| Literature DB >> 34125300 |
Sri Hari Sundararajan1, Srirajkumar Ranganathan2, Vaishnavi Kishore3, Raphael Doustaly3, Athos Patsalides4.
Abstract
BACKGROUND: This report addresses the feasibility of virtual injection software based on contrast-enhanced cone-beam CTs (CBCTs) in the context of cerebrovascular lesion embolization. Intracranial arteriovenous malformation (AVM), dural arteriovenous fistula (AVF) and mycotic aneurysm embolization cases with CBCTs performed between 2013 and 2020 were retrospectively reviewed. Cerebrovascular lesions were reviewed by 2 neurointerventionalists using a dedicated virtual injection software (EmboASSIST, GE Healthcare; Chicago, IL). Points of Interest (POIs) surrounding the vascular lesions were first identified. The software then automatically displayed POI-associated vascular traces from vessel roots to selected POIs. Vascular segments and reason for POI identification were recorded. Using 2D multiplanar reconstructions from CBCTs, the accuracy of vascular traces was assessed. Clinical utility metrics were recorded on a 3-point Likert scale from 1 (no benefit) to 3 (very beneficial).Entities:
Keywords: AVM; CBCT; Cerebrovascular lesion; Cone-beam CT; Embo ASSIST; Endovascular embolization; Mycotic aneurysm; Vessel detection software; Virtual catheterization; Virtual injection; dAVF
Year: 2021 PMID: 34125300 PMCID: PMC8203774 DOI: 10.1186/s42155-021-00242-6
Source DB: PubMed Journal: CVIR Endovasc ISSN: 2520-8934
Fig. 1Use of virtual injection software in neurointerventional radiology. Patient with an AVM the left medial frontal lobe with subjacent flow-related aneurysm. The vascular tree was automatically extracted, and the bones removed (a). The neuro interventionalist used the virtual microcatheter (the red trace) to review the potential AVM feeders on both the 3D volume rendering (b) and the cross-sectional views (c). On initial glance, apparent primary feeder to the AVM seems to be the anterior cerebral artery (c, blue arrow). However, the software accurately identified this as an en passage vessel supplying the flow-related aneurysm, with subsequent correct identification of the true AVM feeders arising from small caliber lenticulostriate vessels (c-d, red line). Even though it was also possible to simulate injections from the same points (additional distal contrast flow is simulated past the red line in green, d-e), the interventionalist were less interested by this feature as the software prediction are unreliable inside the AVM. The simulated catheterizations were saved as 3D model (f), which could be used in addition to the full vascular in augmented fluoroscopy (g- full vascular tree; h- targeted vessel; i – example of catheterization guidance)
Accuracy Classifications for Traced Vessels
| Classification | Definition |
|---|---|
| Accurate | Vessel tracking is correct from the vascular tree root to the POI |
| Clinically Usable | Vessel tracking is correct for major branch points but incorrectly traces distal vessels |
| Not Clinically Usable | Vessel tracking is wrong for major branch points and distal vessels |
| Not Detected | Vessel cannot be tracked using VI |
Clinical Utility Questions
| How helpful was VI in distinguishing between close arterial branches? | |
| How helpful would you expect VI to be in decreasing necessary catheterizations? | |
| How helpful would you expect the VI 3D overlay to be in navigating to the POI? | |
| How helpful would you expect VI to be in decreasing contrast usage? | |
| How helpful would you expect VI to be in decreasing the necessity of 2D roadmapping during procedures? | |
| How helpful would you expect VI to be in improving your ability to select the correct vessels for embolization? | |
| How helpful would you expect VI to be planning a procedure? | |
| Were you able to select (an) embolization point(s) for this case using VI? |
Summary Characteristics
| | 9 | ||
| Injection Point | Right Internal Carotid Artery | 4 | |
| Left Internal Carotid Artery | 2 | ||
| Right Vertebral Artery | 1 | ||
| Left Vertebral Artery | 2 | ||
| | 13 | 21 | |
| Avg Segmental Location | 3.3 | 3.6 | |
| Total Segments | 43 | 76 | |
| Segmental Location | 1st order | – | – |
| 2nd order | 2 | 1 | |
| 3rd order | 5 | 6 | |
| 4th order | 6 | 14 | |
| Arterial Location | Posterior Cerebral Artery | 5 | 5 |
| Middle Cerebral Artery | 2 | 5 | |
| Anterior Cerebral Artery | 2 | 6 | |
| Superior Cerebellar Artery | – | 2 | |
| Anterior Choroidal Artery | 1 | 1 | |
| Posterior Inferior Cerebellar Artery | – | 1 | |
| Inferolateral Trunk | – | 1 | |
| Lenticulostriate Artery | 1 | – | |
| Posterior Communicating Artery | 1 | – | |
| Meningohypophyseal Trunk | 1 | – | |
| Purpose of Selection | Embolization | 13 | 16 |
| Eliminate Suspect Feeder | – | 4 | |
| Confirm En Passage | – | 1 | |
Fig. 2Retrospective review of an AVM. Each potential AVM supplying vessel was interrogated using virtual catheterization software on the 3D volume rendering. Three Points Of Interest (POIs) were identified and exported as 3D models (a). The virtual catherization trace was then reviewed for each POI on cross sectional views to assess its accuracy, as shown in coronal and sagittal reconstruction for POI 1 (b-c), and sagittal reconstructions for POI 2 (b) and POI 3 (c)
Fig. 3Retrospective review of a distal aneurysm. Virtual catheterization software was also evaluated for distal embolization, such as in a context of mycotic aneurysm. The software was used to create a 3D roadmap based on the CBCT (a). The accuracy of the 3D roadmap was assessed using the virtual catheterization trace on the cross-sectional views (b)
Clinical Utility Questions and Scores
| Question | Average Utility Score (Reviewer A Avg, Reviewer B Avg) | Inter-Reader Agreement Percentage |
|---|---|---|
| Distinguishing between close arterial branches | 2.9 (2.8, 3) | 77.8% |
| Decreasing necessary catheterizations | 2.6 (2.6, 2.6) | 66.7% |
| Navigation to POI as a 3D overlay | 2.8 (2.6, 3) | 55.6% |
| Decreasing contrast usage | 2.6 (2.7, 2.6) | 66.7% |
| Decreasing 2D roadmapping during procedures | 2.6 (2.7, 2.6) | 66.7% |
| Improving ability to select vessels for embolization | 2.7 (2.7, 2.8) | 66.7% |
| Planning a procedure | 2.8 (2.8, 2.8) | 66.7% |
| Identification of embolization point(s) | 2.8 (2.8, 2. 8) | 66.7% |