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使用动态计算机断层扫描和伽马残差函数进行肺灌注分析的临床可行性。

Clinical feasibility of pulmonary perfusion analysis using dynamic computed tomography and a gamma residue function.

机构信息

Division of Radiology, Department of Pathophysiological and Therapeutic Science, Faculty of Medicine, Tottori University, Yonago, Tottori, 683-8504, Japan.

出版信息

Jpn J Radiol. 2013 Apr;31(4):243-52. doi: 10.1007/s11604-012-0175-3. Epub 2013 Jan 12.

Abstract

PURPOSE

To create and determine the clinical feasibility of a model based on dynamic computed tomography (CT) and a bolus injection of iodine contrast medium for evaluation of pulmonary perfusion for healthy individuals and for patients with lung diseases.

MATERIALS AND METHODS

We analyzed pulmonary perfusion by means of dynamic 16-row multidetector CT scanning with a gamma residue function with adding a linear component (extended gamma function model) for 20 healthy individuals and in five patients.

RESULTS

Four types of the time-attenuation curve (TAC) were identified for the peripheral lung. Although the TACs of most pixels for the peripheral lung comprised a single peak or a single-peak followed by another increase, no peak was observed for a small proportion of pixels, which either increased linearly or resulted in a delayed peak for healthy subjects. The ratios of these linearly increasing or delayed peak types of lung fields increased for pathological lungs. The analytical results for pathological cases showed that changes in lung perfusion, difficult to identify using only CT imaging, could be detected.

CONCLUSIONS

The extended gamma function model adequately evaluated pulmonary perfusion not only for normal regions, but also for structurally abnormal regions. Regional changes in perfusion could be evaluated by use of our model, and we confirmed its clinical feasibility for pulmonary perfusion analysis.

摘要

目的

创建并确定一种基于动态计算机断层扫描(CT)和碘对比剂团注的模型,用于评估健康个体和肺部疾病患者的肺灌注。

材料与方法

我们通过使用带有线性分量的伽马残差函数(扩展伽马函数模型)对 20 名健康个体和 5 名患者进行了动态 16 排多排 CT 扫描,以分析肺灌注。

结果

为外周肺确定了四种类型的时间衰减曲线(TAC)。尽管外周肺的大多数像素的 TAC 包括单个峰值或单个峰值后再次增加,但对于一小部分像素,未观察到任何峰值,这些像素要么呈线性增加,要么导致健康受试者的峰值延迟。对于病理性肺部,这些线性增加或延迟峰值类型的肺区的比例增加。对病理性病例的分析结果表明,仅使用 CT 成像难以识别的肺灌注变化可以被检测到。

结论

扩展伽马函数模型不仅可以充分评估正常区域的肺灌注,还可以评估结构异常区域的肺灌注。可以使用我们的模型评估灌注的区域变化,并且我们证实了其用于肺灌注分析的临床可行性。

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