Brain mapping in stereotactic surgery: A brief overview from the
probabilistic targeting to the patient-based anatomic mapping
Jean-Jacques Lemaire,a,i,⁎Jérôme Coste,a,hLemlih Ouchchane,d,iFrançois Caire,e,i
Christophe Nuti,f,iPhilippe Derost,bVittorio Cristini,gJean Gabrillargues,c,iSimone Hemm,i
Franck Durif,band Jean Chazala
aCHU Clermont-Ferrand, Hôpital Gabriel Montpied, Service de Neurochirurgie A, Clermont-Ferrand, F-63003, France
bCHU Clermont-Ferrand, Hôpital Gabriel Montpied, Service de Neurologie A, Clermont-Ferrand, F-63003, France
cCHU Clermont-Ferrand, Hôpital Gabriel Montpied, Service de Radiologie A, Clermont-Ferrand, F-63003, France
dUniv Clermont 1, UFR Médecine, Unité de Bio statistiques, télématique et traitement d’image, Clermont-Ferrand, F-63001, France
eCHU Limoges, Hôpital Dupuytren, Service de Neurochirurgie, Limoges, F-87042, France
fCHU Saint-Etienne, Hôpital Bellevue, Service de Neurochirurgie, Saint-Etienne, F-42055, France
gUniversity of Texas Health Science Center, School of Health Information Sciences, Houston, TX, USA
hInserm, E216, Clermont-Ferrand, F-63001, France
iInserm, ERI 14, Clermont-Ferrand, F-63001, France
Received 10 February 2007; revised 18 May 2007; accepted 22 May 2007
Available online 14 June 2007
In this article, we briefly review the concept of brain mapping in
stereotactic surgery taking into account recent advances in stereotactic
imaging. Thegold standard continuesto rely on probabilistic andindirect
and the posterior (PC) commissures. The theoretical position of a target
defined on an atlas is transposed into the stereotactic space of a patient’s
brain; final positioning depends on electrophysiological analysis. The
definition of the AC–PC line, probabilistic location and reliability of the
electrophysiological guidance. Advances in MR imaging, as from 1.5-T
is enabled by high-quality images, an advanced anatomic knowledge and
dedicated surgical software. Labeling associated with manual segmenta-
of patients, could benefit from the concept of membership, the attribution
of a weighted membership degree to a contact or a structure according to
its level of involvement. In the future, more powerful MRI machines,
diffusion tensor imaging, tractography and computational modeling will
further the understanding of anatomy and deep brain stimulation effects.
© 2007 Elsevier Inc. All rights reserved.
Keywords: Stereotaxy; DBS; MRI; Targeting; Anatomy; Computer-aided
Introduction . . . . . . . . . . . . . . . . . . . . . . . . 109
Background in classical stereotactic surgery with
indirect probabilistic targeting. . . . . . . . . . . . . . . 111
The indirect probabilistic targeting . . . . . . . . . . 111
Imaging for indirect targeting . . . . . . . . . . . . . 111
Indirect anatomic analysis of data. . . . . . . . . . . 111
The “direct” patient-based anatomic mapping in
stereotactic surgery . . . . . . . . . . . . . . . . . . . . 112
Future trends . . . . . . . . . . . . . . . . . . . . . . . 114
References. . . . . . . . . . . . . . . . . . . . . . . . . 114
Brain mapping in the classical meaning of stereotactic surgery
is based on intra operative electrophysiological recordings in order
to locate, for a given patient, the so-called invisible targets. Since
the pioneering days, the stereotactic targeting was indirect because
the targets were de facto arranged in areas relative to ventricular
baselines as imaging techniques failed to show the internal
anatomy of the brain (Talairach et al., 1957). For most of the
deep brain structures, basal ganglia, internal subdivision of
thalamus and main white bundles, a reference position in relation
to ventricular landmarks was proposed based on anatomic
specimen studies transcribed in stereotactic atlases (Talairach et
al., 1957; Schaltenbrand and Bailey, 1959). Nowadays in spite of
considerable progresses in magnetic resonance imaging (MRI), few
surgical teams have shifted to pure direct anatomic targeting with
NeuroImage 37 (2007) S109–S115
⁎Corresponding author. CHU Clermont-Ferrand, Hôpital Gabriel
Montpied, Service de Neurochirurgie A, rue Montalembert, F-63003
Clermont-Ferrand, France. Fax: +33 473 752 166.
E-mail address: firstname.lastname@example.org (J.-J. Lemaire).
Available online on ScienceDirect (www.sciencedirect.com).
1053-8119/$ - see front matter © 2007 Elsevier Inc. All rights reserved.
Fig. 1. Stereotactic location of the subthalamic nucleus (STN). STN projection area (pale grey surface) (Benabid et al., 2002); projections of STN boundaries
determined on axial (black dots and lines), sagittal (dark grey dots and lines) and frontal (light grey lines, white circles) slices (Schaltenbrand and Bailey, 1959).
Frontal (left; white circle, projection of ACPC) and lateral (right; doted line, ACPC line; white circles, AC and PC) views (TH, thalamus height; AC, PC see text
Fig. 2. 4.7-T MRI reference of the human thalamus and basal ganglia. Imaging on a Biospec 4.7-T MRI system (Bruker, GmbH, Ettlingen, Germany), anatomic
specimen, 3D spin-echo sequence T1-weighted; isotropic voxel=250 μm3. Isocentric images, reconstructed in the coronal (left) and axial (right) planes: Raw
data (top row): labelled and highlighted structures (bottom row).
S110 J.-J. Lemaire et al. / NeuroImage 37 (2007) S109–S115
neither ventricular baselines and/or atlas matching nor neuronal
activity recordings (Lemaire et al., 1999; Coubes et al., 2002, Caire
et al., 2006; Plaha et al., 2006). This direct targeting concept
depends exclusively on the visualization of the detailed internal
anatomy of each patient’s brain providing a personal MRI map.
Here, we briefly review the concept of brain mapping in stereo-
tactic surgery by indirect and direct methods of targeting, in light
of recent advances in stereotactic MRI.
Background in classical stereotactic surgery with
indirect probabilistic targeting
The indirect probabilistic targeting
The gold standard in classical stereotactic surgery relies world-
wide on indirect probabilistic targeting, relative to a stereotactic
reference. Historically ventricle landmarks represented this refer-
ence because X-ray ventriculography (intraventricular injection of
an iodized contrast agent and/or the air) was the only technique
visualizing the gross internal brain morphology. With the advent of
slice (computerized tomography, CTand MR) imaging, the method
has shifted without redefinition of landmarks yet determined on
radiographic projections. Because slice imaging can often be
anatomically poorly informative in clinical routine, the ventricle
landmarks continue to be used widely: the anterior (AC) and the
posterior (PC) diencephalic white commissures around the third
ventricle, sometimes the floor of the body of the lateral ventricle
(corresponding to the superior border of the thalamus) and the width
of the third ventricle. The stereotactic coordinates of targets, in
relation to the stereotactic reference, are provided by classical
stereotactic atlases and stereotactic graphs (Talairach et al., 1957;
Schaltenbrand and Bailey, 1959). Thus the probabilistic targeting
relies on transposition of the theoretical position of a target, atlas- or
graph-based, into the stereotactic space of a given patient’s brain
through the ventricular stereotactic reference. The use of propor-
of individual variability (Talairach et al., 1957; Schaltenbrand and
Bailey, 1959; Velasco et al., 2001; Benabid et al., 2002) with
continuous effort to optimize this approach (Nowinski et al., 2005;
Yelnik et al., 2007). Although the method seems universally
applicable, basic points can lead to errors of location: (1) the
stereotactic locations provided by atlases and graphs can differ (e.g.
Fig. 1) as an atlas relies on only one brain per plane (Schaltenbrand
and Bailey, 1959) and a geometric figure represents only the area
1957; Schaltenbrand and Bailey, 1959; Benabid et al., 2002); (2) the
commissural points are defined appreciably differently on their
center (Schaltenbrand and Bailey, 1959; Benabid et al., 2002) or
their periphery (Talairach et al., 1957) or according to different
planes for the same atlas (Schaltenbrand and Bailey, 1959).
Moreover the expression of stereotactic coordinates is different
even if the orientation is standardized (x represents the laterality
relative to the vertical midline plane going through ACPC; y
represents the anterior–posterior position along the ACPC line; z
represents the superior–inferior position relative to the ACPC axial
plane, perpendicular to the midline plane). The units are in
millimeters in case of absolute coordinates or in percentage of a
standard, the ACPC line (e.g., 1/12 of ACPC) or the height of the
thalamus (e.g. 1/4 of the thalamus height), in case of proportional
coordinates. Coordinates are only proportional for y or z, since there
is no reliable ventricle landmark to determine a standard in the
frontal plane; however, a lateral proportionality can be applied
(Velasco et al., 2001). Due to this probabilistic approach, it is
(electrophysiological neuronal recordings and/or clinical assess-
ments) and multiple-tract explorations. The strength of the indirect
targetingisabove all the simplicity of the coordinate calculation and
the important electrophysiological knowledge harvested.
Imaging for indirect targeting
Clinical MRI, at least on the first generations of generalist
machines, has non-negligible image distortion making delicate the
ACPC definition and/or the location of surgical fiducials, as well as
a low tissue contrast making reliable recognition of deep brain
structures difficult. Therefore, matching CT with MRI was
proposed (Duffner et al., 2002) in order to take the best of the
two techniques, the geometric accuracy of CT plus the better
ventricular anatomy on MRI. Nowadays because of the progresses
of MRI machines, teams used more and more MRI to determine
ACPC directly (Patel et al., 2003).
Indirect anatomic analysis of data
Even though it was originally designed to reach an invisible
target for a given patient, the method of indirect location is also
applied to analyze the positions of lesions (ablative surgery) or
electrode contacts (deep brain stimulation) for different patients
regardless of the technique of targeting (Benabid et al., 2002; Plaha
et al., 2006). The aim is to determine the anatomic structures
involved in the therapeutic process. The coordinates of lesions or
contacts, for each patient and/or hemisphere, are displayed on an
Fig. 3. Axial 1.5-T MRI slices. Imaging (deep brain stimulation surgery,
Parkinsonian) on a Sonata machine (Siemens, GmbH, Erlangen, Germany),
inversion-recovery sequence, stereotactic conditions; voxel size=0.52×
0.62×2 mm3. Diencephalo-mesencephalic subthalamic structures are out-
lined and labeled (horizontal white bar=10 mm): substantia nigra (deep
blue), red nucleus (orange), subthalamic nucleus (yellow), mammillary
bodies (blue-green), nucleus of ansa lenticularis (light orange), substantia Q
(green), zona incerta (red), peri peduncular nucleus (pink), lateral (light
purple) and medial (deep purple) geniculate bodies.
S111J.-J. Lemaire et al. / NeuroImage 37 (2007) S109–S115
atlas or a graph. It is assumed that locations of lesions or contacts
are effectively in the same structure identified during surgery; this
depends mainly on surgical technical constraints and on the level
of reliability of electrophysiological intra-operative guidance. The
surgical constraints are linked up, among other things, with the
capabilities of stereotactic instrumentation. The reliability of
electrophysiological guidance is not absolute (Schiff et al., 2002;
Israel and Burchiel, 2004; McClelland et al., 2005) in particular
because of our partial, and almost exclusively atlas-based,
knowledge of “electro-anatomic” processes; a better comprehen-
sion of these latter should be allowed by a direct, patient-based,
The “direct” patient-based anatomic mapping in
In order to improve the surgical stereotactic method, since
targets become more visible with new MRI modalities (hardware
and software), a stereotactic reference is not mandatory anymore;
the patient’s brain is its own reference, a direct patient-based
Fig. 4. 3D optimization of trajectory. Electrode implantation planned (same patient as Fig. 2) in the posterior part of the subthalamic nucleus (yellow) near the
zona incerta (red) and the Forel's fields (pale green), see Fig. 2 for the others labeled structures: 3D volume rendering of the subthalamic structures (frontal view;
top left); pseudo coronal, pseudo axial and pseudo sagittal planes reconstructed along the right trajectory (clockwise from top right to bottom left).
Fig. 5. Fiber tracking on stereotactic 1.5-T DTI. Anisotropic diffusion images (diffusion tensor imaging [DTI]; top row, left) matched (mutual information
algorithm) with anatomic images (inversion-recovery sequence, voxel size=0.52×0.62×2 mm3; top row, right) plus 3D anatomic structures (objects were
createdafter manual outlining).DTI acquisitionwas performed on a 1.5-Tmachine(Siemens Sonata,GmbH,Erlangen,Germany):stereotactic conditions,with a
Leksell G frame; 6 directions, b value=750 s/mm2, voxel size=1.8×1.8×3 mm3; image post processing with Iplan (BrainLab, Feldkirchen, Germany), color-
coded fiber direction (blue for superior–inferior, red for left–right, and green for anterior–posterior) plus color map matched with 3D anatomic structures
(intermediate row). Tractography (bottom row): (1) tracking with a fractional anisotropy threshold ≥0.30 and length of fibers ≥40 mm; (2) volume of interest
(blue box displayed on a coronal slice; insert bottom right) placed along the right trajectory on the interface between the subthalamic nucleus and the pre rubral
Forel's field (same patient as Fig. 2); (3) right lateral view of anatomicstructures (see Figs. 2 and 3 for labels; the substantianigra is transparent; left structures are
hidden) fused with color-coded fibers according to the direction: ansa lenticularis (Al), subthalamic occipito-parietal bundle (OP b), frontal bundle going trough
the anterior limb of the internal capsule (Fr b) and the dento-rubro-thalamic fascicle (Fx DRT).
S112 J.-J. Lemaire et al. / NeuroImage 37 (2007) S109–S115
S113 J.-J. Lemaire et al. / NeuroImage 37 (2007) S109–S115
anatomic mapping gets rational as from 1.5 T (Lemaire et al.,
1999; Coubes et al., 2002; Plaha et al., 2006; Derost et al., 2007).
Some teams use transitional methods, locating targets with
reference to easy recognizable structures, like the red nucleus,
coupled with a classic indirect atlas-based approach (Starr et al.,
1999; Bejjani et al., 2000; Patel et al., 2003; Rampini et al.,
2003; Andrade-Souza et al., 2005). Because of the wide range of
anatomical quality of MRI sequences and the variability of
surgical techniques, analysis of the literature concerning direct
targeting reliability can be confusing (Andrade-Souza et al., 2005;
Breit et al., 2006). However, pure direct targeting, allowed by
patient-based anatomic mapping, yields benefits by reducing the
number of exploration tracts and duration of intra operative tests
due to optimal primary positioning (Caire et al., 2006) and by
improving the analysis of relationships between a lesion or a
contact and the structures implied in the clinical effect because of
detailed anatomic analysis (Ulla et al., 2006). The increasing risk
of hemorrhage with numerous exploration tracts (Hariz, 2002)
argues for optimizing the primary positioning. A more wide-
spread application of the method depends mostly on two factors:
technical, the transfer of adequate MRI sequences; anatomic, the
spread of the anatomic knowledge of nuclei and bundles related
to the thalamus and basal ganglia, arranged in a complex manner
and poorly known in detail. In practice, the identification and
targeting of an anatomic structure rely on 3 key-points: namely,
an MRI anatomic knowledge, high-quality images and dedicated
surgical software. Even though anatomical knowledge is mostly
based on anatomy books and stereotactic atlases, the identifica-
tion of structures is facilitated by a very high field MRI anatomic
reference (Lemaire et al., 2004) with contrasts similar to those
used in clinical conditions and with 3D topographic analysis (Fig.
2). The high quality of MRI images is achieved with a small
voxel size, below 1.5 mm3, and a high contrast between white
and grey matters achieved with dedicated T2-weighted (Lemaire
et al., 2001; Patel et al., 2003; Slavin et al., 2006) and inversion-
recovery sequences (Magnotta et al., 2000; Siadoux et al., 2005).
In clinical routine, there is no evidence, because of the intricate
relationships between hardware and software, that 3-T magnetic
field offers higher anatomic definition than 1.5-T magnetic field,
at least with optimized sequences. If the anatomic images are
acquired in stereotactic conditions, i.e. with the stereotactic frame
locked in the head coil, then head motion is minimized during the
acquisition time of about 10 min per plane, increasing the signal/
noise ratio (unpublished data). Anatomic sub structures in the
area of interest, e.g. the thalamo-subthalamic region or the
lenticular nucleus, can be labeled and manually highlighted (Fig.
3) after identification based on the analysis of their known
relative positions. The outlines of the structures can be helpful to
interpret data on non-conventional interpolated planes recon-
structed along the trajectories. Dedicated surgical software
simplifies and improves the manipulation of image sets, allowing
determination of the detailed anatomy, optimization of the
trajectories (Fig. 4) and more detailed study of relationships
between the anatomy and electrophysiological and clinical data.
Anatomic location of a set of lesions or contacts in a group of
patients is still topical. The membership concept could incorpo-
rate the fact that a contact or a lesion can involve several
structures. The membership degree can be weighted by a fuzzy
logic method integrating the expert’s opinion concerning the level
of uncertainty of the membership (Caire et al., 2006). The
membership degree can also be weighted by the level of
involvement of a contact into a structure and vice versa (Lemaire
et al., 2005).
Patient-based anatomic mapping should benefit from higher
magnetic field, although beyond 3 T there are still important
technical constraints preventing a routine clinical use, in particular
in stereotactic conditions. But as from 1.5 T, diffusion tensor
imaging (DTI) and tractography already offer new possibilities.
These techniques enable the analysis of the anisotropy of brain
tissue as well as fibbers constituting white bundles (Mori et al.,
1999; Mori and Van Zijl, 2002; Le Bihan, 2003; Wakana et al.,
2004; Hermoye et al., 2006) and several clinical applications have
been published (Mukherjee, 2005; Nimsky et al., 2005; Arfanakis
et al., 2006; Wilde et al., 2006). As bundles seem to participate in
the DBS effects (Gabriëls et al., 2003; Hamel et al., 2003),
studying their implication becomes possible. Parallel to the
knowledge of the tissue anisotropy, also extracted from DTI,
might be of interest because it could influence the electric current
diffusion (McIntyre et al., 2004). Until now, it has been difficult to
perform such imaging in stereotactic conditions, i.e. with a
stereotactic frame in place, because of an important image
distortion. Recently, modified surgical software yielded this
approach at 1.5 T with routine stereotactic conditions. After
matching of DTI with T2-weighted anatomic images and 3D
tractography, it is possible to determine the main bundles of the sub
thalamic region potentially implied in the DBS process like the
ansa lenticularis (Fig. 5).
Beyond improving stereotactic targeting, the patient-based
anatomic mapping would enable new considerations for functional
treatments relying on the spatial location inside specific brain
areas, like radiosurgery, or the topographic diagnosis of lesions as
during degenerative diseases, at least if the anatomy is not sub-
stantially modified. Furthermore, advances in predictive computa-
tional modeling (Frieboes et al., 2006) might help by reproducing
in the computer the complexity and multi-dimensionality of a
particular patient’s brain structure.
Andrade-Souza, Y.M., Schwalb, J.M., Hamani, C., Eltahawy, H., Hoque, T.,
Saint-Cyr, J., Lozano, A.M., 2005. Comparison of three methods of
targeting the subthalamic nucleus for chronic stimulation in Parkinson’s
disease. Neurosurgery 52 (2), 360–368.
Arfanakis, K., Gui, M., Lazar, M., 2006. Optimization of white matter
tractography for pre-surgical planning and image-guided surgery. Oncol.
Rep. 15 (Spec no.: 1061–4).
Bejjani, B.P., Dormont, D., Pidoux, B., Yelnik, J., Damier, P., Arnulf, I.,
Bonnet, A.M., Marsault, C., Agid, Y., Philippon, J., Cornu, P., 2000.
Bilateral subthalamic stimulation for Parkinson’s disease by using three-
dimensional stereotactic magnetic resonance imaging and electrophy-
siological guidance. J. Neurosurg. 92, 615–625.
Benabid, A.L., Koudsie, A., Benazzouz, A., Le Bas, J.F., Pollak, P., 2002.
Imaging of subthalamic nucleus and ventral intermedius of the thalamus.
Mov. Disord. 17, S123–S129.
Breit, S., LeBas, J.F., Koudsie, A., Schulz, J., Benazzouz, A., Pollak, P.,
Benabid, A.L., 2006. Pretargeting for the implantation of stimulation
electrodes into the subthalamic nucleus: a comparative study of mag-
netic resonance imaging and ventriculography. Neurosurgery 58 (ONS
Suppl. 1) (ONS-83–95).
Caire, F., Derost, P., Coste, J., Bonny, J.M., Durif, F., Frenoux, E., Villéger,
A., Lemaire, J.J., 2006. Stimulation sous-thalamique dans la maladie de
S114 J.-J. Lemaire et al. / NeuroImage 37 (2007) S109–S115
Parkinson sévère: Étude de la localisation des contacts effectifs. Download full-text
Neurochirurgie 52, 15–25.
Coubes, P., Vayssiere, N., El Fertit, H., Hemm, S., Cif, L., Kienlen, J.,
Bonafe, A., Frerebeau, P., 2002. Deep brain stimulation for dystonia:
surgical technique. Stereotact. Funct. Neurosurg. 78, 183–191.
Derost, P.P., Ouchchane, L., Morand, D., Ulla, M., Llorca, P.M., Barget,
M., Debilly, B., Lemaire, J.J., Durif, F., 2007. Is subthalamic nucleus
deep brain stimulation (DBS-STN) appropriate to manage severe
Parkinson disease in an elderly population? Neurology 68,
Duffner, F., Schiffbauer, H., Breit, S., Friese, S., Freudenstein, D., 2002.
Relevance of image fusion for target point determination in functional
neurosurgery. Acta Neurochir. 144, 445–451.
Frieboes, H.B., Zheng, X., Sun, C.H., Tromberg, B., Gatenby, R., Cristini,
V., 2006. An integrated computational/experimental model of tumor
invasion. Cancer Res. 66, 1597–1604.
Gabriëls, L., Cosyns, P., Nuttin, B., Demeulemeester, H., Gybels, J., 2003.
Deep brain stimulation for treatment-refractory obsessive–compulsive
disorder: psychopathological and neuropsychological outcome in three
cases. Acta Psychiatr. Scand. 107, 275–282.
Hamel, W., Fietzek, U., Morsnowski, A., Schrader, B., Herzog, J., Weinert,
D., Pfister, G., Muller, D., Volkmann, J., Deuschl, G., Mehdorn, H.M.,
2003. Deep brain stimulation of the subthalamic nucleus in Parkinson’s
disease: evaluation of active electrode contacts. J. Neurol. Neurosurg.
Psychiatry 74, 1036–1046.
Hariz, M.I., 2002. Safety and risk of microelectrode recording in surgery for
movement disorders. Stereotact. Funct. Neurosurg. 78, 146–157.
Hermoye, L., Saint-Martin, C., Cosnard, G., Lee, S.K., Kim, J., Nassogne,
M.C., Menten, R., Clapuyt, P., Donohue, P.K., Hua, K., Wakana, S.,
Jiang, H., Van Zijl, P.C., Mori, S., 2006. Pediatric diffusion tensor
imaging: normal database and observation of the white matter
maturation in early childhood. NeuroImage 29, 493–504.
Israel, Z., Burchiel, K.J., 2004. Microelectrode Recording in Movement
Disorder Surgery. Thieme, New York.
Le Bihan, D., 2003. Looking into the functional architecture of the brain
with diffusion MRI. Nat. Rev., Neurosci. 4, 469–480.
Lemaire, J.J., Durif, F., Boire, J.Y., Debilly, B., Irthum, B., Chazal, J., 1999.
Direct stereotactic MRI location in the globus pallidus for chronic
stimulation in Parkinson’s disease. Acta Neurochir. (Wien.) 141,
Lemaire, J.J., Durif, F., Debilly, B., Blanc, O., Chazal, J., 2001. Deep brain
stimulation in the subthalamic area for severe idiopathic Parkinson’s
disease: location of plots in the preoperativephase andat the threemonth
follow-up. Parkinson’s Relat. Disord. 7, S80 (Suppl.).
Lemaire, J.J., Caire, F., Bony, J.M., Kemeny, J.L., Villéger, A., Chazal, J.,
2004. Contribution of 4.7-Tesla MRI in the analysis of the MRI anatomy
of the human subthalamic area. Acta Neurochir. 146, 906–907.
Lemaire, J.J., Coste, J., Ouchchane, L., Derost, P., Ulla, M., Durif, F., Caire,
F., Siadoux,S., Gabrillargues, J., Chazal, J., 2005. Stimulation électrique
à haute fréquence du noyau sous thalamique dans la maladie de
Parkinson sévère idiopathique: analyse du site optimale de stimulation à
partir des données électrophysiologiques per opératoires et de l’IRM
anatomique stéréotaxique. Neurochirurgie 519.
McIntyre, C.C., Mori, S., Sherman, D.L., Thakorc, N.V., Vitek, J.L., 2004.
Electric field and stimulating influence generated by deep brain
stimulation of the subthalamic nucleus. Clin. Neurophysiol. 115,
Magnotta, V.A., Gold, S., Andreasen, N.C., Ehrhardt, J.C., Yuh, T.C., 2000.
Visualization of subthalamic nuclei with cortex attenuated inversion
recovery MR imaging. NeuroImage 11, 341–346.
McClelland, S., Ford, B., Senatus, P.B., Winfield, L.M., Du, Y.E., Pullman,
S.L., Yu, Q., Frucht, S.J., McKhann, G.M., Goodman, R.R., 2005.
Subthalamic stimulation for Parkinson disease: determination of
electrode location necessary for clinical efficacy. Neurosurg. Focus 19,
Mori, S., Van Zijl, P.C., 2002. Fiber tracking: principles and strategies – a
technical review. NMR Biomed. 15, 468–480.
Mori, S., Crain, B.J., Chacko, V.P., Van Zijl, P.C., 1999. Three-dimensional
tracking of axonal projections in the brain by magnetic resonance
imaging. Ann. Neurol. 45, 265–269.
Mukherjee, P., 2005. Diffusion tensor imaging and fiber tractography in
acute stroke. Neuroimaging Clin. N. Am. 15, 655–665 (xii).
Nimsky, C., Ganslandt, O., Hastreiter, P., Wang, R., Benner, T., Sorensen,
A.G., Fahlbusch, R., 2005. Preoperative and intraoperative diffusion
tensor imaging-based fiber tracking in glioma surgery. Technique
Applications. Neurosurgery 56, 130–138.
Nowinski, W.L., Belov, D., Pollak, P., Benabid, A.L., 2005. Statistical
analysis of 168 bilateral subthalamic nucleus implantations by means of
the probabilistic functional atlas. Oper. Neurosurg. 57, 319–330.
Patel, N.K., Plaha, P., O’Sullivan, K., McCarter, R., Heywood, P., Gill, S.S.,
2003. MRI directed bilateral stimulation of the subthalamic nucleus in
patients with Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 74,
Plaha, P., Ben-Shlomo, Y., Patel, N.K., Gill, S.S., 2006. Stimulation of the
caudal zona incerta is superior to stimulation of the subthalamic nucleus
in improving contralateral parkinsonism. Brain 129, 1732–1747.
Rampini, P.M., Locatelli, M., Alimehmeti, R., Tamma, F., Caputo, E., Priori,
A., Pesenti, A., Rohr, M., Egidi, M., 2003. Multiple sequential image-
fusion and direct MRI localisation of the subthalamic nucleus for deep
brain stimulation. J. Neurosurg. Sci. 47, 33–39.
Schaltenbrand, G., Bailey, P., 1959. Introduction to Stereotaxis With an
Atlas of the Human Brain: Volume II. Georg Thieme Verlag, Stuttgart.
Schiff, S.J., Dunagan, B.K., Worth, R.M., 2002. Failure of single-unit
neuronal activity to differentiate globus pallidus internus and externus in
Parkinson disease. J. Neurosurg. 97, 119–128.
Siadoux, S., Gabrillargues, J., Coste, J., Claise, B., Chabert, E., Michel, J.L.,
Durif, F., Lemaire, J.J., 2005. IRM stéréotaxique de la région sous
thalamique:optimisation d’une séquencede repérage pré opératoirepour
la mise en place d’electrodes de stimulation profonde chronique.
Neurochirurgie 51, 519.
Slavin, K.V., Thulborn, K.R., Wess, C., Nersesyan, H., 2006. Direct
visualization of the human subthalamic nucleus with 3 T MR imaging.
AJNR (27), 80–84.
Starr, P., Vitek, J., DeLong, M., Bakay, R., 1999. Magnetic resonance
imaging-based stereotactic localization of the globus pallidus and
subthalamic nucleus. Neurosurgery 44, 303–313.
Talairach, J., David, M., Tournoux,P., Corredor, H., Kvasina, T., 1957. Atlas
d’anatomie stéréotaxique. Repérage radiologique indirect des noyaux
gris centraux des régions mésencéphalo-sous-optiques et hypothalami-
ques de l’homme. Masson and Cie, Paris.
Ulla, M., Thobois, S., Lemaire, J.J., Schmitt, A., Derost, P., Broussolle, E.,
Llorca, P.M., Durif, F., 2006. Manic behaviour induced by deep brain
stimulation in Parkinson’s disease: evidence of substantia nigra
implication? J. Neurol. Neurosurg. Psychiatry 77, 1363–1366.
Velasco, F., Jiménez, F., Pérez, M.L., Carrillo-Ruiz, J.D., Velasco, A.L.,
Ceballos, J., Velasco, M., 2001. Electrical stimulation of the prelemnis-
cal radiation in the treatment of Parkinson’s disease: an old target revised
with new techniques. Neurosurgery 49, 293–308.
Wakana,S.,Jiang, H.,Nagae-Poetscher, L.M., Van Zijl, P.C., Mori,S., 2004.
Fiber tract-based atlas of human white matter anatomy. Radiology 230,
Wilde, E.A., Chu, Z., Bigler, E.D., Hunter, J.V., Fearing, M.A., Hanten, G.,
Newsome, M.R., Scheibel, R.S., Li, X., Levin, H.S., 2006. Diffusion
tensor imaging in the corpus callosum in children after moderate to
severe traumatic brain injury. J. Neurotrauma 23, 1412–1426.
Yelnik, J., Bardinet, E., Dormont, D., Malandaine, G., Ourseline, S., Tandéa,
D., Karachia, C., Ayachee, N., Cornu, P., Agid, Y., 2007. A three-
dimensional, histological and deformable atlas of the human basal
ganglia: I. Atlas construction based on immunohistochemical and MRI
data. NeuroImage 34, 618–638.
S115 J.-J. Lemaire et al. / NeuroImage 37 (2007) S109–S115