S V Setlur Nagesh1,2, V Fennel3,2, J Krebs4, C Ionita4,5,2, J Davies3,2,6,7, D R Bednarek4,2,8, M Mokin9, A H Siddiqui4,2,8,7, S Rudin4,5,10,11,8. 1. From the Canon (formerly Toshiba) Stroke and Vascular Research Center (S.V.S.N., J.K., C.I., D.R.B., A.H.S., S.R.) ss438@buffalo.edu. 2. Departments of Neurosurgery (S.V.S.N., V.F., C.I., J.D., D.R.B., A.H.S.). 3. Department of Neurosurgery (V.F., J.D.), Gates Vascular Institute at Kaleida Health, Buffalo, New York. 4. From the Canon (formerly Toshiba) Stroke and Vascular Research Center (S.V.S.N., J.K., C.I., D.R.B., A.H.S., S.R.). 5. Departments of Biomedical Engineering (C.I., S.R.). 6. Bioinformatics (J.D.). 7. Jacobs Institute (J.D., A.H.S.), Buffalo, New York. 8. Radiology (D.R.B., A.H.S., S.R.), Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York. 9. Department of Neurosurgery and Brain Repair (M.M.), University of South Florida, Tampa, Florida. 10. Mechanical and Aerospace Engineering (S.R.). 11. Electrical Engineering (S.R.), University at Buffalo, State University of New York; Buffalo, New York.
Abstract
BACKGROUND AND PURPOSE: Quality of visualization of treatment devices during critical stages of endovascular interventions, can directly impact their safety and efficacy. Our aim was to compare the visualization of neurointerventional procedures and treatment devices using a 194-μm pixel flat panel detector mode and a 76-μm pixel complementary metal oxide semiconductor detector mode (high definition) of a new-generation x-ray detector system using a blinded-rater study. MATERIALS AND METHODS: Deployment of flow-diversion devices for the treatment of internal carotid artery aneurysms was performed under flat panel detector and high-definition-mode image guidance in a neurointerventional phantom simulating patient cranium and tissue attenuation, embedded with 3D-printed intracranial vascular models, each with an aneurysm in the ICA segment. Image-sequence pairs of device deployments for each detector mode, under similar exposure and FOV conditions, were evaluated by 2 blinded experienced neurointerventionalists who independently selected their preferred image on the basis of visualization of anatomic features, image noise, and treatment device. They rated their selection as either similar, better, much better, or substantially better than the other choice. Inter- and intrarater agreement was calculated and categorized as poor, moderate, and good. RESULTS: Both raters demonstrating good inter- and intrarater agreement selected high-definition-mode images with a frequency of at least 95% each and, on average, rated the high-definition images as much better than flat panel detector images with a frequency of 73% from a total of 60 image pairs. CONCLUSIONS: Due to their higher resolution, high-definition-mode images are sharper and visually preferred compared with the flat panel detector images. The improved imaging provided by the high-definition mode can potentially provide an advantage during neurointerventional procedures.
BACKGROUND AND PURPOSE: Quality of visualization of treatment devices during critical stages of endovascular interventions, can directly impact their safety and efficacy. Our aim was to compare the visualization of neurointerventional procedures and treatment devices using a 194-μm pixel flat panel detector mode and a 76-μm pixel complementary metal oxide semiconductor detector mode (high definition) of a new-generation x-ray detector system using a blinded-rater study. MATERIALS AND METHODS: Deployment of flow-diversion devices for the treatment of internal carotid artery aneurysms was performed under flat panel detector and high-definition-mode image guidance in a neurointerventional phantom simulating patient cranium and tissue attenuation, embedded with 3D-printed intracranial vascular models, each with an aneurysm in the ICA segment. Image-sequence pairs of device deployments for each detector mode, under similar exposure and FOV conditions, were evaluated by 2 blinded experienced neurointerventionalists who independently selected their preferred image on the basis of visualization of anatomic features, image noise, and treatment device. They rated their selection as either similar, better, much better, or substantially better than the other choice. Inter- and intrarater agreement was calculated and categorized as poor, moderate, and good. RESULTS: Both raters demonstrating good inter- and intrarater agreement selected high-definition-mode images with a frequency of at least 95% each and, on average, rated the high-definition images as much better than flat panel detector images with a frequency of 73% from a total of 60 image pairs. CONCLUSIONS: Due to their higher resolution, high-definition-mode images are sharper and visually preferred compared with the flat panel detector images. The improved imaging provided by the high-definition mode can potentially provide an advantage during neurointerventional procedures.
Authors: Swetadri Vasan Setlur Nagesh; Kunal Vakharia; Muhammad Waqas; Vernard S Fennell; Gursant S Atwal; Hussain Shallwani; Daniel R Bednarek; Jason M Davies; Kenneth V Snyder; Maxim Mokin; Stephen Rudin; Elad I Levy; Adnan H Siddiqui Journal: J Neuroimaging Date: 2019-07-24 Impact factor: 2.486