Hemodynamic Analysis Shows High Wall Shear Stress Is Associated with Intraoperatively Observed Thin Wall Regions of Intracranial Aneurysms

BACKGROUND

Studying the relationship between hemodynamics and local intracranial aneurysm (IA) pathobiology can help us understand the natural history of IA. We characterized the relationship between the IA wall appearance, using intraoperative imaging, and the hemodynamics from CFD simulations.

METHODS

Three-dimensional geometries of 15 IAs were constructed and used for CFD. Two-dimensional intraoperative images were subjected to wall classification using a machine learning approach, after which the wall type was mapped onto the 3D surface. IA wall regions included thick (white), normal (purple-crimson), and thin/translucent (red) regions. IA-wide and local statistical analyses were performed to assess the relationship between hemodynamics and wall type.

RESULTS

Thin regions of the IA sac had significantly higher WSS, Normalized WSS, WSS Divergence and Transverse WSS, compared to both normal and thick regions. Thicker regions tended to co-locate with significantly higher RRT than thin regions. These trends were observed on a local scale as well. Regression analysis showed a significant positive correlation between WSS and thin regions and a significant negative correlation between WSSD and thick regions.

CONCLUSION

Hemodynamic simulation results were associated with the intraoperatively observed IA wall type. We consistently found that elevated WSS and WSS_Norm were associated with thin regions of the IA wall rather than thick and normal regions.

Use of surgical video-based automated performance metrics to predict blood loss and success of simulated vascular injury control in neurosurgery: a pilot study

OBJECTIVE

Experts can assess surgeon skill using surgical video, but a limited number of expert surgeons are available. Automated performance metrics (APMs) are a promising alternative but have not been created from operative videos in neurosurgery to date. The authors aimed to evaluate whether video-based APMs can predict task success and blood loss during endonasal endoscopic surgery in a validated cadaveric simulator of vascular injury of the internal carotid artery.

METHODS

Videos of cadaveric simulation trials by 73 neurosurgeons and otorhinolaryngologists were analyzed and manually annotated with bounding boxes to identify the surgical instruments in the frame. APMs in five domains were defined-instrument usage, time-to-phase, instrument disappearance, instrument movement, and instrument interactions-on the basis of expert analysis and task-specific surgical progressions. Bounding-box data of instrument position were then used to generate APMs for each trial. Multivariate linear regression was used to test for the associations between APMs and blood loss and task success (hemorrhage control in less than 5 minutes). The APMs of 93 successful trials were compared with the APMs of 49 unsuccessful trials.

RESULTS

In total, 29,151 frames of surgical video were annotated. Successful simulation trials had superior APMs in each domain, including proportionately more time spent with the key instruments in view (p < 0.001) and less time without hemorrhage control (p = 0.002). APMs in all domains improved in subsequent trials after the participants received personalized expert instruction. Attending surgeons had superior instrument usage, time-to-phase, and instrument disappearance metrics compared with resident surgeons (p < 0.01). APMs predicted surgeon performance better than surgeon training level or prior experience. A regression model that included APMs predicted blood loss with an R2 value of 0.87 (p < 0.001).

CONCLUSIONS

Video-based APMs were superior predictors of simulation trial success and blood loss than surgeon characteristics such as case volume and attending status. Surgeon educators can use APMs to assess competency, quantify performance, and provide actionable, structured feedback in order to improve patient outcomes. Validation of APMs provides a benchmark for further development of fully automated video assessment pipelines that utilize machine learning and computer vision.

Resection of cervical ependymoma

Intramedullary ependymomas are surgically curable tumors. However, their surgical resection poses several challenges. In this intraoperative video we illustrate the main steps for the surgical resection of a cervical intramedullary ependymoma. These critical steps include: adequate exposure of the entire length of the tumor; use of the intraoperative ultrasound; identification of the posterior median sulcus and separation of the posterior columns; Identification of the plane between the spinal cord and the tumor; mobilization and debulking of the tumor and disconnection of the vascular supply (usually from small anterior spinal artery branches). Following these basic steps a complete resection can be safely achieved in many cases. The video can be found here: http://youtu.be/QMYXC_F4O4U.

Resection of spinal hemangioblastoma

Spinal cord hemangioblastomas occur as sporadic lesions or in the setting of Von Hippel-Lindau disease. In this intraoperative video we present a case of sporadic cervical cord hemangioblastoma and illustrate the main surgical steps to achieve safe and complete resection which include: identification and division of the feeding arteries; careful circumferential dissection of the tumor from the surrounding gliotic cord; identification, isolation and division of the main venous drainage and single piece removal of the tumor. The video can be found here: http://youtu.be/I7DxqRrfTxc.