Interdepartmental Research Center E. Piaggio, Faculty of Engineering, University of Pisa, via Diotisalvi, 2, 56126 Pisa, Italy.
Eur Arch Otorhinolaryngol. 2010 Jun;267(6):897-902. doi: 10.1007/s00405-009-1161-y. Epub 2009 Nov 19.
Patients with primary ciliary dyskinesia (PCD) have structural and/or functional alterations of cilia that imply deficits in mucociliary clearance and different respiratory pathologies. A useful indicator for the difficult diagnosis is the ciliary beat frequency (CBF) that is significantly lower in pathological cases than in physiological ones. The CBF computation is not rapid, therefore, the aim of this study is to propose an automated method to evaluate it directly from videos of ciliated cells. The cells are taken from inferior nasal turbinates and videos of ciliary movements are registered and eventually processed by the developed software. The software consists in the extraction of features from videos (written with C++ language) and the computation of the frequency (written with Matlab language). This system was tested both on the samples of nasal cavity and software models, and the results were really promising because in a few seconds, it can compute a reliable frequency if compared with that measured with visual methods. It is to be noticed that the reliability of the computation increases with the quality of acquisition system and especially with the sampling frequency. It is concluded that the developed software could be a useful mean for PCD diagnosis.
原发性纤毛运动障碍(PCD)患者的纤毛存在结构和/或功能改变,这意味着黏液纤毛清除功能受损和出现不同的呼吸道病变。纤毛摆动频率(CBF)是一个有助于诊断的有用指标,在病理性病例中,其显著低于生理性病例。然而,CBF 的计算并不迅速,因此,本研究旨在提出一种自动方法,可直接从纤毛细胞的视频中评估 CBF。这些细胞取自下鼻甲,纤毛运动的视频被记录下来,并最终由开发的软件进行处理。该软件包括从视频中提取特征(用 C++语言编写)和计算频率(用 Matlab 语言编写)。该系统在鼻腔样本和软件模型上都进行了测试,结果非常有前景,因为与视觉方法相比,它可以在几秒钟内计算出可靠的频率。需要注意的是,计算的可靠性随着采集系统的质量提高而增加,尤其是采样频率。因此,开发的软件可能是 PCD 诊断的有用手段。