Associations between clinical outcome and navigated transcranial magnetic stimulation characteristics in patients with motor-eloquent brain lesions: a combined navigated transcranial magnetic stimulation–diffusion tensor imaging fiber tracking approach

View More View Less
  • 1 Department of Neurosurgery,
  • | 2 TUM-Neuroimaging Center, and
  • | 3 Section of Neuroradiology, Department of Radiology, Klinikum rechts der Isar, Technische Universität München, Germany
Full access

OBJECTIVE

Navigated transcranial magnetic stimulation (nTMS) and diffusion tensor imaging fiber tracking (DTI FT) based on nTMS data are increasingly used for preoperative planning and resection guidance in patients suffering from motor-eloquent brain tumors. The present study explores whether nTMS-based DTI FT can also be used for individual preoperative risk assessment regarding surgery-related motor impairment.

METHODS

Data derived from preoperative nTMS motor mapping and subsequent nTMS-based tractography in 86 patients were analyzed. All patients suffered from high-grade glioma (HGG), low-grade glioma (LGG), or intracranial metastasis (MET). In this context, nTMS-based DTI FT of the corticospinal tract (CST) was performed at a range of fractional anisotropy (FA) levels based on an individualized FA threshold ([FAT]; tracking with 50%, 75%, and 100% FAT), which was defined as the highest FA value allowing for visualization of fibers (100% FAT). Minimum lesion-to-CST distances were measured, and fiber numbers of the reconstructed CST were assessed. These data were then correlated with the preoperative, postoperative, and follow-up status of motor function and the resting motor threshold (rMT).

RESULTS

At certain FA levels, a statistically significant difference in lesion-to-CST distances was observed between patients with HGG who had no impairment and those who developed surgery-related transient or permanent motor deficits (75% FAT: p = 0.0149; 100% FAT: p = 0.0233). In this context, no patient with a lesion-to-CST distance ≥ 12 mm suffered from any new surgery-related permanent paresis (50% FAT and 75% FAT). Furthermore, comparatively strong negative correlations were observed between the rMT and lesion-to-CST distances of patients with surgery-related transient paresis (Spearman correlation coefficient [rs]; 50% FAT: rs = –0.8660; 75% FAT: rs = –0.8660) or surgery-related permanent paresis (50% FAT: rs = –0.7656; 75% FAT: rs = –0.6763).

CONCLUSIONS

This is one of the first studies to show a direct correlation between imaging, clinical status, and neurophysiological markers for the integrity of the motor system in patients with brain tumors. The findings suggest that nTMS-based DTI FT might be suitable for individual risk assessment in patients with HGG, in addition to being a surgery-planning tool. Importantly, necessary data for risk assessment were obtained without significant additional efforts, making this approach potentially valuable for direct clinical use.

ABBREVIATIONS

BMRC = British Medical Research Council; CST = corticospinal tract; DTI, DTI FT = diffusion tensor imaging, DTI fiber tracking; FA, FAT = fractional anisotropy, FA threshold; fMRI = functional MRI; HGG = high-grade glioma; IOM = intraoperative monitoring; LAD = lesion-to-activation distance; LGG = low-grade glioma; MEP = motor evoked potential; MET = metastasis; nTMS = navigated transcranial magnetic stimulation; rMT = resting motor threshold; ROI = region of interest; rs = Spearman correlation coefficient.

OBJECTIVE

Navigated transcranial magnetic stimulation (nTMS) and diffusion tensor imaging fiber tracking (DTI FT) based on nTMS data are increasingly used for preoperative planning and resection guidance in patients suffering from motor-eloquent brain tumors. The present study explores whether nTMS-based DTI FT can also be used for individual preoperative risk assessment regarding surgery-related motor impairment.

METHODS

Data derived from preoperative nTMS motor mapping and subsequent nTMS-based tractography in 86 patients were analyzed. All patients suffered from high-grade glioma (HGG), low-grade glioma (LGG), or intracranial metastasis (MET). In this context, nTMS-based DTI FT of the corticospinal tract (CST) was performed at a range of fractional anisotropy (FA) levels based on an individualized FA threshold ([FAT]; tracking with 50%, 75%, and 100% FAT), which was defined as the highest FA value allowing for visualization of fibers (100% FAT). Minimum lesion-to-CST distances were measured, and fiber numbers of the reconstructed CST were assessed. These data were then correlated with the preoperative, postoperative, and follow-up status of motor function and the resting motor threshold (rMT).

RESULTS

At certain FA levels, a statistically significant difference in lesion-to-CST distances was observed between patients with HGG who had no impairment and those who developed surgery-related transient or permanent motor deficits (75% FAT: p = 0.0149; 100% FAT: p = 0.0233). In this context, no patient with a lesion-to-CST distance ≥ 12 mm suffered from any new surgery-related permanent paresis (50% FAT and 75% FAT). Furthermore, comparatively strong negative correlations were observed between the rMT and lesion-to-CST distances of patients with surgery-related transient paresis (Spearman correlation coefficient [rs]; 50% FAT: rs = –0.8660; 75% FAT: rs = –0.8660) or surgery-related permanent paresis (50% FAT: rs = –0.7656; 75% FAT: rs = –0.6763).

CONCLUSIONS

This is one of the first studies to show a direct correlation between imaging, clinical status, and neurophysiological markers for the integrity of the motor system in patients with brain tumors. The findings suggest that nTMS-based DTI FT might be suitable for individual risk assessment in patients with HGG, in addition to being a surgery-planning tool. Importantly, necessary data for risk assessment were obtained without significant additional efforts, making this approach potentially valuable for direct clinical use.

For an optimal balance between maximum tumor resection, increased survival, and high postoperative quality of life, several pre- and intraoperative methods for surgical planning and intraoperative mapping and monitoring have been developed in recent years.2,6,12,28,30,40 In this context, anatomical MRI, functional MRI (fMRI), and navigated transcranial magnetic stimulation (nTMS), as well as intraoperative monitoring (IOM) and stimulation mapping are the most broadly used techniques.

Besides their use for preoperative planning and intraoperative resection guidance, these methods are capable of characterizing the integrity of the motor system. Regarding the cortical level, several studies have demonstrated that the rate of motor deficits is likely to increase when the distance between the tumor and the motor cortex decreases—an observation which was largely based on lesion-to-activation distance (LAD) measurements in fMRI data sets in most of these studies.3,16,25,47 Concerning the subcortical level, a comparable trend has been observed in tractography evaluations of the corticospinal tract (CST), although a very wide range of lesion-to-CST distances has been observed in a limited number of studies.3,33,45 Furthermore, intraoperative subcortical stimulation has been applied repeatedly to determine a minimum lesion-to-CST distance, and it has been shown that stimulation intensity correlates with the risk of CST injury.36,41 Additionally, tractography acquired preoperatively has been compared with intraoperative subcortical stimulation results, showing a good overall correlation of up to 95% for the CST.4

Recently, nTMS has been shown to significantly improve tractography results of the CST by providing investigator-independent, functionally confirmed, and more accurate subcortical maps in the context of diffusion tensor imaging fiber tracking (DTI FT).10,15,19,37 Importantly, subcortical stimulation confirmed the CST location and the somatotopic reconstruction based on nTMS data in a recent study.10 Furthermore, the combined approach consisting of nTMS and DTI FT might allow for valuable individualized risk stratification in patients with motor-eloquent brain lesions, which has been captured by only 1 recent study so far.37 Interestingly, in this study no new postoperative motor deficits occurred when the lesion-to-CST distance was > 8 mm. Against this backdrop, the present study aims to validate this finding by enrolling a large number of patients within a different neurosurgical center. Moreover, it evaluates further nTMS and nTMS-based tractography parameters which, correlated to the clinical outcome, might provide additional insights into further possibilities of risk stratification. Up to now, only one tracking adjustment has been evaluated in terms of risk stratification, leaving space for potential improvements because DTI FT results are highly dependent on preselected parameters. Thus, this study could strengthen the novel technique of nTMS-based DTI FT, and furthermore, it should contribute data regarding tractography-based risk stratification to the currently limited amount of evidence.

Methods

Ethics Approval

The experimental protocol was approved by the local ethics commission and was followed in accordance with the Declaration of Helsinki. Written informed consent was obtained from all patients prior to the procedures.

Patients and Procedures

Enrollment of patients started in 2013 and ended in early 2016 at our neurosurgical department. The following inclusion criteria were applied: 1) age > 18 years; 2) motor-eloquent tumor location according to initial MRI (infiltration or compression of the anatomically suspected motor cortex and/or proximity of the tumor to the CST); 3) indication for preoperative nTMS and nTMS-based DTI FT due to tumor location; 4) surgery for tumor resection required according to evaluation of an interdisciplinary tumor board; 5) postoperative diagnosis of supratentorial high-grade glioma (HGG), low-grade glioma (LGG), or metastasis (MET) according to histopathological examination; and 6) follow-up interval of at least 2 months.

Patients who were not eligible for MRI or nTMS due to metallic implants (e.g., cochlear implant, cardiac pacemaker, deep brain stimulation electrodes) or who did not undergo surgery at our department were excluded from the study.

After initial clinical examination, patients underwent cranial MRI and preoperative motor mapping by nTMS (Fig. 1). Data derived from mappings were used for nTMS-based DTI FT, and both cortical motor maps and tractography were available for surgical planning and during tumor resection.

FIG. 1.
FIG. 1.

Setup overview. This figure depicts the procedures performed during pre- and postoperative assessments and surgery, including nTMS for motor mapping and nTMS-based tractography of the CST. In addition, it shows the study's main approaches regarding data analyses.

Clinical Examination

The preoperative clinical examination of each patient consisted of assessment of sensory function, coordination, muscle strength, and cranial nerve function according to a standardized protocol. In this context, muscle strength was evaluated according to the British Medical Research Council (BMRC) scale. After tumor resection, the clinical examinations were repeated daily from the 1st postoperative day until discharge, again at 6–8 weeks postoperatively, and during follow-ups every 3–12 months depending on the tumor types. In this context, no paresis was present when motor strength was 5/5 for all extremities according to the BMRC scale, whereas a deficit was registered when motor strength was < 5/5. Regarding new or aggravated motor deficits that occurred after surgery, 2 categories were established in accordance with those used in previous reports.20,24 One category was transient paresis: any new or increased motor deficit due to surgery that resolved within the regular 8-week follow-up interval. The other was permanent paresis: any new or increased motor deficit due to surgery that did not resolve to the preoperative status within the regular 8-week follow-up interval.

Magnetic Resonance Imaging

Cranial imaging was performed with a 3-T MR scanner in which an 8-channel phased-array head coil was used (Achieva 3T, Philips Medical Systems). Our standard preoperative scanning protocol included 3D T1-weighted gradient echo sequences (TR/TE 9/4 msec, 1 mm3 isovoxel covering the whole head, acquisition time 6 minutes 58 seconds) with and without contrast enhancement (gado-pentetate dimeglumine; Magnograf, Marotrast GmbH); FLAIR images (TR/TE 12,000/140 msec, voxel size 0.9 × 0.9 × 4 mm3, acquisition time 3 minutes); and DTI sequences with 15 orthogonal diffusion directions (TR/TE 10,737/55 msec, spatial resolution of 2 × 2 × 2 mm3, b values of 0 and 800, acquisition time 6 minutes 26 seconds). On the 1st postoperative day, all patients underwent another MRI scan to check for surgery-related complications and to assess the extent of resection. In this context, the same gradient echo and FLAIR sequences were obtained, and further diffusion-weighted sequences were performed to check for ischemic events. As a standard of care, cranial MRI was repeated during routine follow-up every 3–12 months. All MRI sequences were assessed by at least 2 board-certified neuroradiologists.

Navigated Transcranial Magnetic Stimulation

For preoperative motor mappings by nTMS, the contrast-enhanced gradient echo sequences were uploaded to a Nexstim eXimia NBS system (version 4.3, Nexstim Plc.). For neuronavigation during motor mapping, coregistration of the patient's head and the corresponding MRI sequence was performed based on anatomical landmarks, using an infrared device (Polaris Spectra, Polaris) in combination with a headband with reflective sphere markers.39 Pregelled surface electrodes (Neuroline 720, Ambu) were attached to the abductor pollicis brevis, abductor digiti minimi, flexor carpi radialis, and biceps brachii muscles to record motor evoked potentials (MEPs) from the upper extremity by continuous electromyography, whereas the tibialis anterior and gastrocnemius muscles were used for the recording of MEPs of the lower extremity.

Both hemispheres were mapped by nTMS, starting with the determination of each hemisphere's resting motor threshold (rMT).38 During mapping of cortical representations of the upper extremity, an intensity of 110% of the individual rMT was used, whereas at least 130% of the rMT was applied during stimulation of representations belonging to the lower-extremity muscles. The same protocol has repeatedly been applied in neurosurgical motor mapping.8,20,24,37,44

Post hoc analysis was performed to distinguish between motor-positive and motor-negative points. In this context, a stimulation spot was defined as motor positive when an MEP with an amplitude ≥ 50 μV was elicited with an MEP onset latency within the typical ranges for the upper and lower extremities. Correspondingly, a stimulation spot was regarded as motor negative when these criteria were not fulfilled. Again, in previous studies, this procedure has been applied in similar form.8,20,24,37,44

Fiber Tracking

The stack of preoperative MRI sequences and the motor-positive nTMS spots were uploaded to a BrainLAB iPlan Net server (version 3.0.1, BrainLab AG), and all data sets were fused. Eddy current correction was applied throughout for DTI sequences, and deterministic tractography was performed with an algorithm that uses the principle of fiber assignment by continuous tracking. For seeding of the region of interest (ROI) within the supposed motor cortex, motor-positive nTMS spots were used, which replaces manual ROI drawing, as outlined in previous reports.10,15,19,37 During generation of the nTMS-based ROI, a rim of 2 mm was added to each individual motor-positive spot.19 Then, a second ROI was manually placed in the ipsilateral brainstem at the level of the tentorium by using the manual drawing tool. Then, tracking of fibers passing through both ROIs was performed with a minimum fiber length of 110 mm and a fractional anisotropy (FA) value that was individually adjusted according to a previous protocol: the FA value was increased step by step until no more fibers were displayed, and then the FA was decreased by 0.01, thus visualizing only a minimal number of fibers.15 The FA value leading to this tracking result was defined as 100% FA threshold (FAT). Tractography of the CST was then conducted at 50%, 75%, and 100% FAT. The output of tracking consisted of a color-coded visualization of fibers attributable to the CST (Fig. 2 left). Clearly aberrant fibers presumably not belonging to the CST were excluded from further analysis. All tractography was achieved based on preoperative imaging and stimulation without reproduction during the course of follow-up.

FIG. 2.
FIG. 2.

Tractography and measurement of the minimum lesion-to-CST distance. This figure visualizes DTI FT based on nTMS data for reconstruction of the CST (left). The motor-positive nTMS spots are depicted as green points, and the tumor volume is shown in orange. Furthermore, an axial MRI slice is shown, providing an example of how minimum lesion-to-CST distances were measured (right). Figure is available in color online only.

Surgery Protocol

All patients underwent tumor resection in which we used an asleep approach at our department, and the data set consisting of anatomical MRI sequences, motor-positive nTMS spots, and nTMS-based DTI FT was used for surgical planning and during tumor resection throughout. Thus, the data set was available on the intraoperative navigational screen (BrainLAB Curve, BrainLab AG).

Intraoperative monitoring and cortical and subcortical mapping were applied in all cases. Therefore, intravenous anesthesia with remifentanyl and propofol, without additional neuromuscular blockade, was used. After dura mater opening, the motor threshold for intraoperative stimulation was determined, and mapping of the rolandic region was conducted by a monopolar stimulation electrode (Inomed Medizintechnik). In this context, square-waved pulses (duration 0.2–0.4 msec, frequency 500 Hz) were applied in a train-of-five fashion, and stimulation intensity started with 6 mA and was increased continuously in steps of 1 mA until we were able to record potentials, similar to previous reports.9,42,43 Following cortical mapping, a strip electrode (Inomed Medizintechnik) was positioned over the precentral gyrus, and subcortical stimulation was continued during further tumor resection. An MEP amplitude reduction of 50% was considered as a stop criterion during tumor resection.18,21,23

Data Analysis

For patient details and nTMS mapping characteristics, descriptive statistics, including means ± SD, minimum and maximum values, and medians were calculated. Moreover, statistical comparison between patients with HGG, LGG, and MET in terms of patient- and mapping-related characteristics was achieved by Kruskal-Wallis tests or chi-square tests.

In tractography sequences, lesion-to-CST distances were measured in axial MRI slices (BrainLAB iPlan Net server, version 3.0.1, and BrainLAB Elements, BrainLab AG). In this context, the borders of the tumor were visually identified, and the point closest to the CST, as visualized by nTMS-based DTI FT, was marked (Fig. 2 right). Measurement was then performed from the tumor border to the closest CST fibers, and the distance was saved and defined as the minimum lesion-to-CST distance. We documented whether tumor-related edema overlapped with the CST fiber course according to visual inspection, but careful attention was paid to assure that measurements always related to the distance between the tumor borders and the CST and not between the borders of tumor-related edema and the CST. In addition, the total amount of visualized fibers was noted as a quantitative measure for tract integrity, and descriptive statistics were also calculated for both lesion-to-CST distances and fiber numbers. Based on ranges for lesion-to-CST distances, cutoff values for surgery-related permanent paresis were identified. In this context, the cutoff value is the maximum lesion-to-CST distance that was observed among patients with surgery-related permanent paresis. Thus, patients who showed distances larger than the cutoff value did not suffer from any new surgery-related permanent paresis.

Furthermore, lesion-to-CST distances and fiber numbers were compared between patients grouped by motor function levels at different time points. In this context, all enrolled subjects were grouped according to their preoperative (no deficit/deficit), postoperative (no deficit/deficit), follow-up (no deficit/deficit), and surgery-related motor status (no deficit/transient deficit/permanent deficit). Statistical assessment was conducted with the help of Mann-Whitney tests for preoperative, postoperative, and followup motor functions (irrespective of the initial motor status) and through Kruskal-Wallis tests for the surgery-related motor status. Potential correlations between the individual rMTs of the lesion-affected hemisphere and lesion-to-CST distances or fiber numbers were assessed using the Spearman correlation coefficient (rs) for each patient group according to motor status. Furthermore, the presence of edema overlapping with CST reconstructions, which can be an important influencing factor concerning reliable DTI FT, was compared between patient groups with different deficit grades. GraphPad Prism software (GraphPad Prism 6) was used for all statistical testing, and a p value < 0.05 was considered statistically significant. Figure 1 provides an overview of procedures and analyses performed in the course of this study.

Results

Patient Details

Overall, 86 patients suffering from HGG, LGG, or intracranial MET were enrolled. Four patients suffered from isolated bihemispheric lesions. Table 1 provides information on further patient details and patient-related pre- and postoperative characteristics.

TABLE 1.

Characteristics of 86 patients with brain tumors in whom nTMS mapping was used

CharacteristicHGG PatientsLGG PatientsMET Patientsp Value
No. of patients492017
Age in yrs, mean ± SD55.9 ± 14.139.9 ± 11.058.5 ± 14.1<0.0001
Sex (%, M/F)61.2/38.855.0/45.047.1/52.90.5843
Tumor hemisphere (%, lt/rt)52.0/48.050.0/50.045.0/55.00.8694
Paresis (%)
  Preop32.710.047.10.5512
  Postop46.915.035.3
  Follow-up34.725.029.4
Surgery-related paresis (%)
  None71.485.088.20.4177
  Transient6.20.05.9
  Permanent22.415.05.9
Follow-up in mos, mean ± SD6.4 ± 4.37.6 ± 4.76.2 ± 4.50.3054
Size of nTMS area in cm3, mean ± SD3.8 ± 2.24.5 ± 2.23.4 ± 1.60.2407
rMT in %, mean ± SD
  Affected hemisphere34.0 ± 10.035.8 ± 8.636.9 ± 12.90.5753
  Unaffected hemisphere30.8 ± 6.932.9 ± 7.731.0 ± 6.30.5329

Overview of patient numbers and patient-related characteristics including age, sex, tumor hemisphere, paresis, and maximum follow-up. Also, the sizes of the cortical motor areas according to mapping by nTMS and the rMTs are depicted. All data are displayed separately for patients diagnosed with supratentorial HGG, LGG, or MET.

Because motor deficit rates in patients with LGG and MET were very low (Table 1), statistical testing for the association of motor function with nTMS or tractography parameters was not achieved in these cohorts. Accordingly, lesion-to-CST distance measurements in patients with LGG and MET are not reported.

Mapping by nTMS

Motor mapping by nTMS was successfully conducted in all enrolled patients without any adverse events. Accordingly, clear motor-positive stimulation spots were identified during post hoc analysis and exported for later nTMS-based DTI FT in all cases. In this context, Table 1 depicts the volume of the cortical area of motor-positive nTMS spots and average rMT values.

Tractography Analysis

For patients with HGG, the association with paresis was assessed based on the obtained results for lesion-to-CST distances and fiber numbers. In this context, results for lesion-to-CST distances are shown in Table 2. At certain FA levels, a statistically significant difference in lesion-to-CST distances was observed between patients with HGG who had no impairment and those who developed surgery-related transient or permanent motor deficits (75% FAT: p = 0.0149; 100% FAT: p = 0.0233). Concerning cutoff values, no patient with a lesion-to-CST distance ≥ 12 mm suffered from any new surgery-related permanent paresis (50% FAT and 75% FAT).

TABLE 2.

Lesion-to-CST distances versus motor impairment in patients with HGG

Motor StatusLesion-to-CST Distance (mm)
50% FAT75% FAT100% FAT
Mean ± SD (range)p ValueMean ± SD (range)p ValueMean ± SD (range)p Value
Preop paresis
  Yes6.5 ± 8.0 (0.0–25.9)0.43319.1 ± 8.0 (0.0–26.2)0.286816.6 ± 10.1 (0.0–35.5)0.7851
  No10.1 ± 11.3 (0.0–38.3)11.3 ± 10.7 (0.0–38.5)16.5 ± 13.3 (0.0–39.1)
Postop paresis
  Yes6.7 ± 7.8 (0.0–25.9)0.34078.8 ± 8.4 (0.0–26.9)0.967614.9 ± 10.6 (0.0–35.3)0.7412
  No10.9 ± 12.0 (0.0–38.3)12.1 ± 10.9 (0.0–38.5)17.8 ± 13.5 (0.0–39.1)
Follow-up paresis
  Yes3.5 ± 4.5 (0.0–11.4)0.01375.3 ± 5.5 (0.0–14.1)0.006110.9 ± 8.2 (0.0–25.7)0.1205
  No11.8 ± 11.5 (0.0–38.3)13.4 ± 10.5 (0.0–38.5)19.3 ± 13.0 (0.0–39.1)
Surgery-related paresis
  No deficit10.5 ± 11.3 (0.0–38.3)0.077712.1 ± 10.1 (0.0–38.5)0.014919.8 ± 12.1 (0.0–39.1)0.0233
  Transient13.1 ± 8.8 (5.5–22.7)16.2 ± 9.3 (9.9–26.9)20.6 ± 10.4 (13.2–27.9)
  Permanent2.7 ± 3.9 (0.0–11.4)3.5 ± 4.7 (0.0–11.8)6.1 ± 6.4 (0.0–17.9)

Results regarding lesion-to-CST distances, which were compared between groups of patients with HGG, determined by the patients' motor status at different time points. The results are based on tractography with motor-positive nTMS spots as the seed region, which was acquired preoperatively. In this context, all enrolled subjects were grouped according to their preoperative (no deficit/deficit), postoperative (no deficit/deficit), follow-up (no deficit/deficit), and surgery-related motor status (no deficit/transient deficit/permanent deficit). The values are expressed as the mean lesion-to-CST distances ± SD and ranges.

Moreover, lesion-to-CST distances were compared between patients with and without tumor-associated edema, based on the severity of their respective deficits. In this context, no statistically significant differences were revealed between patients with and without edema, except for DTI FT with 50% FAT among patients without surgery-related deficits (p = 0.0007, Table 3).

TABLE 3.

Lesion-to-CST distances versus tumor-related edema in patients with HGG

Motor Status & EdemaLesion-to-CST Distance (mm)
50% FAT75% FAT100% FAT
Mean ± SD (range)p ValueMean ± SD (range)p ValueMean ± SD (range)p Value
No deficit
  Edema5.0 ± 7.9 (0.0–25.9)0.00078.4 ± 8.8 (0.0–26.2)0.052716.7 ± 13.5 (0.0–35.3)0.4085
  No edema16.7 ± 11.5 (0.0–38.3)15.1 ± 10.3 (1.3–38.5)20.9 ± 11.8 (5.4–39.1)
Transient deficit
  Edema
  No edema8.4 ± 4.0 (5.5–11.2)10.9 ± 1.3 (9.9–11.8)
Permanent deficit
  Edema2.6 ± 3.9 (0.0–11.4)0.93943.9 ± 5.1 (0.0–11.8)0.88897.1 ± 7.0 (0.0–17.9)0.8571
  No edema3.1 ± 4.5 (0.0–8.2)3.9 ± 2.9 (0.0–4.1)3.4 ± 4.8 (0.0–6.8)

Summary of the findings concerning lesion-to-CST distances, which were compared among patients with HGG regarding the presence of tumor-related edema (no edema/edema). The values are expressed as the mean lesion-to-CST distances ± SD and ranges.

Furthermore, fiber numbers were compared between patients at different examination time points, depending on their levels of motor function (Table 4). In this context, no statistically significant differences were observed except for the preoperative status (100% FAT: p = 0.0197).

TABLE 4.

Fiber numbers versus motor impairment in patients with HGG

Motor StatusFiber Nos.
50% FAT75% FAT100% FAT
Mean ± SD (range)p ValueMean ± SD (range)p ValueMean ± SD (range)p Value
Preop paresis
  Yes297.9 ± 528.4 (1–2026)0.628368.3 ± 139.2 (1–561)0.20051.1 ± 0.3 (1–2)0.0197
  No309.1 ± 425.6 (1–2062)94.4 ± 117.6 (1–600)2.8 ± 3.0 (1–13)
Postop paresis
  Yes280.3 ± 463.2 (1–2026)0.657072.7 ± 124.7 (1–561)0.32371.3 ± 0.6 (1–3)0.1326
  No327.0 ± 456.6 (1–2062)97.0 ± 126.4 (1–600)3.0 ± 3.3 (1–13)
Follow-up paresis
  Yes269.1 ± 501.6 (1–2026)0.428173.0 ± 138.7 (1–561)0.38741.4 ± 0.7 (1–3)0.2816
  No324.3 ± 436.9 (1–2062)91.8 ± 118.4 (1–600)2.7 ± 3.1 (1–13)
Surgery-related paresis
  No deficit352.3 ± 508.3 (1–2062)0.416199.5 ± 140.4 (1–600)0.36522.0 ± 2.0 (1–9)0.7561
  Transient249.3 ± 276.2 (5–549)61.3 ± 98.4 (4–175)1.5 ± 0.7 (1–2)
  Permanent167.8 ± 259.4 (1–902)46.0 ± 58.7 (1–196)3.0 ± 4.1 (1–13)

Summary of the findings concerning fiber numbers, which were compared between groups of patients with HGG, determined by the patients' motor status at different time points. The results are based on tractography with motor-positive nTMS spots as the seed region, which was acquired preoperatively. In this context, all enrolled subjects were grouped according to their preoperative (no deficit/deficit), postoperative (no deficit/deficit), follow-up (no deficit/deficit), and surgery-related motor status (no deficit/transient deficit/permanent deficit). The values are expressed as the mean fiber numbers ± SD and ranges.

Association With Motor Thresholds

The individual rMTs of the lesion-affected hemispheres were correlated with lesion-to-CST distances and fiber numbers. In this context, comparatively strong negative correlations were observed between the rMTs of patients with surgery-related transient motor deficits and corresponding lesion-to-CST distances (50% FAT: rs = –0.8660; 75% FAT: rs = –0.8660), as well as between the rMTs of patients suffering from surgery-related permanent paresis and their lesion-to-CST distances, respectively (50% FAT: rs = –0.7656; 75% FAT: rs = –0.6763) (Table 5). Hence, the higher the preoperatively determined rMT was, the lower the lesion-to-CST distance, and vice versa.

TABLE 5.

Correlation of lesion-to-CST distances and rMTs depending on motor function in patients with HGG

Motor Statusrs for Correlation of Lesion-to-CST Distances & rMT
50% FAT75% FAT100% FAT
Surgery-related paresis
  No deficit0.09790.06570.0264
  Transient−0.8660−0.8660
  Permanent−0.7656−0.6763−0.3235

Spearman correlation coefficients for the correlation of individual rMTs of the lesion-affected hemisphere and lesion-to-CST distances in each motor status group in patients with HGG.

Moreover, regarding correlations between rMTs and fiber numbers depending on motor status, considerable correlations were again revealed for surgery-related transient paresis (75% FAT: rs = 0.8660) and surgery-related permanent paresis (75% FAT: rs = −0.5482) (Table 6).

TABLE 6.

Correlation of fiber numbers and rMTs depending on motor function in patients with HGG

Motor Statusrs for Correlation of Fiber Nos. & rMT
50% FAT75% FAT100% FAT
Surgery-related paresis
  No deficit−0.1312−0.0543−0.4496
  Transient0.00000.8660
  Permanent−0.4518−0.5482−0.2090

Spearman correlation coefficients for the correlation of individual rMTs of the lesion-affected hemisphere and fiber numbers in each motor status group in patients with HGG.

Discussion

In the present study, patients with different types of brain lesions underwent preoperative imaging and motor mapping by nTMS, followed by nTMS-based DTI FT. Measurements acquired during preoperative tractography (lesion-to-CST distance, fiber count) were used to explore associations with deficit grades at different time points, to define cutoff values, and to correlate with rMTs (Fig. 1). The main purpose of our approach was to investigate the role of nTMS-based DTI FT of the CST in risk stratification.

Association Between nTMS and Clinical Outcome

Regarding overall outcome in terms of motor function, comparatively low surgery-related deficit rates have been observed despite motor-eloquent tumor location for all of the entities included, but particularly for LGG and MET. In a previous study among patients with HGG, the rate of new surgery-related permanent deficits was 12.9% in subjects who underwent preoperative nTMS, whereas a historic control group showed a rate of 25.7%.24 A decreased risk of motor deficits, presumably due to presurgical nTMS, has been reported in other studies also enrolling patients with LGG and MET in addition to those with HGG.14,20 The comparatively low deficit rates in patients of our study correspond to the findings reported in these articles, and might be attributable to thorough preoperative planning completed using nTMS, allowing more targeted IOM and stimulation mapping. However, low rates of surgery-related transient or permanent paresis restricted statistical data analysis for patients with LGG and MET (Table 1).

The ROI seeding for tractography is commonly achieved manually based on anatomical data. However, this approach is typically severely hampered by comparatively high interobserver variability and the difficult identification of anatomical landmarks for seeding in patients with large brain lesions.29,33,46 In this context, ROI seeding can also be performed based on fMRI motor mapping results, but this approach has frequently been shown to lack reliability in subjects with brain tumors. This effect is due to affected neovasculature and the presumable uncoupling of the neurovascular response, effects to which patients with HGG are particularly susceptible.1,13,17 In this context, it has recently been demonstrated that nTMS-based DTI FT, as applied in this study, can overcome the limitations of manual ROI seeding by relying on neurophysiological functional parameters that should not be severely distorted by changed oxygenation levels.10,15,19,37 Additionally, nTMS-based DTI FT for detection and somatotopic visualization of the CST has already shown a good overall correlation with intraoperative stimulation results.10

However, both cortical nTMS motor mapping and nTMS-based DTI FT have, so far, primarily been used for surgical planning and guidance in neurosurgery.15,19,22,34,44 Thus, up to now, only 1 single-center study has focused on nTMS-based DTI FT of the CST for risk stratification.37 The motivation for risk assessment with respect to functional long-term deficits emerges from 2 perspectives: first, patients with brain tumors could be counseled regarding their individual perioperative risk of deterioration, and second, the surgeon in charge could be directly supported in the decision-making process regarding treatment choices or even regarding possible referrals to specialized IOM centers.

Against this backdrop, previous trials among patients with brain tumors have assessed LADs in fMRI setups, and it has been shown that the effect on motor function depends on LADs, with a distance of ≥ 10 mm leading to a clearly decreased risk of postoperative loss of function.3,16,25,47 For nTMS-based DTI FT, it has been shown that no new postoperative motor deficits occurred when the lesion-to-CST distance was > 8 mm for tracking with 75% FAT.37 In our study, no patient with a lesion-to-CST distance ≥ 12 mm suffered from any new surgery-related permanent paresis (50% FAT and 75% FAT). Thus, our approach extends the previous findings by adding further tracking paradigms. Because DTI FT results are highly dependent on preselected tracking adjustments like the FA value used for fiber reconstruction, it is important to add further FATs to explore whether other adjustments might lead to more favorable results. Although nTMS-based DTI FT is increasingly used for delineation of the CST in different neurosurgical centers, the selection of optimal tracking parameters is still a topic of debate, as reflected by various approaches over recent years.15,19,22,34,44 Accordingly, exploration of different settings in terms of nTMS-based risk stratification seems to be mandatory for evaluation of the most beneficial use.

However, the measured cutoff value for tracking with 75% FAT was slightly higher than the one reported previously.37 This could be due to differences in ROI seeding and CST visualization: whereas we used a rim of 2 mm and measured the distance to the closest CST fibers, the authors of the previous report added a 3-mm rim and assessed the lesion-to-CST distance to a covering tube surrounding the reconstructed fiber bundle, which is likely to reduce the distance measured. Thus, it appears logical that slightly lower lesion-to-CST distances were achieved, and taking the difference in approaches into account, our study seems to confirm these earlier data while expanding the previous findings by exploring a wider range of FA-level configurations. Furthermore, the results for tracking with 50% and 75% FAT are in comparatively good accordance with the fMRI-based LADs used to predict and prevent motor deficits in the aforementioned reports.16,25

In terms of lesion-to-CST distances, we also assessed differences between patients with different levels of motor function at different time points, and statistically significant results were observed for surgery-related paresis (Table 2). This finding principally suggests that lesion-to-CST distances measured in preoperative nTMS-based tractography might be more suitable for long-term risk assessment as opposed to the prediction of short-term effects occurring immediately after surgery. In light of the findings regarding lesion-to-CST distance cutoff values and lesion-to-CST distance differences between patient groups, it seems evident that the initial role of nTMS-based tractography as a tool for surgical planning and resection guidance might be expanded to aspects of clinical risk assessment. However, regarding the comparison of fiber numbers, we did not observe statistically significant differences between patients with or without transient or permanent surgery-related paresis (Table 4).

Furthermore, the rMT has been described as a key parameter for nTMS motor mapping in general, and perioperative risk assessment in particular.35,37 In this context, a so-called rMT ratio has been established, which is the result of the rMT value of the affected hemisphere divided by the corresponding value of the healthy hemisphere. Clearly elevated ratios have already been suggested to serve as an indication of imminent damage to the motor system, although further research is required to support the understanding of the exact neurophysiological relationships involved. Hence, the rMT can be regarded as a plausible indicator in the context of assessment of the functional status of the motor system, but this has primarily been observed in the context of rMT ratios without taking nTMS-based DTI FT into account. In this context, comparatively strong negative correlation coefficients were observed between rMTs of patients with surgery-related transient motor deficits and lesion-to-CST distances and between rMTs of patients suffering from new surgery-related permanent paresis and lesion-to-CST distances, whereas less distinct values were achieved for patients without surgery-related paresis (Table 5). Hence, the higher the preoperatively determined rMT was, the lower the lesion-to-CST distance, and vice versa. For patients with paresis, this finding might indicate that tumors directly affected the motor system, impairing the integrity of the CST. The important point is based on the finding that preoperative evaluation of correlations between rMT and lesion-to-CST distances can already provide a hint regarding surgery-related transient or permanent deterioration in motor function, and therefore such correlations can be helpful in risk assessment and patient counseling. However, comparable results for correlations between rMTs and fiber numbers have not been obtained because most coefficients did not indicate a strong level of correlation (Table 6). Additionally, they ranged between negative and positive values when considering subjects with surgery-related transient or permanent paresis, thus not providing a reasonable pattern for interpretation at this stage.

Significance and Outlook

To summarize, this is one of the first studies using nTMS-based DTI FT for risk stratification in patients with brain tumors. In this context, the results regarding cutoff values presented in an earlier study are extended by further tracking paradigms.37 Furthermore, associations between lesion-to-CST distances and motor function as well as rMTs are evaluated for the first time, with significant results concerning surgery-related paresis. Accordingly, we were able to demonstrate direct correlations between preoperative imaging (lesion-to-CST distance, fiber count), clinical status, and neurophysiological markers (rMT), which can be used for evaluation of the integrity of the motor system in patients with brain tumors. Importantly, this evaluation may facilitate individual assessment of the surgical risk prior to tumor removal in terms of any possible worsening of motor function.

Against this backdrop, the present study delivers significant results indicating that nTMS-based DTI FT is a valid tool for risk stratification regarding surgery-related permanent paresis and, more generally speaking, long-term motor status. Importantly, both motor mapping and tractography are already routinely performed for surgical planning and resection guidance in an increasing number of neurosurgical centers. Because these 2 modalities provide all values used for risk stratification in this study, adding our approach to the clinical routine would only require a very limited amount of additional effort. In exchange, this would help surgeons provide patients with better information on individual opportunities and risks in terms of brain tumor resection. To achieve optimal results for this purpose, tracking should be performed at 50% or 75% FAT until further DTI FT settings are evaluated for risk stratification based on nTMS motor data.

Regarding the cutoff values for new surgery-related permanent paresis, one could speculate that preoperative measurements of lesion-to-CST distances might allow for a reassessment as to whether IOM is needed for patients with lesion-to-CST distances ≥ 12 mm, because no new surgery-related permanent deficits were observed in such patients. The present study primarily evaluated risk stratification based on preoperative data, but a direct impact on intraoperative approaches in terms of IOM needs to be validated by considering the results presented by our group as well as those delivered by our Berlin colleagues.37

Limitations of the Study

It is well known that DTI FT faces reconstruction problems when fibers cross, and fibers close to tumor margins or edema are vulnerable to incorrect tracking results, which hampers broad acceptance of this technique in the context of clinical neurosurgery.5,11,27,32 In principle, such issues can lead to incorrect fiber tract visualizations, with incorrect measurements of lesion-to-CST distances or wrong estimations of overall fiber numbers. However, no statistically significant differences regarding lesion-to-CST distances were observed between patients with or without tumor-related edema and surgery-related transient or permanent motor deficits in the present study (Table 3). This is in line with the findings of a previous study on nTMS-based DTI FT of language pathways.31 In this context, other methods, such as high angular resolution diffusion imaging, are currently being promoted for tractography purposes, with promising results. Yet, they are still not routinely applied in most neurosurgical centers because they represent much more elaborate approaches, which can hamper integration into the workflow of clinical routine.7,26

Furthermore, although a comparatively large cohort of patients with different types of brain tumors has been enrolled, our results are primarily restricted to patients with HGG because the low numbers of deficits among patients with LGG and MET did not allow for systematic statistical analyses. Hence, lesion-to-CST distances and correlations were only achieved among patients with HGG. Therefore, it is mandatory to consider the findings of the present study as the basis for further studies among larger samples with other tumor types. Especially in nonenhancing lesions, measurements of lesion-to-CST distances might be hampered due to more difficult identification of tumor borders or more difficult differentiation between edema and the tumor volume. Consequently, it has to be determined whether comparable results can also be achieved in nonenhancing brain lesions.

Conclusions

This is one of the first studies to show a direct correlation between imaging (lesion-to-CST distance, fiber count), clinical status, and neurophysiological markers (rMT) for the integrity of the motor system in patients with brain tumors. Hence, nTMS-based tractography of the CST might allow for preoperative risk stratification with only limited additional effort. As a consequence, the current role of preoperative nTMS mapping and nTMS-based DTI FT for surgical planning and resection guidance in neurosurgery could be expanded significantly.

Acknowledgments

Dr. Sollmann and Mrs. Wildschuetz gratefully acknowledge the support of the TUM (Technische Universität München) Graduate School's Faculty Graduate Center of Medicine.

Disclosures

Dr. Krieg is a consultant for BrainLAB AG and Nexstim Plc.

Author Contributions

Conception and design: Krieg, Sollmann. Acquisition of data: Krieg, Sollmann, Wildschuetz, Kelm, Conway, Moser, Bulubas, Kirschke. Analysis and interpretation of data: Krieg, Sollmann, Wildschuetz. Drafting the article: Sollmann, Wildschuetz. Critically revising the article: Krieg, Conway. Reviewed submitted version of manuscript: Krieg, Kirschke, Meyer. Approved the final version of the manuscript on behalf of all authors: Krieg. Statistical analysis: Krieg, Sollmann. Administrative/technical/material support: Krieg, Meyer. Study supervision: Krieg, Meyer.

References

  • 1

    Agarwal S, Sair HI, Yahyavi-Firouz-Abadi N, Airan R, Pillai JJ: Neurovascular uncoupling in resting state fMRI demonstrated in patients with primary brain gliomas. J Magn Reson Imaging 43:620626, 2016

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2

    Almenawer SA, Badhiwala JH, Alhazzani W, Greenspoon J, Farrokhyar F, Yarascavitch B, et al.: Biopsy versus partial versus gross total resection in older patients with high-grade glioma: a systematic review and meta-analysis. Neuro Oncol 17:868881, 2015

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3

    Bailey PD, Zacà D, Basha MM, Agarwal S, Gujar SK, Sair HI, et al.: Presurgical fMRI and DTI for the prediction of perioperative motor and language deficits in primary or metastatic brain lesions. J Neuroimaging 25:776784, 2015

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4

    Bello L, Gambini A, Castellano A, Carrabba G, Acerbi F, Fava E, et al.: Motor and language DTI fiber tracking combined with intraoperative subcortical mapping for surgical removal of gliomas. Neuroimage 39:369382, 2008

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5

    Berman JI, Berger MS, Chung SW, Nagarajan SS, Henry RG: Accuracy of diffusion tensor magnetic resonance imaging tractography assessed using intraoperative subcortical stimulation mapping and magnetic source imaging. J Neurosurg 107:488494, 2007

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6

    Brown TJ, Brennan MC, Li M, Church EW, Brandmeir NJ, Rakszawski KL, et al.: Association of the extent of resection with survival in glioblastoma: a systematic review and meta-analysis. JAMA Oncol 2:14601469, 2016

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7

    Bucci M, Mandelli ML, Berman JI, Amirbekian B, Nguyen C, Berger MS, et al.: Quantifying diffusion MRI tractography of the corticospinal tract in brain tumors with deterministic and probabilistic methods. Neuroimage Clin 3:361368, 2013

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8

    Bulubas L, Sabih J, Wohlschlaeger A, Sollmann N, Hauck T, Ille S, et al.: Motor areas of the frontal cortex in patients with motor eloquent brain lesions. J Neurosurg 125:14311442, 2016

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9

    Cedzich C, Taniguchi M, Schäfer S, Schramm J: Somatosensory evoked potential phase reversal and direct motor cortex stimulation during surgery in and around the central region. Neurosurgery 38:962970, 1996

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10

    Conti A, Raffa G, Granata F, Rizzo V, Germanò A, Tomasello F: Navigated transcranial magnetic stimulation for “somatotopic” tractography of the corticospinal tract. Neurosurgery 10 :Suppl 4 542554, 2014

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11

    Duffau H: Diffusion tensor imaging is a research and educational tool, but not yet a clinical tool. World Neurosurg 82:e43e45, 2014

  • 12

    Duffau H, Mandonnet E: The “onco-functional balance” in surgery for diffuse low-grade glioma: integrating the extent of resection with quality of life. Acta Neurochir (Wien) 155:951957, 2013

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 13

    Fraga de Abreu VH, Peck KK, Petrovich-Brennan NM, Woo KM, Holodny AI: Brain tumors: the influence of tumor type and routine MR imaging characteristics at BOLD functional MR imaging in the primary motor gyrus. Radiology 281:876883, 2016

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14

    Frey D, Schilt S, Strack V, Zdunczyk A, Rösler J, Niraula B, et al.: Navigated transcranial magnetic stimulation improves the treatment outcome in patients with brain tumors in motor eloquent locations. Neuro Oncol 16:13651372, 2014

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15

    Frey D, Strack V, Wiener E, Jussen D, Vajkoczy P, Picht T: A new approach for corticospinal tract reconstruction based on navigated transcranial stimulation and standardized fractional anisotropy values. Neuroimage 62:16001609, 2012

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16

    Håberg A, Kvistad KA, Unsgård G, Haraldseth O: Preoperative blood oxygen level-dependent functional magnetic resonance imaging in patients with primary brain tumors: clinical application and outcome. Neurosurgery 54:902915, 2004

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17

    Holodny AI, Schulder M, Liu WC, Wolko J, Maldjian JA, Kalnin AJ: The effect of brain tumors on BOLD functional MR imaging activation in the adjacent motor cortex: implications for image-guided neurosurgery. AJNR Am J Neuroradiol 21:14151422, 2000

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18

    Kombos T, Suess O, Ciklatekerlio O, Brock M: Monitoring of intraoperative motor evoked potentials to increase the safety of surgery in and around the motor cortex. J Neurosurg 95:608614, 2001

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19

    Krieg SM, Buchmann NH, Gempt J, Shiban E, Meyer B, Ringel F: Diffusion tensor imaging fiber tracking using navigated brain stimulation—a feasibility study. Acta Neurochir (Wien) 154:555563, 2012

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20

    Krieg SM, Sabih J, Bulubasova L, Obermueller T, Negwer C, Janssen I, et al.: Preoperative motor mapping by navigated transcranial magnetic brain stimulation improves outcome for motor eloquent lesions. Neuro Oncol 16:12741282, 2014

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21

    Krieg SM, Schäffner M, Shiban E, Droese D, Obermüller T, Gempt J, et al.: Reliability of intraoperative neurophysiological monitoring using motor evoked potentials during resection of metastases in motor-eloquent brain regions: clinical article. J Neurosurg 118:12691278, 2013

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22

    Krieg SM, Shiban E, Buchmann N, Gempt J, Foerschler A, Meyer B, et al.: Utility of presurgical navigated transcranial magnetic brain stimulation for the resection of tumors in eloquent motor areas. J Neurosurg 116:9941001, 2012

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23

    Krieg SM, Shiban E, Droese D, Gempt J, Buchmann N, Pape H, et al.: Predictive value and safety of intraoperative neurophysiological monitoring with motor evoked potentials in glioma surgery. Neurosurgery 70:10601071, 2012

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24

    Krieg SM, Sollmann N, Obermueller T, Sabih J, Bulubas L, Negwer C, et al.: Changing the clinical course of glioma patients by preoperative motor mapping with navigated transcranial magnetic brain stimulation. BMC Cancer 15:231, 2015

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25

    Krishnan R, Raabe A, Hattingen E, Szelenyi A, Yahya H, Hermann E, et al.: Functional magnetic resonance imaging-integrated neuronavigation: correlation between lesion-to-motor cortex distance and outcome. Neurosurgery 55:904915, 2004

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26

    Kuhnt D, Bauer MH, Egger J, Richter M, Kapur T, Sommer J, et al.: Fiber tractography based on diffusion tensor imaging compared with high-angular-resolution diffusion imaging with compressed sensing: initial experience. Neurosurgery 72 :Suppl 1 165175, 2013

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27

    Le Bihan D, Poupon C, Amadon A, Lethimonnier F: Artifacts and pitfalls in diffusion MRI. J Magn Reson Imaging 24:478488, 2006

  • 28

    Lee CH, Kim DG, Kim JW, Han JH, Kim YH, Park CK, et al.: The role of surgical resection in the management of brain metastasis: a 17-year longitudinal study. Acta Neurochir (Wien) 155:389397, 2013

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29

    Lehéricy S, Duffau H, Cornu P, Capelle L, Pidoux B, Carpentier A, et al.: Correspondence between functional magnetic resonance imaging somatotopy and individual brain anatomy of the central region: comparison with intraoperative stimulation in patients with brain tumors. J Neurosurg 92:589598, 2000

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30

    McGirt MJ, Mukherjee D, Chaichana KL, Than KD, Weingart JD, Quinones-Hinojosa A: Association of surgically acquired motor and language deficits on overall survival after resection of glioblastoma multiforme. Neurosurgery 65:463470, 2009

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31

    Negwer C, Ille S, Hauck T, Sollmann N, Maurer S, Kirschke JS, et al.: Visualization of subcortical language pathways by diffusion tensor imaging fiber tracking based on rTMS language mapping. Brain Imaging Behav [epub ahead of print], 2016

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32

    Nimsky C: Fiber tracking—a reliable tool for neurosurgery?. World Neurosurg 74:105106, 2010

  • 33

    Nimsky C, Ganslandt O, Merhof D, Sorensen AG, Fahlbusch R: Intraoperative visualization of the pyramidal tract by diffusion-tensor-imaging-based fiber tracking. Neuroimage 30:12191229, 2006

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34

    Picht T, Mularski S, Kuehn B, Vajkoczy P, Kombos T, Suess O: Navigated transcranial magnetic stimulation for preoperative functional diagnostics in brain tumor surgery. Neurosurgery 65 :6 Suppl 9399, 2009

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 35

    Picht T, Strack V, Schulz J, Zdunczyk A, Frey D, Schmidt S, et al.: Assessing the functional status of the motor system in brain tumor patients using transcranial magnetic stimulation. Acta Neurochir (Wien) 154:20752081, 2012

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 36

    Raabe A, Beck J, Schucht P, Seidel K: Continuous dynamic mapping of the corticospinal tract during surgery of motor eloquent brain tumors: evaluation of a new method. J Neurosurg 120:10151024, 2014

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 37

    Rosenstock T, Grittner U, Acker G, Schwarzer V, Kulchytska N, Vajkoczy P, et al.: Risk stratification in motor area-related glioma surgery based on navigated transcranial magnetic stimulation data. J Neurosurg [epub ahead of print June 3, 2016. DOI: 10.3171/2016.4.JNS152896]

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 38

    Rossini PM, Burke D, Chen R, Cohen LG, Daskalakis Z, Di Iorio R, et al.: Non-invasive electrical and magnetic stimulation of the brain, spinal cord, roots and peripheral nerves: Basic principles and procedures for routine clinical and research application. An updated report from an I.F.C.N. Committee. Clin Neurophysiol 126:10711107, 2015

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 39

    Ruohonen J, Karhu J: Navigated transcranial magnetic stimulation. Neurophysiol Clin 40:717, 2010

  • 40

    Sanai N, Berger MS: Glioma extent of resection and its impact on patient outcome. Neurosurgery 62:753764, 2008

  • 41

    Seidel K, Beck J, Stieglitz L, Schucht P, Raabe A: The warning-sign hierarchy between quantitative subcortical motor mapping and continuous motor evoked potential monitoring during resection of supratentorial brain tumors. J Neurosurg 118:287296, 2013

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 42

    Shiban E, Krieg SM, Haller B, Buchmann N, Obermueller T, Boeckh-Behrens T, et al.: Intraoperative subcortical motor evoked potential stimulation: how close is the corticospinal tract?. J Neurosurg 123:711720, 2015

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 43

    Taniguchi M, Cedzich C, Schramm J: Modification of cortical stimulation for motor evoked potentials under general anesthesia: technical description. Neurosurgery 32:219226, 1993

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 44

    Tarapore PE, Tate MC, Findlay AM, Honma SM, Mizuiri D, Berger MS, et al.: Preoperative multimodal motor mapping: a comparison of magnetoencephalography imaging, navigated transcranial magnetic stimulation, and direct cortical stimulation. J Neurosurg 117:354362, 2012

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 45

    Ulmer JL, Salvan CV, Mueller WM, Krouwer HG, Stroe GO, Aralasmak A, et al.: The role of diffusion tensor imaging in establishing the proximity of tumor borders to functional brain systems: implications for preoperative risk assessments and postoperative outcomes. Technol Cancer Res Treat 3:567576, 2004

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 46

    Wakana S, Jiang H, Nagae-Poetscher LM, van Zijl PC, Mori S: Fiber tract-based atlas of human white matter anatomy. Radiology 230:7787, 2004

  • 47

    Wood JM, Kundu B, Utter A, Gallagher TA, Voss J, Nair VA, et al.: Impact of brain tumor location on morbidity and mortality: a retrospective functional MR imaging study. AJNR Am J Neuroradiol 32:14201425, 2011

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • View in gallery

    Setup overview. This figure depicts the procedures performed during pre- and postoperative assessments and surgery, including nTMS for motor mapping and nTMS-based tractography of the CST. In addition, it shows the study's main approaches regarding data analyses.

  • View in gallery

    Tractography and measurement of the minimum lesion-to-CST distance. This figure visualizes DTI FT based on nTMS data for reconstruction of the CST (left). The motor-positive nTMS spots are depicted as green points, and the tumor volume is shown in orange. Furthermore, an axial MRI slice is shown, providing an example of how minimum lesion-to-CST distances were measured (right). Figure is available in color online only.

  • 1

    Agarwal S, Sair HI, Yahyavi-Firouz-Abadi N, Airan R, Pillai JJ: Neurovascular uncoupling in resting state fMRI demonstrated in patients with primary brain gliomas. J Magn Reson Imaging 43:620626, 2016

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2

    Almenawer SA, Badhiwala JH, Alhazzani W, Greenspoon J, Farrokhyar F, Yarascavitch B, et al.: Biopsy versus partial versus gross total resection in older patients with high-grade glioma: a systematic review and meta-analysis. Neuro Oncol 17:868881, 2015

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3

    Bailey PD, Zacà D, Basha MM, Agarwal S, Gujar SK, Sair HI, et al.: Presurgical fMRI and DTI for the prediction of perioperative motor and language deficits in primary or metastatic brain lesions. J Neuroimaging 25:776784, 2015

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4

    Bello L, Gambini A, Castellano A, Carrabba G, Acerbi F, Fava E, et al.: Motor and language DTI fiber tracking combined with intraoperative subcortical mapping for surgical removal of gliomas. Neuroimage 39:369382, 2008

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5

    Berman JI, Berger MS, Chung SW, Nagarajan SS, Henry RG: Accuracy of diffusion tensor magnetic resonance imaging tractography assessed using intraoperative subcortical stimulation mapping and magnetic source imaging. J Neurosurg 107:488494, 2007

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6

    Brown TJ, Brennan MC, Li M, Church EW, Brandmeir NJ, Rakszawski KL, et al.: Association of the extent of resection with survival in glioblastoma: a systematic review and meta-analysis. JAMA Oncol 2:14601469, 2016

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7

    Bucci M, Mandelli ML, Berman JI, Amirbekian B, Nguyen C, Berger MS, et al.: Quantifying diffusion MRI tractography of the corticospinal tract in brain tumors with deterministic and probabilistic methods. Neuroimage Clin 3:361368, 2013

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8

    Bulubas L, Sabih J, Wohlschlaeger A, Sollmann N, Hauck T, Ille S, et al.: Motor areas of the frontal cortex in patients with motor eloquent brain lesions. J Neurosurg 125:14311442, 2016

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9

    Cedzich C, Taniguchi M, Schäfer S, Schramm J: Somatosensory evoked potential phase reversal and direct motor cortex stimulation during surgery in and around the central region. Neurosurgery 38:962970, 1996

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10

    Conti A, Raffa G, Granata F, Rizzo V, Germanò A, Tomasello F: Navigated transcranial magnetic stimulation for “somatotopic” tractography of the corticospinal tract. Neurosurgery 10 :Suppl 4 542554, 2014

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11

    Duffau H: Diffusion tensor imaging is a research and educational tool, but not yet a clinical tool. World Neurosurg 82:e43e45, 2014

  • 12

    Duffau H, Mandonnet E: The “onco-functional balance” in surgery for diffuse low-grade glioma: integrating the extent of resection with quality of life. Acta Neurochir (Wien) 155:951957, 2013

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 13

    Fraga de Abreu VH, Peck KK, Petrovich-Brennan NM, Woo KM, Holodny AI: Brain tumors: the influence of tumor type and routine MR imaging characteristics at BOLD functional MR imaging in the primary motor gyrus. Radiology 281:876883, 2016

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14

    Frey D, Schilt S, Strack V, Zdunczyk A, Rösler J, Niraula B, et al.: Navigated transcranial magnetic stimulation improves the treatment outcome in patients with brain tumors in motor eloquent locations. Neuro Oncol 16:13651372, 2014

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15

    Frey D, Strack V, Wiener E, Jussen D, Vajkoczy P, Picht T: A new approach for corticospinal tract reconstruction based on navigated transcranial stimulation and standardized fractional anisotropy values. Neuroimage 62:16001609, 2012

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16

    Håberg A, Kvistad KA, Unsgård G, Haraldseth O: Preoperative blood oxygen level-dependent functional magnetic resonance imaging in patients with primary brain tumors: clinical application and outcome. Neurosurgery 54:902915, 2004

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17

    Holodny AI, Schulder M, Liu WC, Wolko J, Maldjian JA, Kalnin AJ: The effect of brain tumors on BOLD functional MR imaging activation in the adjacent motor cortex: implications for image-guided neurosurgery. AJNR Am J Neuroradiol 21:14151422, 2000

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18

    Kombos T, Suess O, Ciklatekerlio O, Brock M: Monitoring of intraoperative motor evoked potentials to increase the safety of surgery in and around the motor cortex. J Neurosurg 95:608614, 2001

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19

    Krieg SM, Buchmann NH, Gempt J, Shiban E, Meyer B, Ringel F: Diffusion tensor imaging fiber tracking using navigated brain stimulation—a feasibility study. Acta Neurochir (Wien) 154:555563, 2012

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20

    Krieg SM, Sabih J, Bulubasova L, Obermueller T, Negwer C, Janssen I, et al.: Preoperative motor mapping by navigated transcranial magnetic brain stimulation improves outcome for motor eloquent lesions. Neuro Oncol 16:12741282, 2014

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21

    Krieg SM, Schäffner M, Shiban E, Droese D, Obermüller T, Gempt J, et al.: Reliability of intraoperative neurophysiological monitoring using motor evoked potentials during resection of metastases in motor-eloquent brain regions: clinical article. J Neurosurg 118:12691278, 2013

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22

    Krieg SM, Shiban E, Buchmann N, Gempt J, Foerschler A, Meyer B, et al.: Utility of presurgical navigated transcranial magnetic brain stimulation for the resection of tumors in eloquent motor areas. J Neurosurg 116:9941001, 2012

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23

    Krieg SM, Shiban E, Droese D, Gempt J, Buchmann N, Pape H, et al.: Predictive value and safety of intraoperative neurophysiological monitoring with motor evoked potentials in glioma surgery. Neurosurgery 70:10601071, 2012

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24

    Krieg SM, Sollmann N, Obermueller T, Sabih J, Bulubas L, Negwer C, et al.: Changing the clinical course of glioma patients by preoperative motor mapping with navigated transcranial magnetic brain stimulation. BMC Cancer 15:231, 2015

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25

    Krishnan R, Raabe A, Hattingen E, Szelenyi A, Yahya H, Hermann E, et al.: Functional magnetic resonance imaging-integrated neuronavigation: correlation between lesion-to-motor cortex distance and outcome. Neurosurgery 55:904915, 2004

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26

    Kuhnt D, Bauer MH, Egger J, Richter M, Kapur T, Sommer J, et al.: Fiber tractography based on diffusion tensor imaging compared with high-angular-resolution diffusion imaging with compressed sensing: initial experience. Neurosurgery 72 :Suppl 1 165175, 2013

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27

    Le Bihan D, Poupon C, Amadon A, Lethimonnier F: Artifacts and pitfalls in diffusion MRI. J Magn Reson Imaging 24:478488, 2006

  • 28

    Lee CH, Kim DG, Kim JW, Han JH, Kim YH, Park CK, et al.: The role of surgical resection in the management of brain metastasis: a 17-year longitudinal study. Acta Neurochir (Wien) 155:389397, 2013

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29

    Lehéricy S, Duffau H, Cornu P, Capelle L, Pidoux B, Carpentier A, et al.: Correspondence between functional magnetic resonance imaging somatotopy and individual brain anatomy of the central region: comparison with intraoperative stimulation in patients with brain tumors. J Neurosurg 92:589598, 2000

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30

    McGirt MJ, Mukherjee D, Chaichana KL, Than KD, Weingart JD, Quinones-Hinojosa A: Association of surgically acquired motor and language deficits on overall survival after resection of glioblastoma multiforme. Neurosurgery 65:463470, 2009

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31

    Negwer C, Ille S, Hauck T, Sollmann N, Maurer S, Kirschke JS, et al.: Visualization of subcortical language pathways by diffusion tensor imaging fiber tracking based on rTMS language mapping. Brain Imaging Behav [epub ahead of print], 2016

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32

    Nimsky C: Fiber tracking—a reliable tool for neurosurgery?. World Neurosurg 74:105106, 2010

  • 33

    Nimsky C, Ganslandt O, Merhof D, Sorensen AG, Fahlbusch R: Intraoperative visualization of the pyramidal tract by diffusion-tensor-imaging-based fiber tracking. Neuroimage 30:12191229, 2006

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34

    Picht T, Mularski S, Kuehn B, Vajkoczy P, Kombos T, Suess O: Navigated transcranial magnetic stimulation for preoperative functional diagnostics in brain tumor surgery. Neurosurgery 65 :6 Suppl 9399, 2009

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 35

    Picht T, Strack V, Schulz J, Zdunczyk A, Frey D, Schmidt S, et al.: Assessing the functional status of the motor system in brain tumor patients using transcranial magnetic stimulation. Acta Neurochir (Wien) 154:20752081, 2012

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 36

    Raabe A, Beck J, Schucht P, Seidel K: Continuous dynamic mapping of the corticospinal tract during surgery of motor eloquent brain tumors: evaluation of a new method. J Neurosurg 120:10151024, 2014

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 37

    Rosenstock T, Grittner U, Acker G, Schwarzer V, Kulchytska N, Vajkoczy P, et al.: Risk stratification in motor area-related glioma surgery based on navigated transcranial magnetic stimulation data. J Neurosurg [epub ahead of print June 3, 2016. DOI: 10.3171/2016.4.JNS152896]

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 38

    Rossini PM, Burke D, Chen R, Cohen LG, Daskalakis Z, Di Iorio R, et al.: Non-invasive electrical and magnetic stimulation of the brain, spinal cord, roots and peripheral nerves: Basic principles and procedures for routine clinical and research application. An updated report from an I.F.C.N. Committee. Clin Neurophysiol 126:10711107, 2015

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 39

    Ruohonen J, Karhu J: Navigated transcranial magnetic stimulation. Neurophysiol Clin 40:717, 2010

  • 40

    Sanai N, Berger MS: Glioma extent of resection and its impact on patient outcome. Neurosurgery 62:753764, 2008

  • 41

    Seidel K, Beck J, Stieglitz L, Schucht P, Raabe A: The warning-sign hierarchy between quantitative subcortical motor mapping and continuous motor evoked potential monitoring during resection of supratentorial brain tumors. J Neurosurg 118:287296, 2013

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 42

    Shiban E, Krieg SM, Haller B, Buchmann N, Obermueller T, Boeckh-Behrens T, et al.: Intraoperative subcortical motor evoked potential stimulation: how close is the corticospinal tract?. J Neurosurg 123:711720, 2015

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 43

    Taniguchi M, Cedzich C, Schramm J: Modification of cortical stimulation for motor evoked potentials under general anesthesia: technical description. Neurosurgery 32:219226, 1993

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 44

    Tarapore PE, Tate MC, Findlay AM, Honma SM, Mizuiri D, Berger MS, et al.: Preoperative multimodal motor mapping: a comparison of magnetoencephalography imaging, navigated transcranial magnetic stimulation, and direct cortical stimulation. J Neurosurg 117:354362, 2012

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 45

    Ulmer JL, Salvan CV, Mueller WM, Krouwer HG, Stroe GO, Aralasmak A, et al.: The role of diffusion tensor imaging in establishing the proximity of tumor borders to functional brain systems: implications for preoperative risk assessments and postoperative outcomes. Technol Cancer Res Treat 3:567576, 2004

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 46

    Wakana S, Jiang H, Nagae-Poetscher LM, van Zijl PC, Mori S: Fiber tract-based atlas of human white matter anatomy. Radiology 230:7787, 2004

  • 47

    Wood JM, Kundu B, Utter A, Gallagher TA, Voss J, Nair VA, et al.: Impact of brain tumor location on morbidity and mortality: a retrospective functional MR imaging study. AJNR Am J Neuroradiol 32:14201425, 2011

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation

Metrics

All Time Past Year Past 30 Days
Abstract Views 413 0 0
Full Text Views 1127 448 145
PDF Downloads 686 229 32
EPUB Downloads 0 0 0