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Airway shape assessment with visual feed-back in asthma and obstructive diseases

机译:通过视觉反馈对哮喘和阻塞性疾病进行气道形状评估

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Airway remodeling in asthma patients has been studied in vivo by means of endobronchial biopsies allowing to assess structural and inflammatory changes. However, this technique remains relatively invasive and difficult to use in longitudinal trials. The development of alternative non-invasive tests, namely exploiting high-resolution imaging modalities such as MSCT, is gaining interest in the medical community. This paper develops a fully-automated airway shape assessment approach based on the 3D segmentation of the airway lumen from MSCT data. The objective is to easily notify the radiologist on bronchus shape variations (stenoses, bronchiectasis) along the airway tree during a simple visual investigation. The visual feed-back is provided by means of a volume-rendered color coding of the airway calibers which are robustly defined and computed, based on a specific 3D discrete distance function able to deal with small size structures. The color volume rendering (CVR) information is fuerther on reinforced by the definition and computation of a shape variation index along the airway medial axis enabling to detect specific configurations of stenoses. Such cases often occur near bifuercations (bronchial spurs) and they are either missed in the CVR or difficult to spot due to occlusions by other segments. Consequently, all detected shape variations (stenoses, dilations and thickened spurs) can be additionally displayed on the medial axis and investigated together with the CVR information. The proposed approach was evaluated on a MSCT database including twelve patients with severe or moderate persistent asthma, or severe COPD, by analyzing segmental and subsegmental bronchi of the right lung. The only CVR information provided for a limited number of views allowed to detect 78% of stenoses and bronchial spurs in these patients, whereas the inclusion of the shape variation index enabled to complement the missing information.
机译:哮喘患者的气道重塑已通过体内支气管内活检进行了研究,以评估结构和炎症变化。但是,该技术仍然具有相对侵入性,并且难以在纵向试验中使用。替代性非侵入性测试的发展,即利用诸如MSCT之类的高分辨率成像方式,正在引起医学界的关注。本文基于MSCT数据对气道腔进行3D分割,开发了一种全自动气道形状评估方法。目的是在简单的视觉检查过程中轻松地告知放射科医生沿气道树的支气管形状变化(狭窄,支气管扩张)。视觉反馈是通过对气道口径进行体积渲染的彩色编码来提供的,该编码基于能够处理小尺寸结构的特定3D离散距离函数进行了稳健的定义和计算。通过定义和计算沿气道中轴的形状变化指数,可以进一步增强颜色体积渲染(CVR)信息,从而能够检测出狭窄的特定形态。这种情况通常发生在分叉支气管分支(支气管刺)附近,或者在CVR中遗漏,或者由于其他段的阻塞而难以发现。因此,所有检测到的形状变化(狭窄,扩张和增厚的刺刺)都可以额外显示在内侧轴上,并与CVR信息一起进行检查。通过分析右肺的节段性和亚节段性支气管,在MSCT数据库中对提议的方法进行了评估,该数据库包括12名重度或中度持续性哮喘或重度COPD患者。仅提供了有限数量的视图的CVR信息就可以检测出这些患者中78%的狭窄和支气管骨刺,而包含形状变异指数可以弥补缺失的信息。

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