Computational biomarkers are a promising area of research for the decision of neurosurgical treatment for brain tumors. These biomarkers can help to predict the biological behavior of tumors, such as their growth rate, invasiveness, and response to treatment. Computational biomarkers can play an important role in the decision-making process for the neurosurgical treatment of brain tumors. These biomarkers provide quantitative and objective measures of tumor characteristics that can help inform the choice of treatment and predict patient outcomes.
Some potential computational biomarkers that may be useful in this context include:
Introduction
Spinal intramedullary dermoid is very rare, accounting for <1% of intraspinal tumors. It can be congenital or acquired. They usually present in 2nd or 3rd decade of life in adults. It may or may not associated with spinal dysraphism. It is asymptomatic in most cases, manifest acutely if it ruptures.
Long segment involvement of spinal intramedullary tumor in adult without the history of trauma makes this case unique. Fat suppression imaging helps to distinguish adipose tissue from lesions causing hematomyelia in patients presented with intramedullary hyperintensity in both T1 & T2 sequences of MRI spine.
Case presentation
We report here a rare case of 30 years old male who presented to us with sudden urinary retention followed by rapidly progressive quadriparesis and paresthesia in his right arm. In MRI, spinal intramedullary tumor was noted from medulla till D5 vertebra. We performed subtotal excision of tumor and sample sent for histopathology which proved it to be intramedullary spinal dermoid cyst.
Conclusion
Long segment involvement of spinal intramedullary dermoid cyst in adult without history of trauma makes this case different. Fat suppression imaging must be done in patients with intramedullary hyperintensity in both T1 and T2 sequences of MRI spine. Early diagnosis and appropriate management will be helpful in reducing morbidity.
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