Cell Morphology and Shape Change

Introduction

By combining several parameters you can generate outputs that can provide insight into what is happening to your sample beyond what the base measurements will show. In this example we will use the ratio of the perimeter of a cell to its convex hull to represent the complexity or “spikiness” of the cell. If the convex hull and perimeter are the same value, the ratio will be 1 and would represent a smooth cell. As the cell becomes more complex or spiky the ratio between the two deviates more and more. Additionally several intensities measures (Standard deviation, Skewness and Kurtosis) will be measured to look at changes in actin staining. In the advanced module of this manual there is a section on automating this process to batch analyse multiple cells.

Measuring Cell Complexity

1. Open Actin Stained – Control.tif from the Demo Images\Confocal\\Cell Complexity folder 

2. Separate the channels (Image 🡪 Colour 🡪 Split Channels) 

3. Make a copy of the red actin channel (right click and choose Duplicate). Select the duplicate and go to Process 🡪 Filters 🡪 Gaussian Blur… 

4. In the dialog that comes up enter a Sigma value of 2 and press OK 

5. You will now have two versions of the actin channel .One original and one blurry. The blurry one will be used for the next couple of steps. 

6. Select the blurred image and apply a threshold (Image 🡪 Adjust 🡪 Threshold) using the Li auto setting to create a binary image. 

7. Select the binary image and go to Analyze 🡪 Analyze Particles and configure it only to add the generated ROIs into the ROI manager and press OK 

You should get a single ROI around the cell and one entry in the ROI manager 

8. Go to Analyse 🡪 Set Measurements and configure it to measure Area,  Mean gray value, Standard deviation, Perimeter, Skewness and Kurtosis as shown below 

9. Select the ROI from the ROI manager and got to Analyze 🡪 Measure or press Ctrl + M 

The only number of importance from this measurement is the Perimeter value

10. Select the binary image again and make sure the ROI is selected. Go to Edit 🡪 Selection 🡪 Convex Hull 

11. This will create a convex hull selection around the cell. The convex hull is the result of joining the other most points of an object together. 

12. Once again run the Measure command 

As before the only number of interest is the Perimeter value. The other values (mean, stdev etc) are a bit strange because the region of the convex hull covers both the white of the binary object and the black of the background.

13. Finally select the original actin channel image, go to the ROI manager and tick the show all box to copy the ROI to the selected image.

14. For the last time select the ROI in the list and run the Measure command 

15. You now have all the information you need for this cell. We know its Area (641.846um^2) from the first row. Its Perimeter (113.715um) from the first row. Its Convex Hull perimeter (105.999) from the second row and the Skewness and Kurtosis values (1.121, 2.819) from the last row. We can also calculate the Perimeter to Convex Hull Ratio 105.999/113.715=0.93

16. Close all the open images, delet the ROI from the ROI manager and repeat these steps for the other image in the folder (Actin Stain – Treated.tif). 

The treated cell gives a ratio of 0.79 meaning it is more spikey. It also gives quite a different Kurtosis value (while the other values don’t change much). A lower kurtosis value means the intensities are flatter and more smooth with a less pronounced peak.