Trigeminal neuralgia: Assessment of neurovascular decompression by 3D fast imaging employing steady-state acquisition and 3D time of flight multiple overlapping thin slab acquisition magnetic resonance imaging.

BACKGROUND: Trigeminal neuralgia is most commonly caused by vascular compression at the trigeminal nerve (TN) root entry zone. Microvascular decompression (MVD) has been established as a useful treatment. Outcome depends on the correct identification of the compression site and its adequate decompression at surgery. Preoperative identification of neurovascular compression might predict which patients will benefit from MVD. Management of persistent or recurrent trigeminal neuralgia after an MVD is a baffling problem for neurosurgeons. An accurate neuroradiological evaluation of the TN padding following a failed MVD might help identify the underlying cause and plan further treatment.

CASE DESCRIPTION: A 68-year-old female presented with a right-sided trigeminal neuralgia (V3) refractory to medical therapy. A high-resolution three-dimensional magnetic resonance imaging (3D MRI) study included fast imaging employing steady-state acquisition (FIESTA) and time of flight multiple overlapping thin slab acquisition (TOF MOTSA) sequences to evaluate the neurovascular anatomy in the cerebellopontine angle. An unambiguous compression of the right TN at the rostral-medial site by the superior cerebellar artery (SCA) was identified. The SCA loop compressing the TN was identical in location and configuration to that predicted in the preoperative study. After the MVD, the patient was relieved from her pain and a postoperative high-resolution 3D MRI study confirmed the appropriate placement of the Teflon implant between the TN and SCA.

CONCLUSION: To our knowledge, this is the first report that characterizes the proper TN padding by high-resolution 3D MRI after trigeminal MVD. The present case also emphasizes the importance of performing a 3D MRI in patients with trigeminal neuralgia to anticipate the surgeon's view and predict the outcome after MVD.