A Systematic Review of the Complications Associated with Free Fibular Flaps in Adult and Pediatric Spinal Reconstruction.

Background:  Free fibular flaps have been suggested as a modality of reconstruction for complex spinal deformities. However, there is limited data that describes associated postoperative outcomes. The purpose of this systematic review was to characterize outcomes after spinal reconstruction using the free fibular flap for both adults and children.

Machine Learning Predicts Cerebral Vasospasm in Subarachnoid Hemorrhage Patients.

Background: Cerebral vasospasm (CV) is a feared complication occurring in 20-40% of patients following subarachnoid hemorrhage (SAH) and is known to contribute to delayed cerebral ischemia. It is standard practice to admit SAH patients to intensive care for an extended period of vigilant, resource-intensive, clinical monitoring. We used machine learning to predict CV requiring verapamil (CVRV) in the largest and only multi-center study to date.

Lumbar Spinal Canal Segmentation in Cases with Lumbar Stenosis Using Deep-U-Net Ensembles.

Background: Narrowing of the lumbar spinal canal, or lumbar stenosis (LS), may cause debilitating radicular pain or muscle weakness. It is the most frequent indication for spinal surgery in the elderly population. Modern diagnosis relies on magnetic resonance imaging and its inherently subjective interpretation.

Upper lumbar spine far lateral disc herniations masquerading as peripheral nerve sheath tumors: illustrative cases.

Background: Migratory disc herniations can mimic neoplasms clinically and on imaging. Far lateral lumbar disc herniations usually compress the exiting nerve root and can be challenging to distinguish from a nerve sheath tumor due to the proximity of the nerve and characteristics on magnetic resonance imaging (MRI). These lesions can occasionally present in the upper lumbar spine region at the L1-2 and L2-3 levels.

Structural Changes in the Cervicomedullary Junction in Adult Chiari Patients.

Objective: To assess volumetric changes in the spinal cord at the cervicomedullary junction, diameter of the cervicomedullary cord, and width of the brainstem following posterior fossa decompression (PFD).

Methods: A retrospective analysis of adult patients with Chiari malformation who underwent PFD was performed. Segmentations were done on clinical quality T2-weighted cervical magnetic resonance images obtained before and after decompression using ITK-SNAP.

Imaging Biomarker Development for Lower Back Pain Using Machine Learning: How Image Analysis Can Help Back Pain.

State-of-the-art diagnosis of radiculopathy relies on "highly subjective" radiologist interpretation of magnetic resonance imaging of the lower back. Currently, the treatment of lumbar radiculopathy and associated lower back pain lacks coherence due to an absence of reliable, objective diagnostic biomarkers. Using emerging machine learning techniques, the subjectivity of interpretation may be replaced by the objectivity of automated analysis.

High-Dose Rate Interstitial Spine Brachytherapy Using an Intraoperative Mobile Computed Tomography-Guided Surgical Navigation System.

Background: Up to 15% of previously irradiated metastatic spine tumors will progress. Re-irradiation of these tumors poses a significant risk of exceeding the radiation tolerance to the spinal cord. High-dose rate (HDR) brachytherapy is a treatment alternative.

Perioperative dual antiplatelet therapy for patients undergoing spine surgery soon after drug eluting stent placement.

Background: Performing emergent spinal surgery within 6 months of percutaneous placement of drug-eluting coronary stent (DES) is complex. The risks of spinal bleeding in a "closed space" must be compared with the risks of stent thrombosis or major cardiac event from dual antiplatelet therapy (DAPT) interruption.

Methods: Eighty relevant English language papers published in PubMed were reviewed in detail.

Predicting Spinal Surgery Candidacy From Imaging Data Using Machine Learning.

Background: The referral process for consultation with a spine surgeon remains inefficient, given a substantial proportion of referrals to spine surgeons are nonoperative.

Objective: To develop a machine-learning-based algorithm which accurately identifies patients as candidates for consultation with a spine surgeon, using only magnetic resonance imaging (MRI).

Methods: We trained a deep U-Net machine learning model to delineate spinal canals on axial slices of 100 normal lumbar MRI scans which were previously delineated by expert radiologists and neurosurgeons.

Updated external validation of the SORG machine learning algorithms for prediction of ninety-day and one-year mortality after surgery for spinal metastasis.

Background Context: Surgical decompression and stabilization in the setting of spinal metastasis is performed to relieve pain and preserve functional status. These potential benefits must be weighed against the risks of perioperative morbidity and mortality. Accurate prediction of a patient's postoperative survival is a crucial component of patient counseling.

Eigenrank by committee: Von-Neumann entropy based data subset selection and failure prediction for deep learning based medical image segmentation.

Manual delineation of anatomy on existing images is the basis of developing deep learning algorithms for medical image segmentation. However, manual segmentation is tedious. It is also expensive because clinician effort is necessary to ensure correctness of delineation.

United States Medical Licensing Examination step 2 scores do not predict American Board of Neurological Surgery scores: A single-institution experience.

Objectives: The neurosurgery residency match is becoming increasingly competitive, with numerous factors being considered as part of the application. We aim to determine whether USMLE Step 2 scores were a significant predictor of neurosurgery board performance.

Patients And Methods: Residents who entered a neurological surgery residency program at a single academic institution during 2000-2017 provided scores for all ABNS attempts, USMLE Step 1 and Step 2 scores.

Clinical and surgical management of holocervical spinal cord ependymomas.

Background: Spinal ependymomas are rare tumors of the central nervous system, and those spanning the entire cervical spine are atypical. Here, we present two unusual cases of holocervical (C1-C7) spinal ependymomas.

Case Description: Two patients, a 32-year-old female and a 24-year-old male presented with neck pain, motor, and sensory deficits.

Comparison of Clinical Outcomes Stratified by Target Delineation for Patients Undergoing Stereotactic Body Radiotherapy for Spinal Metastases.

Objective: Stereotactic body radiotherapy (SBRT) is an effective treatment of spinal metastases in the vertebral body. However, variation has existed between practitioners regarding the appropriate target delineation. As such, we compared the tumor control, rates of compression fractures, and pain control for patients who had undergone SBRT for spinal metastases to either the lesion only (LO) or the full vertebral body (FVB).

Natural history of the aging spine: a cross-sectional analysis of spinopelvic parameters in the asymptomatic population.

Objective: There have been numerous studies demonstrating increased pain and disability when patients' spinopelvic parameters fall outside of certain accepted ranges. However, these values were established based on patients suffering from spinal deformities. It remains unknown how these parameters change over a lifetime in asymptomatic individuals.

Cangrelor Bridging Within 6 Months of a Drug-Eluting Stent in a Patient for Emergency Cervical Spine Surgery: A Case Report.

The recommended duration of dual antiplatelet therapy after drug-eluting stent placement presents a dilemma for patients with recent stenting who require urgent or emergency noncardiac surgery. We present the case of a patient with recent drug-eluting stent placement (<6 months) on dual antiplatelet therapy who underwent successful emergency cervical spine surgery with antiplatelet therapy bridged using cangrelor, an intravenous P2Y12 inhibitor antiplatelet agent. Our experience illustrates the multidisciplinary approach to a patient with high thrombotic and bleeding risk who underwent neurosurgery off both aspirin and a P2Y12 inhibitor.

Quantitative Analysis of Neural Foramina in the Lumbar Spine: An Imaging Informatics and Machine Learning Study.

Purpose: To use machine learning tools and leverage big data informatics to statistically model the variation in the area of lumbar neural foramina in a large asymptomatic population.

Materials And Methods: By using an electronic health record and imaging archive, lumbar MRI studies in 645 male (mean age, 50.07 years) and 511 female (mean age, 48.

Cell Counting and Segmentation of Immunohistochemical Images in the Spinal Cord: Comparing Deep Learning and Traditional Approaches.

Estimation of cell nuclei in images stained for the c-fos protein using immunohistochemistry (IHC) is infeasible in large image sets. Use of multiple human raters to increase throughput often creates variance in the data analysis. Machine learning techniques for biomedical image analysis have been explored for cell-counting in pathology, but their performance on IHC staining, especially to label activated cells in the spinal cord is unknown.

ORCHESTRAL FULLY CONVOLUTIONAL NETWORKS FOR SMALL LESION SEGMENTATION IN BRAIN MRI.

White matter (WM) lesion identification and segmentation has proved of clinical importance for diagnosis, treatment and neurological outcomes. Convolutional neural networks (CNN) have demonstrated their success for large lesion load segmentation, but are not sensitive to small deep WM and sub-cortical lesion segmentation. We propose to use multi-scale and supervised fully convolutional networks (FCN) to segment small WM lesions in 22 anemic patients.

Autonomous Trajectory Planning for External Ventricular Drain Placement.

Background: External ventricular drain (EVD) placement is the most frequently performed neurosurgical procedure for management of various conditions including hydrocephalus, traumatic brain injury, and stroke. State-of-the-art computational pattern recognition techniques could improve the safety and accuracy of EVD placement. Placement of the Kocher's point EVD is the most common neurosurgical procedure which is often performed in urgent conditions.

Multi-Parameter Ensemble Learning for Automated Vertebral Body Segmentation in Heterogeneously Acquired Clinical MR Images.

The development of quantitative imaging biomarkers in medicine requires automatic delineation of relevant anatomical structures using available imaging data. However, this task is complicated in clinical medicine due to the variation in scanning parameters and protocols, even within a single medical center. Existing literature on automatic image segmentation using MR data is based on the analysis of highly homogenous images obtained using a fixed set of pulse sequence parameters (TR/TE).

Amyloid-β-related angiitis: a report of 2 cases with unusual presentations.

Amyloid-β-related angiitis (ABRA) is a rare complication of cerebral amyloid angiopathy in which amyloid-β deposition in the leptomeningeal and cortical vessels is associated with vasculitis characterized by transmural lymphohistiocytic, often granulomatous, inflammation. Patients usually present with acute to subacute cognitive dysfunction, headaches, and focal neurologic deficits. We report 2 cases of ABRA with unusual clinical presentations, including one case with fatal cerebral edema leading to herniation and Duret hemorrhages, and another associated with both lobar and deep parenchymal hemorrhages with intraventricular extension as well as hypercoagulability.