Login / Signup

Anterior Ethmoidal Artery: A Computed Tomography Analysis and New Classifications.

Mohammad Waheed El-AnwarAlaa Omar KhazbakDiaa Bakry EldibHesham Youssef Algazzar
Published in: Journal of neurological surgery. Part B, Skull base (2020)
Objective  to determine the anterior ethmoidal artery (AEA) anatomy and variations by computed tomography (CT) in adult and their relations to and presents new AEA classifications. Methods  One hundred and fifty paranasal CT scans (300 sides) were included. Axial images were acquired with multiplanar reformates to obtain delicate details in coronal and sagittal planes. Results  One hundred and forty-four AEAs canal (48%), 293 AEAs foramen (97.7%), and 229 AEAs sulcus could be detected (76.3%). The mean AEA intranasal length was 6.7 ± 1.27 mm (range: 4.24-10.6 mm). The mean angle between AEA and lamina papyracea was 105.49 ± 9.28 degrees (range: 76.41-129.76 degrees). Of them, 95.8% AEAs had an angle with lamina >90 degrees, while 4.2% had angle <90 degrees. The mean angle between AEA and lateral lamella of cribriform plate was 103.95 ± 13.08 degrees (range: 65.57-141.36 degrees). Of them, 87.5% AEAs had an angle >90 degrees and 12.5% had an angle <90 degrees. The mean distance between AEA and skull base was 1.37 ± 1.98 mm (range: 0-8.35 mm). The AEA types in relation to skull base was type 1 (0-2 mm from skull base; 64.6%), type 2 (2-4 mm; 22.2%), type 3 (4-6 mm; 11.1%), and type 4 (>6 mm; 2.1%). The mean distance between the AEA and frontal sinus ostium was 9.17 ± 4.72 mm (range: 0-25.36 mm). AEA classification according to distance from AEA to frontal sinus ostium was 17.4% type 1 (<5 mm), 41.7% type 2 (5-10 mm), 31.9% type 3 (10-15 mm), and 9% type 4 (>15 mm). Conclusion  Provided AEA details improve surgeons' awareness of AEA variations in the endoscopic field and can help residents in training.
Keyphrases
  • computed tomography
  • high resolution
  • positron emission tomography
  • dual energy
  • machine learning
  • deep learning
  • magnetic resonance
  • mass spectrometry
  • young adults
  • quality improvement
  • virtual reality