Localization of protoporphyrin IX during glioma-resection surgery via paired stimulated Raman histology and fluorescence microscopy.

The most widely used fluorophore in glioma-resection surgery, 5-aminolevulinic acid (5-ALA), is thought to cause the selective accumulation of fluorescent protoporphyrin IX (PpIX) in tumour cells. Here we show that the clinical detection of PpIX can be improved via a microscope that performs paired stimulated Raman histology and two-photon excitation fluorescence microscopy (TPEF). We validated the technique in fresh tumour specimens from 115 patients with high-grade gliomas across four medical institutions.

Development and validation of an artificial intelligence model to accurately predict spinopelvic parameters.

Objective: Achieving appropriate spinopelvic alignment has been shown to be associated with improved clinical symptoms. However, measurement of spinopelvic radiographic parameters is time-intensive and interobserver reliability is a concern. Automated measurement tools have the promise of rapid and consistent measurements, but existing tools are still limited to some degree by manual user-entry requirements.

Hierarchical discriminative learning improves visual representations of biomedical microscopy.

Learning high-quality, self-supervised, visual representations is essential to advance the role of computer vision in biomedical microscopy and clinical medicine. Previous work has focused on self-supervised representation learning (SSL) methods developed for instance discrimination and applied them directly to image patches, or fields-of-view, sampled from gigapixel whole-slide images (WSIs) used for cancer diagnosis. However, this strategy is limited because it (1) assumes patches from the same patient are independent, (2) neglects the patient-slide-patch hierarchy of clinical biomedical microscopy, and (3) requires strong data augmentations that can degrade downstream performance.

Unlocking glioma genetics with deep learning.

The AI era in medicine has ushered in new opportunities to improve the diagnosis and treatment of human disease. CHARM, an AI algorithm described in this issue, has the potential to streamline molecular classification, intraoperative diagnosis, surgical decision making, and trial enrollment for glioma patients.

OpenSRH: optimizing brain tumor surgery using intraoperative stimulated Raman histology.

Accurate intraoperative diagnosis is essential for providing safe and effective care during brain tumor surgery. Our standard-of-care diagnostic methods are time, resource, and labor intensive, which restricts access to optimal surgical treatments. To address these limitations, we propose an alternative workflow that combines stimulated Raman histology (SRH), a rapid optical imaging method, with deep learning-based automated interpretation of SRH images for intraoperative brain tumor diagnosis and real-time surgical decision support.

A comparison of ventricular volume and linear indices in predicting shunt dependence in aneurysmal subarachnoid hemorrhage.

Background: Guidelines for determining shunt dependence after aneurysmal subarachnoid hemorrhage (aSAH) remain unclear. We previously demonstrated change in ventricular volume (VV) between head CT scans taken pre- and post-EVD clamping was predictive of shunt dependence in aSAH. We sought to compare the predictive value of this measure to more commonly used linear indices.

Generation of 3D ex vivo mouse- and patient-derived glioma explant slice model for integration of confocal time-lapse imaging and spatial analysis.

Development of spatial-integrative pre-clinical models is needed for glioblastoma, which are heterogenous tumors with poor prognosis. Here, we present an optimized protocol to generate three-dimensional ex vivo explant slice glioma model from orthotopic tumors, genetically engineered mouse models, and fresh patient-derived specimens. We describe a step-by-step workflow for tissue acquisition, dissection, and sectioning of 300-μm tumor slices maintaining cell viability.

Perigeniculate Giant Cell Tumor of Temporal Bone.

Giant cell tumors of bone (GCTBs) are benign osteolytic neoplasms that can be treated with either gross-total resection or subtotal resection with adjuvant radiotherapy. For the rare GCTB of the temporal bone, close proximity to critical structures can produce functional deficits and make gross-total resection difficult to achieve without significant morbidity. We present the case of a 28-year-old woman with progressive facial paresis, otalgia, neck pain, imbalance, and subjective hearing loss.

Spatiotemporal analysis of glioma heterogeneity reveals COL1A1 as an actionable target to disrupt tumor progression.

Intra-tumoral heterogeneity is a hallmark of glioblastoma that challenges treatment efficacy. However, the mechanisms that set up tumor heterogeneity and tumor cell migration remain poorly understood. Herein, we present a comprehensive spatiotemporal study that aligns distinctive intra-tumoral histopathological structures, oncostreams, with dynamic properties and a specific, actionable, spatial transcriptomic signature.

Rapid Automated Analysis of Skull Base Tumor Specimens Using Intraoperative Optical Imaging and Artificial Intelligence.

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.

Laminectomy at T4 and T5 for Resection of Symptomatic Cavernous Malformation.

Although rare, intramedullary spinal cavernous malformations have a 1.4%-6.8% annual hemorrhage risk and can cause significant morbidity.

Cranio-Orbital Approach for Single-Stage En Bloc Resection of Optic Nerve Glioma: Technical Note.

Background And Importance: There is no consensus on the optimal surgical approach for managing optic nerve gliomas. For solely intraorbital tumors, a single-stage lateral orbitotomy approach for resection may be performed, but when the nerve within the optic canal is affected, two-stage cranial and orbital approaches are often used. The authors describe their technique to safely achieve aggressive nerve resection to minimize the probability of recurrence that might affect the optic tracts, optic chiasm, and contralateral optic nerve.

Far Lateral Craniotomy for Obliteration of High-Risk Craniocervical Junction Arteriovenous Fistula.

Background And Introduction: Dural arteriovenous fistulas (dAVFs) are a rare pathology with a clinical presentation related to their anatomical location. Craniocervical junction (CCJ) dAVFs are challenging to treat given the delicate structures that surround the CCJ. Endovascular treatment has evolved significantly in the past decade, but open microsurgery remains an invaluable tool for this pathology.

Microsurgical Excision of Ruptured Lenticulostriate Artery Aneurysm.

Lenticulostriate artery aneurysms are uncommon lesions, usually found in adults after hemorrhage. Despite their challenging location, mortality rates after initial hemorrhage are favorable. Securing the hemorrhage source is critical but may be complicated by lesional compression or thrombosis on posthemorrhage vascular imaging.

Ventricular Volume Change as a Predictor of Shunt-Dependent Hydrocephalus in Aneurysmal Subarachnoid Hemorrhage.

Background: Hydrocephalus is a common complication of aneurysmal subarachnoid hemorrhage (aSAH) that often requires acute placement of an external ventricular drain (EVD). The current systems available for determining which patients will require long-term cerebrospinal fluid diversion remain subjective. We investigated the ventricular volume change (ΔVV) after EVD clamping as an objective predictor of shunt dependence in patients with aSAH.

Idiopathic chronic temporal lobe herniation with associated epilepsy.

Herniation of parahippocampal gyrus is usually caused by pressure differentials intracranially, and herniation without known risk factors is extremely rare. We describe a patient with a long history of seizures and a remote status epilepticus event. On magnetic resonance imaging, a presumed left temporal lobe tumor was observed.

Lateral Suboccipital Craniotomy With C1-C2 Hemilaminectomies and C1-C3 Fusion for the Treatment of a C1-C2 Synovial Cyst Causing Spinal Cord Compression: 2-Dimensional Operative Video.

Atlantoaxial synovial cysts are a rare cause of cervical myelopathy. Here we describe a case of a 26-yr-old woman who presented with progressively decreasing right arm and leg strength and associated gait imbalance. On examination, she had diffuse weakness in the right upper and lower extremities, a positive right-sided Hoffman sign, and clonus in the right lower extremity.

Normal cerebral ventricular volume growth in childhood.

Objective: Normal percentile growth charts for head circumference, length, and weight are well-established tools for clinicians to detect abnormal growth patterns. Currently, no standard exists for evaluating normal size or growth of cerebral ventricular volume. The current standard practice relies on clinical experience for a subjective assessment of cerebral ventricular size to determine whether a patient is outside the normal volume range.

Rapid, label-free detection of diffuse glioma recurrence using intraoperative stimulated Raman histology and deep neural networks.

Background: Detection of glioma recurrence remains a challenge in modern neuro-oncology. Noninvasive radiographic imaging is unable to definitively differentiate true recurrence versus pseudoprogression. Even in biopsied tissue, it can be challenging to differentiate recurrent tumor and treatment effect.

Automated histologic diagnosis of CNS tumors with machine learning.

The discovery of a new mass involving the brain or spine typically prompts referral to a neurosurgeon to consider biopsy or surgical resection. Intraoperative decision-making depends significantly on the histologic diagnosis, which is often established when a small specimen is sent for immediate interpretation by a neuropathologist. Access to neuropathologists may be limited in resource-poor settings, which has prompted several groups to develop machine learning algorithms for automated interpretation.

An automated tissue-to-diagnosis pipeline using intraoperative stimulated Raman histology and deep learning.

We recently developed and validated a bedside tissue-to-diagnosis pipeline using stimulated Raman histology (SRH), a label-free optical imaging method, and deep convolutional neural networks (CNN) in prospective clinical trial. Our CNN learned a hierarchy of interpretable histologic features found in the most common brain tumors and was able to accurately segment cancerous regions in SRH images.