Neurocognition in adults with intracranial tumors:Does location really matter?

OBJECTIVE: As preservation of cognitive functioning increasingly becomes important in the light of ameliorated survival after intracranial tumor treatments, identification of eloquent brain areas would enable optimization of these treatments. METHODS: This cohort study enrolled adult intracranial tumor patients who received neuropsychological assessments pre-irradiation, estimating processing speed, verbal fluency and memory. Anatomical magnetic resonance imaging scans were used for multivariate voxel-wise lesion-symptom predictions of the test scores (corrected for age, gender, educational level, histological subtype, surgery, and tumor volume). Potential effects of histological and molecular subtype and corresponding WHO grades on the risk of cognitive impairment were investigated using Chi square tests. P-values were adjusted for multiple comparisons (p < .001 and p < .05 for voxel- and cluster-level, resp.). RESULTS: A cohort of 179 intracranial tumor patients was included [aged 19-85 years, median age (SD) = 58.46 (14.62), 50% females]. In this cohort, test-specific impairment was detected in 20-30% of patients. Higher WHO grade was associated with lower processing speed, cognitive flexibility and delayed memory in gliomas, while no acute surgery-effects were found. No grading, nor surgery effects were found in meningiomas. The voxel-wise analyses showed that tumor locations in left temporal areas and right temporo-parietal areas were related to verbal memory and processing speed, respectively. INTERPRETATION: Patients with intracranial tumors affecting the left temporal areas and right temporo-parietal areas might specifically be vulnerable for lower verbal memory and processing speed. These specific patients at-risk might benefit from early-stage interventions. Furthermore, based on future validation studies, imaging-informed surgical and radiotherapy planning could further be improved

Survival after resection of malignant peripheral nerve sheath tumors:Introducing and validating a novel type-specific prognostic model

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.</p

Survival after resection of malignant peripheral nerve sheath tumors: Introducing and validating a novel type-specific prognostic model

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

Thyroid Gland F-18-FDG Uptake in Neurofibromatosis Type 1

Purpose: To investigate thyroid gland characteristics on (18)FFDG positron emission tomography/computed tomography (PET/CT) imaging in patients with neurofibromatosis type 1 (NF1). Subjects and Methods: Thyroid gland characteristics of patients with a clinical diagnosis of NF1 who underwent F-18-FDG PET/CT imaging for the first time to distinguish benign neurofibroma from malignant peripheral nerve sheath tumor (MPNST) at our institution (n = 69) were compared to PET/CT imaging of sarcoidosis (n = 25) and early stage lung cancer (T1N0M0 tumors, n = 15) patients. Results: Two NF1 patients (3%) showed a diffuse F-18-FDG uptake in the thyroid gland, 2 patients (3%) had an irregular uptake, and 7 patients (10%) had a focal uptake. Among the sarcoidosis patients, 1 showed a diffuse uptake (4%) and 1 had an irregular uptake (4%). In the early stage lung cancer group, 1 patient showed a diffuse uptake (7%) and 1 had a focal uptake (7%). NF1 patients had larger mean thyroid volume and mean SUVmax compared to sarcoidosis patients but not compared to early stage lung cancer patients. Four NF1 patients were diagnosed with multinodular goiter, 2 patients were diagnosed with benign chronic lymphocytic thyroiditis, 1 patient had metastasis to the thyroid, and 1 patient had medullary thyroid cancer. Conclusion: Even though NF1 patients did not show an increased risk of thyroid incidentaloma on PET/CT compared to previous studies on non-thyroid cancer patients, the incidence shows that awareness of possible thyroid disease is important. (C) 2018 European Thyroid Association Published by S. Karger AG, Base

Temporal muscle thickness as an independent prognostic imaging marker in newly diagnosed glioblastoma patients: A validation study

Background: Previous studies have recognized temporal muscle thickness (TMT) as a prognostic marker in glioblastoma, but clinical implementation is hampered due to studies' heterogeneity and lack of established cutoff values. The aim of this study was to assess the validity of recent proposed sex-specific TMT cutoff values in a real-world population of genotyped primary glioblastoma patients. Methods: We measured TMT in preoperative MR images of 328 patients. Sex-specific TMT cutoff values were used to divide patients into "at risk of sarcopenia" or "normal muscle status". Kaplan-Meier analyses and stepwise multivariate Cox-Regression analyses were used to assess the association with overall survival (OS) and progression-free survival (PFS). The association with occurrence of complications and discontinuation of glioblastoma treatment was investigated using odds ratios (OR). Results: Patients at risk of sarcopenia had a significantly higher risk of progression and death than patients with normal muscle status, which remained significant in the multivariate analyses (OS HR = 1.437; 95%CI: 1.046-1.973; P = .025 and PFS HR = 1.453; 95%CI: 1.037-2.036; P = .030). Patients at risk of sarcopenia also had a significantly higher risk of early discontinuation of treatment (OR = 2.45; 95%CI: 1.011-5.952; P = .042) and a significantly lower chance of receiving second-line treatment (OR = 0.23; 95%CI: 0.09-0.60; P = .001). There was no association with the occurrence of complications. Conclusions: Our study confirms external validity of the use of proposed sex-specific TMT cutoff values as an independent prognostic marker in newly diagnosed glioblastoma patients. This simple, noninvasive marker could improve patient counseling and aid in treatment decision processes or trial stratification

Temporal muscle thickness as an independent prognostic imaging marker in newly diagnosed glioblastoma patients:A validation study

Background: Previous studies have recognized temporal muscle thickness (TMT) as a prognostic marker in glioblastoma, but clinical implementation is hampered due to studies' heterogeneity and lack of established cutoff values. The aim of this study was to assess the validity of recent proposed sex-specific TMT cutoff values in a real-world population of genotyped primary glioblastoma patients. Methods: We measured TMT in preoperative MR images of 328 patients. Sex-specific TMT cutoff values were used to divide patients into "at risk of sarcopenia" or "normal muscle status". Kaplan-Meier analyses and stepwise multivariate Cox-Regression analyses were used to assess the association with overall survival (OS) and progression-free survival (PFS). The association with occurrence of complications and discontinuation of glioblastoma treatment was investigated using odds ratios (OR). Results: Patients at risk of sarcopenia had a significantly higher risk of progression and death than patients with normal muscle status, which remained significant in the multivariate analyses (OS HR = 1.437; 95%CI: 1.046-1.973; P = .025 and PFS HR = 1.453; 95%CI: 1.037-2.036; P = .030). Patients at risk of sarcopenia also had a significantly higher risk of early discontinuation of treatment (OR = 2.45; 95%CI: 1.011-5.952; P = .042) and a significantly lower chance of receiving second-line treatment (OR = 0.23; 95%CI: 0.09-0.60; P = .001). There was no association with the occurrence of complications. Conclusions: Our study confirms external validity of the use of proposed sex-specific TMT cutoff values as an independent prognostic marker in newly diagnosed glioblastoma patients. This simple, noninvasive marker could improve patient counseling and aid in treatment decision processes or trial stratification

Correlation of reduced temporal muscle thickness and systemic muscle loss in newly diagnosed glioblastoma patients

PURPOSE: Reduced temporal muscle thickness (TMT) has recently been postulated as a prognostic imaging marker and an objective tool to assess patients frailty in glioblastoma. Our aim is to investigate the correlation of TMT and systemic muscle loss to confirm that TMT is an adequate surrogate marker of sarcopenia in newly diagnosed glioblastoma patients. METHODS: TMT was assessed on preoperative MR-images and skeletal muscle area (SMA) was assessed at the third lumbar vertebra on preoperative abdominal CT-scans. Previous published TMT sex-specific cut-off values were used to classify patients as 'patient at risk of sarcopenia' or 'patient with normal muscle status'. Correlation between TMT and SMA was assessed using Spearman's rank correlation coefficient. RESULTS: Sixteen percent of the 245 included patients were identified as at risk of sarcopenia. The mean SMA of glioblastoma patients at risk of sarcopenia (124.3 cm2, SD 30.8 cm2) was significantly lower than the mean SMA of patients with normal muscle status (146.3 cm2, SD 31.1 cm2, P < .001). We found a moderate association between TMT and SMA in the patients with normal muscle status (Spearman's rho 0.521, P < .001), and a strong association in the patients at risk of sarcopenia (Spearman's rho 0.678, P < .001). CONCLUSION: Our results confirm the use of TMT as a surrogate marker of total body skeletal muscle mass in glioblastoma, especially in frail patients at risk of sarcopenia. TMT can be used to identify patients with muscle loss early in the disease process, which enables the implementation of adequate intervention strategies

Prognostic and Predictive Value of Integrated Qualitative and Quantitative Magnetic Resonance Imaging Analysis in Glioblastoma

Glioblastoma (GBM) is the most malignant primary brain tumor for which no curative treatment options exist. Non-invasive qualitative (Visually Accessible Rembrandt Images (VASARI)) and quantitative (radiomics) imaging features to predict prognosis and clinically relevant markers for GBM patients are needed to guide clinicians. A retrospective analysis of GBM patients in two neuro-oncology centers was conducted. The multimodal Cox-regression model to predict overall survival (OS) was developed using clinical features with VASARI and radiomics features in isocitrate dehydrogenase (IDH)-wild type GBM. Predictive models for IDH-mutation, 06-methylguanine-DNA-methyltransferase (MGMT)-methylation and epidermal growth factor receptor (EGFR) amplification using imaging features were developed using machine learning. The performance of the prognostic model improved upon addition of clinical, VASARI and radiomics features, for which the combined model performed best. This could be reproduced after external validation (C-index 0.711 95% CI 0.64–0.78) and used to stratify Kaplan–Meijer curves in two survival groups (p-value EGFR amplification (area-under-the-curve (AUC) 0.707, 95% CI 0.582–8.25) and MGMT-methylation (AUC 0.667, 95% CI 0.522–0.82) but not for IDH-mutation (AUC 0.695, 95% CI 0.436–0.927). The integrated clinical and imaging prognostic model was shown to be robust and of potential clinical relevance. The prediction of molecular markers showed promising results in the training set but could not be validated after external validation in a clinically relevant manner. Overall, these results show the potential of combining clinical features with imaging features for prognostic and predictive models in GBM, but further optimization and larger prospective studies are warranted