Volumetry of Hippocampus and Amygdala with High-resolution MRI and Three-dimensional Analysis Software: Minimizing the Discrepancies between Laboratories

J.C. Pruessner, L.M. Li, W. Serles, M. Pruessner, D.L. Collins, N. Kabani, S. Lupien and A.C. Evans

McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada


    Abstract
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Notes
 References
 
Within the medial temporal lobe, both the hippocampus and amygdala are frequently targeted by researchers and clinicians for volumetric analysis based on magnetic resonance imaging (MRI). However, different data acquisition techniques, analysis software and anatomical boundaries have in the past made it difficult to compare results of MRI studies from different laboratories. In order to reduce these differences, a segmentation protocol was established with 40 healthy normal control subjects recently scanned in our laboratory. Data acquisition was performed with a three-dimensional gradient echo technique, and scans were corrected for non-uniformity and registered into standard stereotaxic space prior to segmentation. Volumetric analysis was performed manually using three-dimensional software that allows simultaneous analysis of sagittal, coronal and horizontal images. Intra- and inter-rater coefficients yielded correlation coefficients comparable with other protocols. The hippocampal volume was larger in the right hemisphere (3324 versus 3208 mm3), while no interhemispheric differences for the amygdala (1154 versus 1160 mm3) could be observed. Most importantly, results from recent segmentation protocols for hippocampus and amygdala seem to approach each other with regard to mean volumes and interhemispheric differences. This indicates that the advances in scanning technique, volume preparation and segmentation protocols allow a more precise definition of medial temporal lobe structures with MRI, and that results for mean volumes for hippocampus and amygdala from different laboratories will eventually become comparable.


    Introduction
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Notes
 References
 
Medial temporal lobe structures play an important role in learning, memory and emotion (LeDoux, 1989Go; Nagy et al., 1996Go; Squire and Zola, 1996Go). These structures are also involved in a number of neurological and psychiatric disorders, including epilepsy, schizophrenia, depression and Alzheimer's disease (Cendes et al., 1993Go; Coffey et al., 1993Go; Jacobsen et al., 1996Go; Killiany et al., 1993Go). In particular, hippocampus (HC) and amygdala (AG) are related to these diseases, and are crucial for normal functioning. Magnetic resonance imaging (MRI)-based volume quantification of HC and AG has been established as a research tool to investigate the contribution of these structures to the onset and course of the above-mentioned disease states (Bogerts et al., 1990Go; Jack, 1994Go; Bremner et al., 1995Go; de Leon et al., 1996Go; Sheline et al., 1996Go). In addition, as the availability of MRI increases, its utilization is no longer restricted to clinical studies; it is now being introduced to adjacent fields (e.g. psychology), with the aim of investigating relationships between brain structures and, for example, memory processes, emotion and personality (Sullivan et al., 1995Go; Seidman et al., 1997Go;Mori et al., 1999Go).

Although results from these studies continue to provide important findings and broaden the knowledge of the function of these and other structures in the brain, comparing results between different laboratories is limited due to several reasons.

First, since the introduction of the MRI-based segmentation technique, laboratories have varied in their specific image acquisition protocols, with differences in pulse sequence parameters and slice thickness. Today, most of the laboratories involved in HC and AG volume quantification employ T1 images, although the exploratory use of T2 or proton density (PD) images is also recognized (Pucci et al., 1998Go). Furthermore, three-dimensional image acquisition protocols have become the standard method for image acquisition and have replaced the two-dimensional image sets. This has led to improvements in image precision, resolution and contrast, and reductions in slice thickness. Although it has been suggested that these differences do not necessarily result in systematic changes of mean HC and AG volumes between laboratories, they must be taken into account when comparing results from different research groups (Jack et al., 1995Go; Laakso et al., 1997Go).

Second, different research groups have employed different methods for quantification of specific medial temporal lobe volumes in the brain. In addition to the widely used method of manually tracing the boundaries of the specific structure in subsequent slices and calculating the volume within the traced structure, some groups have investigated alternative approaches. These methods include tracing and calculating the volumes from dimensional brain mapping or surface tessellation (Arndt et al., 1994Go; Csernansky et al., 1998Go). The comparability of these methods with manual segmentation has yet to be demonstrated.

Third, research groups use different software packages to trace the target structure. Most of the softwares employ a two-dimensional visualization of the brain images, without the possibility of adjusting resolution or image contrast (Watson et al., 1992Go). On the other hand, fully scalable three-dimensional imaging is also available, allowing for precise display and enlargement of regions of interest in coronal, saggital and horizontal orientations (Csernansky et al., 1998Go). As pointed out by Jack, differences in the calculating algorithms of these programs might further enhance interlaboratory variability (Jack et al., 1995Go).

Finally, differences in definition of HC and AG borders from different research groups have hindered the comparison of results. Existing segmentation protocols differ in their definition of the posterior boundaries of the HC, the delineation between HC and AG, and the anterior boundaries of the AG (Cendes et al., 1993Go; Kates et al., 1997Go). This in part reflects the ongoing neuroanatomical debate about the delineation of HC and AG. Due to these divergent definitions, even though it is possible to approximate technical differences, some inconsistencies can be expected to remain in the future.

We report here data from manual HC and AG segmentation in 40 healthy adults with a three-dimensional data acquisition protocol (Mazziotta et al., 1995Go). Analysis of the images was performed with a special software package that allowed simultaneous three-dimensional visualization of brain structures. Moreover, with the improved visualization of the structures, a more precise definition of HC and AG borders was possible. With improved definitions, it is believed that different research groups will eventually converge on the HC and AG mean volumes in normal populations.


    Materials and Methods
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Notes
 References
 
Subjects and Sociodemographic Assessment

A total of 40 brain volumes (20 male and 20 female subjects) were employed for this study. All subjects recruited for MRI scanning were healthy normal controls. Information of age, gender, neurological and psychiatric condition was obtained directly from the subjects. The subjects were aged 18–42 years (mean age 25.45 ± 5.4 years). None of the subjects had a history of neurological or psychiatric conditions. All subjects were right-handed. Neurological and psychological information was obtained with a computerized self-report described in detail elsewhere (Giedd et al., 1996aGo,bGo).

MR Image Acquisition

The scans were collected as part of the ongoing ‘International Consortium of Brain Mapping’ (ICBM) initiative to create a statistical atlas of the normal adult brain (Mazziotta et al., 1995Go). In short, this protocol generates T1, T2 and PD-weighted image volumes with a slice separation of 1 mm. The T1 volumes were acquired using a three-dimensional spoiled gradient echo acquisition with sagittal volume excitation (TR = 18, TE = 10, flip angle = 30°, 140 1 mm sagittal slices). The rectangular field of view (FOV) for the sagittal images was 256 mm (SI) x 204 mm (AP). For the purpose of this study, only the T1-weighted acquisition scans were used.

MR Image Analysis

All images were transferred to a Silicon Graphics O2 workstation (Silicon Graphics, Mountain View, CA). A combination of different algorithms was used to prepare the raw MRI volumes for manual segmentation. This process included correction for magnetic field non-uniformities (Sled et al., 1998Go), linear stereotaxic transformation (Collins et al., 1994Go) into coordinates based on the Talairach atlas (Talairach and Tournoux, 1988Go) and resampling onto a 1 mm voxel grid prior to image segmentation using a linear interpolation kernel (Mazziotta et al., 1995Go). It has been shown that the automatic stereotaxic transformation is as accurate as the manual procedure, but shows higher stability (Collins et al., 1994Go). Also, the correction for field non-uniformities has been proven to recover most of the image artifacts (Sled et al., 1998Go).

Volumetric analysis was performed with the interactive software package DISPLAY developed at the Brain Imaging Centre of the Montreal Neurological Institute. This program allows simultaneous viewing of volumes in coronal, sagittal and horizontal orientations. Due to the contiguous 1 mm slices, the investigator can navigate through the brain in 1 mm intervals in coronal, sagittal and horizontal orientations. Volumes of labeled structures are calculated automatically by the software. Regions of interest can be edited manually and semiautomatically by thresholding the image. The program also allows three-dimensional surface rendering and interactive manipulation.

Assessment of HC Volume

The HC is a bilaminar formed structure, located symmetrically in the medial temporal lobes of both hemispheres. It can be subdivided in an anterior part, which is referred to as head (HH), a medial part, often referred to as body (HB), and a posterior part, or tail (HT). Each part of the HC shows marked differences in form and structure. Classification of the HC included all three components.

The coronal plane was used as default view for labeling. References to sagittal or horizontal orientations were made whenever these were felt to prove more valuable for identification of structure boundaries.

The HT was defined as including the dentate gyrus, the cornu ammonis (CA) regions, the part of the fasciolar gyrus that is adjacent to the CA regions, the alveus and the fimbria. The Andreas–Retzius gyrus (ARG), the part of the fasciolar gyrus (FG) that is adjacent to this gyrus, and the crus of the fornix were omitted from the HT. The most posterior part of the HT was found in the slice where an ovoid mass of gray matter started to appear inferiomedially to the trigone of the lateral ventricle (TLV; see Fig. 1aGo). Laterally, the HT at this point is attached to the TLV. For a consistent segmentation approach in this area, two rows of gray matter pixels were excluded laterally, assuming that they represent parts of the TLV. Medially, the border of the HT is easy to identify by white matter (Fig. 1bGo).



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Figure 1.  In Figures 1–6GoGoGoGoGoGo the following abbreviations are used: AC, ambient cistern; AG, amygdala; ARG, andreas retzius gyrus; cfx, crus of the fornix; EC, entorhinal cortex; FCSI, fundus of the inferior portion of the circular sulcus of the insula; FG, fasciolar gyrus; HB, hippocampal body; HH, hippocampal head; HT, hippocampal tail; IHLV, inferior horn of lateral ventricle; LV, lateral ventricle; MTL, medial temporal lobe; OT, optic tract; QG, quadrigeminal cistern; sbcm, subiculum; TLV, trigone of lateral ventricle; URIHLV, uncal recess of inferior horn of lateral ventricle. (a) Coronal section of the MTL; first appearance of the HT inferiomedial to the TLV. (b) Horizontal section of the MTL; the tip of the HT anterior to the LV.

 
In the adjacent anterior slices of the coronal view, special care was taken to discriminate the tail of the HC from the FG and ARG, which lie medially to the tail of the HC and are attached to the quadrigeminal cistern (QC). Since these gyri appear as gray matter in the T1 images, they were indistinguishable from the tail of the HC. As a consequence, an arbitrary border between HT and ARG was employed by drawing a vertical line from the medial end of the TLV down to the parahippocampal gyrus. Another arbitrary border was defined for the superior border of HT. This part is often difficult to discriminate from the crus of the fornix (cfx), which also appears as gray matter attached to the TLV. In order to prevent inclusion of this structure, a horizontal line was drawn from the superior border of the QC to the TLV. Both arbitrary borders are shown in Figure 2aGo. Although these procedures could sometimes have led to an exclusion of medial and superior parts of the HT, this approach seemed to be the most consistent for labeling of the HT. The inferior border of the HT is easy to identify by the transition of gray to white matter (Fig. 2bGo).



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Figure 2.  (a) Coronal section of the MTL; discrimination of HT from ARG and FG and cfx by employing arbitrary borders. (b) Sagittal section of the MTL; the HT and its superior and inferior borders. Note the clearly visible white matter inferior to the HT.

 
Laterally, the HT had to be discriminated from the inferior horn of the lateral ventricle and the tail of the caudate nucleus. In order to ensure the exclusion of these structures, two rows of pixels with gray matter were consistently rejected on the lateral side (Fig. 2aGo).

Moving further anteriorly, the gray matter of the HT descended in the coronal slices. Next, the HB is reached, whose superior and inferior borders are clearly perceptible in the sagittal orientation (Fig. 3bGo). In coronal orientation, HB and entorhinal cortex (EC) consist of several parts that fold onto each other to form an S-shaped structure (left HB; Fig. 3aGo) or an inverted S-shaped structure respectively (right HB). The upper half of this S-like structure (from inferior to superior) includes the subiculum, the four CA regions, the dentate gyrus and the fimbria. Subiculum, CA regions and dentate gyrus are gray matter; the fimbria consists of fiber connections and thus appears as white matter. Inferior to these hippocampal structures is the parahippocampal gyrus. Its most superior layer sometimes blends into the CA regions and thus complicates the labeling process.



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Figure 3.  (a) Coronal section of the MTL; segmentation of the HB. (c) Sagittal section of the MTL; delineation of the fimbria as superior border of the HB.

 
At this point, the following landmarks of the HB were employed for labeling. First, the most visible inferiolateral layer of gray matter was excluded, assuming that it actually represents parahippocampal gyrus. Next, the fimbria was included in the HB. It is located at the superomedial level of the HB and is identified as white matter in the image. In addition, if gray matter appeared superior to the fimbria, the first row of gray matter pixels was also included in the segmentation of the HB. It can be assumed that this row of gray matter still comprises HC cells, since the fimbria at this point is sometimes partly embedded in the CA2 or CA3 region. The sagittal view of the MRI images offers the best visualization of this superior border of the HB (Figs 2bGo, 3bGo). Finally, the dentate gyrus, located in between the four CA regions in the hippocampal formation, together with the CA regions themselves and the subiculum, were included. Separating the subiculum from entorhinal cortex proved difficult since the images usually did not show any differences in intensity between these structures. However, in order to maintain a consistent approach to differentiating these two structures, a straight line with an angle of ~45° was drawn from the most inferior part of the HB medially to the cistern (Figs 3aGo, 4a,bGo). In cases where the subiculum was more detached from entorhinal cortex, and thus a line of white matter was visible between the two structures, this line was employed as border for the HB (Fig. 5aGo). The lateral border of the HB was identified by the inferior horn of the lateral ventricle or the caudally adjacent white matter. For consistency across subjects, one row of pixels of gray matter was excluded from the CA regions at this point, assuming it represented the lateral ventricle, if the ventricle was not itself visible (Fig. 4a,bGo). In most cases, the superior excess of the quadrigeminal cistern could easily be identified as the superomedial border of the HB. For reasons of consistency, the last row of pixels of gray matter was excluded medially from the HB, assuming it actually represented part of the cistern (Fig. 4a,bGo).



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Figure 4.  (a) Coronal section of the MTL; anterior end of the HB; note that the lateral, superior and inferior borders are identical to the beginning of the HB.

 


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Figure 5.  (a) Coronal section of the MTL; arbitrary landmark for the superior border of the AG and disappearance of the HH; note that due to the visibility of the border between sbcm and EC, no straight line is drawn to the QC. (b) Horizontal section of the MTL; delineation of AG and HC by IHLV and alveus.

 
Moving further anteriorly, one reaches the HH. The first coronal slice showing the HH can be identified by the emergence of the uncal recess of the HH in the superomedial region of the HC. The borders of the HH are the most difficult to identify. In the superior part of the HH, gray matter is a mixture of amygdala, HC and basal ganglia (putamen and globus pallidus). The most important structure for identification of lateral, anterior and superior borders of the HC was the uncal recess of the inferior horn of the lateral ventricle. Also, the alveus served as landmark for definition of the superior and anterior border of HC (Fig. 4bGo). However, if visible, the alveus itself was not defined as the border of the HH; the HH continued one additional row of pixels anterior to this structure. The sagittal view was employed for identification of the anterior border, since the alveus could often be better identified in this plane. The horizontal view was consistently employed in addition to the coronal and sagittal views for demarcation of the anterior and medial borders of the HC (Figs 5bGo, 6a,bGo). In this particularly difficult region the constant reference to all dimensions was felt to be the best approach. The medial and inferior borders were identified in the same way as in the body of the HC, including subiculum, the four CA regions and the dentate gyrus. In the superomedial part, the HH often forms a distinct protuberance, which can be best identified in the coronal plane (Fig. 4bGo). Also, the uncal cleft often served as an excellent marker of the inferior border of the HH.



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Figure 6.  (a) Horizontal section of the MTL; delineation of AG and HC by IHLV alveus, and URIHLV. (b) Horizontal section of the MTL; inferior portion of HC and AG; delineation of AG and HC by IHLV and URIHLV.

 
Assessment of AG volume

The AG is an olive-shaped mass of gray matter located in the superomedial part of the temporal lobe, partly superior and anterior to the HH. The AG has a less complex structure than the HC. However, due to its position in the superomedial temporal lobe with parts of the basal ganglia from superior and entorhinal cortex from inferior blending in, definition of AG borders in MR images proves difficult. Anatomically, the AG can be separated into several distinct nuclei. In its superomedial part, the cortical amygdaloid nucleus can be identified as a distinct protuberance, often itself separated into a dorsal and ventral part. Superomedially, the endorhinal sulcus separates the cortical amygdaloid nucleus from the substantia innominata. Laterally, the gray matter of the AG blends together with the ventral putamen, and is not clearly separated by the amygdalo-striatal transition area. Inferomedially, the AG can be separated from the entorhinal cortex by the intrarhinal sulcus, or tentorial indentation, which forms a marked indent at the site of the inferior border of the AG. Inferolaterally, the temporal horn of the lateral ventricle separates the AG from adjacent structures. However, the anatomical landmarks can often only partly be identified in MR images, and as a consequence different borders have to be employed for the segmentation of this structure.

The posterior end of the AG was defined in the coronal plane, at the point where gray matter first started to appear superior to the alveus and laterally to the HH (Fig. 4bGo). If the alveus was not visible, the inferior horn of the lateral ventricle was employed as border. The superior border of the AG was arbitrarily defined by drawing a horizontal line between the superolateral part of the optic tract and the fundus of the inferior portion of the circular sulcus of the insula. This allowed a consistent approach for the definition of the AG, although small amounts of the medial and central nuclei of the AG were excluded (Fig. 5aGo). This approach prevented erroneous inclusion of parts of putamen and claustrum in the amygdaloid measurement. In some cases, the superior border of the AG could be identified despite the fact that it was blending in with the gray matter of putamen. In these cases, a small layer of white matter divided the AG from the adjacent structures. If this layer was identifiable, it was used as the superior border of the AG.

The horizontal view was used to identify the medial and lateral border. In the posterosuperior section of the AG, the medial border was easily identifiable since it is attached to the border of the ambient cistern at this point. In order to have a consistent approach for labeling, one layer of gray matter directly adjacent to the cistern was omitted, assuming that a clear separation from the cisternal area is impossible. Further anterior and inferior, entorhinal cortex (EC) blends into the AG medially. If possible, these structures were identified in the horizontal view and excluded from the AG. If the EC could be identified in the horizontal view, it was excluded from the AG. If the EC was not visible in more than two consecutive slices, a semicircle drawn from the lateral end of the lateral ventricle to the alveus was employed as an arbitrary landmark but allowed for a consistent labeling approach (Fig. 5bGo). If the alveus was not visible, the uncal recess of the inferior horn of the lateral ventricle was used instead (Fig. 6a,bGo).

The lateral border of the AG was defined by the lateral half of the semicircle drawn from the uncal recess of the inferior horn of the lateral ventricle medially to the inferior horn of the lateral ventricle laterally, viewed horizontally. Again, if the uncal recess of the inferior horn of the lateral ventricle was not visible, the alveus was employed. If neither of the two structures was visible in the horizontal view, the slices adjacent to the current slice were employed for identification of these structures (Figs 5bGo, 6a,bGo).

For the inferior border of the AG, coronal images were employed for best separation. The tentorial indentation served as a demarcation line between AG and entorhinal cortex, by excluding the gray matter inferolateral to the indentation. The anterior border of the AG, finally, was defined at the level of the closure of the lateral sulcus. This closure could easily be identified in horizontal sections without great difficulty. Although the setting of this border might have led to the exclusion of parts of the anterior cortical amygdaloid nucleus, it was chosen for reasons of consistency across brain images.

Reliability Assessment

Of the 40 subjects, five randomly chosen subjects were analyzed by four different raters. Interrater reliability for these five subjects was then calculated using Intraclass correlations (Shrout and Fleiss, 1979Go), assuming that the four raters were the only raters of interest.

To assess intrarater reliability, one of the four raters (J.C.P.) subsequently labeled HC and AG of the same five subjects five times, with a 1 week interval between ratings. Intrarater reliability was calculated using the same method as described above. This rater performed hippocampal and amygdaloid segmentation of the remaining 36 subjects in this study. All raters were blind to subject age and gender, but not to left and right hemisphere.

Statistical Analysis

For description of hippocampal and amygdaloid volume in the 40 subjects, the minimum and maximum volume, mean and standard deviations were calculated for the whole group, and separately for men and women. In order to evaluate putative differences between left and right hippocampal and amygdaloid volumes, and gender differences, a two-factor (gender by hemisphere) within ANOVA was calculated with the hippocampal and amygdaloid volumes as dependent variables. In order to investigate whether the transformation into Talairach space had an effect on interhemispheric differences or gender differences, all calculations were also performed with the native volumes. The formula for transformation of the volumes back into native space is [standard volume = stereotaxic volume/(x x y x z)], where x, y and z are the scaling factors of the linear transformation.

The power of all statistical tests was calculated, using the formulas provided by Cohen (Cohen, 1988Go). These calculations tested the probability of finding an existing population effect in this sample of subjects, given different effect sizes.


    Results
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 Abstract
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 Materials and Methods
 Results
 Discussion
 Notes
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The results of the intraclass calculations for reliability measurement are shown in Table 1Go. In the five subjects that were rated by four different raters, the differences between the raters ranged between 1.8% (right HC) and 5% (right AG); the intrarater variability for these five subjects was in the range of 2.2% (right AG and HC) to 2.5% (left amygdala).


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Table 1 Inter- and intrarater intraclass reliability coefficients
 
Minimum and maximum volume, mean values and standard deviation for the right and left hippocampal and amygdaloid structures in standard stereotaxic as well as in native space for the whole group of n = 40 are shown in Table 2Go. Results from the two factor within ANOVA for the stereotaxic volumes showed no effect of gender on the HC (F < 1; df = 32; P > 0.20), but indicated a significant difference between right and left hippocampal volume (F = 5.9; df = 32; P = 0.02). A Scheffé post-hoc test indicated that the right HC was bigger than the left (4395 versus 4243 mm3 in stereotaxic space). The interaction between gender and hemisphere for the HC was not significant.


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Table 2 Minimum and maximum, mean and standard deviation (SD) for the right and left hippocampal and amygdaloid structures (n = 40)
 
No differences were found for the AG with regard to gender and left and right hemispheric volumes in stereotaxic space (all main effects with F < 1; df = 32; P > 0.20). The interaction between left and right AG and gender was also not significant (F = 1.8; df = 38; P = 0.20). There was no significant age difference between men and women in this sample (women 26.2 ± 7.1 years; men 24.7 ± 4.2 years; t < 1; df = 38; P > 0.20).

The results from the ANOVA in native space revealed the same hemispheric difference (F = 5.8; df = 32; P = 0.02) with regard to HC volume, but in addition also showed a significant gender difference (F = 4.3; df = 32: P = 0.03). The gender by hemisphere interaction was again not significant (F < 1, P > 0.20). A Scheffé post-hoc comparison indicated that again the right HC was bigger than the left (3324 versus 3208 mm3), and that men had a bigger HC than women (3521 versus 3011 mm3). For the AG, the ANOVA performed with the native space volumes revealed a similar picture: as with the stereotaxic volumes, there was no hemispheric difference for the AG (F < 1, P > 0.20), but again, in contrast to the stereotaxic volumes, an effect of gender appeared (F = 7.5; df = 38; P = 0.01). The interaction between gender and interaction was not significant (F < 1, P > 0.20). Again, the men had bigger AGs than the women in native space (Scheffé post hoc, 1247 versus 1065 mm3).

Computation of the power for the tests for the AG and HC showed a {lambda} = 13. Given an {alpha} = 0.05, the chance of revealing an existing population effect in this group was t = 0.95, assuming a population effect size of f2 = 0.25. Assuming a smaller population effect of f2 = 0.10, however, the chance to reveal a significant difference between men or women with regard to HC or AG volumes in stereotaxic space, or to reveal a significant difference between the hemispheres of AG structures in this group decreased to t = 0.50. Computation of the size effect for the reported hemispheric difference between left and right HC volume revealed a f2 = 0.29. Thus, the hemisphere accounted for 22% of the variability found in the HC volumes (w2 = 0.22).


    Discussion
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Notes
 References
 
The present study describes a protocol for manual segmentation of HC and AG structures using high-resolution, uniform and standardized T1 MR images of 1 mm slice thickness. The three-dimensional analysis software allowed simultaneous employment of coronal, transverse and sagittal images for visualization and segmentation. The results indicate that with three-dimensional visualization, the irregularly shaped HC and AG can be reliably and precisely segmented. It is believed that this protocol presents a number of refinements compared to earlier segmentation protocols.

First, the differentiation between anterior HC and AG has proven to be a consistent problem for recent MRI protocols. The layer of the alveus divides these gray matter structures from each other medially, and the inferior horn of the lateral ventricle divides them laterally. Both structures are irregularly shaped in that region. In addition, the posterior part of the AG is partly overlapping the anterior part of the HC head, thus additionally complicating a precise segmentation, especially with a two-dimensional approach. It is felt that with simultaneous employment of all three dimensions together with the three-dimensional cursor, segmentation can be cross-validated in the different planes, thus allowing a more consistent approach. In the horizontal view the inferior horn of the lateral ventricle could be identified laterally and the thicker end of the alveus medially, which made differentiation between HC and AG possible in many images. This could be cross-validated in the coronal and sagittal views by identifying alveus and inferior horn of the lateral ventricle as the superior and anterior border of the HC. When neither of the two structures was visible in one slice, adjacent images usually provided sufficient information to allow a consistent approach for delineation of the boundaries (Bartzokis et al., 1998Go).

In comparison, protocols from other laboratories show an inconsistent approach for segmentation of this region. Some protocols avoided the delineation of the HC/AG borders completely and used a combined segmentation of the two structures (Bogerts et al., 1990Go, 1993Go; Breier et al., 1992Go; Becker et al., 1996Go). Alternatively, some protocols excluded the HH completely from the HC segmentation (Ashtari et al., 1991Go; Spencer et al., 1993Go). Other protocols employed arbitrary landmarks to find a consistent approach to segmentation of that region. Arbitrary landmarks for the anterior border of the HC included the mammillary body (Shenton et al., 1992Go; Jacobsen et al., 1996Go), the superior colliculi (Bremner et al., 1995Go) or the superior choroidal fissure (Lencz et al., 1992Go). Most of the more recent protocols correctly defined the alveus or the inferior horn of the lateral ventricle as separation of the AG from the HH (Cook et al., 1992Go; Watson et al., 1992Go; Cendes et al., 1993Go; Jack et al., 1995Go; Hasboun et al.,1996Go; Mori et al., 1997Go; Bartzokis et al., 1998Go; Strakowski et al., 1999Go). However, identification of these two structures simultaneously in protocols using a two-dimensional software is difficult since the structures are shifted sidewards (Watson et al., 1992Go; Becker et al., 1996Go; Hasboun et al., 1996Go). Instead, with the three-dimensional software analysis tool of this protocol, the tilted and shifted demarcation structures can be excellently visualized and followed, which allows a better segmentation of the HC and AG borders.

Another problem area can be found in the demarcation of the HT. Protocols differ from each other by the amount of gray matter that is included in the HT adjacent to the trigone of the lateral ventricle. Suggestions for the definition of this posterior border can be roughly divided into two categories. The first category contains definitions that are based on arbitrary landmarks. Examples from this category include ‘the slice that is 3 mm anterior to the superior colliculi’ (Spencer et al., 1993Go), ‘the slice where the mammillary bodies can be seen in full profile’ (Becker et al., 1996Go), ‘the slice that is 60 mm posterior to the Anterior Commissure’ (Marsh et al., 1997Go), ‘the slice that shows a bifurcation of the basilar artery’ (Bremner et al., 1995Go), or ‘the slice at which the internal auditory canal appears’ (Reiss et al., 1994Go).

Protocols in the second category include the fornix in their definition of the posterior border of the HC. Examples from this category are ‘the slice where the crus of the fornix can be seen in full profile’ (Hasboun et al., 1996Go; Mori et al., 1997Go), ‘the slice where the crus of the fornix separates from the HC’ (Watson et al., 1992Go; Honeycutt and Smith, 1995Go), ‘the slice where the fornices are still detectable in their full length’ (Soininen et al., 1994Go), ‘the slice where the fibers of the crus of the fornix last appear’ (Shenton et al., 1992Go), or ‘the slice where the bulk of the splenium of the corpus callosum fuses with the fornix’ (Kates et al., 1997Go).

Again, with the protocol described here, it is believed that the simultaneous view of the posterior part of the HT in all three dimensions allows for a more precise segmentation. The gray matter of the HT was followed in the coronal plane and cross-validated in the horizontal and axial planes. Thus, the posterior border of the HT was defined as the first appearance of gray matter inferiomedial to the trigone of the lateral ventricle, which is believed to be an accurate demarcation of the HT.

The clearest benefit of this three-dimensional protocol emerged in the segmentation of the anterior AG, where the single use of the coronal view proved particularly deficient in the past. Protocols unable to employ three-dimensional analysis software generally depend upon the identification of arbitrary landmarks for segmentation. Unfortunately, no standard has developed as to which landmark should be used to demarcate the anterior border of the AG, resulting in a wide variety of outcomes. Landmarks defined by other protocols include ‘the closure of the lateral sulcus to form the endorhinal sulcus’ (Watson et al., 1992Go), ‘the white matter tract linking the temporal lobe with the rest of the brain’ (Shenton et al., 1992Go), ‘the anterior end of the uncal portion ventral to the amygdala’ (Soininen et al., 1994Go), ‘the most anterior portion of the temporal stem which appears as thickening of gray matter’ (Mori et al., 1997Go), ‘the anterior commissure’ (Kates et al., 1997Go), or ‘the slice where the amygdala is 2.5 times thicker than the adjacent entorhinal cortex’ (Strakowski et al., 1999Go).

It is felt that the simultaneous use of the horizontal, coronal and (to a smaller extent) sagittal view in this region allowed a more adequate definition of the medial, anterior and lateral borders of the anterior part of the AG, making references to arbitrary landmarks obsolete. In the horizontal view, the anteriomedial border of the AG often could be traced from the medial end of the alveus, describing a half-circle until it fused on the lateral side with the lateral end of the inferior horn of the lateral ventricle.

With regard to intraclass intra- and interrater reliability coefficients, this protocol produced results comparable to other studies (Becker et al., 1996Go; Marsh et al., 1997Go; Mori et al., 1999Go; Strakowski et al., 1999Go). However, since the utilization of arbitrary landmarks was minimal, there were higher chances for measurement errors in this protocol. It can be expected that the use of easily identifiable arbitrary landmarks in other studies facilitated the segmentation process. This facilitation might have resulted in lower measurement errors across different raters, but at the same time might have impaired the validity of the segmentation. Taking this into account, the intraclass interrater coefficients reported here in the range r = 0.83–0.94 indicate a good accordance between raters.

Regarding the relative volumes of the targeted structures, the comparison of left and right HC and AG volumes revealed a significantly larger right HC volume and no differences in the AG volume. This holds true for both the native as well as the transformed stereotaxic volumes. Earlier publications tended to be inconsistent with regard to volume differences. Very few protocols reported the left HC to be bigger than the right (Ashtari et al., 1991Go; Cook et al., 1992Go). The vast majority of the available protocols either reported a bigger right HC (Watson et al., 1992Go; Cendes et al., 1993Go; Hasboun et al., 1996Go; Jacobsen et al., 1996Go; Kidron et al., 1997Go; Marsh et al., 1997Go; Mori et al., 1997Go; Csernansky et al., 1998Go;) or no differences between left and right hemispheres (Bhatia et al., 1993Go; Honeycutt et al., 1995; Fox et al., 1996Go; Becker et al., 1996Go; Laakso et al., 1997Go; Schuff et al., 1997Go; Reiman et al., 1998Go; Strakowski et al., 1999Go). However, different populations studied and differences in anatomical boundaries have to be taken into account when comparing the results. Another possible explanation for the disagreement with regard to the reported hemispheric differences lies in the power of the statistical analysis. This information has merely been included in the reports from other laboratories in the past. Depending on the effect size of the actual left and right differences and the number of subjects studied, the chances of detecting those differences in some of the protcols might have been rather low. A call for cautious interpretation of the results from this study stems from the fact that the raters were not blinded with regard to the hemisphere. Although the raters were not aware of systematic hemispheric differences from other studies at the time of the segmentation, this introduced a potential subjectivity in the segmentation process that the reader should be aware of.

For the AG, only a few publications have reported mean volumes for this structure, or have tested for right and left hemispheric differences. As with the HC, results are inconsistent with regard to interhemispheric differences, reporting a bigger right AG (Watson et al., 1992Go), or no interhemispheric differences for that structure (Soininen et al., 1994Go; Mori et al., 1997Go; Strakowski et al., 1999Go). The reported mean volumes range from 1.15 cm2 (this protocol) to 3.4 cm2 (Watson et al., 1992Go). However, previous protocols that described AG measurement relied upon two-dimensional segmentation strategies and the use of arbitrary landmarks for segmentation. With the three-dimensional segmentation protocol employed here, no differences between this structure in the left and right hemisphere could be reported. It is possible that this is a result of the rather small number of subjects investigated in this study. The power calculations employed to calculate the chance of finding population effects of AG differences in this sample yielded a 95% chance for a medium population effect size to become apparent. Given a smaller population effect, however, the chance for detecting AG differences dropped to 50%. As a result, possible AG differences in normal healthy controls require further investigation in the future. A conclusion that can be drawn from this study is that possible AG differences between the left and right hemisphere, if they exist, will be rather small.

With regard to the relation between native and stereotaxic volumes, this study supports results from earlier studies. When uncorrected for head size, men tended to have larger medial temporal lobe structures than women. This was true both for HC and AG. Earlier studies from other laboratories also demonstrated gender differences that disappeared once the volumes were corrected for head size (Blatter et al., 1995Go; Raz et al., 1997Go, 1998Go).

The mean volumes for HC found in this study are in the range of volumes reported by other MRI protocols (Watson et al., 1992Go; Honeycutt and Smith, 1995Go; Kates et al., 1997Go). The reported mean HC volumes from other MRI studies show a wide range, varying from 1.23 cm3 (Bremner et al., 1995Go) to 5.68 cm3 (Bartzokis et al., 1993Go). As pointed out by Jack et al. (Jack et al., 1995Go), different structure boundaries, different correction and slice preparation methods, and different analysis methods can partly explain these differences. Thus, commenting on the results of other studies with regard to the mean volumes of the HC is limited to those studies where structure boundaries, image acquisition protocols and population are comparable. When restricting the comparison to those protocols, an interesting observation can be made. Over time, the reported inter- laboratory differences of HC mean volume constantly decreased, from over 100% difference in the early protocols [1.78 versus 5.68 cm3 (Suddath et al., 1990Go; Bartzokis et al., 1993Go)], to only ~30% today [3.2 versus 4.2 cm2 (Mori et al., 1999Go; Strakowski et al., 1999Go)]. Calculating a mean volume from published protocols comparable to our study with regard to age and population (i.e. only using the mean volumes from control groups when looking at clinical studies) yields a HC volume of 3.57 cm3, ~10% more than the mean volume reported in this study (Cook et al., 1992Go; Watson et al., 1992Go; Bartzokis et al., 1993Go, 1998Go; Bhatia et al., 1993Go; Cendes et al., 1993Go; Soininen et al., 1994Go; Honeycutt et al., 1995; Hasboun et al., 1996Go; Schuff et al., 1997Go; Mori et al., 1997Go, 1999Go; Csernansky et al., 1998Go; Ghanei et al., 1998Go; Laakso et al., 1997Go; Reiman et al., 1998Go; Strakowski et al., 1999Go). This convergence over time might be a result of refined segmentation protocols, higher-resolution images and more common structure boundaries between laboratories. It can be expected that three-dimensional software tools for segmentation of brain structures will be introduced to more laboratories, thus allowing superior visualization of structure boundaries (Csernansky et al., 1998Go; Freeborough et al., 1997Go; Hopkins et al., 1997Go). As a consequence, it is hoped that the results of different laboratories will eventually become comparable.

Calculating a mean volume for the left and right HC from histological studies results in values of 3.45 and 3.63 cm3 respectively, which is even less than 10% different from the results reported in this protocol for HC and AG volumes in native space (Kretschman et al., 1986; Bogerts et al., 1985Go; Heckers et al., 1990Go; Klekamp et al., 1991Go; Bogerts et al., 1993Go). However, it has to be kept in mind that employment of reported mean volumes from histological studies is restricted to those studies that corrected for the volume shrinkage of the brain.

In summary, these results suggest that the ‘true’ volume of the HC for normal healthy adults lies between 3 and 4 cm3, and that results from recent segmentation protocols are approaching this volume. If the advanced imaging and segmentation techniques continue to become available to other research groups as well, comparison of results from studies with similar subjects across laboratories will become a possibility in the near future.


    Notes
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Notes
 References
 
We thank Dr Tomás Paus for the discussion of the concept of the manuscript and two anonymous reviewers for their helpful comments. This work was supported in part by the International Consortium for Brain Mapping, the Human Brain Map Project, and the German Research Foundation (Pr597/1–1).

Address correspondence to Dr Jens Pruessner, McConnell Brain Imaging Centre, Montreal Neurological Institute, 3801 University Street, Montreal, Canada H3A 2B4. Email jens{at}bic.mni.mcgill.ca.


    References
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 Notes
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