Pendleton, Courtney

Abstract Background Malignant peripheral nerve sheath tumors (MPNSTs) are rare, aggressive sarcomas, with 40% associated with neurofibromatosis type 1 (NF1). Surgical excision is the main treatment for localized disease; however, local recurrence (LR) remains high. Radiotherapy (RTx) is increasingly used to enhance local control in STS, but its use remains controversial due to the potential for increased major wound complications and an increased risk of secondary malignancies in NF1 patients. This study investigated the use and impact of RTx on local control in MPNSTs, particularly in the NF1 setting. Methods Surgically treated primary MPNSTs from 1988 to 2019 in the MONACO multicenter cohort were included. Differences in demographics, treatment, and RTx use between NF1 and non-NF1 cases were examined. Factors influencing RTx administration and LR were assessed via multivariable analyses. Results Among 499 patients (33.1% NF1), 143 (28.7%) experienced LRs. Radiotherapy was administered to 56.3% of patients (57.0% in the NF1 group), with 27.3% receiving neoadjuvant and 72.7% adjuvant RTx. RTx was administered significantly more often to high-grade and extremity tumors. While RTx did not affect overall survival, it reduced LR risk in sporadic cases (hazard ratio [HR] 0.530; 95% confidence interval [CI], 0.354–0.793) but not in the NF1 subgroup (HR 1.00; 95% CI, 0.545–1.85). In NF1 patients, a microscopically positive margin (R1) was the only risk factor for LR development (HR 2.1; 95% CI, 1.19–3.79). Conclusions RTx is frequently used in the treatment of MPNSTs, regardless of NF1 status. While it may affect the LR rate in sporadic cases, its impact on NF1 patients is less clear.

Abstract Background This study aimed to assess the performance of currently available risk calculators in a cohort of patients with malignant peripheral nerve sheath tumors (MPNST) and to create an MPNST-specific prognostic model including type-specific predictors for overall survival (OS). Methods This is a retrospective multicenter cohort study of patients with MPNST from 11 secondary or tertiary centers in The Netherlands, Italy and the United States of America. All patients diagnosed with primary MPNST who underwent macroscopically complete surgical resection from 2000 to 2019 were included in this study. A multivariable Cox proportional hazard model for OS was estimated with prespecified predictors (age, grade, size, NF-1 status, triton status, depth, tumor location, and surgical margin). Model performance was assessed for the Sarculator and PERSARC calculators by examining discrimination (C-index) and calibration (calibration plots and observed-expected statistic; O/E-statistic). Internal–external cross-validation by different regions was performed to evaluate the generalizability of the model. Results A total of 507 patients with primary MPNSTs were included from 11 centers in 7 regions. During follow-up (median 8.7 years), 211 patients died. The C-index was 0.60 (95% CI 0.53–0.67) for both Sarculator and PERSARC. The MPNST-specific model had a pooled C-index of 0.69 (95%CI 0.65–0.73) at validation, with adequate discrimination and calibration across regions. Conclusions The MPNST-specific MONACO model can be used to predict 3-, 5-, and 10-year OS in patients with primary MPNST who underwent macroscopically complete surgical resection. Further validation may refine the model to inform patients and physicians on prognosis and support them in shared decision-making.

BACKGROUND: Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive soft tissue sarcomas. Their resection may lead to serious morbidity. Incidence of postoperative motor and sensory deficits is unknown, and reconstruction aimed at restoring such deficits is infrequently carried out. OBJECTIVE: To identify the incidence and risk factors of postoperative morbidity in MPNST as well as the use and outcomes of functional reconstructions in these patients. METHODS: Postoperative function and treatment of MPNSTs diagnosed from 1988 to 2019 in 10 cancer centers was obtained. Two models were constructed evaluating factors independently associated with postoperative motor (<M3) or critical sensory loss. Critical sensation was defined as partial or complete loss of hand, foot, or buttocks sensation. RESULTS: A total of 756 patients (33.4% neurofibromatosis type 1, NF1) were included. MPNSTs originated in 34.4% from a major nerve. Of 658 surgically treated patients, 27.2% had <M3 muscle power and 24.3% critical sensory loss. Amputations were carried out in 61 patients. Independent risk factors for motor and sensory loss included patients with NF1, symptomatic, deep-seated, extremity, or plexus tumors originating from major nerves (all P < .05). A total of 26 patients underwent functional reconstructions. The majority (64%) of these patients regained at least M3 muscle power and 33% M4 despite 86% receiving multimodal therapy. CONCLUSION: Resection of MPNSTs commonly results in motor and sensory deficits. Patients with NF1, symptomatic, deep-seated tumors, arising from major nerves were associated with a higher risk for developing postoperative morbidity. Functional reconstructions are infrequently performed but can improve functional outcomes.

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.

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.

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.

AbstractBackgroundMultiple mononeuropathy is a rare presentation of primary (AL) amyloidosis and nerve biopsy is usually needed for diagnosis. Conventional imaging is useful to identify proximal nerve involvement but may be inadequate. We report a patient with multiple mononeuropathy whose presentation was suggestive of AL amyloid neuropathy and in whom repeated tissue biopsies were negative for amyloid (including two sensory nerves and one muscle).MethodsThe patient underwent magnetic resonance imaging (MRI) and whole body 18F‐florbetapir positron emission tomography (PET)/MRI.ResultsWhole body 18F‐florbetapir PET/MRI revealed abnormal low‐level florbetapir uptake in the right proximal tibial and peroneal nerves, which provided a target for a sciatic bifurcation fascicular nerve biopsy that was diagnostic of AL amyloidosis.Conclusions 18F‐florbetapir PET/MRI imaging is a promising diagnostic tool for patients with suspected peripheral nerve amyloidosis (including multiple mononeuropathy) in whom conventional imaging and nerve and muscle biopsies miss the pathology.

Harvey Cushing is widely regarded as one of the forefathers of neurosurgery, and is primarily associated with his work on intracranial pathology. However, he had a clinical and academic interest in peripheral nerve surgery. Through the courtesy of the Alan Mason Chesney Medical Archives, the surgical records of the Johns Hopkins Hospital from 1896 to 1912 were reviewed. The records of a single patient undergoing brachial plexus exploration and cervical rib resection were selected for detailed review. The operative report and accompanying illustrations demonstrate Cushing’s interest in adding approaches to the pathology of the brachial plexus to his operative armamentarium.