Faculty Bibliography

PURPOSE/OBJECTIVE:New therapies for melanoma have been associated with increasing survival expectations, as opposed to the dismal outcomes of only a decade ago. Using a prospective registry, we aimed to define current survival goals for melanoma patients with brain metastases (BM), based on state-of-the-art multimodality care. METHODS:We reviewed 171 melanoma patients with BM receiving stereotactic radiosurgery (SRS) who were followed with point-of-care data collection between 2012 and 2020. Clinical, molecular and imaging data were collected, including systemic treatment and radiosurgical parameters. RESULTS:SRS were predictors of long-term survival ([Formula: see text] 5 years) from initial SRS (p = 0.023 and p = 0.018, respectively). Five patients (16%) of the long-term survivors required no active treatment for [Formula: see text] 5 years. CONCLUSION/CONCLUSIONS:Long-term survival in patients with melanoma BM is achievable in the current era of SRS combined with immunotherapies. For those alive [Formula: see text] 5 years after first SRS, 16% had been also off systemic or local brain therapy for over 5 years. Given late recurrences of melanoma, caution is warranted, however prolonged survival off active treatment in a subset of our patients raises the potential for cure.

BACKGROUND:Accurate specimen analysis of skull base tumors is essential for providing personalized surgical treatment strategies. Intraoperative specimen interpretation can be challenging because of the wide range of skull base pathologies and lack of intraoperative pathology resources. OBJECTIVE:To develop an independent and parallel intraoperative workflow that can provide rapid and accurate skull base tumor specimen analysis using label-free optical imaging and artificial intelligence. METHODS:We used a fiber laser-based, label-free, nonconsumptive, high-resolution microscopy method (<60 seconds per 1 × 1 mm2), called stimulated Raman histology (SRH), to image a consecutive, multicenter cohort of patients with skull base tumor. SRH images were then used to train a convolutional neural network model using 3 representation learning strategies: cross-entropy, self-supervised contrastive learning, and supervised contrastive learning. Our trained convolutional neural network models were tested on a held-out, multicenter SRH data set. RESULTS:SRH was able to image the diagnostic features of both benign and malignant skull base tumors. Of the 3 representation learning strategies, supervised contrastive learning most effectively learned the distinctive and diagnostic SRH image features for each of the skull base tumor types. In our multicenter testing set, cross-entropy achieved an overall diagnostic accuracy of 91.5%, self-supervised contrastive learning 83.9%, and supervised contrastive learning 96.6%. Our trained model was able to segment tumor-normal margins and detect regions of microscopic tumor infiltration in meningioma SRH images. CONCLUSION/CONCLUSIONS:SRH with trained artificial intelligence models can provide rapid and accurate intraoperative analysis of skull base tumor specimens to inform surgical decision-making.

Soon after the World Health Organization declared the severe acute respiratory syndrome coronavirus 2 a global health emergency on January 30, 2020, New York City was plagued by the virus and its health system and economy pushed to their limits. The majority of the limited neurosurgical data in relation to COVID-19 is anecdotal and the higher theoretical risk of transmission of the virus among skull base aerosol generating (SBAG) cases has not been investigated or discussed in a neurosurgical population. We discuss a series of 13 patients who underwent 15 SBAG surgical procedures during the peak of COVID-19 in our hospital system and the protocols use perioperatively for their procedures. Our data support that with proper preoperative testing, a well-delineated surgical algorithm, and appropriate personal protective equipment, emergent/urgent cases can be done safely in hospitals that are currently experiencing high volumes of COVID-19 cases as we did in March to May of 2020.

BACKGROUND:Late pathology after vestibular schwannoma radiosurgery is uncommon. The authors presented a case of a resected hemorrhagic mass 13 years after radiosurgery, when no residual tumor was found. OBSERVATIONS/METHODS:A 56-year-old man with multiple comorbidities, including myelodysplastic syndrome cirrhosis, received Gamma Knife surgery for a left vestibular schwannoma. After 11 years of stable imaging assessments, the lesion showed gradual growth until a syncopal event occurred 2 years later, accompanied by progressive facial weakness and evidence of intralesional hemorrhage, which led to resection. However, histopathological analysis of the resected specimen showed hemorrhage and reactive tissue but no definitive residual tumor. LESSONS/CONCLUSIONS:This case demonstrated histopathological evidence for the role of radiosurgery in complete elimination of tumor tissue. Radiosurgery for vestibular schwannoma carries a rare risk for intralesional hemorrhage in select patients.

BACKGROUND/UNASSIGNED:Hyperglycemia has been associated with worse survival in glioblastoma. Attempts to lower glucose yielded mixed responses which could be due to molecularly distinct GBM subclasses. METHODS/UNASSIGNED:Clinical, laboratory, and molecular data on 89 IDH-wt GBMs profiled by clinical next-generation sequencing and treated with Stupp protocol were reviewed. IDH-wt GBMs were sub-classified into RTK I (Proneural), RTK II (Classical) and Mesenchymal subtypes using whole-genome DNA methylation. Average glucose was calculated by time-weighting glucose measurements between diagnosis and last follow-up. RESULTS/UNASSIGNED:= .02). Methylation clustering did not identify unique signatures associated with high or low glucose levels. Metabolomic analysis of 23 tumors showed minimal variation across metabolites without differences between molecular subclasses. CONCLUSION/UNASSIGNED:Higher average glucose values were associated with poorer OS in RTKI and Mesenchymal IDH-wt GBM, but not RTKII. There were no discernible epigenetic or metabolomic differences between tumors in different glucose environments, suggesting a potential survival benefit to lowering systemic glucose in selected molecular subtypes.

OBJECTIVE:Patients with non-small cell lung cancer (NSCLC) metastatic to the brain are living longer. The risk of new brain metastases when these patients stop systemic therapy is unknown. The authors hypothesized that the risk of new brain metastases remains constant for as long as patients are off systemic therapy. METHODS:A prospectively collected registry of patients undergoing radiosurgery for brain metastases was analyzed. Of 606 patients with NSCLC, 63 met the inclusion criteria of discontinuing systemic therapy for at least 90 days and undergoing active surveillance. The risk factors for the development of new tumors were determined using Cox proportional hazards and recurrent events models. RESULTS:The median duration to new brain metastases off systemic therapy was 16.0 months. The probability of developing an additional new tumor at 6, 12, and 18 months was 26%, 40%, and 53%, respectively. There were no additional new tumors 22 months after stopping therapy. Patients who discontinued therapy due to intolerance or progression of the disease and those with mutations in RAS or receptor tyrosine kinase (RTK) pathways (e.g., KRAS, EGFR) were more likely to develop new tumors (hazard ratio [HR] 2.25, 95% confidence interval [CI] 1.33-3.81, p = 2.5 × 10-3; HR 2.51, 95% CI 1.45-4.34, p = 9.8 × 10-4, respectively). CONCLUSIONS:The rate of new brain metastases from NSCLC in patients off systemic therapy decreases over time and is uncommon 2 years after cessation of cancer therapy. Patients who stop therapy due to toxicity or who have RAS or RTK pathway mutations have a higher rate of new metastases and should be followed more closely.