• Niveditha Manjunath, Rohan Raju Dhanakshirur, Siddharth Joshi, Nikhila Gunna Reddy, Amol Raheja, Leve Joseph Devrajan Sebastian, Ajay Garg, Prem Kumar Kalra, and Ashish Suri.
• Department of Neurosurgery, All India Institute of Medical Sciences, New Delhi.
• World Neurosurg. 2023 Oct 27.

IntroductionMoyamoya disease (MMD) is characterised by supraclinoid internal carotid artery (ICA) narrowing causing cerebral parenchyma to starve. Direct and indirect revascularisation techniques are the treatment norm. We provide a clinicoradiological comparison of single and double barrel superficial temporal artery to middle cerebral artery (STA-MCA) bypass for MMD. The perfusion in cerebral hemispheres and vessel density in DSA have been evaluated using novel algorithms.MethodsDSA, ASL MR imaging methods and Suzuki, Matsushima, Angiographic Outcome Score (AOS) scales were used to quantify perfusion parameters; modified Rankin score (mRS) was used for clinical evaluation. A novel image processing algorithm was designed to perform analysis of ASL sequences and compare perfusion. Vessel density was calculated using connected component analysis on thresholded DSA images.Results54 hemispheres with MMD underwent STA-MCA bypass 42(77.8%) single barrel and 12 (22.2%) double barrel. Clinical outcome - mRS was significant with p<0.001 in single barrel and p=0.001 in double barrel groups. The overall AOS showed improvement post-operatively (p=0.032).Perfusion analysis was performed in 20 hemispheres (13 single barrel; 7 double barrel). MCA territories showed significant improvement in single barrel (2.72%, p=0.0294) and double barrel groups (12.89%, p=0.025). Vessel density calculated in MCA territory, showed an overall post-op improvement (p=1.75 x 10-8).ConclusionDouble barrel STA-MCA bypass clinically as well as radiologically improves perfusion in the ACA as well as MCA territories in MMD. The novel image processing algorithm is an accurate, objective tool to evaluate perfusion in MR images and vessel density in DSA images of MMD.Copyright © 2023. Published by Elsevier Inc.

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