Prediction of long-term restenosis after carotid endarterectomy using quantitative magnetic resonance angiography

Abstract: Background: To detect restenosis after carotid endarterectomy (CEA), long-term monitoring is required. However, non-selective follow-up is controversial and can be limited by costs and logistical considerations.

Objective: To examine the value of immediate perioperative vessel flow measurements after CEA using quantitative magnetic resonance angiography (QMRA) to detect patients at risk of long-term restenosis.

Methods: A prospective cohort study with long-term sonographic follow-up after CEA for symptomatic internal carotid artery stenosis (ICAs) > 50%. In all patients, vessel flow has been assessed both pre- and postoperatively using QMRA within ±3 days of surgery. Data on QMRA assessment were analyzed to identify patients at risk of restenosis for up to 10 years.

Results: Restenosis was recorded in 4 of 24 patients (17%) at a median follow-up of 6.8 ± 2.6 years. None of them experienced an ischemic event. Perioperative flow differences were significantly greater in patients without long-term restenosis, both for the ipsilateral ICA (p < 0.001) and MCA (p = 0.03), compared to those with restenosis (p = 0.22 and p = 0.3, respectively). The ICA mean flow ratio (p = 0.05) tended to be more effective than the MCA ratio in predicting restenosis over the long term (p = 0.35).

Conclusion: Our preliminary findings suggest that QMRA-based mean flow increases after CEA may be predictive of restenosis over the long term. Perioperative QMRA assessment could become an operator-independent screening tool to identify a subgroup of patients at risk for restenosis, in whom long-term monitoring is advised

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• Umfang: Online-Ressource
• Sprache: Englisch
• Anmerkungen: Frontiers in neurology. - 13 (2022) , 862809, ISSN: 1664-2295

Beteiligte, Orts- und Zeitangaben

• Ereignis: Veröffentlichung
• (wo): Freiburg
• (wer): Universität
• (wann): 2022
• Urheber: Andereggen, Lukas ; Amin-Hanjani, Sepideh ; Beck, Jürgen ; Luedi, Markus M. ; Gralla, Jan ; Schubert, Gerrit A. ; Tortora, Angelo ; Andres, Robert H. ; Arnold, Marcel ; Raabe, Andreas ; Reinert, Michael

Weitere Informationen

• DOI: 10.3389/fneur.2022.862809
• URN: urn:nbn:de:bsz:25-freidok-2287095
• Rechteinformation: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 25.03.2025, 13:46 MEZ