NeuroImage 62 (2012) 1600–1609

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A new approach for corticospinal tract reconstruction based on navigatedtranscranial stimulation and standardized fractional anisotropy values

D. Frey a,⁎, V. Strack a, E. Wiener b, D. Jussen a, P. Vajkoczy a, T. Picht a

a Department of Neurosurgery, Charité University Hospital, Berlin, Germanyb Department of Neuroradiology, Charité University Hospital, Berlin, Germany

Abbreviations: BMRC, British Medical Research Costrength); DES, direct electrical stimulation; DTI, diffusitromyogram; M1, primary motor cortex; MEP, motor evresonance imaging; nTMS, navigated transcranial magntract; RMT, resting motor threshold; SD, standard devia⁎ Corresponding author at: Charité University Hospita

Augustenburger Platz 1, 13353 Berlin, Germany. Fax: +4E-mail address: dietmar.frey@charite.de (D. Frey).

1053-8119/$ – see front matter © 2012 Elsevier Inc. Alldoi:10.1016/j.neuroimage.2012.05.059

a b s t r a c t

a r t i c l e i n f o

Article history:

Accepted 22 May 2012Available online 29 May 2012

Keywords:Diffusion tensor imagingTranscranial magnetic stimulationFA thresholdPreoperative planningIntraoperative stimulationBrain tumors

Purpose: To establish a novel approach for fiber tracking based on navigated transcranial magnetic stimulation(nTMS) mapping of the primary motor cortex and to propose a new algorithm for determination of an individ-ualized fractional anisotropy value for reliable and objective fiber tracking.Methods: 50 patients (22 females, 28males, median age 58 years (20–80)) with brain tumors compromising theprimary motor cortex and the corticospinal tract underwent preoperative MR imaging and nTMS mapping.Stimulation spots evoking muscle potentials (MEP) closest to the tumor were imported into the fiber trackingsoftware and set as seed points for tractography. Next the individual FA threshold, i.e. the highest FA value lead-ing to visualization of tracts at a predefined minimum fiber length of 110 mm, was determined. Fiber trackingwas then performed at a fractional anisotropy value of 75% and 50% of the individual FA threshold. In addition,fiber tracking according to the conventional knowledge-based approachwas performed. Results of tractography

of either method were presented to the surgeon for preoperative planning and integrated into the navigationsystem and its impact was rated using a questionnaire.Results: Mapping of the motor cortex was successful in all patients. A fractional anisotropy threshold forcorticospinal tract reconstruction could be obtained in every case. TMS-based results changed or modified surgi-cal strategy in 23 of 50 patients (46%), whereas knowledge-based results would have changed surgical strategyin 11 of 50 patients (22%). Tractography results facilitated intraoperative orientation and electrical stimulation in28 of 50 (56%) patients. Tracking at 75% of the individual FA thresholds was considered most beneficial by therespective surgeons.Conclusions: Fiber tracking based on nTMS by the proposed standardized algorithm represents an objective visu-alization method based on functional data and provides a valuable instrument for preoperative planning andintraoperative orientation and monitoring.

© 2012 Elsevier Inc. All rights reserved.

Introduction

Neurosurgeons must always carefully balance the benefit of surgi-cal therapy against the risk of causing or increasing neurological symp-toms. Since preoperative risk assessment on the basis of standardanatomical imaging alone is often insufficient non-invasive identifica-tion and visualization of eloquent areas in the preoperative work-upare becoming increasingly important in brain tumor surgery (Changet al., 2011). Over the last few years, navigated transcranial magneticstimulation (nTMS) has become a valuable tool for a reliable preopera-tive identification of cortical areas that are essential for motor function

uncil (scale for rating motoron tensor imaging; EMG, elec-oked potential; MRI, magneticetic stimulation; PT, pyramidaltion.l, Department of Neurosurgery,9 30450560929.

rights reserved.

(Forster et al., 2011; Picht et al., 2012).With thismethod, detailedmapsrepresenting the cortical functional organization of the brain can begenerated and provide useful information replenishing the sole ana-tomical data. DTI-based fiber tracking is a method that allows forthe pre- and intraoperative visualization of white matter tracts fromselected seed points. Usually those seed points are placed according toanatomical landmarks such as the brain stem or the precentral gyrus,yet these can be hard to identify especially in patients with space-occupying lesions (Nimsky et al., 2006). Another important parameterinfluencing the resulting tractography is the fractional anisotropy(FA), which represents the direction-dependence in a diffusion processlike DTI (Basser et al., 1994, 2000). Until now this value was set ratherarbitrarily to predefined values for all patients or adjusted accordingto the examiner's a priori expectation about what the tracks shouldlook like. The present study was motivated by our observation thatthe approach with whole brain tractography and subsequent exclusionof all fibers which do not pass anatomical landmarks e.g. the internalcapsule led to remarkably variable results. This holds true especiallyfor tumor cases with obscured anatomy. The hypothesis is that a

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function-based seed area (i.e. the primary motor cortex next to thetumor) will a priori exclude a lot of variation and help to objectify thetracking procedure. This prospective study has been outlined to provethe feasibility of fiber tracking of themotor pathways using a functionalseed point provided by nTMS and to demonstrate its impact on thesurgical strategy. It also defines the notion of a fractional anisotropythreshold allowing for an individually tailored representation of thecorticospinal tract.

Methods

Ethics

The study proposal was approved by the Ethics Commission ofthe Charité University Hospital (reference # EA4/007/06). The patientsprovided written informed consent for all medical evaluation andtreatment.

Patients

The study was designed as a prospective case collection study. Be-tween 01/2008 and 09/2011 patients scheduled for tumor removalin the vicinity of the central region were screened for enrolment. Theinclusion criteria were: 1) existence of a brain tumor compressing/infiltrating the corticospinal tract and 2) obscured anatomy of the pri-mary motor cortex and/or the corticospinal tract due to the masseffect of the tumor or infiltrating growth. The exclusion criteria were:1) frequent seizures (more than 1/week) and 2) existence of a pace-maker or “deep brain stimulation” electrodes. Patients meeting thesecriteria underwent preoperativemagnetic resonance imaging includingnavigational and diffusionweighted sequences. Subsequently, function-al testing of cortical motor representation and special anatomicalimagingwas performed. 50 patients were included in the study. Detailson the study population can be found in Table 1.

Acquisition of MRI data

Conventional imaging was performed on a 1.5 T or 3 T MR imaging-unit (GE Healthcare, Milwaukee, Wis) with an 8-channel head coilincluding a T1-weighted (TR/TE 565 ms/14 ms) and T2-weighted(TR/TE 5200 ms/100 ms) fast spin-echo sequences, a T2-weightedinversion recovery (TR/TE/TI 6000 ms/ 150 ms/ 2000 ms) fast spin-echo sequence, a T2*-weighted (TR/TE/α 800 ms/30 ms/20°) gradient-echo sequence and a 1.0-mm section thickness T1 inversion recovery(TR/TE/TI/α 7.8 ms/3.1 ms/500 ms/16°) 3D gradient-echo sequence(IR 3D-FSPGR).

Diffusion tensor imaging (DTI) was performed on a 3 TMR imaging-unit (GE Healthcare, Milwaukee, Wis) using an 8-channel head coil.Diffusion tensor was sampled by repeating a diffusion weightedsingle-shot echo-planar sequence along 23 different geometric direc-tions at a b-value of 1000 s/mm2. An additional measurement withoutdiffusion weighting (b=0 s/mm2) was performed. Scan param-eters were TR/TE 11,000 ms/83 ms; matrix size 128×128; and FOV240×240 mm. A total of 42 contiguous 3 mm thick axial sectionswere acquired, resulting in a total of 1008 images. The total acquisitiontime was approximately 8 min.

Navigated transcranial magnetic stimulation

Navigated transcranial stimulation (nTMS) deliversmagnetic stimu-lations to precisely defined spots on the patient's motor cortex. Appliedto primary motor areas the magnetic stimulus evokes a corticospinalvolley which elicits muscle twitching recordable with EMG in order todetermine the functional relevance of each spot in the motor cortex(Di Lazzaro et al., 2007). In this study nTMS was performed using a bi-phasic TMS system with a 50 mm-mean wing diameter figure-of-

eight coil (Eximia NBS; Nexstim; Helsinki, Finland). This system per-forms transcranial magnetic stimulation with simultaneous pulse-by-pulse quantification of coil orientation, location, and tilt, as well asestimates of target site, location, and electric field strength. It then esti-mates the induced electric field, based on a spherical model and thephysical parameters of stimulation. The patients were seated in a com-fortable reclining chair to assure a maximal relaxing position.

Prior to stimulation, anatomical data fromMRI scans were importedinto the TMS system, and co-registration was then performed using an-atomical landmarks and surface registration. Surface EMG-electrodeswere attached to the abductor pollicis brevis muscle (APB), the firstdigital interosseus muscle (FDI), the adductor digiti minimi (ADM)and the tibial anterior muscle (TA). The EMG acquisition parameterswere the following: sampling rate of 3 kHz, EMG resolution of 0.3 μV,CMRR>90 dB at frequencies between 10 and 250 Hz, noiseb5 μVpeak-to-peak, frequency band of 10–500 Hz. EMG results were inte-grated and evaluated in the TMS system.

As the initial step of stimulation, the unaffected contralesionalhemisphere was stimulated above threshold level, while systemati-cally varying the location over the suspected primary cortex, andalso varying the coil tilt and rotation (Picht et al., 2009). The coil tiltwas adjusted to achieve maximum field strength at the center ofthe stimulation as visualized by the software. The coil orientationwas varied at the same stimulation points to allow for maximal topo-graphic accuracy, beginning with a perpendicular approach with rela-tion to the sulci. The point eliciting the maximal MEP in the APB wasthen used for definition of the resting motor threshold (RMT). TheRMT was defined statistically with 15 subsequent motor-evokedpotentials (MEPs) according to an efficient maximum-likelihoodalgorithm (Awiszus et al., 1999). Mapping of the motor cortex on thetumor hemisphere was then performed at 110% of the RMT. The stimu-lation was carried out in a close raster, covering the tumor and theadjacent gyri with the stimulation spots separated by 2–5 mm. Inareas of critical interest (e.g. the tumor border), stimulation was per-formed with greater spatial density and more variation of coil rotation,to ensuremaximal topographic accuracy. (Picht et al., 2009, 2012). In allcases where either clinical impairment of the lower extremities wasapparent or the tumor was expanding medially to the anatomicalhand knob we recorded TA EMG (n=27). If no responses could berecorded at 110% APB RMT we subsequently increased the stimulationintensity in steps of 5% stimulator output until responses were seen.MEP over 50 μV (peak-to-peak) were regarded as motor positive spotsand visualized in the final mapping cartography.

Fiber tracking

Fiber tracts were visualized using a dedicated tracking software(Brainlab iPlan 2.0, Heimstetten, Germany). In principle, the fibertracking adhered to the tractography methods previously described(Basser et al., 2000; Mori and Van Zijl, 2002; Mori et al., 2002), exceptwhere noted below. The following settings were applied for all trackings:a vector step length of 1.6 mm, an angular threshold of 30°, and a tracklength of 110 mm. First, fiber tracking was performed by an experiencedneuroradiologist or neurosurgeon applying a predefined FA threshold(0.2) and knowledge-based seed point definition at the level of thebrainstem or the internal capsule (Gerardin et al., 2003; Lazar et al.,2003; Nimsky et al., 2006).

In addition, we performed fiber tracking according to our pro-posed algorithm: The nTMS-stimuli, which were located closest tothe tumor and elicited a MEP were imported into the fiber trackingsoftware and set as seed points for tractography. The use of thesame anatomical MRI datasets for the generation of nTMS maps andDTI based tractography assured the preservation of the spots' originalposition along the exportation process. The defined starting pointswere then enlarged by a concentric halo with a diameter of 6 mm inorder to form a continuous seed area. Calculation of fiber tracts was

Table 1Patient characteristics.

No. Age Sex Histology Location Motor status Thresholdof fractionalanisotropy(FAT)

Change ormodification ofsurgical approacbased onknowledge-basefiber tracking

Change ormodification ofsurgical approachbased onnTMS-basedfiber tracking

Added knowledgebut did not leadto modification/change ofsurgical approach

Facilitation ofintraoperativeorientation andmonitoring

Pre OP Day 1 Day 7 3 months

1 61 M Metastasis R, postcentral HP 4 HP 4 LEP 4 LEP 5 0.202 57 M Glioma IV R, central, PT UEP 4 UEP 4 UEP 4 UEP 3 0.14 x3 59 M Meningioma L, central 5 UEP 2+LEP 0 UEP 2+LEP 0 UEP 2+LEP 0 0.25 x x4 52 F Metastasis L, central HP 3 HP 4+ HP 4+ 5 0.19 x x5 67 F Metastasis L, central HP 3 UEP 0+LEP 3 HP 3 HP 3 0.22 x x6 71 M Glioma IV R, postcentral, PT LEP 4 LEP 4 LEP 4 LEP 4 0.16 x x7 68 M Glioma IV R, parietal HP 3 death n.a. n.a. 0.308 65 M Meningioma L, central 5, Ap UEP 3 5 5 0.25 x9 71 M Metastasis L, central HP 3 HP3 HP 3 n.a. 0.18 x10 50 F Glioma III R, precentral, PT UEP 0+LEP 2 UEP 0+LEP 2 UEP 0+LEP 2 UEP 0+LEP 2 0.14 x x x11 56 F Glioma III L, parietal 5, mild Ap 5, moderate Ap 5, mild Ap mild Ap 0.23 x12 33 F Glioma III L, postcentral 5 UEP 2+LEP 3 HP 3 5 0.33 x13 72 M Glioma IV R, PT HP 4 HP 0 UEP 0+LEP 2 HP 2 0.26 x x14 73 M Metastasis R, frontal, PT LEP 4+ LEP 4+ LEP 4+ follow-up 0.18 x15 68 F Metastasis L, precentral 5 5 5 5 0.2416 71 M Glioma IV L, central, PT HP 3 HP 1 HP 2 HP 3 0.09 x x17 63 F Metastasis R, frontal HP 4 HP 4+ HP 4+ HP 4 0.0818 58 F Metastasis L, frontal, PT HP 4+ 5 5 5 0.15 x x19 78 F Glioma IV R, central 5 5 5 5 0.33 x x20 59 M Metastasis R, central, PT LEP 3 LEP 3 LEP 3 LEP 3 0.11 x x21 80 M Glioma IV R, postcentral, PT HP 3 HP 3 UEP 0+LEP 3 HP2 0.16 x x22 47 F Metastasis R, postcentral HP 3 HP 3 5 5 0.13 x23 20 M Glioma R, postcentral, PT LEP 4 LEP 4 LEP 4 LEP 3 0.14 x x24 58 M Metastasis R, central, PT UEP 4−+LEP 4 HP 4− 5 5 0.15 x x25 32 M Glioma II L, postcentral HP 4 5 5 5 0.2326 48 M Glioma III L, central, PT 5, Ap 5 5 HP 4 0.14 x x x27 71 M Glioma II R, postcentral LEP 4 LEP 4+ LEP 4+ HP 4 0.21 x28 46 M Glioma II R, central 5 UEP 4 UEP 4+ 5 0.21 x x29 50 M Glioma III R, thalamus, PT 5 HP 2 UEP 3 UEP 2+LEP 4 0.08 x30 48 F Metastasis R, postcentral HP 4 HP 4 5 5 0.1531 69 F Glioma II L, frontal, PT 5 5 5 5 0.12 x32 63 M Metastasis R, frontal, PT HP 4 HP 4 HP 4 HP 4 0.19 x33 47 M Glioma IV L, precentral, PT UEP 4 UEP 4 UEP 4 HP 4 0.11 x x x34 26 M Glioma II R, postcentral 5 5 5 5 0.2635 69 M Glioma IV L, postcentral 5 5 5 HP 4 0.0736 29 F Glioma II R, central, PT HP 4 HP 4− HP 4+ HP 4 0.17 x x37 60 F Meningioma I L, central LEP 3 LEP 4 LEP 4+ LEP 4 0.2238 74 F Glioma IV R, precentral HP 4+ UEP 0 UEP 3 HP 4 0.11 x39 64 F Metastasis L, central, PT HP 4 HP 4 HP 4 HP 4 0.12 x x40 58 M Metastasis L, central UEP 4 UEP 4 UEP 4 UEP 4 0.21 x x x41 63 F Metastasis R, central, PT LEP 0+UEP 3 HP 3 HP 4 5 0.14 x x42 54 F Metastasis R, postcentral 5 5 5 5 0.3043 46 M Glioma II R, precentral 5 HP 3 HP 4 HP 4 0.31 x44 69 M Glioma IV R, precentral, PT 5 5 5 5 0.16 x x x45 76 F Metastasis R, precentral, PT 0 n.a. n.a. n.a. 0.09 x x x46 59 F Glioma III R, frontal 5 5 5 5 0.2647 56 M Glioma IV L, parietal UEP 4 HP 0 HP 4− HP 4 0.1848 50 F Glioma IV L, precentral 5 HP 0 UEP 4+ 5 0.34 x x x49 50 M Glioma IV R, frontal, PT 5 5 5 5 0.18 x x50 66 F Glioma IV L, precentral, PT HP 4 5 5 5 0.21 x x

R = right, L = left, PT = pyramidal tract involvement, HP = hemiparesis, UEP = arm paresis, LEP = leg paresis, Ap = aphasia. x = surgeon was presented 1) fiber tracks b ed on knowledge-based approach, and then 2) based on nTMS-based approach.

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then carried out. Tractography was performed in an anterograde direc-tion, according to the principal eigenvector's direction for each voxel inthe region of interest, as previously described (Basser et al., 2000; Moriet al., 2002; Nimsky et al., 2006). For fractional anisotropy threshold(FAT) determination the following procedure was applied: the FAvalue was increased stepwise until no fibers were generated; subse-quently the FA value was reduced by the minimal unit of 0.01, thus vi-sualizing a very thin fiber course originating from one of the importedseed points. The obtained value was set as a fractional anisotropy of100% or fractional anisotropy threshold (FAT). Tractography was thenperformed at 75% and 50% FAT. Color-encoding followed the conven-tion used in FAmaps: superior–inferior directions in blue, left–right di-rections in red, and anterior–posterior directions in green. Fig. 1Asummarizes the sequence of data acquisition and processing.

Integration into surgical planning and procedures

Prior to surgery the respective neurosurgeon was asked to state hissurgical strategy based on the anatomicalMRI scans. The questionnaireincluded: site and size of craniotomy, site of corticotomy, expectedpath of pyramidal tract, and planned extent of resection. Subsequentlythe surgeon was presented with three sets of DTI trackings. He wasblinded to which were generated with knowledge-based seed pointsversus TMS based seed points at 75% and 50% FAT. The surgeon thenrated the quality of each DTI image set. The additional impact of DTIimaging on preoperative planning was documented. During surgerythe generated fiber tracks were displayed via heads-up display in themicroscope. The respective surgeon was then asked if these data hel-ped to guide the intraoperative stimulation probe.

Results

Patient sample

There were 50 patients who were included in this study, all ofthem suffering from space-occupying lesions in the central regionmaking clear distinction and definition of anatomical landmarks diffi-cult or impossible. The patient sample included 22 women and 28

Fig. 1. Subpanel A shows sequence of the proposed work flow: MR scanning navigated tran(FAT), fiber tracking and integration into the surgical work-flow. Subpanel B shows influendividually determined according to the suggested protocol. Seed point definition was performvector step length of 1.6 mm, an angular threshold of 30°, and a track length of 110 mm.

men. The median age was 58 (20–80). Histological diagnosis wasprovided for each patient. There were 29 patients with glioma tumors(WHO grades 2–4), 18 patients with metastases, and 3 with meningi-oma. Patient details can be found in Table 1.

Navigated transcranial stimulation

Brain mapping by nTMS did not evoke any seizures or other neuro-logical side effects. 5 patients complained about transient headache. Adetailed cartography of cortical motor function could be established inall cases. In patients with additional lower extremity impairment TAMEPs could be evoked in 15 patients at 110% APB RMT, in 4 at 115%,in 5 at 120%, and in 2 at 125%. In 1 patient no TA EMG was recordable.The stimulation spots outlining the primary motor cortex closest tothe tumorwere transferred to the navigational planning station for fur-ther analysis. An average (range) of 6.2 (3–9) nTMS spotswas exported.

Fiber tracking

By applying the knowledge-based approach placement or size ofthe knowledge-based seed point was changed on average 2.5 (0–8)times per patient in order to generate reliable images. Tracking wasperformed at an FA value of 0.2 in all cases.

Following the herein proposed algorithm no modification of theexported functional seed areas was necessary. FA threshold valuesranged from 0.07 to 0.33 (median 0.19, SD 0.07). Of all 50 patientsmedian FAT of the affected hemisphere is 0.19 and that of the contralat-eral hemisphere is 0.34 (pb0.001). These data are shown in Fig. 7. In allcases refined fiber tracking at 75% and 50% FATwas primarily successfulmaking any post-processing corrections and changes obsolete. Time forfiber track generation ranged between 10 and 15 min with no signifi-cant difference for both methods.

Impact on surgical planning

In 92% of the cases, surgeons opted for the nTMS-based approachfor preoperative planning rather than basing their judgment on theconventional knowledge-based fiber tracking. The depiction of tracts

scranial magnetic stimulation (nTMS), definition of the fractional anisotropy thresholdce factors for fiber tracking, and, if applicable, the respective settings. The FAT was in-ed based on nTMS as described. The following settings were applied for all trackings: a

Fig. 2. We illustrate case no. 4, a 52 year-old female, who presented with hemiparesis of the right side. In MR scanning a lesion in the left central region was detected. As shown insubpanel A nTMS mapping of the motor cortex generated a map of functional areas. MEP answers are color-coded as follows: red pins: amplitude of related MEPs: 50 μV–500 μV,yellow pins: amplitude of related MEPs: 500 μV–1 mV, white pins: amplitude of related MEPs: >1 mV. Exported seed points depicted in yellow, ROI for knowledge-based approachas yellow box, tumor in red. Subpanels B and E show respective coronal and sagittal views of FAT generation, i.e. the maximum FA value at which fibers are displayed (FA=0.19).Subpanels C and F show tractography at 50% of FAT (FA=0.10), subpanel D/G with 75% of FAT (0.15). Subpanel H shows 3D head model with tractography results of knowledge-based approach (FA=0.20), subpanel I of nTMS-based approach at 75% FAT (FA=0.15). Subpanel H fiber tracks stop at the caudal edge of the tumor whereas subpanel I showsfibers originating from the motor cortex and running ventrolaterally in the edema zone adjacent to the tumor. Subpanels C and F show many aberrant fibers. Results of nTMS-based FAT-defined fiber tracking led to a modification of the surgical strategy in terms of approaching of the tumor and facilitated intraoperative subcortical stimulation. In thiscase the knowledge-based approach would not have led to a change or modification in planning of surgical strategy. Total tumor removal could be achieved and postoperative out-come was excellent with improvement of motor function. The lesion was diagnosed as a metastasis. Follow up at 3 months after surgery no neurological deficit was seen.

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in the immediate vicinity of the tumor combined with less aberrantfibers shown was regarded as superior.

With regard to surgical strategy, fiber tracking based on nTMS-baseddata and following the FAT approach lead to a change or modification ofsurgical strategy in 23/50 of the patients (46%) and added knowledgewithout conflicting with the a-priori surgical planning in another 8 pa-tients (16%). Modification or change of surgical strategy comprehendedthe following: site and size of craniotomy were modified in 7 patients,site of corticotomy in 5, expected path of pyramidal tract in 14 andplanned extent of resection in 5 (multiple answers possible).

Change or modification of surgical strategy on grounds of theknowledge-based approach occurred in 11 patients (22%).

Intraoperative guidance of the subcortical stimulation probe by theDTI information was regarded as beneficial in 56% of the cases. Thesurgeon invested an additional 5–10 min in presurgical planning forevaluation of fiber tracking results and answering the questionnaire.

Illustrative cases

In Figs. 2–4 we illustrate 3 cases, in which fiber tracking based onnTMS-based data and following the FAT approach lead to a change ormodification of surgical strategy. We have chosen representative cases

for each category (tumor location referring to cortical/subcortical,tumor histology, peritumoral infiltration/edema) defined by the meanFA threshold within the respective category (Fig. 5). After having beenpresented fiber tracking results rendered according to knowledge-based approach the respective surgeon would not have changed ormodified surgical strategy in these 3 cases (Fig. 6).

Discussion

Current limitations of fiber tracking

The localization of functional areas of the brain according to anatom-ical landmarks is subject to interindividual variations even in healthypersons. Space-occupying lesions such as brain tumors can, further-more, increase the anatomical variability of cortical structures by infil-trating the latter and/or causing significant brain shift (Pouratian andBookheimer, 2010). Brain tumors may also lead to cellular damage,edema, hypoxia or hyperemia eventually contributing to a disruptionof anatomico-functional structures. These effects can trigger a processof brain plasticity leading to a functional reorganization of the infiltrat-ed areas (Ius et al., 2011). Consequently, the reliability and the accu-racy of fiber tracking based on examiner-dependent definitions of

Fig. 3. We illustrate case no. 16, a 71 year-oldmale, who presentedwithmoderate hemiparesis of the right side caused by a brain lesion in the left central region. As shown in subpanel AnTMSmapping of themotor cortex generated amap of functional areas depictingM1medially to the tumor. MEP answers are color-coded as follows: light red pins: amplitude of relatedMEPs: 50 μV–500 μV, red pins: amplitude of relatedMEPs: 500 μV–1 mV, dark red pins: amplitude of relatedMEPs: >1 mV. Exported seed points depicted in yellow, ROI for knowledge-based approach as yellow box, tumor in red. Subpanels B and E show respective coronal and sagittal views of FAT generation, i.e. the maximum FA value at which fibers are displayed(FA=0.09). Subpanels C and F show tractography at 50% of FAT (FA=0.05), subpanel D/G with 75% of FAT (0.07). Subpanel H shows 3D head model with tractography results ofknowledge-based approach (FA=0.20), subpanel I of nTMS-based approach at 75% FAT (FA=0.07). In subpanel H fiber tracks run ventromedially to the tumor, adjacent to the baseof the tumor but reaching the cortex with a distance of 3–4 cm from the tumor's medial margin. Based on the new algorithm subpanel I shows fibers originating from M1 and runningventromedially to the tumor and along the course of the PT in direct contact to the tumor. Results of nTMS-based FAT-defined fiber tracking led to a change of the surgical strategy inthis case. The surgeon planned craniotomy and approach more from the lateral aspect of the tumor by shifting the craniotomy by approximately 5 cm. Intraoperative stimulation wasfacilitated in the subjective view of the surgeon. In this case the knowledge-based approach would not have led to a change or modification in planning of surgical strategy. Totaltumor removal could be achieved. Histological diagnosis was glioma (WHO grade 4). After surgery transient worsening of the hemiparesis occurred. Three months after surgery neuro-logical deficits were the same as before surgery with moderate hemiparesis of the right side.

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anatomical structures as well as statistical thresholds are a-priorisubjected to imprecision and – to put it in a provocative term – areoften performed to verify pre-existent evaluations and judgments.

Although the variation of fiber tracking is high and test–retestreliability consequently is low until now, no objective, examiner-independent approach has been described (Bürgel et al., 2009).

fMRI based seed region definition

Various research groups have been attempting tomaximize the ac-curacy of seed region definition by combining diffusion tensor imagingwith functionalMRI. Here seed points are selected according to corticalareas with increased blood flow due to voluntary muscle movements(Smits et al., 2007; Guye et al., 2003; Hendler et al., 2003; Watts etal., 2003). The feasibility of this approach in the clinical work-flowhas been demonstrated (Mori et al., 2002; Pamar et al., 2004;Staempfli et al., 2006). Yet, identification of essential functional areasbased onmeasurement of metabolic activitymight bear systematic er-rors. Indeed voluntary motor tasks do not exclusively activate primarymotor areas and brain tumors can have unpredictable effects onneurovascular coupling. As previously demonstrated, fMRI might be

prone to inaccuracy in the vicinity of space occupying lesions (Ruttenand Ramsey, 2010; Picht et al., 2012). Influence of volume effects, i.e.tumors, and background noise on fiber track reconstruction remainsa challenge as well (Tournier et al., 2002; Lazar et al., 2003; Lazarand Alexander, 2005). Several studies have focused on optimizing al-gorithms and techniques for tractography (Lazar et al., 2003;Staempfli et al., 2006, 2007; Weinstein et al., 1999; Westin et al.,2002; Huang et al., 2004). Taken together, functional description ofthe motor cortex by fMRI alone might fail to deliver desired accuracyand precision, sincemetabolic processes do not necessarily correspondconcisely to functional areas.

Seed region definition based on nTMS

nTMS is the only non-invasive method that establishes a causallink between the stimulation of an area and observed motor outputin a fashion similar to the gold standard of direct cortical and subcor-tical stimulation. nTMS-derived functional maps have been matchedwith results of direct cortical stimulation and showed high precisionand reliability (Picht et al., 2009; Forster et al., 2011). The feasibilityof combining TMS and DTI for exploration of the motor system has

Fig. 4.We illustrate case no. 41, a 63-year-old female, who presented with hemiparesis of the left side, affecting severely the leg, and moderately the arm. MR scanning revealed atumor in the left central region. As shown in subpanel A nTMS mapping of the motor cortex generated a map of functional areas depicting the hand representation laterally to thetumor and the leg representation on the dorsomedial aspect of the tumor. MEP answers are color-coded as follows: light red pins: amplitude of related MEPs: 50 μV–500 μV, redpins: amplitude of related MEPs: 500 μV–1 mV, dark red pins: amplitude of related MEPs: > 1 mV. Exported seed points depicted in yellow, ROI for knowledge-based approach asyellow box, tumor in red. Fiber tracking resulted in a FA threshold of 0.14 (100%). Subpanels B, C and D show fiber tracks generated according to nTMS-based FAT-defined resultsin axial, sagittal and coronal views respectively at 75% of FAT (FA=0.11). Subpanels E–G depicting axial, sagittal and coronal views of fiber tracking according to the knowledge-based approach (FA=0.20). In the perifocal edema zone no fibers can be displayed in this approach. The visualized fibers run ventral to the edema and dorsal to the edema with-out showing a supposed representation of hand and arm or leg and without vicinity to the tumor leaving out the perifocal edema. In contrast, subpanel B–D show fibers withdirect contact to the tumor running laterally originating from hand representation areas according to nTMS mapping and dorsomedially originating from areas for leg represen-tation. Besides a reduction of aberrant fibers a much more detailed track location in the vicinity of the tumor can be seen. In subpanels H and I the respective 3D head model forknowledge-based approach versus nTMS-based approach are shown. Surgical planning was rendered more precisely leading to a change of surgical strategy and intraoperativeorientation and stimulation was facilitated in this case on evaluation of fiber tracking according to nTMS-based data. When asked for surgical strategy on grounds of the conven-tional knowledge-based approach the surgeon deemed fiber tracking as not useful and no impact on surgery or intraoperative stimulation was made. Total tumor removal couldbe achieved. Histological diagnosis was metastasis. On the first postoperative day restitution of leg function was seen while arm paresis was unchanged. Fortunately, 3 monthsafter surgery motor function of arm and leg was fully intact leaving no neurological deficit.

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been recently proven (Koch et al., 2010; Kwon et al., 2011; Krieg et al.,2012). In preoperative planning those fibers that are closest to thetumor are of the highest interest; thus, fiber tracking should be initiat-ed in the immediate vicinity of the tumor in order to depict the tractsthat are at the highest risk during surgery. Therefore, NBS-based fibertracking allows, in comparison to the knowledge-based approach, tocustom-tailor the fiber tracking procedure to the surgical needs ofspecific cases.

Definition of seed points according to anatomical landmarks notonly is limited in distorted tissue, but also is based on the individualknowledge and evaluation of the examiner. The determination ofFAT is subject to the examiner's subjective assessment, as well. Toput it in a provocative term, until now fiber tracking was performedto verify pre-existent evaluations and judgments and could inherent-ly not deliver objective results. When it comes to comparing fibertrack volume or distance to tumor and the necessity of finding corre-lations between these results and clinical status or outcome an objec-tive and reliable approach is indispensable. By defining standardized

start points for fiber tracking by nTMS-derived functional data the in-fluence of this confounder is minimized. In addition, by refrainingfrom any individual post processing of the tracts, i.e. erasing orretaining, the evaluation of the results in context with the clinicalfindings becomes more valid, examiner-independent and compre-hensible and may add to a better understanding of the clinicalrelevance of DTI fiber tracking in the future.

FA threshold definition

Up to now, choice of the FA value for fiber visualization has beenhighly subjective due to interindividual variability, data set qualityand the subjective knowledge and preferences of the examiner. Accord-ingly we observed absolute FA threshold values ranging between 0.07and 0.35. To account for this we used relative FA values standardizedfor all patients. We performed fiber tracking with an individual FAT of75% and 50%. An FA value of 50% of the FAT led to a dramatic overrepre-sentation of displayed fibers, which can be seen by the amount of

Fig. 5. We again illustrate case no. 41. We performed fiber tracking with the proposed FA threshold algorithm, but set the seed point in the brainstem. Retrograde fiber tracking isillustrated in subpanels B–D in axial, coronal and sagittal views, respectively. FA thresholding resulted in aberrant fibers and clearly did not integrate supposed motor cortex areasadjacent to the tumor. This finding reflects the fact that tumor infiltration and edema impede fiber tracking and may demonstrate the importance of TMS-based seeding.

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aberrant fibers and thus leading to improbable fiber reconstruction.When following the nTMS-based approach in 84% of the cases DTI tractsgenerated at 75% of FAT were regarded as most beneficial for surgicalplanning. Controversy remains whether 75% is the optimal FA thresh-old, though. We could see in all patients examined by this algorithmfibers running from all seed points adjacent to the tumor and, at thesame time, displaying a minimal amount of supposedly aberrant fibers.For the sake of rendering an objective, examiner-independent and com-prehensive algorithmwe deemed an FAT of 75% therefore to be the bestchoice. Ultimately, this question can only be answered in conjunctionwith intraoperative electrophysiological findings, postoperative MRscanning and functional outcome assessment.

Intraoperative orientation and monitoring

Furthermore and of equal importance, tractography can facilitate di-rect cortical and subcortical stimulation in terms of intraoperative localstimulation of themotor cortex and the pyramidal tract. During surgeryin eloquent areas intraoperative cortical and subcortical stimulation isroutinely carried out with the principal aim of avoiding destruction offunctional structures (Berman et al., 2004; Chang et al., 2011). The sur-geon usually stimulates areas that, founded on his knowledge and expe-rience, reasonably should represent functional areas. For validation andpreservation of integrity of functional structures intraoperative electro-physiological monitoring remains the gold standard. PreoperativenTMS-based DTI tracking cannot replace intraoperative subcorticalstimulation. This procedure, of course, renders no clear-cut resultwhen it comes to resection margins. Nevertheless, we have shownthat our standardized approach influences the surgical strategy in 46%

of cases and led to a subjective reduction of surgical time by guidingthe intraoperative electrical mapping. In general, the surgeon feltmuch more confident in planning and intraoperative orientation byusing the additional fiber tracking information. Thus, reassurement ofanatomical structures based on high quality tractography facilitatedand sped up intraoperativemonitoring in the respective surgeon's view.

Clinical outcome

We observed a rate of new or increased motor deficit of 14% at 3-months follow-up. This rate is in accordance with the literature al-though we are aware of studies stating lower percentages of new defi-cits after surgery in eloquent regions of the brain (Chang et al., 2011;Duffau, 2011).We believe that our comparable high rate of new perma-nent deficits is due to the fact that in our series intraoperative mappingconfirmed immediate vicinity to or even infiltration of the primarymotor cortex and/or the pyramidal tract by the tumor in all cases andthat nevertheless we still achieved a high rate of gross total resections(92%) in this sample of patients with mixed histologies. This is alsoreflected in the impact the TMS derived functional data had on the sur-gical strategy with the majority of the surgeons stating that the addi-tional functional data helped them to plan a more radical resection.

Limitations and perspective

DTI tracking reconstructs anatomical entities the functional rele-vance of which remains unclear. Theoretically tractography initiatedfrom essential motor areas adjacent to the tumor identified by nTMSdepicts only functionally relevant pathways. Introducing another

Fig. 6. We illustrate an exemplary case showing major distortion of brain tissue in the central region making identification of M1 difficult. Subpanel A shows tumor location in red.M1 on the contralateral hemisphere can be identified. On the affected hemisphere the space-occupying lesion leads to distortion of anatomical landmarks. The suspected site of M1is colored in yellow. Dorsal to this region initial fiber tracking did not yield any positive results. The examiner shifted the seed region 4 times in this case to obtain fiber tracks. Sub-panels C and D show respective fiber tracking results in sagittal and axial views with an FA of 0.2. Resulting visualization shows many aberrant fibers.

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methodology into the fiber tracking algorithm increases the likelihoodof systematic errors; e.g. inaccuracies due to image fusion. Moreover,the proposed approach does not foresee the variation of important vari-ables other than the FA threshold thus possibly withholding better re-sults. Various statistical approaches to extracting tensor informationfrom the diffusionweighted image data set other than the deterministic

Fig. 7. We show FA threshold values for both hemispheres for all patients included inthis study. By implementing the described algorithm median FAT of the affected hemi-sphere is 0.19, and that of the contralateral hemisphere is 0.34 (pb0.001) with SD of0.07 and 0.08, respectively. The significant difference of FAT might reflect disruptionand/or impairment of fiber tracks running in vicinity of the tumor.

approach used in the current study have been proposed and mightprove to be superior in the future (Leclercq et al., 2011).

FA thresholding is a crucial step in DTI fiber tracking with significantimpact on theend result and as such intense research effort is focused onoptimization of thresholding. Analysis of connectivity maps and tensordistances, performing tractography from each seed-voxel and conse-quently thresholding at a percentage of the maximum number ofstreamlines, global fiber reconstruction and combination of quantitativeDTI in combinationwithMR spectroscopic imaging highlight a variety ofpromising approaches (Barbieri et al., 2012; Reisert et al., 2011). Theseprocedures are comparably time-consuminganddemandexpert knowl-edge often exceeding the resources in the clinical setting. Examination ofconsecutive patients on a routine base can be achieved in a straightfor-ward fashion as described in our study. This especially holds true for pa-tients with malignant tumors which demand fast examination andtreatment. Tominimize examination time only 1 b0 imagewas acquiredin this study which represents a potential source of noise.

In the future, the proposed approach may serve as an ideal basis forintraindividual comparison between hemispheres as well as longitudi-nal studies in order to better understand the impact of intracraniallesions on DTI tracking. An interhemispheric FA threshold ratio mightalso evolve as a surrogate marker for fiber tract integrity and risk forimminent neurological impairment. Differences in the resulting tracts'diameter or integrity between unaffected healthy hemisphere andtumor-affected hemisphere might correlate to tumor effects on thepyramidal tract. If lower fractional anisotropy values do correlatewith outcome and clinical symptoms as limb weakness, as formerly

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suggested (Lui et al., 2007), this could be validated with the proposedfunction-derived DTI algorithm as it is objective and standardized.

Conclusion

Fiber tracking based on nTMS allows for an examiner-independentvisualization of functionally relevant motor pathways. In this series itproved to be superior to conventional DTI fiber tracking. In 92% of thecases, surgeons opted for the nTMS-based approach for preoperativeplanning and stated an influence on the surgical strategy in nearly halfof the cases (46%). However, the accuracy of fiber tracking has to beproven by comparison to the gold-standard of intraoperative subcorticalelectrical stimulation.

Fiber tracking by the proposed standardized algorithm represents anobjective visualization method based on functional data and provides avaluable instrument for preoperative planning and intraoperative ori-entation and monitoring.

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