Faculty Bibliography

OBJECTIVES:The postoperative management of patients who undergo brain tumor resection frequently occurs in an ICU. However, the routine admission of all patients to an ICU following surgery is controversial. This study seeks to identify the frequency with which patients undergoing elective supratentorial tumor resection require care, aside from frequent neurologic checks, that is specific to an ICU and to determine the frequency of new complications during ICU admission. Additionally, clinical predictors of ICU-specific care are identified, and a scoring system to discriminate patients most likely to require ICU-specific treatment is validated. DESIGN:Retrospective observational cohort study. SETTING:Academic neurosurgical center. PATIENTS:Two-hundred consecutive adult patients who underwent supratentorial brain tumor surgery. An additional 100 consecutive patients were used to validate the prediction score. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:Univariate statistics and multivariable logistic regression were used to identify clinical characteristics associated with ICU-specific treatment. Eighteen patients (9%) received ICU-specific care, and 19 (9.5%) experienced new complications or underwent emergent imaging while in the ICU. Factors significantly associated with ICU-specific care included nonelective admission, preoperative Glasgow Coma Scale, and volume of IV fluids. A simple clinical scoring system that included Karnofsky Performance Status less than 70 (1 point), general endotracheal anesthesia (1 point), and any early postoperative complications (2 points) demonstrated excellent ability to discriminate patients who required ICU-specific care in both the derivation and validation cohorts. CONCLUSIONS:Less than 10% of patients required ICU-specific care following supratentorial tumor resection. A simple clinical scoring system may aid clinicians in stratifying the risk of requiring ICU care and could inform triage decisions when ICU bed availability is limited.

IDH mutation is of central importance in the diagnosis and treatment of gliomas. Fourier-transform infrared spectroscopy, in combination with a supervised machine-learning approach, can be used to detect metabolic alterations induced by IDH1 mutations in a fraction of the time of conventional techniques. Clin Cancer Res; 24(11); 2467-9. ©2018 AACRSee related article by Uckermann et al., p. 2530.

We hypothesized elderly patients with good Karnofsky Performance Status (KPS) treated with standard dose or dose-escalated radiation therapy (SDRT/DERT) and concurrent temozolomide (TMZ) would have favorable overall survival (OS) compared to historical elderly patients treated with hypofractionated RT (HFRT). From 2004 to 2015, 66 patients age ≥ 60 with newly diagnosed, pathologically proven glioblastoma were treated with SDRT/DERT over 30 fractions with concurrent/adjuvant TMZ at a single institution. Kaplan-Meier methods and the log-rank test were used to assess OS and progression-free survival (PFS). Multivariate analysis (MVA) was performed using Cox Proportional-Hazards. Median follow-up was 12.6 months. Doses ranged from 60 to 81 Gy (median 66). Median KPS was 90 (range 60-100) and median age was 67 years (range 60-81), with 29 patients ≥ 70 years old. 32% underwent gross total resection (GTR). MGMT status was known in 28%, 42% of whom were methylated. Median PFS was 8.3 months (95% CI 6.9-11.0) and OS was 12.7 months (95% CI 9.7-14.1). Patients age ≥ 70 with KPS ≥ 90 had a median OS of 12.4 months. Median OS was 27.1 months for MGMT methylated patients. On MVA controlling for age, dose, KPS, MGMT, GTR, and adjuvant TMZ, younger age (HR 0.9, 95% CI 0.8-0.9, p < 0.01), MGMT methylation (HR:0.2, 95% CI 0.1-0.7, p = 0.01), and GTR (HR:0.5, 95% CI 0.3-0.9, p = 0.01) were associated with improved OS. Our findings do not support routine use of a standard 6-week course of radiation therapy in elderly patients with glioblastoma. However, a select group of elderly patients with excellent performance status and MGMT methylation or GTR may experience favorable survival with a standard 6-week course of treatment.

Primary melanocytic disease of the central nervous system is a rarely encountered condition currently without consensus on treatment and lacking major guidelines for management. Understanding the nature of the disease and differentiating primary melanocytic disease from the much more commonly encountered secondary (metastatic) melanoma is important in identifying the condition and pursuing appropriate treatment.

Accurate histopathologic diagnosis is essential for providing optimal surgical management of pediatric brain tumors. Current methods for intraoperative histology are time- and labor-intensive and often introduce artifacts that limit interpretation. Stimulated Raman histology (SRH) is a novel label-free imaging technique that provides intraoperative histologic images of fresh, unprocessed surgical specimens. Here we evaluate the capacity of SRH for use in the intraoperative diagnosis of pediatric type brain tumors. SRH revealed key diagnostic features in fresh tissue specimens collected from 33 prospectively enrolled pediatric type brain tumor patients, preserving tumor cytology and histoarchitecture in all specimens. We simulated an intraoperative consultation for 25 patients with specimens imaged using both SRH and standard hematoxylin and eosin histology. SRH-based diagnoses achieved near-perfect diagnostic concordance (Cohen's kappa, kappa > 0.90) and an accuracy of 92-96%. We then developed a quantitative histologic method using SRH images based on rapid image feature extraction. Nuclear density, tumor-associated macrophage infiltration, and nuclear morphology parameters from 3337 SRH fields of view were used to develop and validate a decision-tree machine-learning model. Using SRH image features, our model correctly classified 25 fresh pediatric type surgical specimens into normal versus lesional tissue and low-grade versus high-grade tumors with 100% accuracy. Our results provide insight into how SRH can deliver rapid diagnostic histologic data that could inform the surgical management of pediatric brain tumors.

Objective We aim to describe a novel, label-free, real-time imaging technique, coherent Raman scattering (CRS) microscopy, for histopathological evaluation of head and neck cancer. We evaluated the ability of CRS microscopy to delineate between tumor and nonneoplastic tissue in tissue samples from patients with head and neck cancer. Study Design Prospective case series. Setting Tertiary care medical center. Subjects and Methods Patients eligible were surgical candidates with biopsy-proven, previously untreated head and neck carcinoma and were consented preoperatively for participation in this study. Tissue was collected from 50 patients, and after confirmation of tumor and normal specimens by hematoxylin and eosin (H&E), there were 42 tumor samples and 42 normal adjacent controls. Results There were 42 confirmed carcinoma specimens on H&E, and CRS microscopy identified 37 as carcinoma. Of the 42 normal specimens, CRS microscopy identified 40 as normal. This resulted in a sensitivity of 88.1% and specificity of 95.2% in distinguishing between neoplastic and nonneoplastic images. Conclusion CRS microscopy is a unique label-free imaging technique that can provide rapid, high-resolution images and can accurately determine the presence of head and neck carcinoma. This holds potential for implementation into standard practice, allowing frozen margin evaluation even at institutions without a histopathology laboratory.

BACKGROUND:Extent of resection (EOR) correlates with glioblastoma outcomes. Resectability and EOR depend on anatomical, clinical, and surgeon factors. Resectability likely influences outcome in and of itself, but an accurate measurement of resectability remains elusive. An understanding of resectability and the factors that influence it may provide a means to control a confounder in clinical trials and provide reference for decision making. OBJECTIVE:To provide proof of concept of the use of the collective wisdom of experienced brain tumor surgeons in assessing glioblastoma resectability. METHODS:We surveyed 13 academic tumor neurosurgeons nationwide to assess the resectability of newly diagnosed glioblastoma. Participants reviewed 20 cases, including digital imaging and communications in medicine-formatted pre- and postoperative magnetic resonance images and clinical vignettes. The selected cases involved a variety of anatomical locations and a range of EOR. Participants were asked about surgical goal, eg, gross total resection, subtotal resection (STR), or biopsy, and rationale for their decision. We calculated a "resectability index" for each lesion by pooling responses from all 13 surgeons. RESULTS:Neurosurgeons' individual surgical goals varied significantly ( P = .015), but the resectability index calculated from the surgeons' pooled responses was strongly correlated with the percentage of contrast-enhancing residual tumor ( R = 0.817, P < .001). The collective STR goal predicted intraoperative decision of intentional STR documented on operative notes ( P < .01) and nonresectable residual ( P < .01), but not resectable residual. CONCLUSION/CONCLUSIONS:In this pilot study, we demonstrate the feasibility of measuring the resectability of glioblastoma through crowdsourcing. This tool could be used to quantify resectability, a potential confounder in neuro-oncology clinical trials.