The Lipid Droplets Tool helps to segment lipid droplets marked with BODIPY.

You can find some example images here:

• Snap-8242%20SGBS%20BDNF10%2040x.jpg
• Snap-8235%20SGBS%20BDNF5%2040x.jpg
• Snap-8224%20SGGS%20BDNF1%2040x.jpg

Getting started

To install the tool, save the file MRI_Lipid_Droplets_Tool.ijm under macros/toolsets in the ImageJ installation and restart ImageJ.

Select the "MRI_Lipid_Droplets_Tool" toolset from the >> button of the ImageJ launcher.

• the first button (the one with the image) opens this help page
• the s button runs the segmentation on the current image

Options

Open the options-dialog by right-clicking on the s-button:

• min. size: objects smaller than min. size will be be considered as artefacts of the segmentation and will be removed from the result

Method

A bandpass filter is applied to the input image by using a Gaussian filter and then scaling the image down and up again with increasing scale and taking the difference between the two low-pass filtered images. On the result an automatic threshold (percentile method) is applied. Holes in the objects are filled. An auto-threshold (triangle) is applied to the input image and the resulting mask is used to remove artefacts from the mask of the droplets image. Objects smaller then a give size are removed and a binary watershed transform is used to separate touching droplets. Objects touching the border of the image are removed.

Publications using this tool

1. Pierre, L., Juszczak, F., Delmotte, V., Decarnoncle, M., Ledoux, B., Bultot, L., Bertrand, L., Boonen, M., Renard, P., Arnould, T., Declèves, A.-E., 2025. AMPK protects proximal tubular epithelial cells from lysosomal dysfunction and dedifferentiation induced by lipotoxicity. Autophagy 21, 860–880.

2. Morishige, J., Yoshioka, K., Nakata, H., Ishimaru, K., Nagata, N., Tanaka, T., Takuwa, Y., Ando, H., 2023. Sphingosine kinase 1 is involved in triglyceride breakdown by maintaining lysosomal integrity in brown adipocytes. Journal of Lipid Research 64, 100450.

3. Ali, U., Wabitsch, M., Tews, D., and Colitti, M. (2023). Effects of allicin on human Simpson-Golabi-Behmel syndrome cells in mediating browning phenotype. Front. Endocrinol. 14, 1141303. 10.3389/fendo.2023.1141303.

4. Florian Juszczak, 2022. New insights into therapeutic strategies for obesity-induced chronic kidney disease Is there a central role for AMP-activated protein kinase? (phD). University of Namur, Université de Mons.

5. Pessoa Rodrigues, C., Chatterjee, A., Wiese, M., Stehle, T., Szymanski, W., Shvedunova, M., Akhtar, A., 2021. Histone H4 lysine 16 acetylation controls central carbon metabolism and diet-induced obesity in mice. Nat Commun 12, 6212.

6. Hammel, J.H., and Bellas, E. (2020). Endothelial cell crosstalk improves browning but hinders white adipocyte maturation in 3D engineered adipose tissue. Integrative Biology 12, 81–89.

7. Montanari, T., Boschi, F., and Colitti, M. (2019). Comparison of the Effects of Browning-Inducing Capsaicin on Two Murine Adipocyte Models. Front. Physiol. 10, 1380.

8. Colitti, M., Boschi, F., and Montanari, T. (2018). Dynamic of lipid droplets and gene expression in response to β-aminoisobutyric acid treatment on 3T3-L1 cells. European Journal of Histochemistry 62.

9. Montanari, T., and Colitti, M. (2018). Simpson–Golabi–Behmel syndrome human adipocytes reveal a changing phenotype throughout differentiation. Histochemistry and Cell Biology, 149, 593–605.