骨盆跑步者:放疗患者队列中盆腔器官变异性的可视化

N. Grossmann, O. Casares-Magaz, L. Muren, V. Moiseenko, J. Einck, E. Gröller, R. Raidou
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引用次数: 7

摘要

在放射治疗中,患者的解剖结构变化可能导致计划剂量和交付剂量之间的偏差,包括肿瘤覆盖不足和健康组织的过度辐射。探索和分析整个治疗期间的解剖变化,可以帮助临床研究人员设计合适的治疗策略,同时识别更容易发生辐射毒性的患者。我们介绍骨盆跑步者,一个新颖的应用程序,以探索在整个放射治疗过程中多个患者的盆腔器官的变异性。我们的应用程序解决了(i)在抽象表格视图中对盆腔器官形状变异性的全局探索和分析,以及(ii)在解剖2D/3D视图中对其进行局部探索和分析,其中比较和整体可视化是集成的。该工作流程基于现有的回顾性队列数据,包括整个放射治疗过程中膀胱、前列腺和直肠的分段。骨盆跑步者应用于四种使用场景,由两名临床研究人员,即医学物理学家进行。我们的应用为临床研究人员证明治疗方案适应解剖变化的重要性提供了有希望的支持。CCS概念•以人为中心的计算→可视化分析;•应用计算→生命和医学科学;
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pelvis Runner: Visualizing Pelvic Organ Variability in a Cohort of Radiotherapy Patients
In radiation therapy, anatomical changes in the patient might lead to deviations between the planned and delivered dose— including inadequate tumor coverage, and overradiation of healthy tissues. Exploring and analyzing anatomical changes throughout the entire treatment period can help clinical researchers to design appropriate treatment strategies, while identifying patients that are more prone to radiation-induced toxicity. We present the Pelvis Runner, a novel application for exploring the variability of segmented pelvic organs in multiple patients, across the entire radiation therapy treatment process. Our application addresses (i) the global exploration and analysis of pelvic organ shape variability in an abstracted tabular view and (ii) the local exploration and analysis thereof in anatomical 2D/3D views, where comparative and ensemble visualizations are integrated. The workflow is based on available retrospective cohort data, which incorporate segmentations of the bladder, the prostate, and the rectum through the entire radiation therapy process. The Pelvis Runner is applied to four usage scenarios, which were conducted with two clinical researchers, i.e., medical physicists. Our application provides clinical researchers with promising support in demonstrating the significance of treatment plan adaptation to anatomical changes. CCS Concepts • Human-centered computing → Visual analytics; • Applied computing → Life and medical sciences;
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