Magnetic resonance imaging techniques for visualization of ...

J Neurosurg / Volume 115 / November 2011

J Neurosurg 115:971–984, 2011

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Deep brain stimulation of the STN was introduced as a treatment for advanced Parkinson disease in 1993.69 Patients who initially showed a good

response to levodopa but suffer from on-off fluctuations after a prolonged medication regimen have been shown to benefit from STN DBS. The beneficial effects of STN DBS on the motor symptoms of Parkinson disease have been described in long-term follow-up studies,74,95,96 but unwanted stimulation-induced side effects can occur. These side effects have been described as cognitive de-

terioration and behavioral changes98 and have been re-ported in approximately 40%–50% of patients.89 It is hy-pothesized that these side effects are the result of direct stimulation of or current spread to the nonmotor parts of the STN.88 In addition to a large dorsolateral motor part, the STN has 2 other functional subterritories, namely a small ventromedial limbic part and a cognitive part inter-mediate in position and size.41,88

Precise targeting of the dorsolateral (motor) part of the STN is of great importance for 2 reasons: first of all, to obtain the best possible effect on motor symptoms, and second, to minimize the undesirable side effects on cog-nition and behavior.35,92 Yet, the operative technique of

Magnetic resonance imaging techniques for visualization of the subthalamic nucleus

A reviewEllEn J. l. BrunEnBErg, M.Sc.,1 BraM PlatEl, Ph.D.,2 Paul a. M. hofMan, Ph.D., M.D.,3 Bart M. tEr haar roMEny, Ph.D.,1,4 anD VEErlE ViSSEr-VanDEwallE, Ph.D., M.D.5,6

1Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven; Departments of 3Radiology, 4Biomedical Engineering, and 5Neurosurgery, and 6Maastricht Institute for Neuromodulative Development, Maastricht University Medical Center, Maastricht, The Netherlands; and 2Fraunhofer MEVIS, Bremen, Germany

The authors reviewed 70 publications on MR imaging–based targeting techniques for identifying the subtha-lamic nucleus (STN) for deep brain stimulation in patients with Parkinson disease. Of these 70 publications, 33 presented quantitatively validated results.

There is still no consensus on which targeting technique to use for surgery planning; methods vary greatly between centers. Some groups apply indirect methods involving anatomical landmarks, or atlases incorporating ana-tomical or functional data. Others perform direct visualization on MR imaging, using T2-weighted spin echo or inver-sion recovery protocols.

The combined studies do not offer a straightforward conclusion on the best targeting protocol. Indirect methods are not patient specific, leading to varying results between cases. On the other hand, direct targeting on MR imaging suffers from lack of contrast within the subthalamic region, resulting in a poor delineation of the STN. These defi-ciencies result in a need for intraoperative adaptation of the original target based on test stimulation with or without microelectrode recording.

It is expected that future advances in MR imaging technology will lead to improvements in direct targeting. The use of new MR imaging modalities such as diffusion MR imaging might even lead to the specific identification of the different functional parts of the STN, such as the dorsolateral sensorimotor part, the target for deep brain stimulation.(DOI: 10.3171/2011.6.JNS101571)

KEy worDS • deep brain stimulation • targeting • subthalamic nucleus • MR imaging • functional neurosurgery

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Abbreviations used in this paper: AC = anterior commissure; DBS = deep brain stimulation; FSE = fast spin echo; IR = inversion recovery; MCP = midcommissural point; MER = microelectrode recording; MPRAGE = magnetization prepared rapid acquisition gradient echo; PC = posterior commissure; STIR = short tau inver-sion recovery; STN = subthalamic nucleus; TSE = turbo spin echo.

This article contains some figures that are displayed in color on line but in black and white in the print edition.

E. J. L. Brunenberg et al.

972 J Neurosurg / Volume 115 / November 2011

STN DBS including the imaging method for primary tar-geting of the STN still varies greatly between centers.53 Magnetic resonance imaging is one of the most frequent-ly used modalities, alone or in combination with CT or ventriculography.90 Most DBS procedures also involve a secondary targeting step using intraoperative assess-ments, such as MER or macrostimulation, to adapt the position of the electrodes to the clinical goals.17,30

The aim of this paper is to review the multitude of available methods and give a systematic overview of techniques for primary targeting of the dorsolateral part of the STN. This review discusses both indirect and di-rect targeting procedures, as well as comparative studies. The overall focus of the review is on MR imaging, be-cause this modality is most widely used. The next section of this paper will summarize indirect and direct targeting methods using MR imaging. Subsequently, the results of the systematic review will be presented. Finally, the ad-vantages and drawbacks of the targeting techniques will be discussed.

Summary of Targeting MethodsMethods for targeting the dorsolateral STN can be

classified as either direct or indirect. Indirect methods rely on contextual information, while direct methods fo-cus on visualizing the STN itself on preoperative images.

Indirect TargetingIndirect targeting can rely on 2 types of contextual

information—patient-specific landmarks or generic atlas information adapted to the patient’s anatomy.

The gold standard in indirect targeting using ana-tomical landmarks involves the AC and PC.82 Once one has localized the AC, PC, and the midcommissural point, the stereotactic coordinates of the STN follow from fixed distances based on classical atlases such as the Schalten-brand-Wahren brain atlas, as can be seen in Fig. 1.77 The second most widely used landmark is the red nucleus (Fig. 2).7,10 Less widespread methods include the use of the nigrocapsular angle (as explained in Fig. 3),34 the supramammillary commissure,52 the postmammillary commissure,91 and the line connecting the mammillary bodies and the PC.73

Furthermore, regions of interest can also be deter-mined by mapping an anatomical and/or functional at-las onto the patient’s MR imaging (see Fig. 4). Anatomi-cal atlases incorporate information about the position of brain structures.62,76 The most popular ones are the Talairach-Tournoux atlas,85 the Schaltenbrand-Wahren atlas,77 and the Montreal Neurological Institute atlas.22 Functional atlases consist of point sets that are collected during MER, postoperative imaging or neurological as-sessments.24,37,39,59,63

Direct TargetingDirect targeting involves the use of specific MR im-

aging protocols that enable direct visualization of the STN, avoiding the need to employ contextual informa-tion.

An often used method is the T2-weighted FSE MR imaging protocol,81,83 on which the STN shows as a hy-pointense area (see Fig. 5). Another popular technique for direct visualization is the IR protocol (see Fig. 6).48 Still subject to more research are the use of relaxation time maps12 and susceptibility-weighted (T2*) imaging (see Fig. 7),33 together with special postprocessing methods to reduce signal loss and enhance contrast.

Systematic ReviewIn order to present a review on the different target-

ing methods, we performed a thorough search for papers on STN targeting. The criteria that we used are briefly outlined below.

Search StrategyFirst, we searched PubMed and ScienceDirect for

papers published between January 1999 and January 2011, using the terms “targeting,” “magnetic resonance imaging,” “MRI,” or “visualization” in combination with “subthalamic nucleus” or “STN.” Second, we explored the bibliographies of relevant publications until no fur-ther additional studies were found. Papers were selected if they provided qualitative descriptions or quantitative results of direct or indirect MR imaging–based STN tar-geting methods. Language other than English was an ex-clusion criterion.

We included 70 publications, of which 33 stud-ies quantitatively validated results of patient trials. The quantitative results are reported in Tables 1–4. The de-tails extracted from the studies for this purpose included the following: number of subjects, targeting techniques used (landmark, MR imaging protocol, atlas, registration method), validation method, outcome, and the main con-clusion.

Indirect Targeting

Anatomical Landmarks. Publications on landmark-

Fig. 1. Diagram showing AC-PC line–based targeting in a sagittal plane. After the AC and PC are identified, the midcommissural point (MCP) is determined. From there, the STN position can be calculated using fixed distances (often 12 mm lateral, 3 mm inferior, and 3 mm posterior) based on an atlas.


Magnetic resonance imaging for STN visualization

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based targeting presenting quantitative results can be found in Table 1. After the ventriculography-based study by Schuurman et al. in 1999,79 one of the first MR imag-ing–based studies was presented by Starr et al.82 Their AC-PC line–based targets differed 1–1.5 mm from di-rectly visualized STNs. Due to the variability in manual selection of the AC-PC line,65 the need for automated methods became apparent. Ardekani and Bachman5 used an atlas-based automatic analysis method, and the result-ing landmarks were very close (within 1 mm) to points determined manually. A similar study by Pallavaram et al.64 yielded more accurate targets than achieved by man-ual selection.

The first studies on red nucleus–based targeting were presented by Aziz et al.7 and Bejjani et al.10 The latter reported selection of the central electrode in 19 of 24 cases. However, authors of other studies, based on best response23 and anatomical relationships,27 have stated that the red nucleus is not reliable enough. To solve this, Liu et al.56 used the red nucleus and the substantia nigra, but they did not report quantitative results. Pollo et al.70 ex-ploited the AC-PC line, red nucleus, thalamus, internal capsule, substantia nigra, and midline, resulting in a mean target in the inferior STN.

Regarding less widespread methods, according to Giller et al.,34 the use of the nigrocapsular angle was jus-tified by the higher visibility of the internal capsule and

substantia nigra on MR imaging. Lee et al.52 proposed the supramammillary commissure, which lacked reliability. Toda et al.91 used the postmammillary commissure and selected the central electrode in 81% of cases. Finally, Rij kers et al.73 suggested the line connecting the mammil-lary bodies and PC, although this remains to be validated.

Brain Atlas Registration. Table 2 summarizes the pa-pers found on atlas-based STN targeting that presented quantitative results. Ortega et al.62 digitized the anatomi-cal Talairach-Tournoux atlas, registered it nonlinearly, and compared the resulting targets with recorded micro-electrode positions, obtaining good results. However, No-winski et al.60 demonstrated inconsistency of the 3 planes for an anatomical atlas in the STN region, restricting the use of the atlas in 3D.

Sánchez-Castro et al. collected MR imaging data with visible STNs to use as a brain atlas.18,76 Duay et al.31 increased the speed of the registration algorithm and showed that the targeting variability is comparable to that of an expert, with a registration error similar to those reported by Sánchez-Castro et al.76 Bardinet et al.9 com-bined 2 kinds of anatomical information, namely histo-logical and MR imaging data, into a human basal ganglia atlas (see also Yelnik et al.100). After atlas registration, the resulting STN coordinates correlated well with MER and postoperative MR imaging. The authors improved the registration step, enabling a better match with individual patient anatomy (error < 1 mm).8

With respect to functional atlases, Nowinski et al.61 investigated the differences in spatial position between the anatomical and functional STN. The anatomical STN was derived from the Schaltenbrand-Wahren atlas,77 while the functional STN was constructed from ventricu-lography, MER, and radiographic data, and neurological assessment of 184 patients with Parkinson disease.59 The anatomical and functional STN correlated well.

D’Haese et al.24 developed a targeting method using MER and optimal electrode contacts determined postop-eratively and showed that automatic target prediction is feasible. Pallavaram et al.63 extended this, achieving a bet-

Fig. 2. Diagram showing red nucleus–based targeting in an axial plane. The center of the STN lies on the same line as the anterior boundary of the red nucleus (RN).

Fig. 3. Diagram showing targeting based on the nigrocapsular an-gle, in a sagittal plane. The STN lies in the corner that is formed by the descending internal capsule (IC) and the substantia nigra (SN).



ter correlation of the electrophysiological maps with the underlying anatomy. Guo et al.37,39 compared 6 methods using functional data, including a brain atlas, MER data, and a collection of previous targets. The combination of all data performed best, followed by the previous targets and the MER data. All 3 methods provided a more accu-rate estimation than techniques solely dependent on anat-omy. The authors used these results to construct probabi-listic maps for STN DBS trajectory planning.38

Direct Targeting

T2-Weighted MR Imaging. As can be seen in Table 3, a multitude of papers have reported validated results of T2-weighted MR imaging for direct STN identifica-tion. Starr et al.83 showed that direct targeting is possible on T2-weighted FSE MR imaging, leading to consistent electrode placement in the dorsolateral STN.81 Bejjani et al.10 selected the central track for implantation in 19 of their 24 cases. Egidi et al.32 reported even slightly better results: their visualized target track was chosen in 85% of cases. Dormont et al.29 examined postmortem tissue and showed that the hypointense signal reported by these first studies correlates with the presence of iron and cor-responds anatomically to the STN. They noted, however, that the most posterior part of the STN was not visible in any of the cases.

In addition, research has been done on the correspon-dence between MR imaging–based and landmark-based STN coordinates. Zhu et al.102 and Richter et al.72 con-cluded that MR imaging is needed, because atlas-based

coordinates suffer from interpatient variability in STN size72 and position.72,102 Littlechild et al.55 and Slavin et al.80 both reported that the STN target varies considerably in relation to the midcommissural point, again suggest-ing that direct visualization on MR imaging enables more accurate targeting than the atlas based method. Ashkan et al.6 confirmed this, finding a significant difference be-tween the atlas target and the STN as visualized on MR imaging. They found that the latter is on average 1.7 mm more medial, 0.7 mm more anterior, and 0.7 mm more ventral than the atlas target.

A substantial interindividual variability of STN size, orientation, and position and a significant difference be-tween MR imaging– and atlas-based coordinates in 66 patients was also demonstrated by Patel et al.67 Davies and Daniluk and colleagues found similar variation, based on series of 60 and 62 patients.25,28 In the latter se-ries, the lateral coordinate of the STN varied by as much as 5.8 mm and the anteroposterior size of the STN varied by 8 mm,26 implying that the use of atlas-based targeting may result in failure to identify the STN during MER.

Patel et al.66 validated direct targeting on axial and coronal MR images. In a first series, they used macro-stimulation for target adjustment; subsequently target verification was based on preoperative MR imaging only. The latter method yielded a mean error of only 0.3–0.4 mm. Together with a follow-up study on the improvement of activities of daily living and the motor score, this led to the conclusion that targeting based on T2-weighted MR imaging is safe and effective.68

Fig. 4. Diagram illustrating the concept of indirect targeting based on atlas mapping. On the upper left, an atlas slice with anatomical information can be seen, containing labeled structures. At the bottom left, a functional atlas is represented, consist-ing of a cloud of target points that were used in previously performed DBS operations. On the right, the patient’s MR imaging data can be seen. The gray arrows represent the transformation that is necessary to map the atlases to the patient’s MR imaging data, resulting in overlaid information as shown in the center.



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Inversion Recovery MR Imaging. Researchers have also investigated IR methods for direct visualization of the basal ganglia. Starr81 identified the globus pallidus internus, while Benabid et al.11 depicted the globus pal-lidus internus and the thalamus. The protocols they used were not suitable for visualizing the STN. Although many research groups have tried to improve upon these results, no quantitative studies on this subject are available yet.

Kitajima et al.48 proposed the STIR method and com-pared this to T2-weighted FSE MR imaging. The upper and lateral STN margins were depicted more clearly by FSE, while fast STIR was superior with respect to the vis-ibility of the lower margin and provided a better contrast between the STN and substantia nigra. In addition, Taoka et al.86 developed 2 sets of guidelines that facilitate identi-fication of the STN on STIR images, the so-called “Suke-roku sign” and the “dent internal-capsule sign.” Ishimori et al.47 investigated phase-sensitive IR and showed that the STN position on IR MR imaging differs by at most 2 mm from the coordinates found with AC-PC line–based targeting—comparable to the results obtained with T2-weighted images.6

Susceptibility-Weighted MR Imaging. Apart from T2-weighted and IR MR imaging, it is also possible to acquire T2*-weighted (susceptibility-weighted) MR im-ages, and T2* imaging is even more sensitive to local iron deposits, as occur in the STN among other areas. Dor-mont et al.29 established the correlation of these iron de-posits and the hypointensities on T2*-weighted MR im-aging, while Slavin et al.80 applied this to 3T data. Taoka et al.87 also visualized the iron content of the STN using

T2*-weighted MR imaging. They compared the results with STIR MR imaging and found that the posterior STN parts were not visible on the T2*-weighted images, lead-ing to the conclusion that a combination with STIR might be more useful to target the STN.

Bonny et al.12 generated multiple images with in-creased T2*-weighting to maximize the contrast between the STN and surrounding structures. Elolf et al.33 also used multiple gradient echoes to add contrast to con-ventional T1-weighted MR imaging. Wu et al.99 used a steady-state free precession MR imaging method, facili-tating the visualization of midbrain nuclei with a heavy T2*-weighting and relatively short echo time. However, none of these studies presented quantitative results on STN targeting.

To enhance T2*-weighted images, Volz et al.97 pre-sented a method to reduce signal loss, resulting in good contrast. Another applicable technique is susceptibility-weighted imaging, a method that uses the phase data. Young and Chen101 exploited this technique to produce T2* contrast additive to the T1 or T2 contrast intrinsic to the imaging protocol, thus improving the contrast be-tween the nuclei of interest. Rauscher et al.71 and Vertin-sky et al.94 also performed postprocessing with phase im-ages, giving rise to a better visibility of the STN and even of the subthalamic fasciculus. However, for these meth-ods again, the STN position as identified on MR imaging has not been validated.

Relaxation-Time Maps Derived From MR Imaging. Apart from T1-, T2- or T2*-weighted acquisitions, it is also possible to map the true relaxation time for each

Fig. 5. Coronal T2-weighted FSE MR image showing direct visual-ization of the STN. Fig. 6. Coronal IR MR image showing direct visualization of the STN.



voxel by performing multiple MR acquisitions with dif-ferent parameters. Bonny et al.12 already reconstructed T2* maps from their measurements in 2001. Helms et al.45 used T2* maps for improved delineation of iron-rich structures, in particular the STN and substantia nigra. Lebel et al.51 investigated T2* mapping of the basal gan-glia at 4.7 T, and obtained increased spatial resolution and sensitivity to iron content.

Guo et al.36 were the first to introduce relaxation-time maps for T1 and T2 into their DBS targeting ap-plication.37,39 They compared the centers of basal ganglia nuclei based on the relaxation-time maps with the coor-dinates derived from the Schaltenbrand-Wahren atlas and the actual surgical targets in 15 patients who underwent surgery. As the mean displacement was 3.21 ± 0.80 mm, these results indicated the potential of the relaxation-time maps for DBS targeting.

High Field Strength MR Imaging. Following the ex-ample of Lebel et al.,51 more studies have recently been published on direct visualization of the STN and other basal ganglia using MR imaging scanners with high field strengths. Abosch et al.1 acquired susceptibility-weighted MR imaging data at 7.0 T and showed that the superior resolution and contrast at this field strength dramatically improved delineation of the STN. Cho et al.19 also visual-ized the STN using T2*-weighted scans obtained with a 7-T MR imaging unit, and in addition imaged the sub-stantia nigra in 9 healthy controls and 8 patients with Par-kinson disease, revealing distinct morphological changes due to this disorder.20

Comparative StudiesMuch research has been done on the comparison

of direct and indirect targeting. Table 4 summarizes the comparative papers that presented quantitative results.

Studies That Favor Indirect Targeting. Zonenshayn et al.103 investigated STN targeting using 4 different meth-ods, namely: 1) coronal MR imaging, 2) the STN center on a Schaltenbrand-Wahren atlas, 3) targeting based on the AC-PC line, and 4) a composite target based on all 3 methods. The results were compared with the final target (found with help of MER). The combination of 3 methods appeared to be best, while the use of MR imaging as a sole method gave the worst result. Cuny et al.23 also compared 3 methods. The first technique was direct identification on T2-weighted MR imaging (see Table 1). The second and third methods both involved indirect targeting based on the AC-PC line, determined by ventriculography or MR imaging, respectively. The most effective contact was taken as the gold standard. The authors concluded that in-direct targeting based on MR imaging worked best, while direct targeting gave the worst outcome.

Andrade-Souza et al.3 investigated direct targeting using coronal MR imaging, indirect targeting using the AC-PC line, and a technique using the red nucleus as a landmark. The implantation was optimized using MER, while the most effective contact was identified using post-operative MR imaging. After comparing the mean dis-tances between the targets and optimal contact, the au-thors concluded that the red nucleus is a reliable marker for STN targeting. This is contradictory to the results of Danish et al.27 (see Table 1). Breit et al.13 also evaluated coronal T2-weighted MR imaging, this time in compari-son with AC-PC line–based targeting using ventriculog-raphy. The implantation was refined using MER, and the actual target was chosen to be the most effective contact. Their findings showed that targeting the STN using the AC-PC line from ventriculography is more accurate than direct targeting on MR imaging. Castro et al.18 compared coronal T2-weighted (IR) MR imaging with indirect tar-geting using a registered atlas based on MR imaging data with visible STNs. Their results showed an average error of 1.72 mm, which they considered small enough to jus-tify the use of the atlas.

In further research, Andrade-Souza et al.4 compared 2D T2-weighted axial and 3D reconstruction MR imag-ing. They found that indirect and direct targets based on 3D reconstruction more closely approximate the optimal contact than targets chosen using 2D MR imaging. How-ever, both indirect targets were better than the direct tar-gets.

Studies That Favor Direct Targeting on MR Imaging. Starr et al.82 performed MR imaging and MER to tar-get the STN. They used a combination of indirect AC-PC line–based targeting and direct targeting on T2-weighted MR imaging. The authors managed to visualize the STN directly for 92% of procedures, which supports the choice for direct imaging instead of AC-PC line–based methods for STN targeting. The reliability of indirect methods as compared with direct targeting was also investigated by

Fig. 7. Axial susceptibility-weighted MR image showing direct visu-alization of the STN.



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Schlaier et al.78 They determined STN targets in 5 differ-ent ways: 1) direct targeting using axial T2-weighted MR imaging, 2) direct targeting on coronal T2-weighted MR imaging, 3) indirect targeting using an axial atlas slice, 4) indirect targeting on a coronal atlas slice, and 5) in-direct targeting using AC-PC references. Direct target-ing seemed more reliable than atlas-based targeting, due to large interpatient variability in the STN coordinates as derived from MR imaging. Ashkan et al.6 confirmed these results on variability in STN position. Their direct target differed on average 0.7–1.7 mm in all 3 directions.

Although the results of all studies described showed superior reliability for direct targeting, the finding was not validated with intra- or postoperative information. Koike et al.49 did use the identified STN thickness dur-ing MER and clinical parameters, namely the effect of DBS on the disease and on the medication dose, as evalu-ation parameters. They compared direct targeting on T2-weighted FSE MR imaging to the conventional indirect AC-PC line–based method. The results showed a signifi-cantly larger mean STN thickness (indicating a longer electrode track through the STN and thus better target-

TABLE 1: Summary of indirect studies based on anatomical landmarks visualized on MR images*

Authors & YearNo. of

Pts Landmarks MRI Protocol Validation Method Outcome Conclusions

Schuurman et al., 1999

15 AC-PC 3D GRE, 1.5 T intraop ventriculog difference in coordinates: 1.29 mm for difft targets

Correspondence btwn ventriculog & MRI justi- fies use of MRI.

Starr et al., 2002 180 AC-PC 3D GRE, 1.5 T MRI: coronal FSE, 1.5 T direct/indirect concordant to w/in 1–1.5 mm

MRI-based targeting should be combined w/ MER & postop MRI.

Pallavaram et al., 200865

2 AC-PC T1-weighted, 1.5 T comp of 38 neurosur- geons

mean distance of 1 mm w/ same SD

Automatic AC-PC selection or direct targeting should be used.

Ardekani & Bachman, 2009

42 AC-PC T1- & T2-weighted, 1.5 & 3 T

comp of manual & automatic method

avg Euclidean distance of 1.1 mm

The authors’ model-based algorithm is better than earlier automatic AC- PC–based methods.

Bejjani et al., 2000

12 RN coronal spin echo, 1.5 T

MER central track selected 19 of 24 times

MRI targeting is useful for STN stimulation but should be combined w/ MER.

Cuny et al., 2002

14 RN coronal double echo spin echo, 1.5 T

AC-PC based using MRI/ventriculog; best clinical response

distances to optimum target: 2.61 mm for AC- PC MRI, 3.92 mm for RN method

Targeting of STN based on RN is less effective than AC-PC–based methods.

Danish et al., 2006

26 AC-PC, RN sagittal T1-weighted, axial FSE, 1.5 T

comp of distances: MCP-STN, MCP-RN, STN-RN

SD of MCP-RN & STN- RN larger than SD of MCP-STN

RN is not a reliable marker for STN position.

Pollo et al., 2003

31 AC-PC, RN, IC, thalamus, SN

3D MPRAGE & coronal IR, 1.5 T

Schaltenbrand-Wahren atlas

mean target coordinates located in inf STN

Combination of different landmarks yields a visual procedure to find the STN.

Giller et al., 2005

29 nigrocapsular angle (IC, SN)

sagittal FSE IR, 1.5 T no quant comp done IC detected in 97% of slices, SN in 95%, STN in 73%

Indirect sagittal method using the nigrocapsular angle can refine STN localization.

Lee et al., 2006 6 SMC coronal MPRAGE, FSE, 1.5 T

RN-based targeting RN based matches atlas (12, −3, −4 mm); SMC- based errors in x (14.25) & z (−5.0)

The method of this paper is sensitive to ventricu- lar enlargement, but the top of the SMC is a reliable landmark.

Toda et al., 2009 26 PMC, RN, mammillo- thalamic tract

axial & coronal TSE, 1.5 & 3 T

RN-based & AC-PC– based targeting, MER

central track selected in 81% of 3-T cases, 31% of 1.5-T cases

Composite targeting method on 3 T offers reliable STN targeting.

* AC-PC = AC-PC line; avg = average; comp = comparison; difft = different; FSE = fast spin echo; GRE = gradient echo; IC = internal capsule; inf = inferior; IR = inversion recovery; MCP = midcommissural point; MPRAGE = magnetization prepared rapid acquisition gradient echo; PMC = postmam-millary commissure; Pts = patients; quant = quantitative; RN = red nucleus; SMC = supramammillary commissure; SN = substantia nigra; TSE = turbo spin echo; ventriculog = ventriculography.



ing) in the direct targeting group, and clinical parameters also displayed larger improvements in the direct targeting group.

Although all studies mentioned previously in this section used 1.5-T MR imaging, Acar et al.2 investigated the benefit of direct targeting on 3.0-T MR images over traditional AC-PC line–based targeting using 1.5-T MR images. They calculated Euclidean distances between the directly and indirectly determined coordinates in 3 di-mensions, resulting in mean differences between the two locations of 0.45 mm, 0.72 mm, and 0.98 mm in the x, y, and z axes, respectively. According to the authors, MR imaging has advanced to the extent that direct targeting of the STN is no longer imprecise.

DiscussionIn this paper we reviewed indirect and direct STN

targeting methods based on MR imaging. The most com-mon indirect methods use either landmarks such as the AC-PC line6,64,65,82 and the red nucleus7,10,23,27 or atlases built from anatomical8,9,18,31,76 and/or functional24,37,39,59,63 information. These methods are applicable in all cases but are not very patient specific. Direct methods already in use clinically comprise T2-weighted FSE10,29,32,83 and IR MR imaging.47,48,86 These techniques can account for interpatient variability6,26,55,67,80 but have drawbacks of their own, including low contrast and technical issues,44 such as a long acquisition time,10,66,102 required reformat-

ting of images, and the need for preparatory T1-weighted sequences used to plan the acquisition of T2-weighted sequences.10,82

The comparative studies presented do not provide us with a straightforward conclusion on the best STN target-ing protocol. Earlier publications tend to favor indirect methods, mainly based on the AC-PC line, while authors of more recent studies are more inclined to prefer direct visualization. Most publications reported the use of 1.5-T MR imaging, and the majority of hospitals still use this field strength, so the recent preference for direct targeting is not likely to be due to 3-T MR imaging. The phenom-enon might be caused by advances in MR imaging at 1.5 T, with respect to contrast, noise, and distortion, resulting in a targeting method that is more specific than AC-PC line–based targeting. Due to continuous progress in MR imaging technology, improvements in direct targeting are still anticipated.

Although it seems that the future of STN target-ing will be focused on patient-specific direct methods, it is nevertheless important to keep in mind the limita-tions of STN visualization on anatomical MR imaging. Often only the anterior STN is visible as a hypointense region.29 In addition, the contrast between the STN and surrounding structures is not optimal, hindering identi-fication of the STN boundaries.33,45,48 Furthermore, the question remains whether the visualized STN coincides with the functional target for DBS (often determined by MER).40,43,55 Promising new methods such as relaxation-time maps and susceptibility-weighted imaging, as well

TABLE 2: Summary of indirect studies based on brain atlases*


Pts Atlas Info Registration MethodValidation Method Outcome Conclusions

Ortega et al., 2008 10 digitized Talairach- Tournoux atlas

nonlinear registration

final microelectrode position

difference in coordinates: 1.89 ± 1.00 mm

System matching the atlas to T1-weighted MRI offers good targeting results.

Sánchez Castro et al., 2005

8 MRI of pt w/ best visible STN

nonrigid (affine & nonlinear)

direct STN targeting by expert

smallest difference in coordinates: 1.80 ± 0.62 mm

Automatic STN location using nonrigid atlas registration is possible & accurate.

Bardinet et al., 2005

16 postmortem MRI & histology data

rigid & affine registration

electrophys recordings (6) & final electrode position (10)

81.5% of recordings & 70% of electrodes w/in STN as defined by atlas

Atlas/MRI coregistration could be used as standard method for targeting deep brain structures.

Nowinski et al., 2007

184 ventriculog, MER, neurol assessment

linear scaling along AC-PC

STN in Schalten- brand-Wahren atlas

functional STN (p ≥ 0.5) completely inside anatomical STN

Functional STN can be used for identification of STN on images.

D’Haese et al., 2005

21 MER, stimulation parameters, final electrode positions

nonlinear registration

preop AC-PC & retrospective automatic targeting

mean distance: 3.66 mm for AC-PC–based targeting, 2.71 mm for automatic targeting (rt STN)

Automatic prediction of STN target from previous targets & electrophys data is an achievable goal.

Guo et al., 200739 28 atlas, MER, optimal contacts, MRI- based methods

nonrigid registration actual surgical target location

mean distance smallest for combination of all atlas data: 1.7 ± 0.7 mm

Method w/ both anatomical & functional data pro- vides most reliable STN target.

* Electrophys = electrophysiological; Info = information; neurol = neurological; sig = significant.



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as imaging at 7 T, have not been validated yet in large clinical studies. Besides, technical issues strongly influ-ence the MR imaging procedure and quality. Examples are the MR compatibility of the stereotactic frame, im-age artifacts due to patient movement, and magnetic field distortion, although distortion can be controlled reason-ably for the midbrain.26,57 Because of these issues, further research into STN localization methods, both direct and indirect, seems necessary.

The comparative studies that have validated the tar-geting with the most effective contact location also have their limitations. The conclusions of Cuny et al.,23 An-drade-Souza et al.3,4 and Breit et al.,13 that indirect target-ing is more relevant for electrode placement, should thus be considered with care. Because the primary targeting in these studies was indirect, the final contact, even after in-traoperative adjustment, was close to the original indirect target. In addition, analyzing indirect versus direct tar-geting according to the optimal contact only emphasizes differences between the final position and the primary targets. This bias would of course also exist if primary targeting were to be performed using a direct method. Caire et al.17 also compared STN localization methods based on the AC-PC line and 1.5-T MR imaging, reveal-

ing significant differences in all 3 dimensions. Instead of drawing conclusions about which targeting method is more suitable, the authors stated that apparently it would be better to conclude that the indirect AC-PC line–based target does not coincide with the center of the STN as visualized on anatomical MR imaging. Moreover, vari-ous follow-up42,50,54,75 and postmortem84 studies state that the best clinical target is located in the dorsolateral part of the STN and the area just superior to the STN (zona incerta, field of Forel).

The results from several papers show that stimulating the dorsolateral motor part of the STN is more effective than stimulating the center.17,42,50,54,75,84 As conventional direct targeting on anatomical MR imaging cannot dis-tinguish the dorsolateral STN due to lack of contrast, it is useful to further investigate the use of other MR imag-ing–based methods to facilitate specific targeting of this area of the STN. Examples of techniques that have not yet proven their clinical utility but might aid in STN lo-calization are the use of landmarks such as the nigrocap-sular angle,34 the mammillary commissures,52,91 and the line connecting the mammillary bodies.73 In addition, a fast-developing line of research focuses on susceptibility-weighted MR imaging and T2* mapping to improve the

TABLE 3: Summary of direct studies using T2-weighted MR imaging and relaxation-time maps*


Pts MRI Protocol Validation Method Outcome Conclusions

Starr et al., 1999 6 coronal T2-weighted FSE MRI, 1.5 T

MER coordinates close to AC-PC– based values; initial MER track passed through the STN in every case

Direct visualization facilitates reliable targeting of the STN, but MER mapping remains necessary.

Starr, 2002 44 coronal T2-weighted FSE MRI, 1.5 T

MER & postop MRI STN directly visualized on MRI in 92% of cases; MER used to adapt target intraoperatively

Combined approach leads to consistent electrode placement in the dorsolateral STN.

Bejjani et al., 2000 12 coronal T2-weighted spin-echo MRI, 1.5 T

MER & optimal contact position

central track selected for 19 of 24 electrodes

MRI targeting is useful for STN stimulation but should be combined w/ MER.

Egidi et al., 2002 13 axial T2-weighted spin- echo MRI, 1.5 T

MER & postop MRI targeted track chosen for 22 of 26 electrodes

1.5-T MR images are highly effective for STN targeting.

Littlechild et al., 2003 25 axial T2-weighted MRI, 1.5 T

MER & optimal contact position

sig variation in target position (4– 5 mm); mean distance btwn target & electrode 1.7 mm

The STN varies in position & can be accurately targeted from MRI alone.

Slavin et al., 2006 13 T2-weighted FSE MRI in 3 directions, 3.0 T

MER variation in target position ~2 mm; all tracks pass through STN

3 T MRI enables accurate direct visualization of the STN.

Patel et al., 2002 26, 19† axial & coronal T2- weighted MRI, 1.5 T

macrostimulation, intraop MRI

mean target error of 0.3 mm me- diolat & 0.4 mm AP

MRI-directed targeting of the STN through guide tubes is accurate & allows direct verification & corrections as necessary.

Guo et al., 2005 15 T1 & T2 maps, 1.5 T atlas coordinates, actual surgical targets

mean displacement 3.21 ± 0.80 mm

The results indicate the potential capability of this system to accurately identify the STN.

* AP = anteroposterior.† The authors performed a first series of 26 cases using intraoperative macrostimulation as the control method and a subsequent series of 19 patients with MR imaging–based verification.



contrast in the STN region.45,51,94,97,99 It is unlikely, how-ever, that this improved contrast would give rise to identi-fication of the dorsolateral STN specifically.

In addition to trying to identify the dorsolateral STN, possibilities of dividing the STN functionally and identi-fying the motor part should also be investigated. Modali-ties such as functional or diffusion-weighted MR imaging could yield features that facilitate separation of the motor part of the STN. Diffusion-weighted MR imaging sen-sitizes the MR acquisition to water diffusion in specific directions. The diffusion profile in a voxel can be fitted as an ellipse (diffusion tensor imaging58) or a higher or-der shape (high angular resolution diffusion imaging93). By analyzing these profiles in the STN itself, it has been

shown that different parts of the STN in a rat brain could be separated visually and automatically.14,16 Recently, Coenen et al.21 also published a case study on diffusion tensor imaging–based fiber anatomy in the STN region, to help identification of the tremor suppression target.

Apart from the primary targeting based on (MR) im-aging, there are other parts of the surgical “pipeline” that influence the clinical outcome of a DBS procedure and should not be ignored. The most important are the type of stereotactic frame, the selection of the trajectory (this can be done manually or automatically15), registration of different imaging modalities, intraoperative brain shift,46 intraoperative electrode adjustment, and postoperative parameter estimation. In striving for the best possible re-

TABLE 4: Summary of studies comparing indirect and direct methods*


Pts Methods Validation Method Outcome Conclusions

Zonenshayn et al., 2000

15 coronal MRI (T2-weighted/ IR), atlas, AC-PC, combination

final target based on MER

distance btwn MRI/final target: 2.6 ± 1.3 mm; btwn composite/ final target: 1.3 ± 1.1 mm

Combination of 3 targeting methods offers best correlation w/ the final target.

Cuny et al., 2002 14 T2-weighted MRI, AC-PC w/ ventriculog, AC-PC w/ MRI

most effective contact distance btwn AC-PC (MRI)/ best contact: 2.6 ± 1.2 mm; btwn direct/best contact: 3.9 ± 1.9 mm

Indirect targeting based on MRI works best; direct targeting gives worst outcome.

Andrade-Souza et al., 20053

14 coronal MRI, AC-PC, RN- based targeting

optimal contact (MER & postop MRI)

distances to optimal contact: MRI: 4.7 mm; AC-PC: 3.4 mm; RN: 3.2 mm

RN is a reliable marker to approximate the optimal contact position.

Breit et al., 2006 30 coronal T2-weighted MRI, AC-PC based on ventriculog

most effective contact mean targeting error 4.1 ± 1.7 mm for MRI & 2.4 ± 1.1 mm for AC-PC

AC-PC using ventriculog is more accurate than direct targeting on MRI.

Castro et al., 2006 39 coronal T2-weighted IR MRI, anatomical atlas based on direct targets

comp in MRI coordinate system

best atlas registration method (B- splines): avg error 1.72 ± 0.48 mm

Automatic STN targeting is possible & as accurate as current expert methods.

Andrade-Souza et al., 20054

14 axial T2-weighted MRI, 3D reconstr (both direct & indirect)

optimal contact (MER & postop MRI)

distances to optimal contact: 2D MRI direct: 4.7 mm; 3D reconstr direct: 3.5 mm; 2D MRI indirect: 3.4 mm; 3D reconstr indirect: 2.6 mm

3D reconstr leads to a better ap- proximation of the optimal contact; indirect methods are better than direct targets.

Starr, 2002 44 coronal T2-weighted FSE MRI, AC-PC

comp in atlas coordinate system

in 34% the STN lies >1 mm more lateral than 12 mm & in 40% the STN lies >1 mm lower than 4 mm

Direct targeting accounts better for interpatient variability than indirect targeting.

Schlaier et al., 2005 14 axial/coronal T2-weighted MRI & atlas, AC-PC


all STN coordinates displayed a range of 4–5 mm

Direct targeting is more reliable due to large interpatient variability.

Ashkan et al., 2007 29 axial T2-weighted MRI, AC-PC


direct: 1.7 mm more medial, 0.7 mm more anterior, 0.7 mm more ventral

Direct targeting is more accurate due to variability in STN position.

Koike et al., 2008 44 T2-weighted FSE MRI (using RN), AC-PC

MER & clinical parameters

direct group: longer track through STN & larger clinical improvement

Direct targeting w/ single-track recording can be standard for DBS.

Acar et al., 2007 20 axial T2-weighted FSE MRI (3T), AC-PC (1.5T)


mean distances were 0.45 mm, 0.72 mm & 0.98 mm in x, y, z directions

Direct targeting is no longer im- practical and/or imprecise.

Caire et al., 2009 22 coronal T2-weighted TSE MRI, AC-PC

comp of STN center coordinates

sig differences in coordinates in all 3 directions

MRI- & AC-PC–based targets do not coincide.

* Reconstr = reconstruction.



981

sults of DBS, all these factors should be given appropriate attention.

ConclusionsThis review gave a systematic overview of studies

on noninvasive STN targeting. The studies either pre-sented a single indirect or direct targeting method, or compared different techniques. Because each method has been shown to have its own benefits but also specific drawbacks, it is not possible to reach a straightforward conclusion on which targeting technique should be used. Therefore, identification of the dorsolateral and motor part of the STN remains an open question, although it is expected that future advances in MRI technology will help to find an answer to this question.

Disclosure

The authors report no conflict of interest concerning the mate-rials or methods used in this study or the findings specified in this paper. Ellen Brunenberg’s research is supported by the Netherlands Organization for Scientific Research (NWO TopTalent grant).

Author contributions to the study and manuscript preparation include the following. Conception and design: Brunenberg, Platel, Visser-Vandewalle. Acquisition of data: Brunenberg. Analysis and interpretation of data: Brunenberg, Platel. Drafting the article: Brunenberg. Critically revising the article: all authors. Reviewed submitted version of manuscript: all authors. Approved the final ver-sion of the manuscript on behalf of all authors: Brunenberg. Study supervision: ter Haar Romeny, Visser-Vandevalle.

References

1. Abosch A, Yacoub E, Ugurbil K, Harel N: An assessment of current brain targets for deep brain stimulation surgery with susceptibility-weighted imaging at 7 tesla. Neurosurgery 67: 1745–1756, 2010

2. Acar F, Miller JP, Berk MC, Anderson G, Burchiel KJ: Safety of anterior commissure-posterior commissure-based target calculation of the subthalamic nucleus in functional stereo-tactic procedures. Stereotact Funct Neurosurg 85:287–291, 2007

3. Andrade-Souza YM, Schwalb JM, Hamani C, Eltahawy H, Hoque T, Saint-Cyr J, et al: Comparison of three methods of targeting the subthalamic nucleus for chronic stimulation in Parkinson’s disease. Neurosurgery 56 (2 Suppl):360–368, 2005

4. Andrade-Souza YM, Schwalb JM, Hamani C, Hoque T, Saint-Cyr J, Lozano AM: Comparison of 2-dimensional magnetic resonance imaging and 3-planar reconstruction methods for targeting the subthalamic nucleus in Parkinson disease. Surg Neurol 63:357–363, 2005

5. Ardekani BA, Bachman AH: Model-based automatic detec-tion of the anterior and posterior commissures on MRI scans. Neuroimage 46:677–682, 2009

6. Ashkan K, Blomstedt P, Zrinzo L, Tisch S, Yousry T, Limou-sin-Dowsey P, et al: Variability of the subthalamic nucleus: the case for direct MRI guided targeting. Br J Neurosurg 21:197–200, 2007

7. Aziz TZ, Nandi D, Parkin S, Liu X, Giladi N, Bain P, et al: Targeting the subthalamic nucleus. Stereotact Funct Neuro-surg 77:87–90, 2001

8. Bardinet E, Bhattacharjee M, Dormont D, Pidoux B, Malan-dain G, Schüpbach M, et al: A three-dimensional histological

atlas of the human basal ganglia. II. Atlas deformation strat-egy and evaluation in deep brain stimulation for Parkinson disease. Clinical article. J Neurosurg 110:208–219, 2009

9. Bardinet E, Dormont D, Malandain G, Bhattacharjee M, Pidoux B, Saleh C, et al: Retrospective cross-evaluation of a histological and deformable 3D atlas of the basal ganglia on series of Parkinsonian patients treated by deep brain stimula-tion. Med Image Comput Comput Assist Interv 8(Pt 2): 385–393, 2005

10. Bejjani BP, Dormont D, Pidoux B, Yelnik J, Damier P, Arnulf I, et al: Bilateral subthalamic stimulation for Parkinson’s dis-ease by using three-dimensional stereotactic magnetic reso-nance imaging and electrophysiological guidance. J Neuro-surg 92:615–625, 2000

11. Benabid AL, Koudsie A, Benazzouz A, Le Bas JF, Pollak P: Imaging of subthalamic nucleus and ventralis intermedius of the thalamus. Mov Disord 17 (3 Suppl 3):S123–S129, 2002

12. Bonny J, Durif F, Bazin JE, Touraille E, Yelnik J, Renou JP: Contrast optimization of Macaca mulatta basal ganglia in magnetic resonance images at 4.7 Tesla. J Neurosci Methods 107:25–30, 2001

13. Breit S, LeBas JF, Koudsie A, Schulz J, Benazzouz A, Pol-lak P, et al: Pretargeting for the implantation of stimulation electrodes into the subthalamic nucleus: a comparative study of magnetic resonance imaging and ventriculography. Neuro-surgery 58 (1 Suppl):ONS83–ONS95, 2006

14. Brunenberg E, Pelgrim E, ter Haar Romeny B, Platel B: k-means and graph cuts clustering of diffusion MRI in rat STN. Proc Intl Soc Mag Reson Med 18:4045, 2010 (Abstract)

15. Brunenberg EJL, Vilanova A, Visser-Vandewalle V, Temel Y, Ackermans L, Platel B, et al: Automatic trajectory planning for deep brain stimulation: a feasibility study. Med Image Comput Comput Assist Interv 10(Pt 1):584–592, 2007

16. Brunenberg EJL, Prckovska V, Platel B, Strijkers GJ, ter Haar Romeny BM: Untangling a fiber bundle knot: preliminary results on STN connectivity using DTI and HARDI on rat brains. Proc Intl Soc Mag Reson Med 17:741, 2009 (Ab-stract)

17. Caire F, Ouchchane L, Coste J, Gabrillargues J, Derost P, Ulla M, et al: Subthalamic nucleus location: relationships between stereotactic AC-PC-based diagrams and MRI anatomy-based contours. Stereotact Funct Neurosurg 87:337–347, 2009

18. Castro FJ, Pollo C, Meuli R, Maeder P, Cuisenaire O, Cuadra MB, et al: A cross validation study of deep brain stimulation targeting: from experts to atlas-based, segmentation-based and automatic registration algorithms. IEEE Trans Med Im-aging 25:1440–1450, 2006

19. Cho ZH, Min HK, Oh SH, Han JY, Park CW, Chi JG, et al: Direct visualization of deep brain stimulation targets in Par-kinson disease with the use of 7-tesla magnetic resonance im-aging. Clinical article. J Neurosurg 113:639–647, 2010

20. Cho ZH, Oh SH, Kim JM, Park SY, Kwon DH, Jeong HJ, et al: Direct visualization of Parkinson’s disease by in vivo human brain imaging using 7.0T magnetic resonance imaging. Mov Disord 26:713–718, 2011

21. Coenen VA, Mädler B, Schiffbauer H, Urbach H, Allert N: Individual fiber anatomy of the subthalamic region revealed with DTI—a concept to identify the DBS target for tremor suppression: erratum. Neurosurgery 68:1780–1781, 2011

22. Collins DL, Zijdenbos AP, Kollokian V, Sled JG, Kabani NJ, Holmes CJ, et al: Design and construction of a realistic digi-tal brain phantom. IEEE Trans Med Imaging 17:463–468, 1998

23. Cuny E, Guehl D, Burbaud P, Gross C, Dousset V, Rougier A: Lack of agreement between direct magnetic resonance imag-ing and statistical determination of a subthalamic target: the role of electrophysiological guidance. J Neurosurg 97:591–597, 2002

24. D’Haese PF, Cetinkaya E, Konrad PE, Kao C, Dawant BM:



Computer-aided placement of deep brain stimulators: from planning to intraoperative guidance. IEEE Trans Med Im-aging 24:1469–1478, 2005

25. Daniluk S, Davies K: Optimal stimulation site. J Neurosurg 108:425–429, 2008 (Letter)

26. Daniluk S, Davies KG, Ellias SA, Novak P, Nazzaro JM: As-sessment of the variability in the anatomical position and size of the subthalamic nucleus among patients with advanced Parkinson’s disease using magnetic resonance imaging. Acta Neurochir (Wien) 152:201–210, 2010

27. Danish SF, Jaggi JL, Moyer JT, Finkel L, Baltuch GH: Con-ventional MRI is inadequate to delineate the relationship be-tween the red nucleus and subthalamic nucleus in Parkinson’s disease. Stereotact Funct Neurosurg 84:12–18, 2006

28. Davies KG, Daniluk S: Stereotactic targeting of the subtha-lamic nucleus: relevance of magnetic resonance-based evalu-ation of interindividual variation in diencephalic anatomy. Stereotact Funct Neurosurg 86:330–331, 2008

29. Dormont D, Ricciardi KG, Tandé D, Parain K, Menuel C, Galanaud D, et al: Is the subthalamic nucleus hypointense on T2-weighted images? A correlation study using MR imaging and stereotactic atlas data. AJNR Am J Neuroradiol 25: 1516–1523, 2004

30. Dormont D, Seidenwurm D, Galanaud D, Cornu P, Yelnik J, Bardinet E: Neuroimaging and deep brain stimulation. AJNR Am J Neuroradiol 31:15–23, 2010

31. Duay V, Bresson X, Castro JS, Pollo C, Cuadra MB, Thiran JP: An active contour-based atlas registration model applied to automatic subthalamic nucleus targeting on MRI: method and validation. Med Image Comput Comput Assist Interv 11(Pt 2):980–988, 2008

32. Egidi M, Rampini P, Locatelli M, Farabola M, Priori A, Pesenti A, et al: Visualisation of the subthalamic nucleus: a multiple sequential image fusion (MuSIF) technique for di-rect stereotaxic localisation and postoperative control. Neurol Sci 23 (2 Suppl 2):S71–S72, 2002

33. Elolf E, Bockermann V, Gringel T, Knauth M, Dechent P, Helms G: Improved visibility of the subthalamic nucleus on high-resolution stereotactic MR imaging by added suscepti-bility (T2*) contrast using multiple gradient echoes. AJNR Am J Neuroradiol 28:1093–1094, 2007

34. Giller CA, Babcock EE, Mendelsohn DB: Use of sagittal im-ages for localization of the subthalamic nucleus. Technical note. J Neurosurg 102:571–575, 2005

35. Guehl D, Edwards R, Cuny E, Burbaud P, Rougier A, Modolo J, et al: Statistical determination of the optimal subthalamic nucleus stimulation site in patients with Parkinson disease. J Neurosurg 106:101–110, 2007

36. Guo T, Deoni SCL, Finnis KW, Parrent AG, Peters TM: Ap-plication of T1 and T2 maps for stereotactic deep-brain neu-rosurgery planning. Conf Proc IEEE Eng Med Biol Soc 5: 5416–5419, 2005

37. Guo T, Finnis KW, Deoni SC, Parrent AG, Peters TM: Com-parison of different targeting methods for subthalamic nucle-us deep brain stimulation. Med Image Comput Comput As-sist Interv 9(Pt 1):768–775, 2006

38. Guo T, Parrent AG, Peters TM: Automatic target and trajec-tory identification for deep brain stimulation (DBS) proce-dures. Med Image Comput Comput Assist Interv 10(Pt 1): 483–490, 2007

39. Guo T, Parrent AG, Peters TM: Surgical targeting accuracy analysis of six methods for subthalamic nucleus deep brain stimulation. Comput Aided Surg 12:325–334, 2007

40. Hamani C, Richter EO, Andrade-Souza Y, Hutchison W, Saint-Cyr JA, Lozano AM: Correspondence of microelec-trode mapping with magnetic resonance imaging for subtha-lamic nucleus procedures. Surg Neurol 63:249–253, 2005

41. Hamani C, Saint-Cyr JA, Fraser J, Kaplitt M, Lozano AM: The subthalamic nucleus in the context of movement disor-ders. Brain 127:4–20, 2004

42. Hamel W, Fietzek U, Morsnowski A, Schrader B, Herzog J, Weinert D, et al: Deep brain stimulation of the subthalamic nucleus in Parkinson’s disease: evaluation of active electrode contacts. J Neurol Neurosurg Psychiatry 74:1036–1046, 2003

43. Hamid NA, Mitchell RD, Mocroft P, Westby GWM, Milner J, Pall H: Targeting the subthalamic nucleus for deep brain stimulation: technical approach and fusion of pre- and post-operative MR images to define accuracy of lead placement. J Neurol Neurosurg Psychiatry 76:409–414, 2005

44. Hariz MI, Krack P, Melvill R, Jorgensen JV, Hamel W, Hira-bayashi H, et al: A quick and universal method for stereotac-tic visualization of the subthalamic nucleus before and after implantation of deep brain stimulation electrodes. Stereotact Funct Neurosurg 80:96–101, 2003

45. Helms G, Gringel T, Knauth M, Dechent P, Elolf E: Delin-eation of the subthalamic nucleus (STN) on high-resolution maps of R2*. Proc Intl Soc Mag Reson Med 16:880, 2008 (Abstract)

46. Hunsche S, Sauner D, Maarouf M, Poggenborg J, Lackner K, Sturm V, et al: Intraoperative X-ray detection and MRI-based quantification of brain shift effects subsequent to implanta-tion of the first electrode in bilateral implantation of deep brain stimulation electrodes. Stereotact Funct Neurosurg 87:322–329, 2009

47. Ishimori T, Nakano S, Mori Y, Seo R, Togami T, Masada T, et al: Preoperative identification of subthalamic nucleus for deep brain stimulation using three-dimensional phase sensi-tive inversion recovery technique. Magn Reson Med Sci 6: 225–229, 2007

48. Kitajima M, Kakeda S, Moriya J, Ohnari N, Sato T, Hayashida Y, et al: Direct visualization of normal subthalamic nucleus with high resolution MR imaging at 3.0 T: comparison be-tween FSE T2-WI and fast STIR image. Proc Intl Soc Mag Reson Med 15:780, 2007 (Abstract)

49. Koike Y, Shima F, Nakamizo A, Miyagi Y: Direct localization of subthalamic nucleus supplemented by single-track elec-trophysiological guidance in deep brain stimulation lead im-plantation: techniques and clinical results. Stereotact Funct Neurosurg 86:173–178, 2008

50. Lanotte MM, Rizzone M, Bergamasco B, Faccani G, Mel-carne A, Lopiano L: Deep brain stimulation of the subtha-lamic nucleus: anatomical, neurophysiological, and outcome correlations with the effects of stimulation. J Neurol Neuro-surg Psychiatry 72:53–58, 2002

51. Lebel RM, Eissa A, Gee M, Wieler M, Martin WR, Wilman AH: MRI methods at 4.7 T for imaging Parkinson’s disease. Proc Intl Soc Mag Reson Med 16:2283, 2008 (Abstract)

52. Lee C, Young B, Sanders MF: The role of the supramammilla-ry commissure in MR localization of the subthalamic nucleus. Stereotact Funct Neurosurg 84:193–204, 2006

53. Lemaire JJ, Coste J, Ouchchane L, Caire F, Nuti C, Derost P, et al: Brain mapping in stereotactic surgery: a brief overview from the probabilistic targeting to the patient-based anatomic mapping. Neuroimage 37 (1 Suppl 1):S109–S115, 2007

54. Lemaire JJ, Coste J, Ouchchane L, Hemm S, Derost P, Ulla M, et al: MRI anatomical mapping and direct stereotactic tar-geting in the subthalamic region: functional and anatomical correspondence in Parkinson’s disease. Int J CARS 2:75–85, 2007

55. Littlechild P, Varma TRK, Eldridge PR, Fox S, Forster A, Fletcher N, et al: Variability in position of the subthalamic nucleus targeted by magnetic resonance imaging and micro-electrode recordings as compared to atlas co-ordinates. Ste-reotact Funct Neurosurg 80:82–87, 2003

56. Liu X, Rowe J, Nandi D, Hayward G, Parkin S, Stein J, et al: Localisation of the subthalamic nucleus using Radionics Image Fusion and Stereoplan combined with field potential recording. A technical note. Stereotact Funct Neurosurg 76: 63–73, 2001



983

57. Menuel C, Garnero L, Bardinet E, Poupon F, Phalippou D, Dormont D: Characterization and correction of distortions in stereotactic magnetic resonance imaging for bilateral sub-thalamic stimulation in Parkinson disease. J Neurosurg 103: 256–266, 2005

58. Mori S, Zhang J: Principles of diffusion tensor imaging and its applications to basic neuroscience research. Neuron 51:527–539, 2006

59. Nowinski WL, Belov D, Pollak P, Benabid AL: A probabilistic functional atlas of the human subthalamic nucleus. Neuroin-formatics 2:381–398, 2004

60. Nowinski WL, Liu J, Thirunavuukarasuu A: Quantification and visualization of the three-dimensional inconsistency of the subthalamic nucleus in the Schaltenbrand-Wahren brain atlas. Stereotact Funct Neurosurg 84:46–55, 2006

61. Nowinski WL, Thirunavuukarasuu A, Liu J, Benabid AL: Correlation between the anatomical and functional human subthalamic nucleus. Stereotact Funct Neurosurg 85:88–93, 2007

62. Ortega M, Juan MC, Alcañiz M, Gil JA, Monserrat C: De-formable brain atlas validation of the location of subthalamic nucleus using T1-weighted MR images of patients operated on for Parkinson’s. Comput Med Imaging Graph 32:367–378, 2008

63. Pallavaram S, D’Haese PF, Kao C, Yu H, Remple M, Neimat J, et al: A new method for creating electrophysiological maps for DBS surgery and their application to surgical guidance. Med Image Comput Comput Assist Inter 11(Pt 1):670–677, 2008

64. Pallavaram S, Dawant BM, Koyama T, Yu H, Neimat J, Kon-rad PE, et al: Validation of a fully automatic method for the routine selection of the anterior and posterior commissures in magnetic resonance images. Stereotact Funct Neurosurg 87:148–154, 2009

65. Pallavaram S, Yu H, Spooner J, D’Haese PF, Bodenheimer B, Konrad PE, et al: Intersurgeon variability in the selection of anterior and posterior commissures and its potential effects on target localization. Stereotact Funct Neurosurg 86:113–119, 2008

66. Patel NK, Heywood P, O’Sullivan K, Love S, Gill SS: MRI-directed subthalamic nucleus surgery for Parkinson’s disease. Stereotact Funct Neurosurg 78:132–145, 2002

67. Patel NK, Khan S, Gill SS: Comparison of atlas- and mag-netic-resonance-imaging-based stereotactic targeting of the subthalamic nucleus in the surgical treatment of Parkinson’s disease. Stereotact Funct Neurosurg 86:153–161, 2008

68. Patel NK, Plaha P, O’Sullivan K, McCarter R, Heywood P, Gill SS: MRI directed bilateral stimulation of the subthalamic nucleus in patients with Parkinson’s disease. J Neurol Neuro-surg Psychiatry 74:1631–1637, 2003

69. Pollak P, Benabid AL, Gross C, Gao DM, Laurent A, Benaz-zouz A, et al: [Effects of the stimulation of the subthalamic nucleus in Parkinson disease.] Rev Neurol (Paris) 149:175–176, 1993 (Fr)

70. Pollo C, Meuli R, Maeder P, Vingerhoets F, Ghika J, Ville-mure JG: Subthalamic nucleus deep brain stimulation for Par-kinson’s disease: magnetic resonance imaging targeting using visible anatomical landmarks. Stereotact Funct Neurosurg 80:76–81, 2003

71. Rauscher A, Witoszynskyj S, Kolind S, Coenen V, Li D: Vi-sualization of the subthalamic nuclei at high spatial resolution and high contrast with susceptibility weighted phase imaging. Proc Intl Soc Mag Reson Med 16:879, 2008 (Abstract)

72. Richter EO, Hoque T, Halliday W, Lozano AM, Saint-Cyr JA: Determining the position and size of the subthalamic nucle-us based on magnetic resonance imaging results in patients with advanced Parkinson disease. J Neurosurg 100:541–546, 2004

73. Rijkers K, Temel Y, Visser-Vandewalle V, Vanormelingen L,

Vandersteen M, Adriaensen P, et al: The microanatomical en-vironment of the subthalamic nucleus. Technical note. J Neu-rosurg 107:198–201, 2007

74. Rodriguez-Oroz MC, Zamarbide I, Guridi J, Palmero MR, Obeso JA: Efficacy of deep brain stimulation of the subtha-lamic nucleus in Parkinson’s disease 4 years after surgery: double blind and open label evaluation. J Neurol Neurosurg Psychiatry 75:1382–1385, 2004

75. Saint-Cyr JA, Hoque T, Pereira LCM, Dostrovsky JO, Hutchi-son WD, Mikulis DJ, et al: Localization of clinically effec-tive stimulating electrodes in the human subthalamic nucleus on magnetic resonance imaging. J Neurosurg 97:1152–1166, 2002

76. Sánchez Castro FJ, Pollo C, Villemure JG, Thiran JP: Auto-matic subthalamic nucleus targeting for deep brain stimula-tion. A validation study, in: International Congress Series (CARS 2005: Computer Assisted Radiology and Surgery). Amsterdam: Elsevier, 2005, Vol 1281, pp 804–809

77. Schaltenbrand G, Wahren W: Atlas for Stereotaxy of the Hu-man Brain, ed 2. Stuttgart: Thieme, 1977

78. Schlaier J, Schoedel P, Lange M, Winkler J, Warnat J, Doren-beck U, et al: Reliability of atlas-derived coordinates in deep brain stimulation. Acta Neurochir (Wien) 147:1175–1180, 2005

79. Schuurman PR, de Bie RM, Majoie CB, Speelman JD, Bosch DA: A prospective comparison between three-dimensional magnetic resonance imaging and ventriculography for target-coordinate determination in frame-based functional stereo-tactic neurosurgery. J Neurosurg 91:911–914, 1999

80. Slavin KV, Thulborn KR, Wess C, Nersesyan H: Direct vi-sualization of the human subthalamic nucleus with 3T MR imaging. AJNR Am J Neuroradiol 27:80–84, 2006

81. Starr PA: Placement of deep brain stimulators into the subtha-lamic nucleus or globus pallidus internus: technical approach. Stereotact Funct Neurosurg 79:118–145, 2002

82. Starr PA, Christine CW, Theodosopoulos PV, Lindsey N, Byrd D, Mosley A, et al: Implantation of deep brain stimu-lators into the subthalamic nucleus: technical approach and magnetic resonance imaging-verified lead locations. J Neuro-surg 97:370–387, 2002

83. Starr PA, Vitek JL, DeLong M, Bakay RA: Magnetic reso-nance imaging-based stereotactic localization of the globus pallidus and subthalamic nucleus. Neurosurgery 44:303–314, 1999

84. Sun DA, Yu H, Spooner J, Tatsas AD, Davis T, Abel TW, et al: Postmortem analysis following 71 months of deep brain stimulation of the subthalamic nucleus for Parkinson disease. Case report. J Neurosurg 109:325–329, 2008

85. Talairach J, Tournoux P: Co-planar Stereotaxic Atlas of the Human Brain. New York: Thieme, 1988

86. Taoka T, Hirabayashi H, Nakagawa H, Sakamoto M, Kitano S, Takahama J, et al: “Sukeroku sign” and “dent internal-cap-sule sign”—identification guide for targeting the subthalamic nucleus for placement of deep brain stimulation electrodes. Neuroradiology 51:11–16, 2009

87. Taoka T, Kubota Y, Hirabayashi H, Nakagawa H, Sakamoto M, Iwasaki S, et al: Signal and shape of subthalamic nucleus on susceptibility-weighted image (SWI): comparison with STIR image. Proc Intl Soc Mag Reson Med 15:2175, 2007 (Abstract)

88. Temel Y, Blokland A, Steinbusch HWM, Visser-Vandewalle V: The functional role of the subthalamic nucleus in cognitive and limbic circuits. Prog Neurobiol 76:393–413, 2005

89. Temel Y, Kessels A, Tan S, Topdag A, Boon P, Visser-Vande-walle V: Behavioural changes after bilateral subthalamic stimulation in advanced Parkinson disease: a systematic re-view. Parkinsonism Relat Disord 12:265–272, 2006

90. Temel Y, Prinsenberg T, Visser-Vandewalle V: Imaging of the subthalamic nucleus for deep brain stimulation: a systematic review. Neuromodulation 11:8–12, 2008



91. Toda H, Sawamoto N, Hanakawa T, Saiki H, Matsumoto S, Okumura R, et al: A novel composite targeting method using high-field magnetic resonance imaging for subthalamic nucleus deep brain stimulation. Clinical article. J Neurosurg 111:737–745, 2009

92. Tsai ST, Lin SH, Lin SZ, Chen JY, Lee CW, Chen SY: Neuropsychological effects after chronic subthalamic stimula-tion and the topography of the nucleus in Parkinson’s disease. Neu rosurgery 61:E1024–E1030, 2007

93. Tuch DS, Reese TG, Wiegell MR, Makris N, Belliveau JW, Wedeen VJ: High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity. Magn Reson Med 48:577–582, 2002

94. Vertinsky AT, Coenen VA, Lang DJ, Kolind S, Honey CR, Li D, et al: Localization of the subthalamic nucleus: optimization with susceptibility-weighted phase MR imaging. AJNR Am J Neuroradiol 30:1717–1724, 2009

95. Visser-Vandewalle V, van der Linden C, Temel Y, Celik H, Ac kermans L, Spincemaille G, et al: Long-term effects of bilat-eral subthalamic nucleus stimulation in advanced Parkinson dis-ease: a four year follow-up study. Parkinsonism Relat Disord 11:157–165, 2005

96. Volkmann J, Allert N, Voges J, Weiss PH, Freund HJ, Sturm V: Safety and efficacy of pallidal or subthalamic nucleus stimula-tion in advanced PD. Neurology 56:548–551, 2001

97. Volz S, Hattingen E, Preibisch C, Gasser T, Deichmann R: Reduction of susceptibility-induced signal losses in multi-gra-dient-echo images: application to improved visualization of the subthalamic nucleus. Neuroimage 45:1135–1143, 2009

98. Voon V, Kubu C, Krack P, Houeto JL, Tröster AI: Deep brain stimulation: neuropsychological and neuropsychiatric issues. Mov Disord 21 (Suppl 14):S305–S327, 2006

99. Wu ML, Young GS, Chen NK: Midbrain nuclei visualization improved by susceptibility-enhanced 3D multi-echo SSFP for deep brain stimulation guidance. Proc Intl Soc Mag Reson Med 18:701, 2010 (Abstract)

100. Yelnik J, Bardinet E, Dormont D, Malandain G, Ourselin S, Tandé D, et al: 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, 2007

101. Young GS, Chen NK: High contrast susceptibility weighted imaging: Reliable Unwrapping Susceptibility Technique (RUST SWI) improved visualization of midbrain nuclei for deep brain stimulation. Proc Intl Soc Mag Reson Med 15: 937, 2007 (Abstract)

102. Zhu XL, Hamel W, Schrader B, Weinert D, Hedderich J, Herzog J, et al: Magnetic resonance imaging-based morphometry and landmark correlation of basal ganglia nuclei. Acta Neurochir (Wien) 144:959–969, 2002

103. Zonenshayn M, Rezai AR, Mogilner AY, Beric A, Sterio D, Kelly PJ: Comparison of anatomic and neurophysiological methods for subthalamic nucleus targeting. Neurosurgery 47: 282–294, 2000

Manuscript submitted September 9, 2010.Accepted June 8, 2011.Please include this information when citing this paper: pub-

lished online July 29, 2011; DOI: 10.3171/2011.6.JNS101571.Address correspondence to: Ellen J. L. Brunenberg, Eindhoven

University of Technology, Department of Biomedical Engineering, WH 2.106, PO Box 513, 5600 MB Eindhoven, The Netherlands. email: [email protected].

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