Bypass-assisted trapping and excision of a thrombosed giant M1 aneurysm with unpreservable lenticulostriate arteries: A case report

Background: Giant thrombosed aneurysms of the M1 segment of the middle cerebral artery (MCA) are rare and technically demanding lesions. Surgical management is particularly challenging when the lenticulostriate arteries (LSAs) are involved, as their preservation is often difficult and the risk of ischemic complications is substantial. Case Description: A 15-year-old boy presented with seizures, and neuroimaging revealed a partially thrombosed giant aneurysm measuring 55 mm involving the entire M1 segment. Digital subtraction angiography demonstrated severe flow stagnation within the aneurysm, associated with reduced cerebral blood flow (CBF) and the development of collateral circulation. No LSAs or other perforating arteries arising from the M1 trunk were identified angiographically. The patient was initially managed conservatively; however, progressive aneurysm enlargement resulted in neurological deterioration, cerebral edema, and infarction of the caudate head. Surgical intervention consisting of superficial temporal artery–MCA bypass, complete M1 trapping, and aneurysm excision was subsequently performed. Postoperative imaging showed no additional ischemic lesions, and postoperative CBF increased with clinical improvement. The unexpectedly favorable course following complete M1 trapping may have been influenced by preexisting collateral circulation, including leptomeningeal pathways; however, the precise contribution of perforator-related collateral flow could not be determined. Conclusion: This case illustrates an uncommon clinical course following complete M1 trapping for a thrombosed giant aneurysm. Although preservation of LSAs is generally considered critical, this experience suggests that bypass-assisted trapping may be feasible in carefully selected cases with well-developed collateral circulation, highlighting the complexity of cerebral collateral pathways and the difficulty of predicting ischemic risk.