Publications by authors named "Xinben Hu"

Current navigation systems employing intraoperative CT have been applied in spinal interventions for accurate and visualized guidance. The consequential issue of radiation doses and surgical workflow disruption spotlighted ultrasound (US) as an alternative imaging modality. However, the challenge of anatomy interpretation left US-based navigation inadequate in visualization, resulting in the necessity of registration of preoperative images.

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Background: Spinal epidural arachnoid cysts (SEACs) are rare, non-neoplastic pathologies that can cause compressive myelopathy. Preoperative identification of the exact fistula location is crucial for minimally invasive management.

Methods: This single-center retrospective study included 27 patients with SEACs who underwent "double-needle puncture myelography" to precisely localize the fistula before minimally invasive surgery.

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Handheld robots offer accessible solutions with a short learning curve to enhance operator capabilities. However, their controllable degree-of-freedoms are limited due to scarce space for actuators. Inspired by muscle movements stimulated by nerves, we report a handheld time-share driven robot.

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Background: Schwannoma, a benign peripheral nerve sheath tumor, is perhaps only secondary to degenerative pathology as the most common lesion at neural foramen. The surgical dilemma here is either risking nerve injury because of inadequate exposure or the need for internal fixation because of facet joint sacrifice.

Objective: To evaluate the feasibility and safety of management of foraminal schwannomas by percutaneous full-endoscopic technique.

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Background And Objectives: Spontaneous spinal epidural hematoma (SSEH) is an uncommon but serious condition with a high morbidity rate. Although SSEH is related to numerous risk factors, its etiology remains unclear. There is a paucity of data on its prognostic factors.

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Article Synopsis
  • This study evaluated how well convolutional neural network (CNN) models can diagnose Chiari malformation type I (CMI) by comparing the craniocervical junction features of patients with CMI to healthy controls using MRI images.
  • A total of 148 CMI patients and 205 healthy controls were included, utilizing various MRI slices to train and test the CNN models.
  • The results showed that the CNN models had exceptional diagnostic accuracy, with 100% accuracy in one dataset, demonstrating their potential as a reliable tool for diagnosing CMI.
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Background: Pituitary adenoma (PA) is a benign neuroendocrine tumor caused by adenohypophysial cells, and accounts for 10%-20% of all primary intracranial tumors. The surgical outcomes and prognosis of giant pituitary adenomas measuring ≥3 cm in diameter differ significantly due to the influence of multiple factors such as tumor morphology, invasion site, pathological characteristics and so on. The aim of this study was to explore the risk factors related to the recurrence or progression of giant and large PAs after transnasal sphenoidal surgery, and develop a predictive model for tumor prognosis.

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Mitochondria are highly dynamic organelles which are joined by mitochondrial fusion and divided by mitochondrial fission. The balance of mitochondrial fusion and fission plays a critical role in maintaining the normal function of neurons, of which the processes are both mediated by several proteins activated by external stimulation. Cerebral ischemia-reperfusion (I/R) injury can disrupt the balance of mitochondrial fusion and fission through regulating the expression and post-translation modification of fusion- and fission-related proteins, thereby destroying homeostasis of the intracellular environment and causing neuronal death.

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