Analysis of the effect of intraoperative neuromonitoring during resection of benign nerve sheath tumors on gross-total resection and neurological complications

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  • 1 Department of Neurosurgery, Stanford University, Stanford, California;
  • | 2 Department of Neurosurgery, University of Utah, Salt Lake City, Utah;
  • | 3 Department of Clinical Neurosciences, University of Calgary, Alberta, Canada;
  • | 4 Department of Neurosurgery, Washington University in St. Louis, Missouri;
  • | 5 Department of Neurosurgery, University of Michigan, Ann Arbor, Michigan;
  • | 6 Department of Neurosurgery, Mayo Clinic, Rochester, Minnesota; and
  • | 7 Department of Neurosurgery, University of Pennsylvania, Philadelphia, Pennsylvania
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OBJECTIVE

The aim of this study was to examine the role of intraoperative neuromonitoring (IONM) during resection of benign peripheral nerve sheath tumors in achieving gross-total resection (GTR) and in reducing postoperative neurological complications.

METHODS

Data from consecutive adult patients who underwent resection of a benign peripheral nerve sheath tumor at 7 participating institutions were combined. Propensity score matching was used to balance covariates. The primary outcomes of interest were the association between IONM and GTR and the association of IONM and the development of a permanent postoperative neurological complication. The secondary outcomes of interest were the association between IONM and GTR and the association between IONM and the development of a permanent postoperative neurological complication in the subgroup of patients with tumors involving a motor or mixed nerve. Univariate and multivariate logistic regression were then performed on the propensity score–matched samples to assess the ability of the independent variables to predict the outcomes of interest.

RESULTS

A total of 337 patients who underwent resection of benign nerve sheath tumors were included. In multivariate analysis, the use of IONM (OR 0.460, 95% CI 0.199–0.978; p = 0.047) was a significant negative predictor of GTR, whereas none of the variables, including IONM, were associated with the occurrence of a permanent postoperative neurological complication. Within the subgroup of motor/mixed nerve tumors, in the multivariate analysis, IONM (OR 0.263, 95% CI 0.096–0.723; p = 0.010) was a significant negative predictor of a GTR, whereas IONM (OR 3.800, 95% CI 1.925–7.502; p < 0.001) was a significant positive predictor of a permanent postoperative motor deficit.

CONCLUSIONS

Overall, 12% of the cohort had a permanent neurological complication, with new or worsened paresthesias most common, followed by pain and then weakness. The authors found that formal IONM was associated with a reduced likelihood of GTR and had no association with neurological complications. The authors believe that these data argue against IONM being considered standard of care but do not believe that these data should be used to universally argue against IONM during resection of benign nerve sheath tumors.

ABBREVIATIONS

BPNST = benign peripheral nerve sheath tumor; GTR = gross-total resection; IONM = intraoperative neuromonitoring; NF = neurofibromatosis; NF1 = NF type 1; NF2 = NF type 2.

OBJECTIVE

The aim of this study was to examine the role of intraoperative neuromonitoring (IONM) during resection of benign peripheral nerve sheath tumors in achieving gross-total resection (GTR) and in reducing postoperative neurological complications.

METHODS

Data from consecutive adult patients who underwent resection of a benign peripheral nerve sheath tumor at 7 participating institutions were combined. Propensity score matching was used to balance covariates. The primary outcomes of interest were the association between IONM and GTR and the association of IONM and the development of a permanent postoperative neurological complication. The secondary outcomes of interest were the association between IONM and GTR and the association between IONM and the development of a permanent postoperative neurological complication in the subgroup of patients with tumors involving a motor or mixed nerve. Univariate and multivariate logistic regression were then performed on the propensity score–matched samples to assess the ability of the independent variables to predict the outcomes of interest.

RESULTS

A total of 337 patients who underwent resection of benign nerve sheath tumors were included. In multivariate analysis, the use of IONM (OR 0.460, 95% CI 0.199–0.978; p = 0.047) was a significant negative predictor of GTR, whereas none of the variables, including IONM, were associated with the occurrence of a permanent postoperative neurological complication. Within the subgroup of motor/mixed nerve tumors, in the multivariate analysis, IONM (OR 0.263, 95% CI 0.096–0.723; p = 0.010) was a significant negative predictor of a GTR, whereas IONM (OR 3.800, 95% CI 1.925–7.502; p < 0.001) was a significant positive predictor of a permanent postoperative motor deficit.

CONCLUSIONS

Overall, 12% of the cohort had a permanent neurological complication, with new or worsened paresthesias most common, followed by pain and then weakness. The authors found that formal IONM was associated with a reduced likelihood of GTR and had no association with neurological complications. The authors believe that these data argue against IONM being considered standard of care but do not believe that these data should be used to universally argue against IONM during resection of benign nerve sheath tumors.

In Brief

The goal of this study was to examine the role of intraoperative neuromonitoring (IONM) during resection of benign peripheral nerve sheath tumors in achieving gross-total resection and reducing postoperative neurological complications. Formal IONM was associated with a reduced likelihood of gross-total resection and had no association with neurological complications. Understanding the benefits and consequences of using IONM will help surgeons choose when to selectively utilize IONM during these operations.

Resection of benign peripheral nerve sheath tumors (BPNSTs) carries the risk of neurological worsening, including new or worsened neuropathic pain or paresthesias, numbness, or weakness. Rates of reported postoperative deficits vary but often approach 30%.1–4 With less-experienced surgeons often excluded from these reports, postoperative deficits may be underestimated. Intraoperative neuromonitoring (IONM) is thought by some to be an essential tool during resection of BPNSTs. However, little is known about the risks or benefits of using IONM.

Routine use of IONM for both BPNSTs and other pathologies remains somewhat controversial.5 Alternative approaches used by some surgeons during resection of BPNSTs include visual mapping of the surface of the tumor and using a handheld nerve stimulator to map and assess motor fascicles, examining visibly for movement. Many times, a combination of visual mapping and handheld nerve stimulation is used in the absence of formal IONM. Levi and colleagues reported that the use of neuromonitoring reduced the likelihood of a postoperative motor deficit in neurofibromas, but not in schwannomas, but it is not clear whether a handheld nerve stimulator or formal IONM was used.2 Importantly, surgical outcome data indicate better postoperative outcomes after complete resection of PNSTs.6 Thus, there is a need to further examine the relationship between IONM and gross-total resection (GTR), as well as IONM and the occurrence of neurological complications. Because of the uncertain benefit that IONM confers for BPNST resection, we sought to examine the role of IONM in achieving GTR and in reducing postoperative neurological complications.

Methods

Study Population

Surgeons at 7 institutions retrospectively collected data for consecutive patients undergoing resection of BPNSTs. Only adults (age ≥ 18 years) were included. Tumors within the spinal canal, including dumbbell tumors, were excluded. The study was approved by the institutional review board.

Variables of Interest

Demographic data, including age at the time of surgery and sex, were abstracted. Other variables of interest included diagnosis of a genetic syndrome, including neurofibromatosis (NF) type 1 (NF1), NF type 2 (NF2), and schwannomatosis; size of the tumor on imaging; location of the tumor and nerve involved; presence of spontaneous unprovoked pain, pain with contact to the tumor, paresthesias, or objective weakness in the distribution of the involved nerve; indication(s) for surgery; history of open or percutaneous biopsy; pathologic diagnosis; whether GTR was achieved, IONM was used, or a handheld nerve stimulator was used; and whether there was new transient or permanent postoperative pain, paresthesias, or weakness. IONM was used at the operating surgeon’s discretion, as part of routine clinical care based on individual surgeon’s practice patterns and without any specific, prespecified criteria.

Definition of Terms

Tumor location was classified as brachial plexus, arm, lumbosacral plexus, leg, or other. Nerve type was classified as motor/mixed versus sensory. Assessment of GTR was based on the surgeon’s report and not on postoperative imaging and was dichotomized to GTR versus subtotal resection. Tumor size was considered the largest measurement of the tumor in any dimension on preoperative imaging. IONM included the use of any or all of the following: triggered electromyography (EMG), free-running EMG, motor evoked potentials (MEPs), and somatosensory evoked potentials (SSEPs). Note that the use of a handheld stimulator alone was not considered to meet the criteria for the use of IONM. Postoperative neurological complications, including pain, paresthesias, and weakness, were considered permanent if they were present at the last follow-up. Weakness was considered present if the objective neurological examination documented a decrement in postoperative motor function in any of the muscles innervated by the nerve involved by the operated tumor in comparison with the preoperative examination. Pain and paresthesias were considered to be present if the postoperative clinical assessment noted new or worsened pain or paresthesias. For the purposes of the primary outcome, the presence of a neurological complication included new or worsened pain, paresthesias, and/or weakness.

Primary Outcomes of Interest

The primary outcomes of interest were the association between IONM and GTR of the tumor and the association between IONM and the development of a permanent postoperative neurological complication.

Secondary Outcomes of Interest

For secondary analysis, the subgroup of tumors involving motor or mixed nerves was analyzed, excluding the tumors involving sensory nerves.

The secondary outcomes of interest were the association between IONM and GTR of the tumor in this subgroup and the association between IONM and the development of a permanent postoperative neurological complication in this subgroup.

Statistical Methods

All statistical analyses were performed using StataSE version 16.1 (StataCorp).

Balance on preoperative covariates was assessed using standardized mean bias. Preoperative covariates that were assessed included sex, genetic syndrome, tumor location, preoperative biopsy, age, tumor size, and nerve type. Propensity score model estimation was performed using logistic regression. Propensity score matching was then performed using 1:1 nearest-neighbor matching without replacement. Pre- and post-matching standardized mean biases were compared to assess balance improvement (Fig. 1A), with adequate and improved balance suggested by the post-matching standardized mean biases.

FIG. 1.
FIG. 1.

Assessment of standardized mean bias was used as a method of assessing the matching before and after propensity score matching. A: Assessment of standardized mean bias pre- and post-matching for all tumors. B: Assessment of standardized mean bias pre- and post-matching for the tumors involving motor/mixed nerves.

For the secondary analyses, propensity score matching was performed on the cohort of motor/mixed nerve tumors, excluding the sensory nerve tumors. Propensity score matching was performed using 1:1 nearest-neighbor matching with replacement. Pre- and post-matching standardized mean biases were compared to assess balance improvement (Fig. 1B), with adequate and improved balance suggested by the post-matching standardized mean biases.

Univariate and multivariate logistic regression were then performed on the propensity score–matched samples to assess the ability of the independent variables to predict our outcomes of interest. We planned a priori to include IONM and all variables with p < 0.20 in the univariate analysis in subsequent multivariate analyses.

Sensitivity analysis was performed using Rosenbaum’s method to test the sensitivity of the model to unobserved confounding.

A p value < 0.05 was considered statistically significant for all analyses.

Results

Participants, Descriptive Data, and Basic Outcomes

A total of 337 patients (149 males [44%] and 188 females [56%]) who underwent resection of BPNSTs were included. The average age of the cohort was 47.4 years (SD 15.6 years, range 18–87 years). The median postoperative follow-up was 4 months (IQR 3–9 months). A total of 121 patients had a neurogenetic syndrome, including NF1 (n = 55, 16%), NF2 (n = 34, 10%), and schwannomatosis (n = 32, 9%). The tumor involved a motor or mixed nerve in 270 patients (80%) versus a sensory nerve in 67 patients (20%). The average largest dimension of the tumor was 35.5 mm (SD 24.4 mm). The leg was the most common tumor location (n = 134, 40%), followed by the arm (n = 80, 24%), brachial plexus (n = 60, 18%), other location (n = 53, 16%), and lumbosacral plexus (n = 10, 3%).

Spontaneous, unprovoked pain was reported for 231 patients (69%). Pain with contact to the tumor was reported in 240 patients (71%). Paresthesias were present in 143 patients (42%). An objective motor deficit in the distribution of the involved nerve was present in 60 patients (18%). Pain/bothersome paresthesias were the most common surgical indication (n = 284, 84%), followed by tumor growth (n = 85, 25%), presence of a motor deficit (n = 28, 8%), concern for malignancy (n = 16, 5%), and other indication (n = 8, 2%). Multiple indications were present in 83 patients (25%). Percutaneous biopsy was performed preoperatively in 77 patients (23%), while open biopsy had been performed prior to resection in 24 patients (7%). Any biopsy preoperatively was performed in 96 patients (28%).

IONM was utilized for 115 patients (34%), and a handheld nerve stimulator was used for 214 patients (64%). Both formal IONM and a handheld nerve stimulator were used for 77 patients (23%). Neither formal IONM nor a handheld nerve stimulator was used for 85 patients (25%). Table 1 shows the practice patterns for each individual institution. GTR was achieved in 286 patients (85%). New or worsened postoperative neuropathic pain was present in 28 patients (8%), including 13 (4%) with permanently worsened neuropathic pain. New or worsened bothersome paresthesias were present in 72 patients (21%), including 29 (9%) with permanently worsened paresthesias. A new motor deficit was present postoperatively in 24 patients (7%), including 10 (3%) who had a permanent motor deficit. Any neurological complication was present in 91 patients (27%), including 39 (12%) who had a permanent neurological complication (Fig. 2).

TABLE 1.

Practice patterns regarding the use of IONM and handheld nerve stimulation at individual institutions

No. of Patients (%)
IONMIONM OnlyHandheldHandheld OnlyBothNeither
Institution 1 (n = 4)
 Sensory (n = 0)NANANANANANA
 Motor/mixed (n = 4)1 (25)0 (0)4 (100)3 (75)1 (25)0 (0)
Institution 2 (n = 32)
 Sensory (n = 3)0 (0)0 (0)1 (33)1 (33)0 (0)2 (67)
 Motor/mixed (n = 29)6 (21)2 (7)21 (72)17 (59)4 (14)6 (21)
Institution 3 (n = 63)
 Sensory (n = 9)7 (78)1 (11)7 (78)1 (11)6 (67)1 (11)
 Motor/mixed (n = 54)48 (89)3 (6)49 (91)4 (7)45 (83)2 (4)
Institution 4 (n = 42)
 Sensory (n = 11)0 (0)0 (0)10 (91)10 (91)0 (0)1 (9)
 Motor/mixed (n = 31)2 (6)1 (3)28 (90)27 (87)1 (3)2 (6)
Institution 5 (n = 52)
 Sensory (n = 2)1 (50)1 (50)0 (0)0 (0)0 (0)1 (50)
 Motor/mixed (n = 50)39 (78)22 (44)24 (48)7 (14)17 (34)4 (8)
Institution 6 (n = 42)
 Sensory (n = 10)0 (0)0 (0)0 (0)0 (0)0 (0)10 (100)
 Motor/mixed (n = 32)6 (19)6 (19)20 (63)20 (63)0 (0)6 (19)
Institution 7 (n = 102)
 Sensory (n = 32)0 (0)0 (0)3 (9)3 (9)0 (0)29 (91)
 Motor/mixed (n = 70)5 (7)2 (3)47 (67)44 (63)3 (4)21 (30)
FIG. 2.
FIG. 2.

Bar graph showing the percentage of patients with neurological complications after resection of a BPNST. Neurological complications included new or worsened neuropathic pain in the distribution of the involved nerve, new or worsened paresthesias in the distribution of the involved nerve, and new or worsened weakness in the distribution of the involved nerve.

The most common tumor pathology was schwannoma (n = 233, 69%), followed by neurofibroma (n = 75, 22%) and hybrid tumor (n = 28, 8%).

For patients who had neuropathic pain preoperatively, 201 of 240 patients (84%) reported improvement in pain. For patients who had bothersome paresthesias preoperatively, 99 of 143 patients (69%) reported improved paresthesias. For patients who had a motor deficit preoperatively, 40 of 60 (67%) had improvement in the motor deficit.

Propensity score matching was utilized, with the matched sample having a total of 212 patients (n = 106 with IONM and n = 106 without IONM).

Primary Outcome 1: GTR With and Without IONM

In univariate analysis using the propensity score–matched cohort, IONM, tumor size, hybrid tumor pathology, and lumbosacral plexus location were all predictive of GTR status (Table 2). Schwannoma pathology, brachial plexus location, arm location, and preoperative biopsy were also included in the multivariate analysis because they met the a priori level of significance for inclusion. In the multivariate analysis, IONM, tumor size, and hybrid tumor pathology all remained significant predictors. All three were negative predictors of GTR: IONM (OR 0.460, 95% CI 0.199–0.978; p = 0.047), tumor size (OR 0.975, 95% CI 0.959–0.991; p = 0.003), and hybrid pathology (OR 0.185, 95% CI 0.035–0.975; p = 0.047).

TABLE 2.

Univariate and multivariate logistic regression analyses of the propensity score–matched cohort examining the association of the listed variables with GTR of the tumor

Univariate OR (95% CI)p ValueMultivariate OR (95% CI)p Value
IONM0.375 (0.174–0.809)0.0120.460 (0.199–0.978)0.047
Age0.990 (0.967–1.014)0.407
Male0.936 (0.457–1.920)0.858
Size0.973 (0.959–0.986)<0.0010.975 (0.959–0.991)0.003
Syndrome
 NF11.410 (0.396–5.023)0.596
 NF20.607 (0.061–6.006)0.669
 Schwannomatosis1.243 (0.266–5.813)0.781
Pathology
 Neurofibroma0.719 (0.299–1.731)0.462
 Schwannoma2.053 (0.951–4.429)0.0671.125 (0.408–3.099)0.820
 Hybrid0.257 (0.077–0.861)0.0280.185 (0.035–0.975)0.047
Motor/mixed nerve1.708 (0.518–5.634)0.379
Tumor location
 Brachial plexus0.479 (0.218–1.053)0.0670.426 (0.162–1.117)0.083
 Arm2.123 (0.781–5.809)0.1401.467 (0.454–4.742)0.522
 Lumbosacral plexus0.181 (0.050–0.663)0.0100.305 (0.070–1.335)0.115
 Leg1.592 (0.749–3.383)0.227
 Other1.469 (0.319–6.765)0.621
Preop biopsy0.511 (0.248–1.053)0.0690.670 (0.277–1.622)0.375
Any postop deficit0.826 (0.390–1.749)0.617
Permanent postop deficit0.714 (0.267–1.910)0.503

In sensitivity analysis using Rosenbaum’s method, the gamma was 2.536 where the transition from significant to insignificant occurred.

Primary Outcome 2: Any Permanent Neurological Complication With and Without IONM

In univariate analysis using the propensity score–matched cohort, IONM was a marginally significant positive predictor of a permanent neurological complication. Tumor size was also included in the multivariate analysis because it met the a priori level of significance for inclusion. In the multivariate analysis, none of the variables were a significant predictor of a permanent neurological complication (Table 3).

TABLE 3.

Univariate and multivariate logistic regression analyses of the propensity score–matched cohort examining the association of the listed variables with a permanent neurological complication

Univariate OR (95% CI)p ValueMultivariate OR (95% CI)p Value
IONM2.354 (1.012–5.475)0.0472.266 (0.970–5.298)0.059
Age1.000 (0.976–1.026)0.955
Male1.305 (0.585–2.910)0.516
Size1.009 (0.995–1.023)0.1961.007 (0.993–1.021)0.304
Syndrome
 NF10.984 (0.272–3.555)0.980
 NF22.143 (0.215–21.329)0.516
 Schwannomatosis0.467 (0.059–3.712)0.472
Pathology
 Neurofibroma0.735 (0.239–2.258)0.591
 Schwannoma1.187 (0.453–3.110)0.727
 Hybrid1.338 (0.278–6.454)0.716
Motor/mixed nerve1.071 (0.230–4.984)0.931
Tumor location
 Brachial plexus0.982 (0.373–2.586)0.970
 Arm1.352 (0.556–3.291)0.506
 Lumbosacral plexus1.692 (0.341–8.410)0.520
 Leg0.602 (0.259–1.402)0.240
 Other1.578 (0.420–5.931)0.499
Preop biopsy1.194 (0.533–2.670)0.667
GTR0.714 (0.267–1.910)0.503

Secondary Outcome 1: GTR With and Without IONM in the Motor/Mixed Nerve Tumor Subgroup

In univariate analysis using the propensity score–matched subgroup of patients with tumors involving a motor or mixed nerve, IONM, tumor size, brachial plexus location, lumbosacral plexus location, and leg location were all significantly predictive of GTR status (Table 4). Preoperative biopsy and hybrid tumor pathology were also included in the multivariate analysis because they met the a priori level of significance for inclusion. In the multivariate analysis, IONM (OR 0.263, 95% CI 0.096–0.723; p = 0.010), size (OR 0.973, 95% CI 0.955–0.991; p = 0.003), brachial plexus location (OR 0.263, 95% CI 0.077–0.896; p = 0.033), and lumbosacral plexus location (OR 0.144, 95% CI 0.032–0.648; p = 0.012) all remained significant negative predictors of GTR.

TABLE 4.

Univariate and multivariate logistic regression analyses of the propensity score–matched subgroup of motor/mixed nerve tumors examining the association of the listed variables with GTR

Univariate OR (95% CI)p ValueMultivariate OR (95% CI)p Value
IONM0.308 (0.130–0.731)0.0080.263 (0.096–0.723)0.010
Age0.998 (0.972–1.024)0.865
Male1.316 (0.605–2.866)0.489
Size0.967 (0.953–0.983)<0.0010.973 (0.955–0.991)0.003
Syndrome
 NF11.455 (0.317–6.678)0.630
 NF20.345 (0.030–3.932)0.392
 Schwannomatosis0.969 (0.204–4.606)0.968
Pathology
 Neurofibroma0.964 (0.365–2.547)0.940
 Schwannoma1.440 (0.610–3.398)0.406
 Hybrid0.329 (0.078–1.340)0.1320.331 (0.050–2.203)0.253
Tumor location
 Brachial plexus0.416 (0.181–0.958)0.0390.263 (0.077–0.896)0.033
 Arm1.855 (0.670–5.133)0.234
 Lumbosacral plexus0.118 (0.039–0.358)<0.0010.144 (0.032–0.648)0.012
 Leg3.391 (1.319–8.717)0.0111.172 (0.295–4.659)0.822
Preop biopsy0.548 (0.250–1.201)0.1330.982 (0.357–2.698)0.971

Secondary Outcome 2: Permanent Motor Deficit With and Without IONM in the Motor/Mixed Nerve Tumor Subgroup

In univariate analysis using the propensity score–matched subgroup of patients with tumors involving a motor or mixed nerve, IONM and tumor size were significant predictors of a permanent postoperative motor deficit (Table 5). Arm location, lumbosacral plexus location, and preoperative biopsy were also included in the multivariate model because they met the a priori level of significance for inclusion. In the multivariate analysis, IONM (positive predictor: OR 3.800, 95% CI 1.925–7.502; p < 0.001), tumor size (positive predictor: OR 1.018, 95% CI 1.003–1.033; p = 0.019), and lumbosacral plexus location (negative predictor: OR 0.156, 95% CI 0.030–0.821; p = 0.028) were all significant predictors of a permanent postoperative motor deficit.

TABLE 5.

Univariate and multivariate logistic regression analyses of the propensity score–matched subgroup of motor/mixed nerve tumors examining the association of the listed variables with a permanent motor deficit

Univariate OR (95% CI)p ValueMultivariate OR (95% CI)p Value
IONM3.549 (1.858–6.782)<0.0013.800 (1.925–7.502)<0.001
Age1.009 (0.989–1.030)0.380
Male0.869 (0.477–1.583)0.647
Size1.013 (1.001–1.025)0.0321.018 (1.003–1.033)0.019
Syndrome
 NF10.909 (0.302–2.737)0.865
 NF21.984 (0.122–32.245)0.630
 Schwannomatosis1.367 (0.372–5.026)0.638
Pathology
 Neurofibroma1.489 (0.712–3.115)0.291
 Schwannoma0.708 (0.356–1.408)0.326
 Hybrid1.008 (0.244–4.169)0.991
Tumor location
 Brachial plexus1.010 (0.489–2.087)0.979
 Arm1.845 (0.942–3.614)0.0741.763 (0.844–3.683)0.131
 Lumbosacral plexus0.288 (0.063–1.316)0.1080.156 (0.030–0.821)0.028
 Leg0.892 (0.485–1.639)0.712
 Other0.394 (0.045–3.442)0.399
Preop biopsy1.574 (0.861–2.876)0.1401.600 (0.809–3.163)0.176
GTR0.595 (0.269–1.318)0.201

Discussion

IONM has been used during resection of BPNSTs, and its use has been stressed by some surgeons.7,8 In fact, Desai stated, “continuous electrophysiological monitoring is absolutely necessary . . . reducing the risk of neurological deficit.”8 However, this statement is not supported, as few, if any, data exist evaluating the role of neuromonitoring in this setting, despite multiple series reporting outcomes associated with resection.3,4,9–13 The goals for this study were to report outcomes associated with resection of BPNSTs, to evaluate the relationship between IONM and GTR, and to evaluate the relationship between neuromonitoring and neurological complications. We hypothesized that IONM would be associated with a reduced likelihood of GTR and a reduced likelihood of neurological complications. We found that IONM was associated with a reduced likelihood of GTR and had no association with permanent neurological complications.

It is important to note that the current study excludes dumbbell tumors and tumors within the spinal canal, so the data should only be extrapolated to tumors distal to the neural foramina. The data set predominantly includes tumors of the brachial plexus and extremities. Desai previously reported a large series (442 tumors) of BPNSTs of the neck and extremities. He reported an incidence of nearly 18% of postoperative neuropathic pain and 6% of new weakness (although the majority had recovered by 1 year).8 These data support that these are not trivial tumors to remove, and risks must be discussed and considered when deciding on management. We believe that our data may help in counseling patients in this regard. It is important to understand both the rate of new or worsened symptoms postoperatively and how likely preoperative symptoms are to improve with resection. Similar to Desai’s study, we found a not insignificant rate of neurological complications. Overall, 12% of patients had a permanent neurological complication (neuropathic pain, bothersome paresthesias, and/or weakness), although an additional 15% had a temporary worsening. Bothersome paresthesias were the most common (9%), followed by pain (4%) and then weakness (3%). On the benefits side, 84% of patients with preoperative pain had improvement post-resection, 69% had improvement in paresthesias, and 67% had improvement in weakness.

The typical goal during surgery for BPNSTs is function-sparing complete resection. GTR was achieved in 85% of patients in this study. We wanted to understand whether IONM affects either one of these aims (GTR or neurological complication) and whether any other identifiable variables affected these outcomes. Due to the nonrandomized design of the study, we were concerned that there may have been significant differences, recognized or unrecognized, in the cohort of patients for whom IONM was used compared with the cohort for whom IONM was not used. We used propensity score matching to try to make the cohorts as similar as possible on recognized covariates to try to mimic a randomized trial as closely as possible. We then used sensitivity analysis to be able to discuss the significance of potential unrecognized confounding. Propensity score matching resulted in a well-matched cohort, as assessed with the standardized mean bias (Fig. 1). With regard to GTR, including all tumors (both motor/mixed and sensory nerve tumors), IONM was a strong negative predictor. Increasing size and hybrid tumor pathology were also negative predictors. Using Rosenbaum’s method for sensitivity analysis, the gamma was 2.536. This means that an unrecognized confounder would have to be nearly perfectly predictive of the use of IONM and would have to be predictive of a GTR with an odds ratio of at least 2.536 before the association between IONM and GTR would be insignificant. This suggests that our finding is moderately insensitive to unrecognized confounding. With regard to permanent neurological complications, we did not identify any variables that were predictive.

In our subgroup analysis of motor/mixed nerve tumors, we found that IONM, increasing size, brachial plexus location, and lumbosacral plexus location were all negative predictors of GTR. We also found that IONM and increasing size were positive predictors of a permanent postoperative motor deficit, while lumbosacral plexus location was a negative predictor.

We hypothesized that IONM would be associated with a reduced likelihood of GTR, which is what we found analyzing all tumors and separately analyzing the motor/mixed nerve tumor subset. However, we hypothesized that IONM would be associated with a reduced likelihood of neurological complications, but we found no association for all tumors and found that IONM was actually associated with an increased, rather than reduced, likelihood of a postoperative motor deficit in the motor/mixed nerve tumors. Identification of the true capsule of the tumor and differentiation from the layers of pseudocapsule are essential for function-sparing complete resection. The plane between the capsule and pseudocapsule is developed to elevate, separate, and protect the uninvolved fascicles of the nerve.14–16 We speculate that IONM may simultaneously reduce the likelihood of GTR while not changing the rate or even increasing the rate of postoperative neurological complications by emboldening surgeons and leading them to abandon these fundamental techniques. Surgeons may use IONM as a crutch, assuming that they will have an early warning if their technique is too aggressive or has gone astray. The monitoring changes may not happen until a nerve injury has already occurred. However, the change may then make the surgeon reluctant to continue forward, also reducing the likelihood of GTR. It is important to emphasize that this is purely a hypothesized mechanism that might explain our findings.

It has been suggested that neurofibromas are more difficult to resect without deficit than schwannomas.17 Anecdotally, many of the authors believe this to be true. However, our data did not bear this out. There was no association with tumor pathology and GTR or with postoperative neurological complications. Size was an important predictor of both GTR and neurological complications. Many have used size thresholds to consider a tumor to be higher risk, such as larger than 3 cm or larger than 5 cm.13 We found that the larger the maximal size of the tumor, the lower the chance of GTR and the higher the likelihood of a neurological complication. The odds ratio for size as a predictor of GTR was 0.975. That means that for every 1-mm increase in size, the odds of a GTR are 0.975. For example, for a tumor with a maximum size of 40 mm versus a tumor with a maximum size of 20 mm, the odds of a GTR would be 0.97520, which is 0.603. This emphasizes the importance in identifying growing tumors and considering earlier resection, when appropriate. An important diagnostic development will occur when we can reliably predict growing and nongrowing tumors.

While these data can be used to support the idea that IONM is not standard of care, we do not believe that the data can be used to make a firm argument against IONM during resection of BPNSTs. Indeed, in most cases a handheld stimulator was used as an adjunct, even though formal IONM was not employed. One important detail of the study is that we examined the occurrence of neurological complications, not the severity. It remains possible that IONM reduces the severity of postoperative neurological complications, even if it does not prevent neurological complications. Overall, we argue that IONM should not be considered a substitute for good operative technique, but still may be appropriate in selected cases. For example, IONM may be particularly useful for tumors in which complete visualization of the tumor and normal nerve on both poles of the tumor is difficult or not possible.

Perez-Roman and colleagues18 recently reported a 23% preoperative biopsy rate in their large series. There was a high rate of biopsy-related complications, and they also found that having a preoperative biopsy significantly increased the risk of a postoperative neurological complication after resection.18 We had a similar distressing rate of preoperative biopsy (28%). Biopsy, except in select cases in which there is a high suspicion for malignancy, is unnecessary and likely harmful. We found a strong trend toward biopsy reducing the likelihood of GTR and increasing the likelihood of a neurological complication, although this did not reach significance. Perez-Roman and colleagues did not analyze tumor size in their study. In our cohort, there was a strong association between the size of the tumor and preoperative biopsy (data not shown). This may explain the lack of strong findings in our study compared with those of Perez-Roman et al. The rate of neurological complications was also higher in their study (28%) compared with that in ours (12%), which may account for why their findings were stronger. Regardless, education is needed to dissuade clinicians from unnecessary preoperative biopsy of nerve sheath tumors that are likely to be benign.

The strengths of this study include the multi-institutional data set which adds to the generalizability of the study. The data set is also relatively large. The study design is a strength. Using propensity score matching led to a well-matched cohort, attempting to reproduce a randomized trial.

Limitations

Despite the strengths, there are multiple limitations that must be considered when interpreting the data. While we attempted to recreate a randomized trial methodology, this is not a randomized trial. There may be unrecognized confounding, although we tried to address this with sensitivity analysis. One potential area of unrecognized confounding is a possible link between tumors perceived to be difficult to resect and the use of IONM. This may not have been captured by adjusting for other variables, such as size or location, but if these tumors were in fact more difficult or risky, this may account for some of our findings. The study is also limited by the fact that different institutions used different metrics to assess pain and paresthesias. To merge these data, pain, paresthesias, and motor deficits were dichotomized into yes/no, rather than having a gauge of severity. We did not have any patient-reported outcome metrics. Without these metrics, it is difficult to assess how impactful any given complication was. For example, many patients would be very happy to get rid of their preoperative nerve pain or worry about cancer in exchange for new paresthesias or mild weakness. We also did not collect data on sensory loss, which may have led us to underreport the rate of postoperative complications. For many nerves, sensory loss may not be important, but for some (e.g., tibial nerve or median nerve), sensory loss can be extremely debilitating. With regard to GTR, we did not rely on postoperative imaging to assess extent of resection but rather relied on the surgeons’ reported extent of resection. There are no data regarding surgeons’ assessment versus radiographic assessment of GTR for benign nerve tumors, so it is unclear how inaccurate surgeons’ reports are likely to be. The median postoperative follow-up was relatively short at 4 months, so it remains possible that some of the deficits may have resolved over time, giving us an overestimate of permanent deficits.

Conclusions

Resection of BPNSTs typically results in good outcomes, with preoperative neuropathic pain most likely to improve, followed by bothersome paresthesias and then weakness. While good outcomes are often achieved, there are significant risks. Overall, 12% had a neurological complication, with new or worsened paresthesias most common, followed by pain and then weakness. We found that formal IONM was associated with a reduced likelihood of GTR and had no association with neurological complications. We believe that these data argue against IONM being considered standard of care but do not believe these data should be used to universally argue against IONM during resection of BPNSTs. Multiple limitations of the study make this argument inappropriate, particularly that we do not have any assessment of severity, which IONM could help reduce. For that reason, formal IONM is appropriate in select cases, and most, if not all, of the authors will continue to use formal IONM selectively. Furthermore, we frequently use handheld nerve stimulators as a technique for informal nerve monitoring and will continue to do so.

Disclosures

Dr. Ray: consultant for DePuy Synthes, Globus, and NuVasive.

Author Contributions

Conception and design: Wilson, Ali, Mahan, Midha, Ray, Yang, Zager, Spinner. Acquisition of data: Wilson, Hamrick, Alzahrani, Dibble, Koduri, Pendleton, Saleh. Analysis and interpretation of data: Wilson, Ali, Mahan, Midha, Ray, Yang, Zager, Spinner. Drafting the article: Wilson, Hamrick. Critically revising the article: all authors. Reviewed submitted version of manuscript: all authors. Approved the final version of the manuscript on behalf of all authors: Wilson. Statistical analysis: Wilson. Study supervision: Wilson.

References

  • 1

    Artico M, Cervoni L, Wierzbicki V, et al. Benign neural sheath tumours of major nerves: characteristics in 119 surgical cases. Acta Neurochir (Wien). 1997;139(12):11081116.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 2

    Levi AD, Ross AL, Cuartas E, et al. The surgical management of symptomatic peripheral nerve sheath tumors. Neurosurgery. 2010;66(4):833840.

  • 3

    Siqueira MG, Socolovsky M, Martins RS, et al. Surgical treatment of typical peripheral schwannomas: the risk of new postoperative deficits. Acta Neurochir (Wien). 2013;155(9):17451749.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 4

    Kim DH, Murovic JA, Tiel RL, et al. A series of 397 peripheral neural sheath tumors: 30-year experience at Louisiana State University Health Sciences Center. J Neurosurg. 2005;102(2):246255.

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

    Daniel JW, Botelho RV, Milano JB, et al. Intraoperative neurophysiological monitoring in spine surgery: a systematic review and meta-analysis. Spine (Phila Pa 1976). 2018;43(16):11541160.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6

    Guha D, Davidson B, Nadi M, et al. Management of peripheral nerve sheath tumors: 17 years of experience at Toronto Western Hospital. J Neurosurg. 2018;128(4):12261234.

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

    Kwok K, Davis B, Kliot M. Resection of a benign brachial plexus nerve sheath tumor using intraoperative electrophysiological monitoring. Neurosurgery. 2007;60(4)(suppl 2):316321.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8

    Desai KI. The surgical management of symptomatic benign peripheral nerve sheath tumors of the neck and extremities: an experience of 442 cases. Neurosurgery. 2017;81(4):568580.

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

    Kim DH, Murovic JA, Tiel RL, Kline DG. Operative outcomes of 546 Louisiana State University Health Sciences Center peripheral nerve tumors. Neurosurg Clin N Am. 2004;15(2):177192.

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

    Siqueira MG, Martins RS, Teixeira MJ. Management of brachial plexus region tumours and tumour-like conditions: relevant diagnostic and surgical features in a consecutive series of eighteen patients. Acta Neurochir (Wien). 2009;151(9):10891098.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 11

    Huang JH, Samadani U, Zager EL. Brachial plexus region tumors: a review of their history, classification, surgical management, and outcomes. Neurosurg Q. 2003;13(3):151161.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12

    Huang JH, Zaghloul K, Zager EL. Surgical management of brachial plexus region tumors. Surg Neurol. 2004;61(4):372378.

  • 13

    Montano N, D’Alessandris QG, D’Ercole M, et al. Tumors of the peripheral nervous system: analysis of prognostic factors in a series with long-term follow-up and review of the literature. J Neurosurg. 2016;125(2):363371.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14

    Stone JJ, Boland JM, Spinner RJ. Analysis of peripheral nerve schwannoma pseudocapsule. World Neurosurg. 2018;119:e986e990.

  • 15

    Stone JJ, Puffer RC, Spinner RJ. Interfascicular resection of benign peripheral nerve sheath tumors. JBJS Essential Surg Tech. 2019;9(2):e18.

  • 16

    Stone JJ, Spinner RJ. Go for the gold: a “plane” and simple technique for resecting benign peripheral nerve sheath tumors. Oper Neurosurg (Hagerstown). 2020;18(1):6068.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 17

    Donner TR, Voorhies RM, Kline DG. Neural sheath tumors of major nerves. J Neurosurg. 1994;81(3):362373.

  • 18

    Perez-Roman RJ, Burks SS, Debs L, et al. The risk of peripheral nerve tumor biopsy in suspected benign etiologies. Neurosurgery. 2020;86(3):E326E332.

Illustration from Kim et al. (pp 1164–1172). Copyright Eui Hyun Kim. Published with permission.

  • View in gallery

    Assessment of standardized mean bias was used as a method of assessing the matching before and after propensity score matching. A: Assessment of standardized mean bias pre- and post-matching for all tumors. B: Assessment of standardized mean bias pre- and post-matching for the tumors involving motor/mixed nerves.

  • View in gallery

    Bar graph showing the percentage of patients with neurological complications after resection of a BPNST. Neurological complications included new or worsened neuropathic pain in the distribution of the involved nerve, new or worsened paresthesias in the distribution of the involved nerve, and new or worsened weakness in the distribution of the involved nerve.

  • 1

    Artico M, Cervoni L, Wierzbicki V, et al. Benign neural sheath tumours of major nerves: characteristics in 119 surgical cases. Acta Neurochir (Wien). 1997;139(12):11081116.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 2

    Levi AD, Ross AL, Cuartas E, et al. The surgical management of symptomatic peripheral nerve sheath tumors. Neurosurgery. 2010;66(4):833840.

  • 3

    Siqueira MG, Socolovsky M, Martins RS, et al. Surgical treatment of typical peripheral schwannomas: the risk of new postoperative deficits. Acta Neurochir (Wien). 2013;155(9):17451749.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 4

    Kim DH, Murovic JA, Tiel RL, et al. A series of 397 peripheral neural sheath tumors: 30-year experience at Louisiana State University Health Sciences Center. J Neurosurg. 2005;102(2):246255.

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

    Daniel JW, Botelho RV, Milano JB, et al. Intraoperative neurophysiological monitoring in spine surgery: a systematic review and meta-analysis. Spine (Phila Pa 1976). 2018;43(16):11541160.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6

    Guha D, Davidson B, Nadi M, et al. Management of peripheral nerve sheath tumors: 17 years of experience at Toronto Western Hospital. J Neurosurg. 2018;128(4):12261234.

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

    Kwok K, Davis B, Kliot M. Resection of a benign brachial plexus nerve sheath tumor using intraoperative electrophysiological monitoring. Neurosurgery. 2007;60(4)(suppl 2):316321.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8

    Desai KI. The surgical management of symptomatic benign peripheral nerve sheath tumors of the neck and extremities: an experience of 442 cases. Neurosurgery. 2017;81(4):568580.

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

    Kim DH, Murovic JA, Tiel RL, Kline DG. Operative outcomes of 546 Louisiana State University Health Sciences Center peripheral nerve tumors. Neurosurg Clin N Am. 2004;15(2):177192.

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

    Siqueira MG, Martins RS, Teixeira MJ. Management of brachial plexus region tumours and tumour-like conditions: relevant diagnostic and surgical features in a consecutive series of eighteen patients. Acta Neurochir (Wien). 2009;151(9):10891098.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 11

    Huang JH, Samadani U, Zager EL. Brachial plexus region tumors: a review of their history, classification, surgical management, and outcomes. Neurosurg Q. 2003;13(3):151161.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12

    Huang JH, Zaghloul K, Zager EL. Surgical management of brachial plexus region tumors. Surg Neurol. 2004;61(4):372378.

  • 13

    Montano N, D’Alessandris QG, D’Ercole M, et al. Tumors of the peripheral nervous system: analysis of prognostic factors in a series with long-term follow-up and review of the literature. J Neurosurg. 2016;125(2):363371.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14

    Stone JJ, Boland JM, Spinner RJ. Analysis of peripheral nerve schwannoma pseudocapsule. World Neurosurg. 2018;119:e986e990.

  • 15

    Stone JJ, Puffer RC, Spinner RJ. Interfascicular resection of benign peripheral nerve sheath tumors. JBJS Essential Surg Tech. 2019;9(2):e18.

  • 16

    Stone JJ, Spinner RJ. Go for the gold: a “plane” and simple technique for resecting benign peripheral nerve sheath tumors. Oper Neurosurg (Hagerstown). 2020;18(1):6068.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 17

    Donner TR, Voorhies RM, Kline DG. Neural sheath tumors of major nerves. J Neurosurg. 1994;81(3):362373.

  • 18

    Perez-Roman RJ, Burks SS, Debs L, et al. The risk of peripheral nerve tumor biopsy in suspected benign etiologies. Neurosurgery. 2020;86(3):E326E332.

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