IEEE Trans Biomed Eng. 2019 Oct;66(10):2882-2888. doi: 10.1109/TBME.2019.2897825. Epub 2019 Feb 6.
The ability of cells to collectively move is essential in various biological contexts including cancer metastasis. In this paper, we propose an automatic video analysis tool to correlate the cell movement inhibition with replication block induced by dose-dependent chemotherapy administration.
The novel approach combines individual and collective cell kinematic analysis performed over time-lapse microscopy video frames. Cells are first localized and tracked, and then kinematic descriptors are extracted for each track. Selective track identification is performed assuming diversified cell roles within the same cluster (spontaneously forming groups of cells), and finally individual results are grouped exploiting consensus of coordinated motility within cell clusters.
Recognition performance of three different experimental conditions (no drug, 0.5-5 μM merged in the same condition, and 50 μM) reached an average accuracy value of 88% over 958 different tracks collected in 36 clusters of diverse dimensions in eight independent experiments.
An extensive application of this methodology could give a different point of view of the cancer mechanisms.
细胞的集体迁移能力在多种生物学背景下都很重要，包括癌症转移。在本文中，我们提出了一种自动视频分析工具，用于将细胞运动抑制与剂量依赖性化疗诱导的复制阻断相关联。
该新方法结合了在延时显微镜视频帧上进行的个体和集体细胞运动学分析。首先对细胞进行定位和跟踪，然后为每个轨迹提取运动学描述符。假设在同一簇内（自发形成细胞群）的细胞具有多样化的作用，对选择性轨迹进行识别，最后利用细胞簇内协调运动的共识对个体结果进行分组。
在 8 个独立实验中，在 36 个不同尺寸的细胞簇中收集了 958 个不同的轨迹，对三种不同实验条件（无药物、0.5-5 μM 合并在同一条件下和 50 μM）的识别性能平均准确率达到 88%。
这种方法的广泛应用可以为癌症机制提供一个不同的视角。
