Current Trends in Neurosurgical Management of Adult Diffuse Low-Grade Gliomas in Canada.

There is considerable variability in the management of diffuse low-grade gliomas (LGGs). To characterize treatment paradigms, a survey of Canadian neurosurgeons was performed with forty neurosurgeons responding. Their responses show that the management of patients with LGGs has evolved in the past decade and findings from the RTOG9802 trial have been integrated into the practice of Canadian neurosurgeons. Most respondents stated that the patient selection and treatment strategy advocated by the RTOG9802 trial needs further evaluation. Overall, there is a trend toward more aggressive surgical resections, and future investigations will have to more accurately stratify patient risk profiles.

A History of Diagnostic Investigations in Epilepsy Surgery.

Epilepsy surgery has progressed significantly in the last 150 years. Functional brain maps allowed for the localization of epileptogenic lesions based on seizure patterns, allowing surgeons like McEwan and Horsely to treat epilepsy surgically. Berger's electroencephalogram marked the first modality directly identifying epileptic abnormalities. Penfield and Jasper collaborated, as neurosurgeon and neurologist, to use EEG for surgery. Meanwhile, Wada developed the amobarbital test, improving the protection of language and memory. Talairach and Bancaud pioneered invasive monitoring of deep brain activity with stereoelectroencephalography before the computer age made CT and MRI possible. Looking forward, AI and robotics hold promise for further improving outcomes.

Evaluating the clinical utility of artificial intelligence assistance and its explanation on the glioma grading task.

Clinical evaluation evidence and model explainability are key gatekeepers to ensure the safe, accountable, and effective use of artificial intelligence (AI) in clinical settings. We conducted a clinical user-centered evaluation with 35 neurosurgeons to assess the utility of AI assistance and its explanation on the glioma grading task. Each participant read 25 brain MRI scans of patients with gliomas, and gave their judgment on the glioma grading without and with the assistance of AI prediction and explanation. The AI model was trained on the BraTS dataset with 88.0% accuracy. The AI explanation was generated using the explainable AI algorithm of SmoothGrad, which was selected from 16 algorithms based on the criterion of being truthful to the AI decision process. Results showed that compared to the average accuracy of 82.5±8.7% when physicians performed the task alone, physicians' task performance increased to 87.7±7.3% with statistical significance (p-value = 0.002) when assisted by AI prediction, and remained at almost the same level of 88.5±7.0% (p-value = 0.35) with the additional assistance of AI explanation. Based on quantitative and qualitative results, the observed improvement in physicians' task performance assisted by AI prediction was mainly because physicians' decision patterns converged to be similar to AI, as physicians only switched their decisions when disagreeing with AI. The insignificant change in physicians' performance with the additional assistance of AI explanation was because the AI explanations did not provide explicit reasons, contexts, or descriptions of clinical features to help doctors discern potentially incorrect AI predictions. The evaluation showed the clinical utility of AI to assist physicians on the glioma grading task, and identified the limitations and clinical usage gaps of existing explainable AI techniques for future improvement.

Guidelines and evaluation of clinical explainable AI in medical image analysis.

Explainable artificial intelligence (XAI) is essential for enabling clinical users to get informed decision support from AI and comply with evidence-based medical practice. Applying XAI in clinical settings requires proper evaluation criteria to ensure the explanation technique is both technically sound and clinically useful, but specific support is lacking to achieve this goal. To bridge the research gap, we propose the Clinical XAI Guidelines that consist of five criteria a clinical XAI needs to be optimized for. The guidelines recommend choosing an explanation form based on Guideline 1 (G1) Understandability and G2 Clinical relevance. For the chosen explanation form, its specific XAI technique should be optimized for G3 Truthfulness, G4 Informative plausibility, and G5 Computational efficiency. Following the guidelines, we conducted a systematic evaluation on a novel problem of multi-modal medical image explanation with two clinical tasks, and proposed new evaluation metrics accordingly. Sixteen commonly-used heatmap XAI techniques were evaluated and found to be insufficient for clinical use due to their failure in G3 and G4. Our evaluation demonstrated the use of Clinical XAI Guidelines to support the design and evaluation of clinically viable XAI.

Generating post-hoc explanation from deep neural networks for multi-modal medical image analysis tasks.

Explaining model decisions from medical image inputs is necessary for deploying deep neural network (DNN) based models as clinical decision assistants. The acquisition of multi-modal medical images is pervasive in practice for supporting the clinical decision-making process. Multi-modal images capture different aspects of the same underlying regions of interest. Explaining DNN decisions on multi-modal medical images is thus a clinically important problem. Our methods adopt commonly-used post-hoc artificial intelligence feature attribution methods to explain DNN decisions on multi-modal medical images, including two categories of gradient- and perturbation-based methods. • Gradient-based explanation methods - such as Guided BackProp, DeepLift - utilize the gradient signal to estimate the feature importance for model prediction. • Perturbation-based methods - such as occlusion, LIME, kernel SHAP - utilize the input-output sampling pairs to estimate the feature importance. • We describe the implementation details on how to make the methods work for multi-modal image input, and make the implementation code available.

Intraparenchymal Mucosa-Associated Lymphoid Tissue Lymphoma: A Case Report.

Marginal zone B-cell lymphoma (MZBCL) of mucosa-associated lymphoid tissue (MALT) type, which is primary to the central nervous system (CNS), is a rare lesion, with those originating within the parenchyma even more so. We present the case of a 64-year-old male with weakness in the left hand and focal motor seizures of his arm, who was found to have a right frontal intraparenchymal lesion. Following resection, histopathological and immunohistochemical evaluations were completed, leading to a diagnosis of a primary CNS MZBCL of MALT type in the context of a negative workup of systemic disease. Neuroimaging, histopathological, and immunohistochemical findings, as well as a comprehensive literature review of similar cases, are discussed.

Enhanced Interplay of Neuronal Coherence and Coupling in the Dying Human Brain.

The neurophysiological footprint of brain activity after cardiac arrest and during near-death experience (NDE) is not well understood. Although a hypoactive state of brain activity has been assumed, experimental animal studies have shown increased activity after cardiac arrest, particularly in the gamma-band, resulting from hypercapnia prior to and cessation of cerebral blood flow after cardiac arrest. No study has yet investigated this matter in humans. Here, we present continuous electroencephalography (EEG) recording from a dying human brain, obtained from an 87-year-old patient undergoing cardiac arrest after traumatic subdural hematoma. An increase of absolute power in gamma activity in the narrow and broad bands and a decrease in theta power is seen after suppression of bilateral hemispheric responses. After cardiac arrest, delta, beta, alpha and gamma power were decreased but a higher percentage of relative gamma power was observed when compared to the interictal interval. Cross-frequency coupling revealed modulation of left-hemispheric gamma activity by alpha and theta rhythms across all windows, even after cessation of cerebral blood flow. The strongest coupling is observed for narrow- and broad-band gamma activity by the alpha waves during left-sided suppression and after cardiac arrest. Albeit the influence of neuronal injury and swelling, our data provide the first evidence from the dying human brain in a non-experimental, real-life acute care clinical setting and advocate that the human brain may possess the capability to generate coordinated activity during the near-death period.

Large Subependymoma Inferior to the Cerebellopontine Angle With Significant Obstructive Hydrocephalus: A Case Report on an Extremely Rare Tumor.

Subependymomas are rare yet benign tumors that are commonly found within the ventricular system. We describe the case of a 51-year-old male presenting with hydrocephalus and progressive headaches found to have a right cerebellopontine angle (CPA) lesion encasing multiple blood vessels and cranial nerves (CN). The lesion was resected subtotally via a retrosigmoid approach and was found to be a subependymoma. CPA subependymomas are extremely rare lesions. The neuroimaging and histopathological findings as well as a comprehensive literature review of similar cases are discussed.

Ependymoma and Chordoma.

Ependymoma and chordoma are 2 tumors that occur throughout the craniospinal axis, and for which the extent of neurosurgical resection has a key prognostic role. Both tumors have distinctive pathologic features, yet can present significant diagnostic challenges to pathologists in cases without classical histology. The molecular understanding of ependymoma has had significant advances in the past decade, with the identification of 9 molecular groups with significant prognostic and clinical implications, while a comprehensive study of chordoma further emphasized the key role of brachyury overexpression in its pathogenesis. In this review, we discuss the pathogenesis, radiology and gross pathology, histology, and molecular features of these 2 tumors, as well as active research into targeted therapies, with an emphasis on practical diagnostic challenges, and the use of immunohistochemical and molecular tests in routine diagnostic practice.

Artificial intelligence in glioma imaging: challenges and advances.

Primary brain tumors including gliomas continue to pose significant management challenges to clinicians. While the presentation, the pathology, and the clinical course of these lesions are variable, the initial investigations are usually similar. Patients who are suspected to have a brain tumor will be assessed with computed tomography (CT) and magnetic resonance imaging (MRI). The imaging findings are used by neurosurgeons to determine the feasibility of surgical resection and plan such an undertaking. Imaging studies are also an indispensable tool in tracking tumor progression or its response to treatment. As these imaging studies are non-invasive, relatively cheap and accessible to patients, there have been many efforts over the past two decades to increase the amount of clinically-relevant information that can be extracted from brain imaging. Most recently, artificial intelligence (AI) techniques have been employed to segment and characterize brain tumors, as well as to detect progression or treatment-response. However, the clinical utility of such endeavours remains limited due to challenges in data collection and annotation, model training, and the reliability of AI-generated information. We provide a review of recent advances in addressing the above challenges. First, to overcome the challenge of data paucity, different image imputation and synthesis techniques along with annotation collection efforts are summarized. Next, various training strategies are presented to meet multiple desiderata, such as model performance, generalization ability, data privacy protection, and learning with sparse annotations. Finally, standardized performance evaluation and model interpretability methods have been reviewed. We believe that these technical approaches will facilitate the development of a fully-functional AI tool in the clinical care of patients with gliomas.

Functional Outcomes After Treatment of Posterior Inferior Cerebellar Artery Aneurysms.

Objective Aneurysms of the posterior inferior cerebellar artery (PICA) are a rare cause of subarachnoid hemorrhage. Treatment for this type of aneurysm may be microsurgical clipping or endovascular. This decision is based on patient characteristics, aneurysm location and dimensions, along with surgeon and institutional experience. In this study we aim to assess the outcomes of surgical and endovascular treatment of PICA aneurysms. Methods We retrospectively reviewed the charts of 52 patients who were admitted to Vancouver General Hospital for ruptured or symptomatic PICA aneurysms between 2005 and 2015. Modified Rankin scores were assigned at the time of discharge and at two subsequent follow-up time points. The mean short-term follow-up period post-operatively was 11.1 months and the mean long-term follow-up period was 19.3 months. Clinical and radiological characteristics were collected for all patients. Results Of the 52 patients, two died prior to obtaining treatment. Of the 50 patients who were treated for their PICA aneurysm, 39 presented with subarachnoid hemorrhage while 11 had symptomatic unruptured PICA aneurysms. Overall, 11 patients had endovascular treatment (coil embolization) while 39 patients underwent microsurgical clipping/trapping of the aneurysm. At the time of hospital discharge, patients in the microsurgical group trended towards a better the modified Rankin Scale score (2.3) compared to the endovascular group, though this did not reach significance (3.0) (p=0.20). The long-term score in the endovascular group (1.6) was also comparable to the microsurgical group (1.9) (p=0.55). Conclusion While the early outcomes in patients treated endovascularly appear better, there is no statistically significant difference in outcomes between the microsurgical and endovascular treatment groups at short- and long-term follow-up.

Persistent Disparities in Survival for Patients with Glioblastoma.

BACKGROUND: Glioblastoma (GBM) is the most common malignant primary brain cancer in adults. Recent efforts have elucidated genetic features of tumor cells and thus enhanced our knowledge of GBM pathophysiology. The most recent clinical trials report median overall survival between 14 and 20 months. However, population level outcomes are quite variable and there is a paucity of such data within the literature. METHODS: Three hundred seventy-two patients with GBM were diagnosed in the Canadian province of British Columbia between January 2013 and January 2015 and 278 patients had surgery. Of these, 268 had surgery in British Columbia and we have performed a retrospective review of their survival outcomes. RESULTS: Our results indicate a median age of 61.8 years at time of diagnosis, with a slight preponderance of male patients. The median overall survival was 10 months for patients in our cohort. As expected, patients older than the age of 65 and those with worse initial Karnofsky Performance Status scores had a poorer prognosis. Moreover, we have found extent of resection, treatment strategies, and treatment location affect overall survival. CONCLUSIONS: The present study highlights factors that affect patient survival after surgery in British Columbia. Our data are gathered within a single-payer, high-resource setting which removes possible confounders in outcome analysis. We find persistent differences in overall survival when compared with clinical trials and the Surveillance, Epidemiology, and End Results database. Further efforts should ensure access to the gold standard of care. All neuro-oncology centers should analyze the real-world outcomes of their local glioblastoma treatment strategies. Knowledge of the variance from expected and comparative results are fundamental for appropriate patient care.

Suboccipital Decompressive Craniectomy for Cerebellar Infarction: A Systematic Review and Meta-Analysis.

BACKGROUND: Suboccipital decompressive craniectomy (SDC) for cerebellar infarction has been traditionally performed with minimal high-quality evidence. The aim of this systematic review and meta-analysis is to investigate the impact of SDC on functional outcomes, mortality, and adverse events in patients with cerebellar infarcts. METHODS: A systematic review and meta-analysis in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Our primary outcome was the proportion of patients with moderate-severe disability after SDC. Secondary outcomes included mortality and adverse events. A sensitivity analysis was conducted to examine the roles of age, preoperative neurologic status, external ventricular drain insertion, and debridement of infarcted tissue on SDC outcomes. RESULTS: Eleven studies (with 283 patients) met our inclusion criteria. The pooled event rate for moderate-severe disability was 28% (95% confidence interval [CI], 20%-37%) and for mortality, it was 20% (95% CI, 12%-31%). The estimated overall rate of adverse events for SDC was 23% (95% CI, 14%-35%). Sensitivity analysis found less mortality with mean age <60 years, higher rates of concomitant external ventricular drain insertion, and debridement of infarcted tissue. Several factors were identified for heterogeneity between studies, including follow-up time, outcomes scale, extent of infarction, and other neuroimaging features. CONCLUSIONS: The best available evidence for SDC is based on retrospective observational studies. SDC for cerebellar infarction is associated with better outcomes compared with decompressive surgery for hemispheric infarctions. Lack of standardized reporting methods for SDC is a considerable drawback to the development of a better understanding of the impact of this surgery on patient outcomes.

Uremic tumoral calcinosis in the cervical spine: case report.

Tumoral calcinosis is an uncommon condition characterized by the calcification of periarticular soft tissue. In uremic patients the disease is secondary to metabolic disturbances in predisposed patients. The authors report the case of a 73-year-old woman who presented with a new painful cervical mass while undergoing continuous ambulatory peritoneal dialysis for long-standing end-stage renal disease (ESRD). A CT scan of the neck showed a lobulated, calcified mass in the left paraspinal soft tissue at C2-3. This mass affected the facet joint and also extended into the neural foramen but did not cause any neurological compromise. Due to the patient's significant medical comorbidities, resection was deferred and the patient was followed in the clinic. Subsequent repeat imaging has shown a significant decrease in the size of the mass. In the context of ESRD, a diagnosis of uremic tumoral calcinosis (UTC) was made. The authors conducted a search of the PubMed and EMBASE databases and identified 7 previously reported cases of UTC of the cervical spine. They present a summary of these cases and discuss the etiology, diagnosis, and management of the condition. Although the metabolic disturbances seen in patients undergoing dialysis can lead to tumoral calcinosis, most reported cases involve large joints such as the shoulder or the hip; however, the spine can also be affected and should be considered in the differential diagnosis of patients with uremia as it can mimic aggressive bone-forming neoplasms.

Double-chamber rotating bioreactor for dynamic perfusion cell seeding of large-segment tracheal allografts: comparison to conventional static methods.

Tracheal transplantation with a long-segment recellularized tracheal allograft has previously been performed without the need for immunosuppressive therapy. Recipients' mesenchymal stromal cells (MSC) and tracheal epithelial cells (TEC) were harvested, cultured, expanded, and seeded on a donor trachea within a bioreactor. Prior techniques used for cellular seeding have involved only static-seeding methods. Here, we describe a novel bioreactor for recellularization of long-segment tracheae. Tracheae were recellularized with epithelial cells on the luminal surface and bone marrow-derived MSC on the external surface. We used dynamic perfusion seeding for both cell types and demonstrate an increase in both cellular counts and homogeneity scores compared with traditional methods. Despite these improvements, orthotopic transplantation of these scaffolds revealed no labeled cells at postoperative day 3 and lack of re-epithelialization within the first 2 weeks. The animals in this study had postoperative respiratory distress and tracheal collapse that was incompatible with life.