Publications by authors named "Kevin T Huang"

Background: Stroke imposes an enormous economic burden on patients and caregivers. Online crowdfunding is widely used to address healthcare costs, reflecting social safety net gaps, yet it has not been studied for stroke. We performed the first national analysis of stroke-related crowdfunding, evaluating fund totals, success rates, geography, and stroke etiology.

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Objective: Online crowdfunding, commonly used to cover healthcare costs for vulnerable populations, is directly linked to health disparities and gaps in social safety-net systems. The nationwide impact of crowdfunding on neurosurgery remains unclear. We aimed to characterize the funds raised, success rate, geographic distribution, and most frequent conditions for neurosurgery-related crowdfunding campaigns.

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Objective: Large language models (LLMs) have shown promising performance on medical licensing examinations, but their ability to excel in subspecialty domains and their robustness under adversarial conditions remain unclear. Herein, the authors present AtlasGPT, a subspecialty-focused LLM for neurosurgery, and evaluate its performance on a benchmark multiple-choice question bank and under adversarial testing, as well as its ability to generate high-quality explanations.

Methods: AtlasGPT was built by fine-tuning GPT-4 architecture and retrieval-augmented generation from neurosurgical knowledge sources.

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Background: Large Language Models (LLMs) have demonstrated significant capabilities to date in working with a neurosurgical knowledge-base and have the potential to enhance neurosurgical practice and education. However, their role in the clinical workspace is still being actively explored. As many neurosurgeons seek to incorporate this technology into their local practice environments, we explore pertinent questions about how to deploy these systems in a safe and efficacious manner.

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Article Synopsis
  • Large Language Models (LLMs) are gaining attention in neurosurgery, with potential benefits, but their effectiveness across various surgical tasks remains under-researched.
  • A systematic review of literature revealed 51 articles focusing on LLM applications, notably in clinical text generation, exam question answering, and decision-making support, predominantly using models like GPT-3.5 and GPT-4.
  • While many studies utilized LLMs in a straightforward manner, there is a call for more rigorous guidelines and reproducibility in future research to fully harness their capabilities.
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Objective: Patient-reported outcome measures (PROMs) are utilized to assess surgical success but are limited by data collection, response bias, and subjectivity. The large volume of digital healthcare data offers a new method to utilize healthcare utilization as a longitudinal, individualized, and objective proxy for health needs among surgical patients. This study aimed to design and evaluate a novel resource utilization in spine healthcare (RUSH) clustering method that complements PROMs in evaluating postoperative patient outcomes.

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  • Ventricular shunts are the primary treatment for adult hydrocephalus, but diagnosing shunt malfunctions can be tricky; computer vision algorithms might help automate this process.
  • A feasibility study involved 191 adult hydrocephalus patients and their CT scans, where a machine learning algorithm was trained to identify brain ventricle sizes.
  • The algorithm showed a high performance (average Dice score of 0.809) and accurately predicted shunt revisions in 92.3% of cases, indicating its potential reliability in clinical settings.
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  • A study assessed the responses of GPT-4.0 to 35 clinical questions in neurosurgery, evaluated by attending neurosurgeons for accuracy, safety, and helpfulness.
  • Overall, GPT-4.0 showed a high consistency with medical guidelines and provided clinically useful information; however, it also generated some unrealistic and potentially risky responses.
  • The model's citation accuracy was poor, with only 50% of references deemed valid, highlighting the need for clinicians to be cautious when using AI in medical practice.
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Article Synopsis
  • Machine learning (ML) is rapidly growing in neurosurgery, leading to more complex publications that neurosurgeons need to understand to effectively use in practice.
  • The authors conducted a literature search for ML studies in neurosurgery and developed a checklist with 14 questions to help readers evaluate ML methodologies and findings.
  • With the goal of enhancing neurosurgeons' ability to incorporate ML into their work, the authors emphasize the need for education on ML techniques and the review process.
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Background And Purpose: Fractal dimension is an objective metric for the notion of structural complexity. We sought to investigate differences in structural complexity between healthy and affected territories of cerebral vasculature in moyamoya, as well as associated scalp vasculature and native transdural collaterals in patients with moyamoya by comparing their respective fractal dimensions.

Methods: Our cohort consisted of 15 transdural collaterals from 12 patients with unilateral anterior circulation moyamoya.

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Background: Interbody fusion is a widely utilized and accepted procedure to treat advanced debilitating lumbar degenerative disc disease (DDD). Increasingly, surgeons are seeking interbody devices that are large for stability and grafting purposes but can be inserted with less invasive techniques. To achieve these contrary objectives a novel, conformable mesh interbody fusion device was designed to be placed in the disc space through a small portal and filled with bone graft in situ to a large size.

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Traumatic spinal cord injury (tSCI) is a life-changing and potentially overwhelming event. The sudden disruption of the spinal cord's integrity necessitates rapid attention at a specialized medical center, and involves a multilateral collaboration between neurologists, spine surgeons, critical care physicians, and trauma specialists. Even with care under ideal conditions, many tSCI patients have significant disability that persists for the rest of their lives.

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Study Design: A prospective multicenter investigational device exempt trial is underway evaluating a novel conformable mesh interbody fusion device in subjects undergoing single-level fusion for degenerative disc disease. Patients meeting inclusion and exclusion criteria were offered enrollment. There is no comparative group in this study.

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Objective: Minimal access ablative techniques have emerged as a less invasive option for spinal metastatic disease reduction and separation from neural tissue. Compared with heat-based ablation modalities, percutaneous image-guided cryoablation allows for more distinct visualization of treatment margins. The authors report on a series of patients undergoing MRI-guided cryoablation as a feasible method for treating spinal metastatic disease.

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Objective: Recent advances in computer vision have revolutionized many aspects of society but have yet to find significant penetrance in neurosurgery. One proposed use for this technology is to aid in the identification of implanted spinal hardware. In revision operations, knowing the manufacturer and model of previously implanted fusion systems upfront can facilitate a faster and safer procedure, but this information is frequently unavailable or incomplete.

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Background: The cervicothoracic junction (CTJ) has often been identified as an area of biomechanical vulnerability; however, few studies have examined the relative merits of extending fusions across this area. In this study, we sought to investigate the tradeoffs involved in fusing across the CTJ in cases of elective posterior cervical laminectomy and fusion.

Methods: We conducted a single-institution retrospective cohort study of patients undergoing elective, multilevel, posterior cervical decompression and fusion for degenerative cervical stenosis.

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Background: Chronic subdural hematoma (cSDH) is a common neurosurgical condition, with symptoms ranging from headaches to coma. Operative evacuation is the treatment of choice. Subdural reaccumulation leading to reoperation is a vexing postoperative complication.

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Objective: Patients with extradural spine tumors are at an increased risk for intraoperative cerebrospinal fluid (CSF) leaks and postoperative wound dehiscence due to radiotherapy and other comorbidities related to systemic cancer treatment. In this case series, we discuss our experience with the management of intraoperative durotomies and wound closure strategies for this complex surgical patient population.

Methods: We reviewed our recent single-center experience with spine surgery for primarily extradural tumors, with attention to intraoperative durotomy occurrence and postoperative wound-related complications.

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Objective: For cases of cervical osteomyelitis that require surgery, concern has continued regarding instrumentation owing to the potential for bacterial seeding of the hardware. We performed a systematic review of the current data.

Methods: A search was performed using Medline, Embase, and Ovid for articles using the keywords "cervical osteomyelitis/spondylodiscitis" and "fusion" or "instrumentation" reported from 1980 to 2017.

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Spinal hemangiomas are common, benign vascular lesions that involve the bony portion of vertebral bodies and are generally asymptomatic. Rarely, they can become aggressive and present with predominantly epidural extension, mimicking other neoplasms. We present the case of a fifty-one year old woman who presented with myelopathy and was discovered to have a large mass causing epidural spinal cord compression, thought to be due to a peripheral nerve sheath tumor.

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