Computerized localization of brain structures in single photon emission computed tomography using a proportional anatomical stereotactic atlas

Computerized Medical Imaging and Graphics, Vol. 18. No. 6, pp. 4 13422, 1994 Copyright 0 1994 Elsevier Science Ltd Printed in the USA. All rights reserved 0895-6 I I l/94 56.00 + .OO

Pergamon

0895-6111(94)00028-X

COMPUTEtRIZED LOCALIZATION OF BRAIN STRUCTURES IN SINGLE PHOTON EMISSION COMPUTED TOMOGRAPHY USING A PRdPORTIONAL ANATOMICAL STEREOTACTIC ATLAS 0. Migneco*‘, J. Darcourt*, J. Benoliel*, F. Martin’, Ph. Robert*,

F. Bussiere-Lapalus*, and I. Mena” *Service de Biophysique et de MCdecine Nuclkaire, Centre Antoine Lacassagne, University of Nice, France +Laboratoire d’Astrophysique, FacultC des Sciences, University of Nice, France ‘Service de Psychiatric et de Psychologie Mkdicale, Hopital Pasteur, University of Nice, France ‘Division of Nuclear Medicine, Harbor-UCLA Medical Center, Torrance, CA, USA (Received 9 December 1993; revised 23 May 1994)

Abstract-An accurate identification of cerebral structures is necessary to perform quantification of single photon emission computed tomography (SPECT). We have developed an anatomical localization system that accounts for individual brain shapes and sizes by using the Talairach proportional grid system. The locations of the commissural lines, which define the stereotactic coordinate system, are calculated from the external landmarks provided by the canthomeatal line. This is validated on MRI images. When applied to SPECK data, the use of a neuroanatomical atlas data along with the automaticity of the processing guarantees a high degree of objectivity and inter-observer reproducibility. Key Words: Localization. Brain SPECT, Stereotactic atlas

anatomy. Neuroanatomical atlases based on a fixed coordinate system (4) are inadequate as well, since they do not take into account the individual variability of brain anatomy even when computer-assisted techniques are applied (5, 6). To overcome these limitations, we developed a method which uses the Talairach Proportional Stereotactic Atlas (7, 8) and provides automatic HMPAO SPECT topographic analysis.

INTRODUCIION Hexamethylpropyleneamine oxime (HMPAO Ceretec, Amersham, Int.) is a 99mTc-labeled radiopharmaceutical that allows the assessment of regional cerebral blood flow using single photon emission computed tomography (SPECT). One of the goals of this technique is to provide quantitative data on specific cerebral regions perfusion. This is particularly needed when one wants to compare an individual to a normal data base or to correlate HMPAO regional uptake with other quantitative parameters such as psychometric evaluation in a series of patients. SPECT images can be paired with high resolution anatomical images such as magnetic resonance imaging (MRI) ( l-3). But this impl-ies an additional costly data acquisition and frequently the use of complex and uncomfortable head holders. Therefore, methods that do not require additional data acquisition should be preferred for clinical use. But the determination of anatomical regions of interest (ROIs) on SPECT images themselves is not satisfactory, whatever spatial resolution is obtained. In fact, the functional information provided by these images does not necessarily correspond to structural

DESCRIPTION

OF THE

METHOD

Main features Imaging and reconstruction protocol. Imaging was carried out with a conventional rotating gamma camera (General Electric 400 T) fitted with a low-energy, highresolution collimator. 128 projections of 25 s each were acquired over 360” using 64 X 64 pixel matrices. No zoom was used, and the corresponding pixel size was 6.3 mm. Reconstruction was performed by backprojection on a Sophy computer (Sopha Medical, France) using a ramp filter without additional low-pass filtering in order to preserve resolution as much as possible. No attenuation correction was used since no attempt was made to analyze deep structures, but only the cortical ribbon. Furthermore, at the end of the tomographic acquisition, the canthus and the tragus were marked on

I Correspondence should tie addressed to Octave Migneco, Service de Mkdecine NuclCaire, Centre Antoine Lacassagne, 36 voie Romaine, 06050 Nice Cedex I, France. 413

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a left lateral

view using a 57Co point source. At this time, the patient was in exactly the same position as during the tomographic acquisition.

Quantitative analysis. To quantify the data, we have developed a highly-reproducible ROI localization method that takes into account the individual variations of brain anatomy. This software has been programmed in FORTH on the SOPHY computer. A high reproducibility is achieved by automatic processing. The anatomic variations are taken care of by the use of the Talairach’s atlas. This atlas is based on three intra-cerebral baselines that keep relatively constant relationships with the telencephalic structures. These lines are: (a) A horizontal line joining the upper part of the anterior commissure (CA) to the lower part of the posterior commissure (CP) and extending to the frontal and occipital lobes (CACP); and (b) Two perpendicular vertical lines, one behind the CA: the VCA, and the other in front of the CP: the VCP. These two lines extend to the vertex and to the base of the temporal lobe. On these three baselines, the proportional localization system is built. It consists in a grid limited by the extreme points of the brain and subdivided in a constant number of rectangles. Taking into account the variations in the shape and size of the human brain, a constant number of rectangles means a variation of their areas. This way, the localization system fits each individual brain, and therefore it is called proportional. Once the proportional grid system is set on a particular brain, using the Talairach’s atlas, the telencephalic structures can be located by their stereotactic coordinates (Fig. 1). A major problem of this approach for our application is that the CA and CP are not identifiable in brain SPECT. We used neuroanatomical data provided by the literature (9) to calculate the location of the commissural lines from the external cantho meatal (CM) landmarks. This technique allows the localization of any brain structure outlined in the atlas and, therefore, the definition of the corresponding ROIs. For our application, we decided to define automatically the boundaries of the lobes and of the temporal gyri.

A

ABCDEFGHI

1

c

ABCDEFGHI Fig. 1. Localization of the cerebral structures in the Talairach atlas. (A) Localization of the CACP, VCA, VCP and of the extreme points of the brain. (B) Building of the Talairach’s proportional reference system. (C) Cerebral structures localization, example: Roland0 scissure.

There are three main steps:

Automatic definition of cerebral lobes boundaries The boundaries of the lobes are delineated on two “cortical lateral views” generated from the tomographic data. These two “cortical lateral views,” one for each hemisphere, are created only with the cortical pixels. They are two-dimensional projections of the three dimensional cortex data. Therefore, each pixel in these views is equivalent to a voxel.

Generation of two “cortical lateral views.” Definition of the proportional grid system. Modeling and delineation of the ROIs.

Generation of two “cortical lateral views. ”On the transverse cuts, the non-cortical pixels are eliminated with a semi-automatic technique. The pixels values inferior to 55% of the maximum count of the series of

Computerized localization of brain structures

images are set to zero. In order to make the cortex “peeling” independent of the reconstruction filter and to avoid the cortical regions with low blood flow (~55%) to be excluded, the 55% isocount is calculated on heavily-smoothed im!ages (Hann filter, cutoff frequency = 0.25 cycles/pixel). Then, it is applied on the cuts reconstructed with the filter chosen for the application. Nevertheless, a manual correction is available if the “peeling” is not optimal. Once the cortex has been isolated, the limit between the right and left hemisphere is manually marked. Afterwards, the transverse cuts are rearranged in sagittal cuts and added independently for each hemisphere (Fig. 2a). In the assumption that one hemisphere would take-up “cortical HMPAO in a uniform waty, the corresponding lateral view” should appear homogeneous. This is not the case, because of the .bend of the brain or the particular shape of some lobes. Therefore, a correction for the thickness of added cortex has to be applied. For this purpose, on the “cor;tical lateral views,” each pixel is divided by the number of non-zero pixels that were added to create it (Fig. 3).

Definition of the proportional grid system. The proportional grid system is built on the CACP, VCA, VCP. As previously said, the CP and the‘CA are not identifiable in brain SPECT. We used fixed anatomical relationships of the commissural lines with the canthomeatal (CM) external landmark. This line joins the canthus (external angle of the eye) and the upper part of the tragus, overlying the external auditory meatus. Despite the individual variability of bone references, Szikla (9) reported fairly constant relationship between CM and CACP lines. We used the average distance he measured on 50 subjects which are reported in the appendix. Using the left lateral view where the CM was marked at the end of the acquisition, the CACP, VCA and VCP are calculated Iby the computer and the two “cortical lateral views” are rotated in order to set the CACP horizontal. The extreme points of the brain are then easily defined manually by the operator. Therefore, the proportional grid system is set. Modeling and delmeation of the ROIs. The boundaries of the brain structures can be modeled as short, straight lines. The (equations of each line are defined in the relative reference system of Talairach. These equations are independent ofthe shape, size and position in the pixel matrix of the brain. The problem is to adapt these equations to a particular brain. This is possible by moving mathematically from the relative to the absolute reference system defined by the tomographic coordinate system. The relationships between the two systems are established by the previous step. Indeed, when the Talairach’s grid is calculated

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??

and positioned on the brain, its coordinates in the tomographic reference system are known. Therefore, the shift of the two reference systems can be performed. The new calculated equations are now characteristic of one particular brain. The delineation of the short, straight lines generates the ROIs. For each hemisphere, 5 ROIs are automatically delineated: frontal, parietal, temporal, occipital and cerebellar. An additional ROI including the parietotemporal area was also defined on the “cortical lateral views” due to the major role of this zone (Fig. 2b).

Automatic segmentation of the temporal lobes The use of Talairach’s Atlas is not restricted to the external cortical structures analyzed on the “cortical lateral views.” Once the proportional grid is set, any structure identified in the atlas can be localized according to the same principle. We tested the possibility of independently analyzing the different segments of the temporal lobe since the cortical lateral view approach averages the mesial and external segments. The same procedure is used, except that the ROIs are defined on two thick coronal cuts instead of the “cortical lateral views.” These two cuts are 1.9-2.5 cm thick, depending on the size of the brain. One is located at the level of the VCA, the other at the level of the VCP. They are computed automatically since the localization of the VCA and VCP is known at this point. The modeling and delineation of the ROIs are the same as previously explained. For each temporal lobe, on each of the two cuts, 4 ROIs are defined: upper, middle, lower temporal gyri, and the internal part of the temporal lobe (Fig. 4). VALIDATION

OF THE

METHOD

Accuracy of the CACP, VCA, VCP calculation Talairach’s Stereotactic proportional system assumes that normal brain structures bear constant relationship between each other within their corresponding parallelograms (7) (Fig. 1). The consistency of this relationship has been validated by stereotactic neurological procedures (7) as well as on MR images (10). In addition to the general assumptions of stereotaxy, our method makes the specific assumption that the commissural lines on which the atlas coordinate system is based can be calculated from the CM external landmarks as proposed by Szikla (9). We validated this step by applying our software to MR images. Ten normal volunteers underwent an MRI examination on a Signa 1.5 Tesla system (General Electric). The canthus and tragus were marked with glycerin. The images were acquired in a sagittal plane using a T l-weighted spin-echo sequence. The slices including

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(4

UN Fig. 2. Definition ofthe boundaries of the lobes. (a) Cortex peeling, separation of the two hemispheres and gem :ration of the two “cortical lateral views.” (b) Upper part: Localization of the CM and calculation of the CACP, VCA, VCP from the CM. Lower part: Building of the Talairach’s grid and delineation of the ROIs.

Computerized localization of brain structures

0. MIGNECOef al.

POSITION

NUMBER

LEFT “CORTICAL LATERAL VIEW”

OF THE

IIIIIII

OF

PIXELS

417

??

RESULTING PIXEL

()

VALUE

i

A/3

OF THE

014

PlXELlNB

H/5

OF PIXELS

N/4

O/3

LEFT “CORTICAL LATERAL VIEWAFTER THICKNESS CORRECTION

Fig. 3. Thickness correction of the left “cortical lateral view” in the case of a complete uniform uptake of HMPAO in the left hemisphere. Similar gray levels represent similar values. (A) Counting of the cortical pixels that belong to the left hemisphere for each row of the matrix for one particular cut. Each row will provide one pixel in the left “cortical lateral view.” (B) Left “cortical lateral view” before thickness correction: pixels A to 0 have different values. (C) Left “cortical lateral view” after thickness correction: pixels A to 0 have similar values.

the canthus and the tragus markers were added to obtain an image equivalent to the lateral view with the CM marks obtained at the end of the SPECT acquisition. The MR image passing through the mid-sagittal plane was used to localize the true CACP, VCA, and VCP lines. These images were processed by our CACP, VCA, and VCP calculation algorithm. The calculated and true commissural lines were then compared (Fig. 5). The results are presented in Table 1. The absolute maximum error in the positioning of the calculated lines were 5.3 mm, 7.4 mm, and 5.8 mm for the CACP, VCP, and VCA respectively, with a maximum error of axial rotation of 5.5”. Given our conditions of acquisition, a distance of 6.3 mm represents only 1 pixel and 1 degree of rotation only half a pixel at the borders of the matrix. Interobserver reproducibility In order to test the reproducibility, 32 patients were processed by two independent observers using the

automatic following

definition of cerebral lobes boundaries. ratios were calculated:

The

mean count per pixel for each cortical region mean count per pixel for the total cerebellum The results of the correlations between the ratios of the two observers are presented in Table 2. The correlation coefficients range from 0.94 with a standard error of the estimate (SEE) of 0.019 for the right occipital lobe to 0.98 with a SEE of 0.01 for the left parietal. As expected, the reproducibility is high due to the fact that the processing is mainly automatic.

DISCUSSION We will discuss our method according to the 13 criteria proposed by Mazziotta for “an optimal functional analysis of the brain” (11).

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Fig. 4. Temporal lobe analysis. Upper quadrants: Thick coronal cuts at VCA and VCP level with the temporal ROIs from a normal control. Lower quadrants: Thick coronal cuts at VCA and VCP level with the temporal ROIs from a ATD patient.

Fig. 5. MRI validation. Upper left quadrant: Localization of the CM line. Upper right quadrant: Calculation of the CACP, VCA, VCP from the CM line. Lower left quadrant: Localization of the real CACP, VCA and VCP. Lower right quadrant: Comparison of the real and calculated lines.

Computerized

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of brain structures

Table 1. Evaluation of the errors induced by calculating the commissural lines from the canthomeatal landmarks. Differences between true (located directly on MRI) and calculated baselines Subject I 2 3 4 5 6 I 8 9 10

d VCP*

d VCA*

0 -1 0 -2.1 0 0 1.1 3.2 -6.8 -7.4

1.6 0 3 -2.1 3.2 3.1 0.5 3.2 -5.8 3.2

ANG CACP+

d CACP+

4.5 2.5 4 2 0 3 -0.5 5.5 0 -2

3.7 2.1 -1.6 1.4 0 9.5 -1.6 -3.7 -5.3 -3.7

CACP anterior commissure-posterior commissure; VCA anterior vertical commissure; VCP posterior vertical commissure. * Distance between true and calculated VCA and VCP measured on the real CACP in mm, positive if the calculated line is in front of the real line. +Angle between the true and calculated CACP in degrees. + Distance between true and calculated CACP measured at the midcommissural point in mm, positive when the calculated line is above the real line.

Reproducibility Our method is mostly automatic and therefore leads to high inter-observer reproducibility with coefficients of correlation ranging from 0.94 to 0.98. Accuracy Although the Talairach Atlas has been constructed on only 20 cadaver hemispheres, it is the best stereotactic system presently available as validated on MRI images (10). But the commissural lines which are the basis of the coordinate system are obtained indirectly since they are not visible on the SPECT images. Therefore, the accuracy of our method is heavily dependent on the precision of this step. We observed on MRI that

??

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the errors induced by this calculation are in the limits of the variation reported by Szikla himself (9) for a confidence interval of 99%. Therefore, the imprecisions of commissural lines localization are due to individual variability of the relationship between cranial landmarks and encephalitic structures. Vannier (12) also validated this step by inserting 10 radiopaque small targets in the brain of 3 cadavers and using CT. She obtained an acceptable precision for all targets with a high precision in 80% of them. The errors induced by the calculation of the commissural lines are of the order of 1 pixel with our matrix size, which is acceptable given the resolution of SPECT tomograms. Independence of tracer employed Our method requires that the external limits of the cortex can be located on the images. This makes it applicable to perfusion and metabolic tracers but probably not to all receptor-specific radiopharmaceuticals. Independence of instrument resolution Since the landmarks are not obtained on the SPECT images, and since any point within the cortex can be accurately localized within the stereotactic atlas, spatial resolution does not, per se, influence the accuracy of the method. A similar method was applied to higher-resolution PET images by Fox ( 13), and high accuracy was obtained for localization of the primary visual cortex in r50-labeled water visual activation studies. Nevertheless, it should be mentioned that the imprecision in the estimation of the CACP lines which are acceptable for SPECT resolution may become significant for higher-resolution images. On the other hand, our method is implemented in such a way that the low-pass filter selected by the user for the tomographic reconstruction will not affect the ROIs local-

Table 2. Interobserver correlations. Cortico-cerebellar ratios measured in 32 patients

RF LF RP LP RPT LPT RT LT RO LO

II

SE

P

A

B

0.5’54 0.964 0.978 0.98 I 0.5’66 0.973 O.S’78 0.95 I 0.944 0.97 I

0.012 0.012 0.013 0.010 0.024 0.018 0.012 0.015 0.019 0.017


0.894 0.984 0.957 0.975 1.015 1.096 1.000 0.892 0.948 0.907

0.100 0.018 0.039 0.02 I -0.260 -0.100 -0.005 0.100 0.046 0.093


L = left, R = right, F = hontal, P = parietal. T = temporal, PT = parietotemporal, 0 = occipital. Table heading abbreviations R = coefficient of correlation; SE = Standard Error of the Estimate; A = slope of the regression B = Y intercept of the regression line.

line;

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ization. The cortical outer edge detection is performed on independently-reconstructed images and secondarily applied to the tomographic cuts filtered with the user’s filter. Therefore, the generation of the cortical lateral view is independent of the spatial resolution resulting from filter reconstruction.

Independence of ancillary technique This method has indeed the advantage of being directly applicable to conventional SPECT protocols. The only additional procedure is the marking of the CM landmarks on a lateral view at the end of the study. In a similar approach proposed by Fox (13) for PET images analysis, the CACP line was calculated from bony landmarks localized on a lateral skull radiograph. Although much simpler than MRI or CT procedures, this approach implies the availability of an x-ray apparatus whereas our method does not need additional equipment. The present method, as well as Fox’s, avoids the necessity of paired anatomical images such as MRI and CT and their attendant cost and logistic data handling problems.

Minimization

of subjectivity and investigator bias

Stereotactic data utilization along with automatization guarantees objective and unambiguous anatomical localization.

Fixed assumption about normal anatomy not required Talairach’s proportional system is designed to facilitate comparisons of brains of different forms and dimensions. It is based on a proportional subdivision of the brains that leads to the concept of a standardized and normalized localization. Subdivision of the individually-variable distances separating the central commissural lines and the extreme points of the brain leads to the construction of a proportional grid. This grid serves as a common denominator for all individual brains, regardless of their actual size. In fact, a “standard brain” is described by the atlas giving each point a set of coordinates. With the assumption that the anatomical structures within each parallelogram are proportionally distributed in any brain, the coordinates of a given point of the standard brain can be mathematically transformed into any individual coordinate system and related to the corresponding point in the measured image. Therefore, our method relies on “proportional assumptions” and not on “fixed assumptions” about normal brain anatomy.

Acceptable to subject’s level tolerance As mentioned above, the additional acquisition required by this method is only the landmarking of the canthus and tragus. The corresponding lateral view

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adds only a few seconds to the acquisition time with no discomfort to the patient since no specific head holder is necessary.

Performs well in serial studies ofthe same patients and individual study of separate patients in a population This technique has been applied to two consecutive HMPAO SPECTs performed on the same patient in a cognitive visual stimulation study. The cortical lateral view obtained under basal condition and under stimulation were subtracted after being matched with this technique. A significant increase of HMPAO uptake was found in the associative visual cortex as expected from the activation paradigm ( 14). This preliminary result confirms the ability of this method to compare two HMPAO brain distribution in the same patient studied under different conditions. We also used this technique to compare a group of 39 patients with Alzheimer type dementia (ATD) and 10 elderly controls. They were all analyzed using the lobe boundaries definition on cortical lateral views described above. The ATD had significantly lower HMPAO cortico-cerebellar ratios in the parietotemporal lobes of the right hemisphere. A significant nonlinear correlation between the Mini Mental State Examination (15) and the HMPAO uptake in the parietotemporal regions was observed (16). This is consistent with the pattern of hypoperfusion and hypometabolism described classically in ATD with SPECT (17, 18) or PET (19). A subgroup of 10 severe ATD patients (Mini Mental State Examination less than 10) were analyzed using the automatic segmentation of the temporal lobes and compared to 5 elderly controls. The ATD group had significantly lower corticocerebellar ratios in 9 of the 16 temporal areas analyzed (20). This is consistent with the pathological evidence of temporal lobe abnormalities in ATD (2 l-23).

Capability of evolving toward greater accuracy as information and instruments improve This approach can be improved toward greater accuracy by better estimation of the commissural lines. Up to now they are calculated from bony landmarks: CM line in the present method or glabella-inion line localized in others ( 13). Though related, variations of the brain are not identical to those of the skull. Therefore, it is desirable to find landmarks directly obtainable on the SPECT data to preserve the accuracy of the stereotactic data. New internal lines related to the bicommissural system will probably be defined when more neuroanatomical validation of the present stereotactic atlases is available along with an increase in spatial resolution of the functional images.

Computerized

localization

Reasonable cost Our method does not imply any additional to standard

of brain structures

cost

brain SPECT protocols.

Equal applicability in both clinical and research settings Our method can be applied case analysis of brain perfusion patient group comparison.

as a routine case-byas well as a tool for

Time eficiency for both a’ata acquisition and analysis Additional time for CM landmarking at the end of the acquisition is less than one minute. The processing time on a Sophy computer is of the order of 5 to 10 min. Furthermore, the use of cortical lateral views of the cortex reduces the entire tomographic information of the cortical HMPAO uptake into 2 two-dimensional images that are very easy to store and display for clinical use. This care for compact SPECT data presentation of cortical activity has also been shared by other authors (24,25), but their approaches do not allow objective neuroanal.omical localization.

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applied on 2 thick (1.9-2.5 cm) coronal cuts for assessment of the temporal lobes. The accuracy of the present method depends mainly on the precision of the calculation of the commissural lines locations which define the stereotactic coordinate system. This calculation is performed using the external landmark provided by the canthomeatal line and was validated on MR images of 10 normal volunteers. The errors induced by this process are on the order of the pixel size of our reconstructed images and are acceptable given the resolution achievable by SPECT. The fact that the regions of interest are determined from neuroanatomical atlas data along with the automaticity of the processing guarantees a high degree of objectivity and interobserver reproducibility. The processing of 32 different studies led to inter-observer coefficients of correlation ranging from 0.94 to 0.98 according to the region studied. This method is easily applicable to any SPECT acquisition protocol and provides objective, structural segmentation of brain HMPAO tomographic studies. REFERENCES

CONCLUSION The automatic stereotactic localization we have described in this paper fulfills the criteria proposed after a series of internal worksh’ops on emission tomography data analysis (11). The stereotactic approach minimizes the effect of subject-to-subject neuroanatomical variations and avoids the bias inherent in localizing ROIs directly on the functional images. The high level of automatization guarantees both reproducibility and easy use. Lastly, all additional measurements needed for implementation are very easily obtained. This makes this method readily applicable to any standard brain SPECT protocol without the need of (ancillary imaging technique. SUMMARY An accurate identification of cerebral structures is necessary to perform quantification of single photon emission computed tomography (SPECT). We have developed an anatomical localization system that accounts for individual brain shapes and sizes by using the Talairach proportional grid system. This method is independent of ancillary techniques. It allows the localization of any brain structure outlined in the atlas and, therefore, the definition of the corresponding ROIs. For our application, we decided to define automatically the boundaries of the lobes and of the temporal gyri. Stereotactically defined lobe boundaries are automatically generated for each hemisphere on “cortical lateral views” of the brain that encompass the entire hemispheric cortex. The same principle is also

I. Mazziotta, J.C.; Phelps, M.E.; Meadors, A.K.; Ricci, A.; Winter, J.; Bentson, J.R. Anatomical localization schemes for use in positron computed tomography using a specially designed headholder. J. Comput. Assist. Tomogr. 6:848-853; 1982. 2. Meltzer, C.C.; Bryan, R.N.; Holcomb, H.H.; et al. Anatomical localization for PET using MR imaging. J. Comput. Assist. Tomogr. I4:4 18-426; 1990. 3. Wilson, M.W.; Mountz, J.M. A reference system for neuroanatomical localization on functional reconstructed cerebral images. J. Comput. Assist. Tomogr. 13: 174- 178; 1989. 4. Matsui, T.; Hurano, A. An atlas of the human brain for comouterized tomoaraohv. Tokvo/New York: Iaaku-Shoin: 1978. assisted 5. kdair, T.; Stein, A.; Bajcsy,-R.; Reivich, MyComputer analysis of tomographic images of the brain. J. Comput. Assist. Tomogr. 5:929-932; 198 1. 6. Herholz, K.; Pawlik, G.; Wienhard, K.; Heiss, W.D. Computer assisted mapping in quantitative analysis of cerebral positron emission tomograms. J. Comput. Assist. Tomogr. 9: 154-l 6 1; 1985. I. Talairach, J.; Szikla, G. Atlas d’anatomie stereotaxique du telencephale. Paris: Masson; 1967. P. Co-planar stereotaxic atlas of the 8. Talairach, J.; Tournoux, human brain. Stuttgart New York: Georg Thieme Verlag; 1988. 9. Szikla, G.; Bouvier, G.; Hori, T.; Petrov, V. Angiography of the human brain cortex. Berlin Heidelberg New York: Springer; 1977. 10 Steinmetz, H.; Furst, G.; Freund, H.J. Cerebral cortical localization: application and validation ofthe proportional grid system in MR imaging. J. Comput. Assist. Tomogr. 13: lo- 19; 1989. Il. Mazziotta, J.C.; Koslow, S.H. Assessments of goals and obstacles in data acquisition and analysis from emission tomography: Report of a series of international workshops. J. Cereb. Blood. Flow. Metab. 7:SI-S3: 1987. I2 Vannier, M.; Roth Lecours, A.; Ethier, R.; et al. Proportional localization system for anatomical interpretation of cerebral computed tomograms. J. Comput. Assist. Tomogr. 9:7 15-724; 1985. 13 Fox, P.T.; Perlemutter, J.S.; Raichle, M.E. A stereotactic method of anatomical localization for positron emission tomography. J. Comput. Assist. Tomogr. 9: 141-153; 1985. 14. Darcourt, J.; Robert, Ph.; Aubin-Brunet, V.; et al. Cognitive stimulation in early Alzheimer type dementia (ATD) using Tc99m-HMPAO. Clin. Nucl. Med. 17:A4 (Abstract); 1992.

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15. Folstein, M.; Folstein, S.; McHugh, P. Mini-mental-state a practical method for grading the cognitive state of patients for the clinician. J. Psychiatry Res. 12:189-198; 1975. 16. Robert, Ph.; Migneco, 0.; Darcourt, J.; et al. Correlations between 99mTc-HMPAO brain uptake and severity of dementia in Alzheimer’s disease: assessment using an automatized technique. Dementia 3: 15-20; 1992. 17. Gemmel, H.G.; Sharp, P.F.; Besson, J.A.; et al. Differential diagnosis in dementia using the cerebral blood flow agent 99mTcHMPAO: A SPECT study. J. Comput. Assist. Tomogr. I 1:398402; 1987. 18. Jagust, W.J.; Budinger, T.F.; Reed, B.R. The diagnosis of dementia with single photon emission computed tomography. Arch. Neurol. 44:258-262; 1987. 19. Frackowiack, R.; Pozzilli, C.; Legg, N.; et al. Regional cerebral oxygen supply and utilization in dementia. Brain 104:753-778; 1981. 20. Migneco, 0.; Darcourt, J.; Benoliel, J.; et al. Computerized analysis oftemporal lobe using a proportional anatomical atlas. Clin. Nucl. Med. 16:pl70 (Abstract); 1991. 21. Barford, P.A.; Blair, J.A.; Eggar, C.; Hamon, C.; Morar, C.; Whitburn, S.B. Tetrahydrobioptetin metabolism in the temporal lobe of patients dying with senile dementia of Alzheimer type. J. Neurol. Neurosurg. Psychiatry 47:736-738; 1984. 22. Perry, E.K.; Blessed, G.; Tomlinson, B.E.; et al. Neurochemical activities in human temporal lobe related to aging and Alzheimer type changes. Neurobiol. Aging 2:25 I-256; 198 I. 23. Van Hoesen, G.W.; Hyman, B.T.; Damasio, A.R. Cell-specific pathology in neural systems of the temporal lobe in Alzheimer’s disease. Proa. Brain Res. 70:321-335: 1986. 24. Ichise, M.; Crisp, S.; Wortzman, G.; Kirsh, J.C.; Shapiro, B.J. A technique of cortical peeling and mapping by Tc-99m-HMPAO brain SPECT. J. Nucl. Med. 29:914; 1988. 25. Lamoureux, G.; DuPont, R.M.; Ashburn, W.L.; Halpern, S.E. “Cort-ex.” A program for quantitative analysis of brain SPECT data. J. Nucl. Med. 31:1862-1871; 1990.

About the Author-OCTAVE

MIGNECO graduated from the medical school ofthe University of Nice Sophia-Antipolis in 1990. He practices in the department of Nuclear Medicine of the Centre Antoine Lacassagne since 1987 with an university appointment in Biophysics and Image Processing since 1990 as assistant professor. His main field of interest is single photon emission tomography of the brain especially applied to Alzheimer’s type dementia.

About the Author-JACQUES

DARCOURT graduated from the medical school ofthe University of Nice Sophia-Antipolis in 1984. He practices in the department of Nuclear Medicine of the Centre Antoine Lacassagne since 198 I with an university appointment in Biophysics and Image Processing since 1984 as assistant professor and now as full professor since 1992. He obtained his PhD in Ingeniering in 1992 on tomographic reconstruction methods. Since then he leads a research group on this topic and is also closely involved in functional brain imaging.

About the Author-JOSE BENOLIEL obtained Sciences at tices in the Lacassagne and Image

his PhD in Computer the University of Nice Sophia-Antipolis in 1977. He pracdepartment of Nuclear Medicine of the Centre Antoine since 1979 with an university appointment in Biophysics Processing since 1984 as assistant professor. His main

November-December/

1994, Volume

18, Number

6

field of interest is image processing, and since 1990, he is in charge of the reorganization of the complete computer network and data processing of the Centre Antoine Lacassagne.

About the Author-FRANCIS

MARTIN obtained his PhD in Physics at the University of Nice Sophia-Antipolis in 1978 on signal and image processing applied to random fields. He has been involved with the development of a special kind of telescope using tomographic reconstruction algorithms and has been particularly interested from 1986 to 199 I by the problems of tomographic imaging. He is now professor at the “Department d’astrophysique” of the University of Nice Sophia Antipolis where his main interest is the study of the “influence of atmospheric turbulence on astronomical imagery.”

About the Author-PHILIPPE ROBERT graduated

from the medical school of the University of Nice Sophia-Antipolis in I98 I. He practices in the department of Psychiatry in the Pasteur hospital of Nice. In this department, he has been involved in the development and the organisation of a memory clinic for the diagnosis and treatment of memory disorders and Alzheimer’s disease.

About the Author-FRmcoIsE BUSSIEREgraduated from the medical school (1968) and the school of lngenieting (1970) of the University of Clermont Ferrand. She is full professor at the medical school of the University of Nice Sophia-Antipolis since 1975 where she leads the laboratory of Biophysics and Image Processing and the department of Nuclear Medicine of the Centre Antoine Lacassagne. Her main fields of interest were first the development of new hepatobiliary radiotracers and now tomographic reconstruction methods.

About the Author-1SMAEL MENAwas born in Santiago, Chile and has been the director of the Division of Nuclear Medicine at Harbor UCLA Medical center and Professor of Radiological Sciences at the University of California at Los Angeles (UCLA) since 1973. During 20 years emphasis in Nuclear Medicine Imaging has been in cardiology: first pass ventticulography, simultaneous myocardial perfusion-and function (‘95mA~ and~ZoiTl and later on 99mTc-Sestamibi). In brain imaaina auantification of rCBF with subseauent SPECT with 13’Xe and TcIHMPAO have provided important information in Alzheimer’s disease, frontal lobe degeneration, depression, obsessive compulsive disorders, etc. Numerous french and american fellows have trained under his guidance.

APPENDIX The commissural lines are estimated using the fixed anatomical relationships between these lines and the canthomeatal landmarks reported by Szikla (9). Angle between CACP and CM = 1.4 + 2.7” Distance between mid-commissural point and CM = 41.4 L 3.1 mm Distance between VCP and center of external auditory meatus = 3.1 -t 2.9 mm Distance between VCA and VCP = 24.4 + 1.6 mm Abbreviations: CACP horizontal commissural line; VCA anterior vertical commissural line; VCP posterior vertical commissural line; CM canthomeatal line.