Margaret Pain

Sinus thrombectomy for purulent cerebral venous sinus thrombosis utilizing a novel combination of the Trevo stent retriever and the Penumbra ACE aspiration catheter: the stent anchor with mobile aspiration technique

Intracranial complications of sinusitis are rare but life threatening. We present a case of a 17-year-old woman with sinusitis who deteriorated over the course of 12 days from subdural empyema and global purulent cerebral venous sinus thrombosis. The patient was managed with surgery and mechanical thrombectomy utilizing a novel ‘stent anchor with mobile aspiration technique’, in which a Trevo stent retriever (Stryker) was anchored in the superior sagittal sinus (SSS) while a 5 MAX ACE reperfusion catheter (Penumbra) was passed back and forth from the SSS to the sigmoid sinus with resultant dramatic improvement in venous outflow. The patient was extubated on postoperative day 3 and was discharged with minimal lower extremity weakness on postoperative day 11. This is the first report using the Trevo stent retriever for sinus thrombosis. It is important to keep these rare complications in mind when evaluating patients with oral and facial infections.

Pilomyxoid astrocytoma of the cerebellar vermis in an elderly patient

Background: Pilomyxoid astrocytoma (PMA) has recently been accepted as an aggressive variant of pilocytic astrocytoma with distinct histopathological features. PMAs have been frequently described in the pediatric population with a predilection for the hypothalamic/chiasmatic region. Case Description: A 72-year-old African American male presented with 6 months of memory loss, difficulty expressing himself, and a progressively worsening gait. Magnetic resonance imaging of the brain demonstrated a heterogeneously enhancing cystic mass centered within the cerebellar vermis with mass effect on the fourth ventricle and ventriculomegaly. The patient underwent placement of a ventriculoperitoneal shunt followed by a surgical resection of the lesion, which after immunohistopathologic evaluation, was diagnosed as a World Health Organization grade II PMA. The patient refused further treatment of the lesion and expired 11 months after initial symptom presentation and 4 months after surgery. Conclusion: To our knowledge, this is the first report of PMA of the cerebellar vermis in a previously unreported age group. This case report describes the natural history of this type of tumor in a patient who refused adjuvant therapy following surgical resection.

Can MRI predict meningioma consistency?: a correlation with tumor pathology and systematic review

Tumor consistency is a critical factor that influences operative strategy and patient counseling. Magnetic resonance imaging (MRI) describes the concentration of water within living tissues and as such, is hypothesized to predict aspects of their biomechanical behavior. In meningiomas, MRI signal intensity has been used to predict the consistency of the tumor and its histopathological subtype, though its predictive capacity is debated in the literature. We performed a systematic review of the PubMed database since 1990 concerning MRI appearance and tumor consistency to assess whether or not MRI can be used reliably to predict tumor firmness. The inclusion criteria were case series and clinical studies that described attempts to correlate preoperative MRI findings with tumor consistency. The relationship between the pre-operative imaging characteristics, intraoperative findings, and World Health Organization (WHO) histopathological subtype is described. While T2 signal intensity and MR elastography provide a useful predictive measure of tumor consistency, other techniques have not been validated. T1-weighted imaging was not found to offer any diagnostic or predictive value. A quantitative assessment of T2 signal intensity more reliably predicts consistency than inherently variable qualitative analyses. Preoperative knowledge of tumor firmness affords the neurosurgeon substantial benefit when planning surgical techniques. Based upon our review of the literature, we currently recommend the use of T2-weighted MRI for predicting consistency, which has been shown to correlate well with analysis of tumor histological subtype. Development of standard measures of tumor consistency, standard MRI quantification metrics, and further exploration of MRI technique may improve the predictive ability of neuroimaging for meningiomas.

Natural Language–based Machine Learning Models for the Annotation of Clinical Radiology Reports

Purpose To compare different methods for generating features from radiology reports and to develop a method to automatically identify findings in these reports. Materials and Methods In this study, 96 303 head computed tomography (CT) reports were obtained. The linguistic complexity of these reports was compared with that of alternative corpora. Head CT reports were preprocessed, and machine-analyzable features were constructed by using bag-of-words (BOW), word embedding, and Latent Dirichlet allocation-based approaches. Ultimately, 1004 head CT reports were manually labeled for findings of interest by physicians, and a subset of these were deemed critical findings. Lasso logistic regression was used to train models for physician-assigned labels on 602 of 1004 head CT reports (60%) using the constructed features, and the performance of these models was validated on a held-out 402 of 1004 reports (40%). Models were scored by area under the receiver operating characteristic curve (AUC), and aggregate AUC statistics were reported for (a) all labels, (b) critical labels, and (c) the presence of any critical finding in a report. Sensitivity, specificity, accuracy, and F1 score were reported for the best performing models (a) predictions of all labels and (b) identification of reports containing critical findings. Results The best-performing model (BOW with unigrams, bigrams, and trigrams plus average word embeddings vector) had a held-out AUC of 0.966 for identifying the presence of any critical head CT finding and an average 0.957 AUC across all head CT findings. Sensitivity and specificity for identifying the presence of any critical finding were 92.59% (175 of 189) and 89.67% (191 of 213), respectively. Average sensitivity and specificity across all findings were 90.25% (1898 of 2103) and 91.72% (18 351 of 20 007), respectively. Simpler BOW methods achieved results competitive with those of more sophisticated approaches, with an average AUC for presence of any critical finding of 0.951 for unigram BOW versus 0.966 for the best-performing model. The Yule I of the head CT corpus was 34, markedly lower than that of the Reuters corpus (at 103) or I2B2 discharge summaries (at 271), indicating lower linguistic complexity. Conclusion Automated methods can be used to identify findings in radiology reports. The success of this approach benefits from the standardized language of these reports. With this method, a large labeled corpus can be generated for applications such as deep learning.

Automated deep-neural-network surveillance of cranial images for acute neurologic events

Rapid diagnosis and treatment of acute neurological illnesses such as stroke, hemorrhage, and hydrocephalus are critical to achieving positive outcomes and preserving neurologic function—‘time is brain’1–5. Although these disorders are often recognizable by their symptoms, the critical means of their diagnosis is rapid imaging6–10. Computer-aided surveillance of acute neurologic events in cranial imaging has the potential to triage radiology workflow, thus decreasing time to treatment and improving outcomes. Substantial clinical work has focused on computer-assisted diagnosis (CAD), whereas technical work in volumetric image analysis has focused primarily on segmentation. 3D convolutional neural networks (3D-CNNs) have primarily been used for supervised classification on 3D modeling and light detection and ranging (LiDAR) data11–15. Here, we demonstrate a 3D-CNN architecture that performs weakly supervised classification to screen head CT images for acute neurologic events. Features were automatically learned from a clinical radiology dataset comprising 37,236 head CTs and were annotated with a semisupervised natural-language processing (NLP) framework16. We demonstrate the effectiveness of our approach to triage radiology workflow and accelerate the time to diagnosis from minutes to seconds through a randomized, double-blinded, prospective trial in a simulated clinical environment.A deep-learning algorithm is developed to provide rapid and accurate diagnosis of clinical 3D head CT-scan images to triage and prioritize urgent neurological events, thus potentially accelerating time to diagnosis and care in clinical settings.

Sensitivity to BUB1B Inhibition Defines an Alternative Classification of Glioblastoma

Glioblastoma multiforme (GBM) remains a mainly incurable disease in desperate need of more effective treatments. In this study, we develop evidence that the mitotic spindle checkpoint molecule BUB1B may offer a predictive marker for aggressiveness and effective drug response. A subset of GBM tumor isolates requires BUB1B to suppress lethal kinetochore-microtubule attachment defects. Using gene expression data from GBM stem-like cells, astrocytes, and neural progenitor cells that are sensitive or resistant to BUB1B inhibition, we created a computational framework to predict sensitivity to BUB1B inhibition. Applying this framework to tumor expression data from patients, we stratified tumors into BUB1B-sensitive (BUB1BS) or BUB1B-resistant (BUB1BR) subtypes. Through this effort, we found that BUB1BS patients have a significantly worse prognosis regardless of tumor development subtype (i.e., classical, mesenchymal, neural, proneural). Functional genomic profiling of BUB1BR versus BUB1BS isolates revealed a differential reliance of genes enriched in the BUB1BS classifier, including those involved in mitotic cell cycle, microtubule organization, and chromosome segregation. By comparing drug sensitivity profiles, we predicted BUB1BS cells to be more sensitive to type I and II topoisomerase inhibitors, Raf inhibitors, and other drugs, and experimentally validated some of these predictions. Taken together, the results show that our BUB1BR/S classification of GBM tumors can predict clinical course and sensitivity to drug treatment. Cancer Res; 77(20); 5518-29. ©2017 AACR.

Multiple Meningiomas in a Patient with Cowden Syndrome.

Background  Cowden syndrome is a rare, multisystem disease manifesting with increased hamartomas and neoplasms. Though meningioma has been documented in patients with Cowden syndrome, the relationship between these two phenomena is still unclear. Case Description  We report a case of a 43-year-old female patient with a known PTEN mutation and clinical history of Cowden syndrome. A workup of headache demonstrated two skull base meningiomas. At the time of surgery, several additional tiny meningiomas were detected in the same region. Conclusions  The development of multiple meningiomas in a patient with predisposition for tumor is more than coincidental. Though PTEN mutations and deletions have not been shown to be critical for meningioma development, this case challenges that conclusion. In light of recent genetic advances in meningioma molecular pathogenesis, the role of the PTEN/AKT/PI3K pathway is discussed.

Ophthalmic artery occlusion immediately following placement of a flow diverter without clinical sequelae.

Branch vessel occlusion is a potential consequence following flow diverter placement for intracranial aneurysms, but the frequency and clinical impact has not been completely elucidated. In this case of a 45-year-old woman with a large left internal carotid artery aneurysm, the ophthalmic artery was covered by two flow diverters and was acutely occluded along with the aneurysm. Common carotid injections failed to demonstrate collateral flow to the ophthalmic artery via the external carotid artery. Nonetheless, the patient woke from anesthesia with objectively stable and subjectively improved vision. This case demonstrates that an acute occlusion of the ophthalmic artery without external carotid artery collaterals can be tolerated clinically.

Treatment-associated TP53 DNA-binding domain missense mutations in the pathogenesis of secondary gliosarcoma

Background Gliosarcoma is a rare variant of glioblastoma (GBM) that exhibits frequent mutations in TP53 and can develop in a secondary fashion after chemoradiation of a primary GBM. Whether temozolomide (TMZ)-induced mutagenesis of the TP53 DNA-binding domain (DBD) can drive the pathogenesis of gliosarcoma is unclear. Methods We identified a case of a primary GBM that rapidly progressed into secondary gliosarcoma shortly after chemoradiation was initiated. Bulk tumor was collected and gliomasphere cultures derived from both the pre- and post-treatment tumors. We performed targeted DNA sequencing and transcriptome analyses of the specimens to understand their phylogenetic relationship and identify differentially expressed gene pathways. Gliomaspheres from the primary GBM were treated with TMZ and then analyzed to compare patterns of mutagenesis in vivo and ex vivo. Results The pre- and post-treatment tumors shared EGFR, CDKN2A, and PTEN mutations, but only the secondary gliosarcoma exhibited TP53 DBD missense mutations. Two mutations, R110C, and R175H, were identified, each in distinct clones. Both were base transitions characteristic of TMZ mutagenesis. Gene expression analysis identified increased JAK-STAT signaling in the gliosarcoma, together with reduced expression of microRNAs known to regulate epithelial-mesenchymal transition. Ex vivo treatment of the GBM spheres with TMZ generated numerous variants in cancer driver genes, including TP53 and CDH1, which were mutated in the post-treatment tumor. Conclusions TMZ-induced TP53 gain-of-function mutations can have a driving role in secondary gliosarcoma pathogenesis. Analysis of variants identified in ex vivo TMZ-treated gliomaspheres may have utility in predicting GBM evolutionary trajectories in vivo during standard chemoradiation.

Transsphenoidal Surgery for Cushing’s Disease

The first line of treatment in Cushing’s disease is surgical resection. All patients with clinical evidence of Cushing’s disease should receive a full work-up to determine the source of the hypercortisolemia. Referral to a neurosurgeon is only necessary if the source of the endocrinopathy is suspected to be the pituitary gland. However, we believe that neurosurgeons operating on patients with Cushing’s disease must understand the preoperative work-up and be secure in the results along with the endocrine team. Mistakes in diagnosis are a frequent event when dealing with these patients. We will not review all the endocrine testing here.