Smith, Brandon W.

OBJECTIVE Common peroneal (fibular) neuropathy is the most common mononeuropathy of the lower extremity. Despite this, there are surprisingly few studies on the topic, and a knowledge gap remains in the literature. As one attempts to address this knowledge gap, a core outcome set (COS) is needed to guide the planning phases of future studies to allow synthesis and comparability of these studies. The objective of this study was to develop the COS–common peroneal neuropathy (CoPe) using a modified Delphi approach. METHODS A 5-stage approach was used to develop the COS-CoPe: 1) stage 1, consortium development; 2) stage 2, a literature review to identify potential outcome measures; 3) stage 3, a Delphi survey to develop consensus on outcomes for inclusion; 4) stage 4, a Delphi survey to develop definitions; and 5) stage 5, a consensus meeting to finalize COS and definitions. The study followed the COS–STAndards for Development (COS-STAD) recommendations. RESULTS The Core Outcomes in Nerve Surgery (COINS) Consortium comprised 23 participants, all neurological surgeons, representing 13 countries. The final COS-CoPe consisted of 31 data points/outcomes covering domains of demographics, diagnostics, patient-reported outcomes, motor/sensory outcomes, and complications. Appropriate instruments, methods of testing, and definitions were set. The consensus minimum duration of follow-up was 12 months. The consensus optimal time points for assessment were preoperatively and 3, 6, 12, and 24 months postoperatively. CONCLUSIONS The COINS Consortium developed a consensus COS and provided definitions, methods of implementation, and time points for assessment. The COS-CoPe should serve as a minimum set of data that should be collected in all future neurosurgical studies on common peroneal neuropathy. Incorporation of this COS should help improve consistency in reporting, data synthesis, and comparability, and should minimize outcome reporting bias.

OBJECTIVE When considering traumatic brachial plexus and upper extremity nerve injuries, iatrogenic nerve injuries, and nontraumatic nerve injuries, brachial plexus and upper extremity nerve injuries are commonly encountered in clinical practice. Despite this, data synthesis and comparison of available studies are difficult. This is at least in part due to the lack of standardization in reporting and a lack of a core outcome set (COS). Thus, there is a need for a COS for adult brachial plexus and upper extremity nerve injuries (COS-BPUE). The objective of this study was to develop a COS-BPUE using a modified Delphi approach. METHODS A 5-stage approach was used to develop the COS-BPUE: 1) consortium development, 2) literature review to identify potential outcome measures, 3) Delphi survey to develop consensus on outcomes for inclusion, 4) Delphi survey to develop definitions, and 5) consensus meeting to finalize the COS and definitions. The study followed the Core Outcome Set-STAndards for Development (COS-STAD) recommendations. RESULTS The Core Outcomes in Nerve Surgery (COINS) Consortium comprised 23 participants, all neurological surgeons, representing 13 countries. The final COS-BPUE consisted of 36 data points/outcomes covering demographic, diagnostic, patient-reported outcome, motor/sensory outcome, and complication domains. Appropriate instruments, methods of testing, and definitions were set. The consensus minimum duration of follow-up was 24 months, with the consensus optimal time points for assessment being preoperatively and 3, 6, 12, and 24 months postoperatively. CONCLUSIONS The COINS Consortium developed a consensus COS and provided definitions, methods of implementation, and time points for assessment. The COS-BPUE should serve as a minimum set of data that should be collected in all future neurosurgical studies on adult brachial plexus and upper extremity nerve injuries. Incorporation of this COS should help improve consistency in reporting, data synthesis, and comparability, and should minimize outcome reporting bias.

OBJECTIVE Ulnar neuropathy at the elbow (UNE) is common, affecting 1%–6% of the population. Despite this, there remains a lack of consensus regarding optimal treatment. This is primarily due to the difficulty one encounters when trying to assess the literature. Outcomes are inconsistently reported, which makes comparing studies or developing meta-analyses difficult or even impossible. Thus, there is a need for a core outcome set (COS) for UNE (COS-UNE) to help address this problem. The objective of this study was to utilize a modified Delphi method to develop COS-UNE. METHODS A 5-stage approach was utilized to develop COS-UNE: stage 1, consortium development; 2, literature review to identify potential outcome measures; 3, Delphi survey to develop consensus on outcomes for inclusion; 4, Delphi survey to develop definitions; and 5, consensus meeting to finalize the COS and definitions. The study followed the Core Outcome Set-STAndards for Development (COS-STAD) recommendations. RESULTS The Core Outcomes in Nerve Surgery (COINS) Consortium comprised 21 participants, all neurological surgeons representing 11 countries. The final COS-UNE consisted of 22 data points/outcomes covering the domains of demographic characteristics, diagnostics, patient-reported outcomes, motor/sensory outcomes, and complications. Appropriate instruments, methods of testing, and definitions were set. The consensus minimum duration of follow-up was 6 months, with the consensus optimal timepoints for assessment identified as preoperatively and 3, 6, and 12 months postoperatively. CONCLUSIONS The authors identified consensus data points/outcomes and also provided definitions and specific scales to be utilized to help ensure that clinicians are consistent in their reporting across studies on UNE. This COS should serve as a minimum set of data to be collected in all future neurosurgical studies on UNE. The authors hope that clinicians evaluating ulnar neuropathy will incorporate this COS into routine practice and that future studies will consider this COS in the design phase.

Abstract Background Non-invasive differentiation between schwannomas and neurofibromas is important for appropriate management, preoperative counseling, and surgical planning, but has proven difficult using conventional imaging. The objective of this study was to develop and evaluate machine learning approaches for differentiating peripheral schwannomas from neurofibromas. Methods We assembled a cohort of schwannomas and neurofibromas from 3 independent institutions and extracted high-dimensional radiomic features from gadolinium-enhanced, T1-weighted MRI using the PyRadiomics package on Quantitative Imaging Feature Pipeline. Age, sex, neurogenetic syndrome, spontaneous pain, and motor deficit were recorded. We evaluated the performance of 6 radiomics-based classifier models with and without clinical features and compared model performance against human expert evaluators. Results One hundred and seven schwannomas and 59 neurofibromas were included. The primary models included both clinical and imaging data. The accuracy of the human evaluators (0.765) did not significantly exceed the no-information rate (NIR), whereas the Support Vector Machine (0.929), Logistic Regression (0.929), and Random Forest (0.905) classifiers exceeded the NIR. Using the method of DeLong, the AUCs for the Logistic Regression (AUC = 0.923) and K Nearest Neighbor (AUC = 0.923) classifiers were significantly greater than the human evaluators (AUC = 0.766; p = 0.041). Conclusions The radiomics-based classifiers developed here proved to be more accurate and had a higher AUC on the ROC curve than expert human evaluators. This demonstrates that radiomics using routine MRI sequences and clinical features can aid in differentiation of peripheral schwannomas and neurofibromas.

OBJECTIVE The objective of this study was to understand the natural history of scoliosis in patients with Chiari malformation type I (CM-I) with and without syringomyelia. METHODS A retrospective review of data was conducted. Patients with CM-I were identified from a cohort of 14,118 individuals age 18 years or younger who had undergone MRI over an 11-year period at the University of Michigan. Patients eligible for study inclusion had a coronal curve ≥ 10° on radiography, associated CM-I with or without syringomyelia, and at least 1 year of clinical follow-up prior to any surgery. Curve magnitude at initial diagnosis, prior to posterior fossa decompression (PFD; if applicable), and at the last follow-up (prior to any surgical correction of scoliosis) was recorded, and clinical and radiographic characteristics were noted. The change in curve magnitude by 10° was defined as curve progression (increase by 10°) or regression (decrease by 10°). RESULTS Forty-three patients met the study inclusion criteria and were analyzed. About one-third (35%) of the patients presented with symptoms attributed to their CM-I. The mean degree of scoliosis at presentation was 32.6° ± 17.7°. Twenty-one patients (49%) had an associated syrinx. The mean tonsil position below the level of the foramen magnum was 9.8 ± 5.8 mm. Patients with a syrinx were more likely to have a curve > 20° (86% vs 41%, p = 0.002). Curve magnitude remained stable (≤ ±10°) in 77% of patients (33/43), progressed in 16% (7/43), and regressed in 7% (3/43). Mean age was higher (14.8 ± 0.59 years) among patients with regressed curves (p = 0.026). All regressed curves initially measured ≤ 20° (mean 14° ± 5.3°), and none of the patients with regressed curves had a syrinx. The change in curve magnitude was statistically similar in patients with (7.32° ± 17.7°) and without (5.32° ± 15.8°) a syrinx (p = 0.67). After a mean follow-up of 3.13 ± 2.04 years prior to surgery, 27 patients (63%) ultimately underwent posterior fossa or scoliosis correction surgery. For those who eventually underwent PFD only, the rate of change in curve magnitude prior to surgery was 0.054° ± 0.79°. The rate of change in curve magnitude was statistically similar before (0.054° ± 0.79°) and after (0.042° ± 0.33°) surgery (p = 0.45) for patients who underwent PFD surgery only. CONCLUSIONS The natural history of scoliosis in the presence of CM-I is variable, though most curves remained stable. All curves that regressed were ≤ 20° at initial diagnosis, and most patients in such cases were older at scoliosis diagnosis. Patients who underwent no surgery or PFD only had similar profiles for the change in curve magnitude, which remained relatively stable overall, as compared to patients who underwent PFD and subsequent fusion, who demonstrated curve progression. Among the patients with a syrinx, no curves regressed, most remained stable, and some progressed. Understanding this variability is a first step toward building a prediction model for outcomes for these patients.

OBJECTIVE The objective of this study was to determine if patients with nerve sheath tumors affecting the C5 spinal nerve are at greater risk for postoperative weakness than those with similar tumors affecting other spinal nerves contributing to the brachial plexus. METHODS A retrospective chart review (1998–2020)identified patients with pathologically confirmed schwannomas or neurofibromas from the C5 to T1 nerves. Patients with plexiform nerve sheath tumors, tumors involving more than 1 nerve, and malignant peripheral nerve sheath tumors were excluded. Collected variables included basic demographics, tumor dimensions, its location relative to the dura, involved nerve level, surgical approach, extent of resection, presenting symptoms, postoperative neurological deficits, and recurrence rate. RESULTS Forty-six patients (23 men, 23 women) were identified for inclusion in the study with an average age of 47 ± 17 years, BMI of 28 ± 5 kg/m2, and follow-up of 32 ± 45 months. Thirty-nine patients (85%) had schwannomas and 7 (15%) had neurofibromas. Tumors involved the C5 (n = 12), C6 (n = 11), C7 (n = 14), C8 (n = 6), and T1 (n = 3) nerves. Multivariable logistic regression analysis with an area under the curve of 0.85 demonstrated C5 tumor level as an independent predictor of new postoperative weakness (odds ratio 7.4, p = 0.028). Of those patients with new postoperative weakness, 75% improved and 50% experienced complete resolution of their motor deficits. CONCLUSIONS Patients with C5 nerve sheath tumor resections are at higher odds of new postoperative weakness. This may be due to the predominant single innervation of shoulder muscle targets in contrast to other upper extremity muscles that receive input from 2 or more spinal nerves. These findings are important for clinical decision-making and preoperative patient counseling.

BACKGROUND The advancement of high-resolution imaging and increased clinical experience have led to an increased understanding of the formation and treatment of intraneural ganglion cysts. Nearly all intraneural ganglion cysts in the common peroneal nerve have been reported to arise from a joint connection to the superior tibiofibular joint. The authors have identified four cases of intraneural ganglion cysts arising from the knee joint itself; however, none of these reported cases were well described, documented, or illustrated with high-resolution imaging. OBSERVATIONS Here the authors present the case of an intraneural ganglion cyst arising from the knee joint and causing intermittent weakness and pain. The articular branch to the knee joint was clearly demonstrated on high-resolution magnetic resonance imaging and confirmed at surgical exploration. The patient was treated with articular branch ligation and has had complete resolution of his symptoms without recurrence of the cyst on follow-up imaging. LESSONS This case adds to the mounting evidence that intraneural cyst pathology is dependent on a connection to a synovial joint as stated in the unifying theory of intraneural cyst development.

Abstract BACKGROUND Clinicoradiologic differentiation between benign and malignant peripheral nerve sheath tumors (PNSTs) has important management implications. OBJECTIVE To develop and evaluate machine-learning approaches to differentiate benign from malignant PNSTs. METHODS We identified PNSTs treated at 3 institutions and extracted high-dimensional radiomics features from gadolinium-enhanced, T1-weighted magnetic resonance imaging (MRI) sequences. Training and test sets were selected randomly in a 70:30 ratio. A total of 900 image features were automatically extracted using the PyRadiomics package from Quantitative Imaging Feature Pipeline. Clinical data including age, sex, neurogenetic syndrome presence, spontaneous pain, and motor deficit were also incorporated. Features were selected using sparse regression analysis and retained features were further refined by gradient boost modeling to optimize the area under the curve (AUC) for diagnosis. We evaluated the performance of radiomics-based classifiers with and without clinical features and compared performance against human readers. RESULTS A total of 95 malignant and 171 benign PNSTs were included. The final classifier model included 21 imaging and clinical features. Sensitivity, specificity, and AUC of 0.676, 0.882, and 0.845, respectively, were achieved on the test set. Using imaging and clinical features, human experts collectively achieved sensitivity, specificity, and AUC of 0.786, 0.431, and 0.624, respectively. The AUC of the classifier was statistically better than expert humans ( P = .002). Expert humans were not statistically better than the no-information rate, whereas the classifier was ( P = .001). CONCLUSION Radiomics-based machine learning using routine MRI sequences and clinical features can aid in evaluation of PNSTs. Further improvement may be achieved by incorporating additional imaging sequences and clinical variables into future models.