Paraganglioma of the cauda equina – Case Report and Literature Review

Paragangliomas of the cauda equina are tumors of rare incidence, with ∼ 220 cases described in the world literature. They are benign lesions, grade I by the World Health Organization (WHO), whose definitive diagnosis can only be made by immunohistochemical analysis. Its neuroendocrine nature is evidenced by the presence of chromogranin. The relevance of reporting this case is because paragangliomas of the cauda equina should be included among the differential diagnoses of intradural and extramedullary tumors, and especially because they can cause perioperative and intraoperative hypertensive crises by adrenergic discharge.The present study presents the case of a 36-year-old male patient diagnosed with a lumbar spine tumor located in the central spinal canal that presented as cauda equina syndrome involving 4 months of bilateral sciatica, paraparesis, urinary and fecal retention. The diagnosis of paraganglioma was confirmed by immunohistochemical positivity for chromogranin after microsurgical resection of the tumor.

Classification of Spine Image from MRI Image Using Convolutional Neural Network

The spine tumor is a fast-growing abnormal cell in the spinal canal or vertebrae of the spine, it affected many people. Thousands of researchers have focused on this disease for better understanding of tumor classification to provide more effective treatment to the patients. The main objective of this paper is to form a methodology for classification of spine image. We proposed an efficient and effective method that helpful for classifying the spine image and identified tumor region without any human assistance. Basically, Contrast Limited Adaptive Histogram Equalization used to improve the contrast of spine images and to eliminate the effect of unwanted noise. The proposed methodology will classify spine images as Normal or Abnormal using Convolutional Neural Network (CNN) model algorithm. The CNN model can classify spine image as Normal or Abnormal with 99.4% Accuracy, 94.5% Sensitivity, 95.6% Precision, and 99.9% specificity. Compared with the previous existing methods, our proposed solution achieved the highest performance in terms of classification based on the spine dataset. From the experimental results performed on the different images, it is clear that the analysis for the spine tumor detection is fast and accurate when compared with the manual detection performed by radiologists or clinical experts, So, anyone can easily identify the tumor affected area also determine abnormal images.

Replantation of Spinous Process-lamina Complex in the Treatment of Cervical Spine Tumor : Two Cases Report and Literature Review

Purpose: The primary aim of our study was to prove that the replantation of spinous process-lamina complex is beneficial to restore the anatomical structure and function of the spine, and to find if it can reduce postoperative complications.Methods: We report two cases of cervical intraspinal tumor, whose postoperative pathological diagnosis, Respectively, are Neurilemmoma and meningioma. They all underwent the resection and replantation of spinous process-lamina complex, in which the resected spinous process-lamina complex was replanted at the end of the procedure, allowing a complete reconstruction of the posterior element of the spinal canal. Results：After the surgery, the symptoms were relieved, and no dysfunction of upper limbs and sphincter was observed. The tumors were benign pathologically and were diagnosed as Neurilemmoma and meningioma. The patient recovered and at 6-month follow-up had no complaints and in good health.Conclusion: After tumor resection, the replantation of spinous process-lamina complex is beneficial to restore the anatomical structure and function of the spine.