Suppr超能文献

优化配准不确定性可视化以支持脑肿瘤切除术中的术中决策。

Optimizing registration uncertainty visualization to support intraoperative decision-making during brain tumor resection.

作者信息

Geshvadi M, Dorent R, Galvin C, Rigolo L, Haouchine N, Kapur T, Pieper S, Vangel M, Wells W M, Golby A J, Haehn D, Frisken S

机构信息

UMass Boston, Boston, USA.

Brigham and Women's Hospital, Boston, USA.

出版信息

Int J Comput Assist Radiol Surg. 2025 May 13. doi: 10.1007/s11548-025-03407-z.

Abstract

PURPOSE

Neurosurgeons need to precisely localize and resect tumors without damaging critical brain tissue. However, deformation of the brain (i.e., 'brain shift') and other factors introduce uncertainty during image-guided surgery. We present a new visualization software that supports qualitative and quantitative exploration of the effectiveness of a broad range of methods for communicating uncertainty. We expect that the ability to visualize uncertainty during surgery will help surgeons better understand uncertainty in neuronavigation and make more informed decisions.

METHODS

We developed UVisExplore, a software module for exploring various visualization techniques for understanding the spatial distribution of uncertainty in image registration. UVisExplore incorporates multiple classic uncertainty visualization techniques and introduces two novel paradigms appropriate for surgical environments. We also introduce a novel game-based approach to evaluate visualization effectiveness before surgery. The game scenario emulates the cognitive decision-making process during tumor resection allowing quantitative evaluation of visualization effectiveness in a non-threatening environment while training neurosurgeons to better understand uncertainty.

RESULTS

Six clinicians and three computer scientists participated in a study using our game. Participants explored different uncertainty visualization techniques in a tumor resection task and provided feedback. Surgeon-participants preferred surgeon-centric approaches, which emphasize uncertainty near the surgical probe. They also preferred explicit numerical measures of uncertainty displayed in millimeters. The game provided valuable insights into uncertainty visualization preferences and interpretation.

CONCLUSIONS

We provide an open-source 3D Slicer module for visualizing registration uncertainty and a game that allows users to explore uncertainty visualization for tumor resection surgery. UVisExplore provides a platform for exploring and comparing various uncertainty visualization techniques while simulating the decision-making process during surgery. The visualization module and the game proved to be a valuable communication tool and helped narrow the field of candidate visualizations that we plan to test during surgical procedures in the next phase of our research.

摘要

目的

神经外科医生需要精确地定位并切除肿瘤,同时不损伤关键脑组织。然而,大脑变形(即“脑移位”)及其他因素在图像引导手术中会引入不确定性。我们展示了一款新的可视化软件,它支持对多种传达不确定性方法的有效性进行定性和定量探索。我们期望手术中可视化不确定性的能力将帮助外科医生更好地理解神经导航中的不确定性,并做出更明智的决策。

方法

我们开发了UVisExplore,这是一个软件模块,用于探索各种可视化技术,以了解图像配准中不确定性的空间分布。UVisExplore整合了多种经典的不确定性可视化技术,并引入了两种适用于手术环境的新颖范式。我们还引入了一种基于游戏的新颖方法,在手术前评估可视化效果。游戏场景模拟肿瘤切除过程中的认知决策过程,在无威胁的环境中对可视化效果进行定量评估,同时训练神经外科医生更好地理解不确定性。

结果

六名临床医生和三名计算机科学家参与了使用我们游戏的研究。参与者在肿瘤切除任务中探索了不同的不确定性可视化技术并提供了反馈。外科医生参与者更喜欢以外科医生为中心的方法,这种方法强调手术探针附近的不确定性。他们也更喜欢以毫米为单位显示的明确的不确定性数值度量。该游戏为不确定性可视化偏好和解释提供了有价值的见解。

结论

我们提供了一个用于可视化配准不确定性的开源3D Slicer模块以及一个游戏,该游戏允许用户探索肿瘤切除手术的不确定性可视化。UVisExplore提供了一个平台,用于探索和比较各种不确定性可视化技术,同时模拟手术过程中的决策过程。可视化模块和游戏被证明是一种有价值的沟通工具,并有助于缩小我们计划在研究的下一阶段手术过程中测试的候选可视化范围。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验