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<b>Purpose</b> <p>Cerebral aneurysms are blood-filled bulges that form at weak points in blood vessel walls, and their rupture can lead to life-threatening consequences. Given the high risk associated with these aneurysms, thorough examination and analysis are essential for determining appropriate treatment. While existing tools such as <span>Aneulysis</span> and its web-based counterpart <span>WebAneulysis</span> provide interactive means for analyzing simulated aneurysm data, they lack support for collaborative analysis, which is crucial for enhancing interpretation and improving treatment decisions in medical team meetings.</p> <b>Methods</b> <p>To address this limitation, we introduce <span>WebCoAneulysis</span>, a novel collaborative tool for aneurysm data analysis. <span>WebCoAneulysis</span> builds upon the established visualization techniques of <span>WebAneulysis</span> while incorporating innovative collaborative features to facilitate joint analysis and discussion among medical professionals. The tool was evaluated by three physicians and two visualization experts, who assessed its usability, functionality, and effectiveness in supporting collaborative decision-making.</p> <b>Results</b> <p>The evaluation results were overwhelmingly positive. The physicians particularly appreciated the tool’s ability to provide a clear overview of aneurysm data while maintaining ease of use despite its complex functionality. Although minor suggestions for improvement were made, the overall feedback highlighted the benefits of <span>WebCoAneulysis</span> in improving collaborative analysis and treatment planning.</p> <b>Conclusion</b> <p><span>WebCoAneulysis</span> enhances aneurysm data analysis by enabling real-time collaboration among medical professionals, thereby supporting more informed treatment decisions. Beyond its primary application in risk analysis and treatment planning, the tool also has potential benefits for patient education and the training of new doctors, making it a valuable addition to the field of medical visualization and decision support systems.</p>

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Visualization support for remote collaborative aneurysm treatment planning

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年9月8日

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  • Rebecca Preßler,
  • Monique Meuschke,
  • Bernhard Preim,
  • Kai Lawonn

摘要

Purpose

Cerebral aneurysms are blood-filled bulges that form at weak points in blood vessel walls, and their rupture can lead to life-threatening consequences. Given the high risk associated with these aneurysms, thorough examination and analysis are essential for determining appropriate treatment. While existing tools such as Aneulysis and its web-based counterpart WebAneulysis provide interactive means for analyzing simulated aneurysm data, they lack support for collaborative analysis, which is crucial for enhancing interpretation and improving treatment decisions in medical team meetings.

Methods

To address this limitation, we introduce WebCoAneulysis, a novel collaborative tool for aneurysm data analysis. WebCoAneulysis builds upon the established visualization techniques of WebAneulysis while incorporating innovative collaborative features to facilitate joint analysis and discussion among medical professionals. The tool was evaluated by three physicians and two visualization experts, who assessed its usability, functionality, and effectiveness in supporting collaborative decision-making.

Results

The evaluation results were overwhelmingly positive. The physicians particularly appreciated the tool’s ability to provide a clear overview of aneurysm data while maintaining ease of use despite its complex functionality. Although minor suggestions for improvement were made, the overall feedback highlighted the benefits of WebCoAneulysis in improving collaborative analysis and treatment planning.

Conclusion

WebCoAneulysis enhances aneurysm data analysis by enabling real-time collaboration among medical professionals, thereby supporting more informed treatment decisions. Beyond its primary application in risk analysis and treatment planning, the tool also has potential benefits for patient education and the training of new doctors, making it a valuable addition to the field of medical visualization and decision support systems.