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Area-based cell colony surviving fraction evaluation: A novel fully automatic approach using general-purpose acquisition hardware

机译：基于地基的细胞殖民地存活分数评估：一种新颖的全自动方法，使用通用采集硬件

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Abstract Background The current methodology for the Surviving Fraction (SF) measurement in clonogenic assay, which is a technique to study the anti-proliferative effect of treatments on cell cultures, involves manual counting of cell colony forming units. This procedure is operator-dependent and error-prone. Moreover, the identification of the exact colony number is often not feasible due to the high growth rate leading to the adjacent colony merging. As a matter of fact, conventional assessment does not deal with the colony size, which is generally correlated with the delivered radiation dose or the administered cytotoxic agent. Method Considering that the Area Covered by Colony (ACC) is proportional to the colony number and size as well as to the growth rate, we propose a novel fully automatic approach exploiting Circle Hough Transform, to automatically detect the wells in the plate, and local adaptive thresholding, which calculates the percentage of ACC for the SF quantification. This measurement relies just on this covering percentage and does not consider the colony number, preventing inconsistencies due to intra- and inter-operator variability. Results To evaluate the accuracy of the proposed approach, we compared the SFs obtained by our automatic ACC-based method against the conventional counting procedure. The achieved results ( r ?=?0.9791 and r ?=?0.9682 on MCF7 and MCF10A cells, respectively) showed values highly correlated with the measurements using the traditional approach based on colony number alone. Conclusions The proposed computer-assisted methodology could be integrated in laboratory practice as an expert system for the SF evaluation in clonogenic assays. Graphical abstract Overall flow diagram of the processing pipeline of the proposed fully automatic approach. Four main stages can be identified: (i) image-preprocessing, basically dealing with the RGB to CIE L*u*v* conversion; (ii) multi-well detection, which identifies and selects the wells inside the multi-well plate image, by exploiting Circle Hough Transform; (iii) colony extraction, based on a local adaptive thresholding algorithm, which segments cell colonies from the well background; (iv) Surviving Fraction (SF) evaluation, which measures the SF of the current well according to the treated ACCT against the reference untreated ACCU (control). Display Omitted Highlights ? Novel fully automatic approach for the Surviving Fraction (SF) evaluation in clonogenic assays. ? No dedicated hardware devices are required for multi-well plate image acquisition. ? The SF is measured considering the percentage of Area Covered by Colony (ACC). ? Circle Hough Transform and local adaptive thresholding techniques are used. ? The achieved SFs were highly correlated with the conventional counting method.
机译：摘要背景技术克隆源测定中存活级分（SF）测量的电流方法，即研究治疗对细胞培养物的抗增殖作用的技术，涉及手动计数细胞菌落形成单元。此过程是依赖的运算符和容易出错的。此外，由于通向相邻殖民地合并的高增长率，确切的菌落数的鉴定通常是不可行的。事实上，常规评估不处理菌落尺寸，其通常与递送的辐射剂量或施用的细胞毒性剂相关。考虑到殖民地（ACC）所涵盖的区域与殖民地数量和规模成比例以及增长率，我们提出了一种新颖的全自动方法利用圆形霍夫变换，自动检测板中的井，以及井自适应阈值处理，其计算SF量化的ACC的百分比。这种测量依赖于这种覆盖率百分比，并且不考虑由于和操作型间的互变异性而导致的不一致性。结果评估所提出的方法的准确性，我们将通过基于自动的ACC的方法获得的SF与传统计数程序进行比较。所达到的结果（R？=Δ= 0.9791和R？=Δ= 0.9682，分别在MCF7和MCF10a细胞上分别显示出与使用基于殖民地数量的传统方法的测量高度相关的值。结论拟议的计算机辅助方法可以在实验室练习中作为用于SF评估的克隆源测定的专家系统。图形抽象的整体流程图，提出了完全自动方法。可以识别四个主要阶段：（i）图像预处理，基本上处理RGB到CIE L * U * V *转换; （ii）通过利用圆轴变换来识别和选择多孔板图像内的井中的多孔检测; （iii）基于局部自适应阈值算法的殖民地提取，从井背景中区段细胞菌落; （iv）存活的级分（SF）评价，根据参考未处理的accu（对照）测量当前孔的SF。显示省略亮点？克隆灭系中存活级分（SF）评价的新型全自动方法。还多孔板图像采集不需要专用硬件设备。还考虑到菌落（ACC）涵盖的面积百分比来测量SF。还使用圆圈变换和局部自适应阈值化技术。还实现的SFS与传统的计数方法高度相关。

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