Osama Ahmed1, Shihao Zhang2, Benjamin L Brown3, Jaime Toms4, Eduardo Gonzalez-Toledo5, Bharat Guthikonda6, Hugo Cuellar7. 1. Department of Neurosurgery, Louisiana State University Health Sciences Center, USA oahmed@lsuhsc.edu. 2. Department of Neurosurgery, Louisiana State University Health Sciences Center, USA. 3. Department of Neurosurgery, Mayo Clinic, USA. 4. Department of Neurosurgery, Virginia Commonwealth University, USA. 5. Department of Radiology, Neurology, and Anesthesiology, Louisiana State University Health Sciences Center, USA. 6. Associate Professor, Director of Skull Base Research, Department of Neurosurgery, Louisiana State University Health Sciences Center, Shreveport, LA, USA. 7. Associated Professor of Neurosurgery, Director of Neurointerventional Surgery, Department of Neurosurgery, Louisiana State University Health Sciences Center, Shreveport, LA, USA.
Abstract
BACKGROUND: Preoperative assessment of anterior communicating artery (AcoA) aneurysms with cerebral angiography is common, but not without risk. Computed tomography angiography (CTA) is a widely available imaging modality that provides quick acquisition, low morbidity, and low cost. One disadvantage is that it does not provide dynamic information. In this study, the authors sought to determine whether CTA alone can reliably predict the inflow dominance to an AcoA aneurysm. METHODS: Eighty-three patients with ruptured AcoA aneurysms were reviewed retrospectively. Only those patients with both preoperative CTA and cerebral angiogram were included, thus excluding six patients. Four independent observers reviewed the CTAs and attempted to identify the dominant A1. Additionally, three mathematical models were created to identify the dominant A1. These responses were compared to cerebral angiograms. RESULTS: Four observers were correct in judging the dominant A1 an average of 93% of the time. Seventeen cases were read incorrectly by only one of four observers, and three cases were read incorrectly by two observers. For cases with incorrect readings, the average percentage difference in A1 sizes was 19.6%. For cases read unanimously correct, the average percentage difference in A1 sizes was 42.7%. Mathematical model #3 correctly evaluated the dominant A1 in 97% of the cases. CONCLUSIONS: This study found CT angiograms can be reliable in predicting the inflow dominance to the majority of AcoA aneurysms.
BACKGROUND: Preoperative assessment of anterior communicating artery (AcoA) aneurysms with cerebral angiography is common, but not without risk. Computed tomography angiography (CTA) is a widely available imaging modality that provides quick acquisition, low morbidity, and low cost. One disadvantage is that it does not provide dynamic information. In this study, the authors sought to determine whether CTA alone can reliably predict the inflow dominance to an AcoA aneurysm. METHODS: Eighty-three patients with ruptured AcoA aneurysms were reviewed retrospectively. Only those patients with both preoperative CTA and cerebral angiogram were included, thus excluding six patients. Four independent observers reviewed the CTAs and attempted to identify the dominant A1. Additionally, three mathematical models were created to identify the dominant A1. These responses were compared to cerebral angiograms. RESULTS: Four observers were correct in judging the dominant A1 an average of 93% of the time. Seventeen cases were read incorrectly by only one of four observers, and three cases were read incorrectly by two observers. For cases with incorrect readings, the average percentage difference in A1 sizes was 19.6%. For cases read unanimously correct, the average percentage difference in A1 sizes was 42.7%. Mathematical model #3 correctly evaluated the dominant A1 in 97% of the cases. CONCLUSIONS: This study found CT angiograms can be reliable in predicting the inflow dominance to the majority of AcoA aneurysms.
Authors: Robert A Willinsky; Steve M Taylor; Karel TerBrugge; Richard I Farb; George Tomlinson; Walter Montanera Journal: Radiology Date: 2003-03-13 Impact factor: 11.105
Authors: Jens-Christian Altenbernd; Sebastian Fischer; Wolfram Scharbrodt; Sebastian Schimrigk; Jens Eyding; Hannes Nordmeyer; Christine Wohlert; Nils Dörner; Yan Li; Karsten Wrede; Daniela Pierscianek; Martin Köhrmann; Benedikt Frank; Michael Forsting; Cornelius Deuschl Journal: Front Neurol Date: 2022-10-03 Impact factor: 4.086