directly only for those scans in which the grey–white interface is not abnormally thickened. So all the individuals studied were also selected by ensuring that no extensive grey–white interface blurring was seen on visual inspection of their MRIs by an experienced neuroradiologist. Thus the surface voxel count is, for these brains, a valid estimate of the area SMA, effectively independent of brain orientation and not complicated by blurring of the grey–white interface. Corpus callosal cross-sectional area The coronally acquired volumetric data set was reformatted in three mutually perpendicular planes using the proprietary image-analysis software, and on these data an optimal interhemispheric plane of section was chosen to produce an approximately sagittal image through the smallest crosssectional area of the corpus callosum, from which CCA was measured by segmentation (Sisodiya et al., 1996). Surface area derivatives From the measurements made above, the following were calculated for each hemisphere (see Sisodiya et al., 1996, for details). First, the extra SM surface area, EA, produced by the folds in the SM, as detailed in Fig. 1. It has been shown that EA correlates highly, in controls, with CCA and with right and left hemispheric GMV separately (Pearson correlation coefficients, P , 0.005). EA also correlates highly in both hemispheres with SMV (P,0.0005). On this basis, the following three ratios were calculated for right and left hemispheres separately for all subjects: (i) for the relationship between GMV (in cm3) and EA (in voxels), EGM 5 EA/GMV voxels/cm3; (ii) for the relationship between SMV (in cm3) and EA, ESM 5 EA/SMV voxels/cm3; (iii) for the relationship between EA and CCA (in cm2), ECC 5 EA/CCA voxels/cm2. For controls, there was no significant sex difference for these ratios or CCA, so that all control subjects were grouped to form sex-independent normal ranges for these variables. Individual hemispheric GMV and SMV normal ranges were segregated for sex. Abnormal values of the ratios are defined as those lying .3 SDs from the mean for control subjects. Abnormal values are categorized as either high or low, allowing interpretation of abnormalities; the actual values are not given as this does not currently add to their interpretation (see below). Reliability The inter- and intra-rater reliabilities of the segmentation process and the measures of hemispheric constituent volumes and surface areas have all been published previously and shown to be high (Sisodiya et al., 1995, 1996). Statistics Analysis was performed using SPSS for Windows, Version 6.1 (SPSS Inc, Chicago, Ill., USA). The statistical test used is indicated in each case. Means6SDs were calculated for each of the derived ratios; the normal range was defined as being within 63 SDs of the mean. Significance was taken at P , 0.01 level. Results Control subjects The mean6SD values for right and left hemispheric volumes GMV and SMV, EA and surface area derivative ratios (EGM, ESM and ECC) are given in Table 2. No control subjects had values for any of these parameters outside the normal range for that parameter. The mean6SD of the CCA across the control group was 696673 mm2. No control subject had more than one abnormal block variable in the total 80 Cerebral surface areas and volumes in cerebral dysgenesis 275 Table 2 Results for normal subjects Variable Right hemisphere (mean6SD) Grey matter volume (GMV) in cm3 Male 263628 Female 225621 Subcortical matter volume (SMV) in cm3 Male 261625 Female 229636 Extra subcortical-matter surface-area and derived ratios EA (voxels) 299 000631 000 EGM (voxels/cm3) 12006140 1200678.3 ESM (voxels/cm3) ECC (voxels/cm2) 435644.7 Left hemisphere (mean6SD) 272628 235624 245621 222631 291 000628 200 11206104 1230681.2 424644.8 EA 5 extra subcortical matter surface area; ECC 5 EA:CCA ratio; EGM 5 EA:GMV ratio; ESM 5 EA:SMV ratio; GMV 5 grey matter volume; SMV 5 subcortical matter volume Table 3 Abnormal values in patients Patient 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Hemispheric volume or corpus callosal area (CCA) abnormality SMV-R, CCA low SMV-R, GMV-R high CCA low SMV-L low SMV-R, SMV-L, GMV-R low CCA absent SMV-L, CCA low CCA low Surface area derivatives† Abnormal blocks (n) Abnormal blocks in normal CH‡ (n) Normal ECC-R, ECC-L, ESM-R high ECC-L high Normal ECC-R, ECC-L high Normal EGM-R, EGM-L, ECC-R, ECC-L low Normal ESM-R, ESM-L high ECC-R, ECC-L high Normal ECC-R, ECC-L, ESM-R, ESM-L high ECC-R high ECC-R, ECC-L high ECC-R, ECC-L, ESM-R, ESM-L high Normal ECC-R, ECC-L, ESM-L high Normal Normal ECC-R, ESM-R, ESM-L high 2 4 17 4 2 8 31 10 4 0 0 16 0 9 * 6 16 3 3 4 0 2 4 1 0 8 NA 0 NA NA NA NA NA 3 * NA 16 NA NA 1 *Block analysis precluded by stereological considerations (see text). †-R or -L 5 right or left; low or high 5 low or high compared with normal ranges. ‡For patients with midline or unilateral CD only (CH 5 cerebral hemisphere); NA 5 not appropriate as CD is bilateral. variables per subject; i.e. no control subject had an abnormal regional distribution of GM or SM, as defined above. Patients Values calculated for the patients were compared with the normal ranges: abnormal results (except for EA) are given in Table 3. EA was abnormal in only one patient (Patient 7; EA low bilaterally). Abnormal surface area measures were found in 12 out of 20 (60%) of patients. The ESM ratio was high in 10 hemispheres (six patients), associated with a low SMV in three hemispheres (two patients). The ECC ratio was high in 10 out of 20 patients (17 out of 40 hemispheres) and low in one patient (both hemispheres); in six out of 11 of the patients with an abnormal ECC ratio, the area of the callosum itself was within the normal range. The EGM ratio was altered in only one patient (bilaterally low in Patient 7). Sixteen of twenty patients had a significant number of abnormalities of the measures of the regional distribution of volume (block abnormalities); block analysis was not possible in one other patient because excessive head tilt confounded measurements. Of 11 patients with visually discernable unilateral or midline CD, seven had abnormality of surface area derivatives in the contralateral hemisphere, 276 S. M. Sisodiya and S. L. Free whilst seven also had at least one abnormal block in the contralateral hemisphere (block measurements were not possible in Patient 15). Discussion Interpretation of surface area derivatives The surface area derivatives quantify mean structural properties of entire hemispheres. The parameters assess the relationship between the extra SM area, EA, and GMV, SMV and CCA. These ratios are independent of brain size and may identify changes in structural proportions even though the underlying variables (surface areas and volumes) fall within the normal range. For control subjects, values all fall within 3 SDs of the mean. In patients, small areas of disproportion, due to structural abnormality, may be averaged out by larger areas of normal proportions (structural normality) within the same hemisphere. If abnormal values for these parameters are found, then the pathological process present in the hemisphere must be quantitatively dominant. The ratio ECC is perhaps most simply interpreted. In control subjects, EA is a measure of the number of projectional axons and the amount of neuropil. CCA is a measure of the number of interhemispheric fibres (Tomasch, 1954; Aboitiz et al., 1992). ECC is a function of these quantities. An increase in ECC implies that either (i) the proportion of (noninterhemispheric) projectional axons is increased and/or the proportion of interhemispheric fibres is reduced (or that they are thinner on average) or (ii) the amount of neuropil is increased (or some combination of these findings). In any case, there must be an alteration in the normal pattern of interneuronal connectivity (as mediated by axons, synapses and dendrites), given that the proportion of neurons belonging to a given functional class is thought to be fixed (Winfield et al., 1980) and that the mean amount of neuropil/neuron in normal brains is also relatively constant (see above). The specific nature of average changes in cortical structure cannot be determined solely from a change in ECC, but a clearer impression might be formed if changes in EGM, ESM and hemispheric volumes were also taken into account. A reduction in ECC has the converse implications with respect to changes in cerebral structure, and also implies extensive alteration in averaged interneuronal connectivity. Geometrically, GMV is a function of grey matter surface area and thickness. Changes in grey matter thickness are very limited in normal brains (Rakic, 1995). It has been suggested that this is because of biophysical constraints acting on the apical dendrites of pyramidal cells (Prothero and Sundsten, 1984). An equally valid reason may be that if an abnormal number of neurons are stacked vertically and yet maintain normal dendritic expansions, then the tangential area available for the passage of the increased number of afferent and efferent axons required to keep the increased number of neurons connected is reduced, limiting the number of neurons that can be supported in such a stack. This is essentially a smaller scale and more superficial (pial) application of the gyral window concept of Prothero and Sundsten (1984). Therefore in abnormally thick cortex, if the number of neurons is increased, then the proportion of axons that cross the grey–white interface must be reduced; if the number of neurons is unchanged or reduced, then in the absence of gross gliosis, the mean amount of neuropil per neuron must increase. EGM is a function of EA and GMV. GMV depends on neuronal numbers and, predominantly, on neuropil volume (Haug, 1956), gross gliosis being excluded in this study by the negative T2 findings. In both focal cortical dysplasia and polymicrogyria, increased astrocyte numbers may be seen histologically (Taylor et al., 1971; Williams et al., 1976), but, to our knowledge, gross gliosis occupying a large volume of the cortex has not been reported in the types of dysgenesis of the varieties under discussion: gliosis per se is therefore unlikely to explain our findings. Any change in neuropil is equivalent to a change in connectivity; changes in neuronal numbers, given the finite volume of GM and that all neurons have neuropil, must be accompanied by neuropil volume change and therefore alteration in connectivity. A reduction in EGM therefore implies (some combination of) either (i) a reduction in the amount of neuropil or in the proportion of projectional axons or (ii) a disproportionate increase in the GMV, that again necessitates a fall in projectional axon number. In pathologically thickened cortex (e.g. as a result of pachygyria), EA may be a better measure of projectional axonal numbers than either SMA or GMV. The ESM ratio is a function of EA and SMV. The biological correlate of SMV is the product of the number of all extracortical projectional axons of various diameters and the mean volume of axons of a given diameter. If ESM is increased, then either (i) EA must be disproportionately large (i.e. there are more projectional axons, demanding a reduced mean volume per axon in the SM, or more total neuropil— but this cannot be associated with increased extracortical projection as then SMV would rise—so that local connectivity must rise disproportionately, without axons entering and contributing to the SM) and/or (ii) there is simply a reduced volume per axon in the SM (with or without a reduction in their number). In either case (or with some combination of the two possibilities), the reduced mean volume per projectional axon implies altered connectivity, as axons must be shorter and/or thinner than normal. Thinner axons cannot support as great a terminal arbor as thicker axons (Mitchison, 1991), therefore any alteration in axon diameter confounding ESM (or ECC) measures is likely a priori to be accompanied by an alteration in connectivity. Shorter axons would suggest a tendency to increased local connectivity at the expense of more distant connectivity. In this group of patients, when the ESM ratio was abnormal, it was always increased. In no case was an increase in the ESM ratio associated with an abnormally high value of EA itself. Cerebral surface areas and volumes in cerebral dysgenesis 277 Surface area derivatives in patients Polymicrogyria The interpretation of surface area derivative abnormalities is exemplified by consideration of changes in patients with known pathological abnormalities. Patients with full thickness clefts of the neopallium commonly have polymicrogyria in the surrounding and distant neocortex, possibly with additional subependymal heterotopia (Dekaban, 1965) and reduction in the subcortical white matter and cross-sectional area of the corpus callosum (Levine et al., 1974). In cases of layered polymicrogyria, as seen in association with pallial clefts, very few axons or dendrites traverse the astroglial-rich layer seen in the deeper layers of the neocortex (Williams et al., 1976). Extracortical projection from neurons pial (superficial) to this cell-sparse layer is reduced, leading to reduced subcortical white matter volume and callosal area, as reported by Levine et al. (1974). Histological analysis (Richman et al., 1974), including Golgi (Williams et al., 1976), has shown, however, that the number of neurons in the remaining layers, and the amount of neuropil, need not be attenuated. In patients with full thickness clefts revealed by MRI in this study, similar structural abnormalities might be expected. In two patients with full thickness clefts, there is indeed reduction of SMV (Patients 9 and 15), with a reduction in CCA in one (Patient 15). Additional abnormalities of connections are revealed by the surface area derivatives. One might predict that in these patients, interhemispheric connections would be fewer than expected for a given brain size, and that extracortical projection would be disproportionately reduced, as axons and dendrites would not cross the astroglial layer in the polymicrogyric cortex. However, the remaining neuropil is normal (see above), so that this contribution to EA may be normal. As a result of these changes, from the interpretation of surface area derivatives given above, the ECC and ESM ratios should both be abnormally high. In four out of six patients with cleft(s), there are precisely such abnormalities of the surface area derivatives. The ESM ratio is increased bilaterally in a patient with bilateral full thickness clefts (Patient 9), and also bilaterally in Patients 12, 15 and 20, who have only unilateral clefts on routine inspection of the MRI. The ECC ratio is also abnormally high in three of these cases. It should be noted that in these cases perilesional polymicrogyria was not obvious or definite on routine inspection, but is presumed to be present. Quantification shows that structural disproportion compatible with polymicrogyria is present in 66% of such cases and may be found in hemispheres that are completely normal on routine inspection. This lends further support to the hypothesis that structural abnormalities in CD may extend beyond visualized boundaries, and be associated with abnormalities of connections (e.g. interhemispheric axons). Therefore in some cases, quantitative changes in postprocessed MRI data and expected histology can be directly correlated, raising the possibility of predicting histopathology Fig. 2 Coronal MRI image of Patient 2. Note the extensive dysgenesis affecting the right hemisphere; the underlying histopathology cannot be uniquely determined on visual inspection of the MRI alone. when this is not directly apparent from routine inspection of the MRI alone. The nature of the dysgenesis in the right hemisphere of Patient 2 is unclear (see Fig. 2). However, analysis of the surface area derivatives shows a pattern similar to that in patients with probable polymicrogyria, with elevation of ECC and ESM in the dysgenetic hemisphere, suggesting that the underlying pathology in this case may also be polymicrogyria. Abnormality is found on quantification in the visually normal left hemisphere, in further support of the extensive and possibly occult nature of dysgenesis. Two patients with clefts, Patient 16 with bilateral full thickness clefts and Patient 4 with unilateral partial thickness clefts, do not have any abnormalities of the surface area derivatives. This is possibly because the extent of presumed structural abnormality (polymicrogyria) around a cleft is variable (Dekaban, 1965; Levine et al., 1974), such that quantitative normality of the rest of the hemisphere swamps localized quantitative abnormality. This may also be the case for Patient 1 who is known to have polymicrogyria. These cases illustrate the need for regionalization of area measures. 278 S. M. Sisodiya and S. L. Free Fig. 3 Surface rendering of the MRI scan of brain of Patient 12 viewed from a right anterior oblique projection. Note the macrogyric region in the temporal lobe. Agenesis of the corpus callosum Agenesis of the corpus callosum may be associated with hemispheric dysgeneses other than the radial rearrangement of gyri on the mesial surfaces (Friede, 1975; Barkovich and Norman, 1988), such as polymicrogyria (Billette de Villemeur et al., 1992) and pyramidal tract hypoplasia (Parrish et al., 1979). The ratio ECC should be, and is, abnormal bilaterally in our cases (Patients 12 and 17), as interhemispheric projection is obviously reduced. In both cases, additional abnormalities of the ESM ratio are found, bilaterally in Patient 12 and on the left only in Patient 17. As interpreted above on the basis of analysis of brains with clefts, this implies some combination of increased (or unchanged) neuropil and reduced mean extracortical projection, associated with the presence, though not necessarily exclusively, of polymicrogyria. It is therefore possible that the gyral abnormality (see Fig. 3) seen in Patient 12, who has a cleft, callosal agenesis and specific surface area derivative abnormalities, is polymicrogyria, though this is not the only diagnosis that can be made on visual inspection only of the reconstruction. Patient 17 has the expected abnormalities of gyral disposition on the mesial surfaces of the hemispheres; the quantitative results suggest that there may also be extensive polymicrogyria in the left hemisphere, though this was not seen on routine inspection. Polymicrogyria may be occult on macroscopic inspection or imaging and be revealed only on histology (Galaburda and Kemper, 1979; Kuzniecky et al., 1994). Macrogyria Bilateral posterior macrogyria is seen in Patient 7, with cortical thickening in the affected area seen on routine inspection in multiple planes. Cortical thickening may be due to several different histopathologies (Friede, 1975; Raymond et al., 1995). A priori, truly thickened cortex implies either reduced projection out of and into the cortex (if the surface Fig. 4 View from the vertex of surface rendering of the MRI scan of cerebral hemispheres in Patient 7. Macrogyria is obvious posteriorly, especially in comparison with the gyral widths anteriorly: note the extent of the obvious gyral abnormality. density of neurons increases), supported by the low EA bilaterally in this case, or increased mean neuronal neuropil (if the surface density of neurons does not increase). Increased total neuropil and reduced projection are associated with an increased ESM ratio in four out of six cases of probable polymicrogyria; the normality of the ESM ratio in this case, despite the extent of visible gyral abnormality (see Fig. 4) and the bilaterally low EA, argue against an increase in neuropil. Instead, extracortical axonal projection is likely to be reduced, irrespective of any alteration in the number of neurons. A reduction in projection is supported by the abnormally low SMV in the left hemisphere. The normal CCA suggests that, although total extracortical projection is reduced, interhemispheric projection seems to be maintained. This suggests lamina 3 neurons have maintained their projectional integrity (Jones, 1984), whether or not they are correctly positioned in the thicker cortex, and necessitates a reduction in intrahemispheric extracortical projection. This combination is therefore unlike polymicrogyria, but compatible with pachygyria, in which reduction in neuropil locally has been reported (Takada et al., 1994). Other histopathologies are possible; confirmation of the interpretation of the changes in surface area derivatives must await analysis, including stereological cell counts, of cases of known agyria (e.g. with familial lissencephaly). It is possible, nevertheless, that abnormality of ESM is seen only in association with polymicrogyria. Cerebral surface areas and volumes in cerebral dysgenesis Alteration in the total number of neurons may complicate these analyses; the effect of changes in cell density has been discussed for Patient 7 above. In all the other cases of dysgenesis, the effect of altered neuronal numbers can be similarly addressed; neurons probably need to be connected to survive in the adult brain (Cowan et al., 1984), so that any change in neuron number must be accompanied by appropriate changes in neuropil and therefore in connections. Alteration in the number of neurons in lesional areas has been reported based on qualitative analysis in both pachygyria (Stewart et al., 1975) and polymicrogyria (Dvorak et al., 1978; Sarnat, 1992), but, to our knowledge, there are no stereological quantitative analysis of cell numbers in CD to confirm this. Indeed, experimental alteration in the number of neurons during various stages of development does not seem to lead to abnormalities of gyration (Langman and Shimada, 1971). There remain patients with abnormal surface area derivatives in whom analysis is limited. Patient 3, for example, has a visually abnormal right hemisphere, with reduced distant connectivity suggested by the low SMV, and reduced interhemispheric connectivity suggested by the low CCA. The ECC ratio is high in the contralateral hemisphere, detecting the extensive connectional disturbance that affects the apparently normal hemisphere if interhemispheric transfer is reduced. Patients 5, 10 and 13 all have subependymal heterotopia, with additional dysgenesis in Patients 5 (subcortical heterotopia) and 13 (unilateral limited posterior macrogyria). All three of these patients appear to have connectional abnormalities as they all have an abnormal ECC ratio, two in visually normal hemispheres, including one patient who does not have any block abnormalities. Patient 14 also has an abnormal ECC ratio bilaterally, although the dysgenesis is limited, on inspection, to the right parietal region. However, further interpretation is not possible from the available results. In a further four patients, the surface area derivatives are normal, though in three there are block abnormalities. Only one patient has no abnormalities of either blocks or surface area derivatives. This suggests that the two methods of quantitative analysis examine different aspects of cerebral structure. The nature of CD The analysis of the surface area derivatives in the patients has revealed structural abnormalities in seven out of 11 hemispheres that, on routine inspection, appeared completely normal, in the same fashion that regional volumetric analysis has revealed changes in apparently normal hemispheres (Sisodiya et al., 1995). This provides further evidence for the hypothesis that CD may extend beyond visualized boundaries. The actual form of the disruption in visually normal regions of the brain may not necessarily fall into a currently recognized histopathological variety of dysgenesis, such as polymicrogyria, for example. In its broadest sense, dysgenesis means abnormal formation and whether this includes qualitative disruption of anatomy, or a quantitative change, 279 is a matter of semantics and the level at which disruption is considered. Purpura (1974) and Huttenlocher (1974), who studied mentally retarded patients with and without epilepsy, respectively, used Golgi staining to demonstrate abnormal synaptic development in hemispheres judged normal on inspection and routine microscopy. These changes may be considered dysgenetic because they are likely to be due to abnormal development. Additionally, their work supports the connectional basis of some forms of structural abnormality, with alteration in neuropil morphology and dendritic spine number; neuronal architectural changes, suggestive of connectional abnormalities in dysgenesis, are also seen in pachygyria (Bordarier et al., 1986; Takada et al., 1994) and polymicrogyria (Ferrer, 1984). It might be argued that the changes found are due to epilepsy rather than associated with its cause. However, there is no significant difference within the patient group between those with surface area derivative abnormalities and those without, in terms of the duration of epilepsy or the history of secondarily generalized seizures. Block-volume abnormalities, it has been shown, are also unlikely to be due to epilepsy (Sisodiya et al., 1995). The changes seen are unlikely to be epiphenomena and are likely to be associated with pathogenic structural abnormalities. Conclusions The results show that order, present in normal cerebral hemispheres and manifest as proportions of quantitative parameters, may be disrupted extensively in patients with cerebral dysgenesis. The changes in surface area parameters predicted from the known histopathology of polymicrogyria are seen in patients presumed to have this condition. The interpretation of the quantitative results in polymicrogyria differs from that in non-polymicrogyric pathology on theoretical grounds and may be useful in identifying cortical thickening that is non-polymicrogyric in nature. In 64% of cases, abnormalities of surface area derivatives were found in visually normal hemispheres, supporting the hypothesis that cerebral dysgenesis is an extensive disorder. Our results also support the hypothesis that in humans this extension of dysgenesis is associated with connectional abnormalities, as seen in 60% of our cases. The regionalization of surface area measures may allow further analysis, possibly revealing localized (and possibly multifocal) abnormalities that are swamped by quantitatively dominant normal cortex (as seen with regional measures of GMV and SMV), and may thus help in the analysis of the eight out of 20 patients who have no surface area derivative abnormalities, though the existence of abnormal connectivity patterns is suggested in seven of the eight by abnormal regionalized volume measures (abnormal blocks). It may also allow better correlation of area changes with predicted pathology: thus regional analysis of patients with bilateral perisylvian syndrome (known to be polymicrogyric in nature) or familial lissencephaly may allow confirmation of the 280 S. M. Sisodiya and S. L. Free interpretation of the changes in surface-area derivatives, without recourse to post-mortem studies. 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