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Wound Healing Tool

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Volker edited this page Nov 13, 2024 · 184 revisions

The MRI Wound Healing Tool can be used to analyze scratch assays. It measures the area of a wound in a cellular tissue on a stack of images representing a time-series. An example image can be found here. An example image for the find-edges method (see below) can be found here.

Getting Started

To install the tools, save the file MRI_Wound_Healing_Tool.ijm under macros/toolsets in your ImageJ installation.

Select the MRI Wound Healing Tool toolset from the >> button of the ImageJ launcher.

Wound_Healing-Tool.png

  • the first button opens this help-page.
  • the m button starts the measurement on the active stack
  • the b button measures all tif-stacks in a folder

Options

By right-clicking on the m button you can open the options dialog.

wound_healing_options.png

  • method: You can choose between a variance based method and a method based on find edges. Note that for find edges the parameters variance-filter-radius and threshold are not taken into account. Use for example the parameters 20, 1, 4 and 999999 on the example image for the variance case.
  • variance filter radius: The radius of the variance filter that is applied to separate the zone occupied by tissue from the empty zone. The radius must be big enough so that the variance due to the tissue plays a role compared to the variance of the noise in the image. Note that the calculation time becomes longer with a bigger radius.
  • threshold The image resulting from the variance filter is converted to a mask by applying the given threshold. If the input images are 16bit the threshold 1 will probably work.
  • radius open This operation will close holes in the tissue. It must be big enough to close small holes in the tissue and small enough to not close the area of the wound in later images.
  • min. size Minimum size from which on the wound is taken into account. This excludes small remaining holes in the tissue.
  • ignore spatial calibration If checked the measurements will be in pixel otherwise the spatial calibration of the image if any is used.

Hints

  • If you have the frames of a timeseries of a closing scratch as individual image-files, open them as a stack in FIJI/ImageJ, before running the analysis. This way you will get all measurements in one table, instead of having one table per image. You can use the command File>Import>Image Sequence to open a series of images as a stack.
  • In ImageJ, select Analyze>Set Measurements to select the features you want to measure. You should at least select area and Display label.
  • It can happen that the result at one time-point consists of more then one area. You can recognize it because they have the same number in the column slice of the results table. To get the total area for one time-point you need to add all the surfaces measured for that time-point

Results

wound-healing-res01.png wound-healing-res02.png wound-healing-res03.png

How to cite the tool

You can use the tool's resource id (see scicrunch.org):

(Wound Healing Tool, RRID:SCR_025260)

History

  • 09.05.2022 Refactored and fixed the border problem. The tool should now be independent from ImageJ's global settings and the gap now goes to the border of the image instead of stopping at a distance depending on the number of iterations of the morphological close-operation.

See also

Other (third party) software for scratch assay analysis

Videos

Publications using this tool

  1. Jiang, J., Lin, Chi‐Hung, Chang, T., Lo, L., Lin, Chien‐Ping, Lu, R., Yang, C., 2024. Decreased interleukin‐ 17RA expression is associated with good prognosis in patients with colorectal cancer and inhibits tumor growth and vascularity in mice. Cancer Medicine 13, e7059. 10.1002/cam4.7059

  2. Enxian, Shi, 2024, Functional characterization of effectors of EGFR-mediated local invasion in head and neck carcinomas. Universität München

  3. Rossini, S., Ambrosino, S., Volpi, C., Belladonna, M.L., Pallotta, M.T., Panfili, E., Suvieri, C., Macchiarulo, A., Mondanelli, G., Orabona, C., 2024. Epacadostat stabilizes the apo-form of IDO1 and signals a pro-tumorigenic pathway in human ovarian cancer cells. Front. Immunol. 15, 1346686. 10.3389/fimmu.2024.1346686

  4. Acebes-Huerta, A., Martínez-Botía, P., Carbajo-Argüelles, G., Fernández-Fuertes, J., Muñoz-Turrillas, M.C., Ojea-Pérez, A.M., López-Vázquez, A., Eble, J.A., Gutiérrez, L., 2024. Characterization of the molecular composition and in vitro regenerative capacity of platelet-based bioproducts and related subfractions. Acta Biomaterialia 177, 132–147. 10.1016/j.actbio.2024.01.029

  5. Tran, S., Sipila, P., Thakur, S., Zhang, C., Narendran, A., 2024. Identification and In Vivo Validation of Unique Anti-Oncogenic Mechanisms Involving Protein Kinase Signaling and Autophagy Mediated by the Investigational Agent PV-10. Cancers 16, 1520. 10.3390/cancers16081520

  6. Kukulage, Dhanushika S.K. et al. 2024, Protein phosphatase PP2Cα S-glutathionylation regulates cell migration. Journal of Biological Chemistry, Volume 300, Issue 10, 107784

  7. Akinlalu, A., Flaten, Z., Rasuleva, K., Mia, M.S., Bauer, A., Elamurugan, S., Ejjigu, N., Maity, S., Arshad, A., Wu, M., Xia, W., Fan, J., Guo, A., Mathew, S., Sun, D., 2024. Integrated proteomic profiling identifies amino acids selectively cytotoxic to pancreatic cancer cells. The Innovation 5, 100626. 10.1016/j.xinn.2024.100626

  8. Abdallah, S., Abu-Reidah, I., Mousa, A., 2024. Phytochemical Components, Hindering Abilities on Cell Proliferation, Cell Migration and Three-Dimensional Spheroids’ Formation Capacity of Micromeria fruticosa Infusion. Natural Product Communications 19, 1934578X241275363. 10.1177/1934578X241275363

  9. Mojahedi, M., Zargar Kharazi, A., and Poorazizi, E. (2024). Preparation and characterization of carboxymethyl cellulose/polyethylene glycol films containing bromelain/curcumin: In vitro evaluation of wound healing activity. Polymer Engineering & Sci 64, 1993–2005.

  10. Kesidou, D., Bennett, M., Monteiro, J.P., McCracken, I.R., Klimi, E., Rodor, J., Condie, A., Cowan, S., Caporali, A., Wit, J.B.M., et al. (2024). Extracellular vesicles from differentiated stem cells contain novel proangiogenic miRNAs and induce angiogenic responses at low doses. .Molecular Therapy 32, 185–203.

  11. Rojas, L., Tobar, N., Espinoza, J., Ríos, S., Martínez, C., Martínez, J., Graves, D.T., and Smith, P.C. (2024). FOXO1 regulates wound‐healing responses in human gingival fibroblasts. J of Periodontal Research 59, 611–621.

  12. Heydari, P., Zargar Kharazi, A., and Shariati, L. (2024). Enhanced wound regeneration by PGS/PLA fiber dressing containing platelet-rich plasma: an in vitro study. Sci Rep 14, 12019.

  13. Ruta, V., Naro, C., Pieraccioli, M., Leccese, A., Archibugi, L., Cesari, E., Panzeri, V., Allgöwer, C., Arcidiacono, P.G., Falconi, M., et al. (2024). An alternative splicing signature defines the basal-like phenotype and predicts worse clinical outcome in pancreatic cancer. Cell Reports Medicine 5, 101411. 10.1016/j.xcrm.2024.101411.

  14. Serwe, G., Kachaner, D., Gagnon, J., Plutoni, C., Lajoie, D., Duramé, E., Sahmi, M., Garrido, D., Lefrançois, M., Arseneault, G., et al. (2023). CNK2 promotes cancer cell motility by mediating ARF6 activation downstream of AXL signalling. Nat Commun 14, 3560. 10.1038/s41467-023-39281-z.

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  16. Novohradsky, V., Marco, A., Markova, L., Cutillas, N., Ruiz, J., Brabec, V., 2023. Ir(III) Compounds Containing a Terdentate Ligand Are Potent Inhibitors of Proliferation and Effective Antimetastatic Agents in Aggressive Triple-Negative Breast Cancer Cells . J. Med. Chem. 66, 9766–9783. 10.1021/acs.jmedchem.3c00586

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  22. Huang, C.-J., Pu, C.-M., Su, S.-Y., Lo, S.-L., Lee, C.H., and Yen, Y.-H. (2023). Improvement of wound healing by capsaicin through suppression of the inflammatory response and amelioration of the repair process. Mol Med Rep 28, 155. 10.3892/mmr.2023.13042.

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  28. Afshar, A., Khoradmehr, A., Nowzari, F., Baghban, N., Zare, M., Najafi, M., Keshavarzi, S.Z., Zendehboudi, F., Mohebbi, G., Barmak, A., Mohajer, F., Basouli, N., Keshtkar, M., Iraji, A., Sari Aslani, F., Irajie, C., Nabipour, I., Mahmudpour, M., Tanideh, N., Tamadon, A., 2023. Tissue Extract from Brittle Star Undergoing Arm Regeneration Promotes Wound Healing in Rat. Marine Drugs 21, 381. 10.3390/md21070381

  29. Dardis, G.J., Wang, J., Simon, J.M., Wang, G.G., and Baldwin, A.S. (2023). An EZH2-NF-κB regulatory axis drives expression of pro-oncogenic gene signatures in triple negative breast cancer. iScience 26, 107115. 10.1016/j.isci.2023.107115.

  30. Mayor, J., Cuesta, A., Espinosa-Ruíz, C., and Esteban, M.Á. (2023). In vitro effects of astaxanthin on bacterial and cell viability, cell migration and mitochondrial activities in four fish cell lines. Aquaculture Reports 31, 101636. 10.1016/j.aqrep.2023.101636.

  31. Stoletov, K., Sanchez, S., Gorroño, I., Rabano, M., Vivanco, M. d. M., Kypta, R., and Lewis, J.D. (2023). Intravital imaging of Wnt/β-catenin and ATF2-dependent signalling pathways during tumour cell invasion and metastasis. Journal of Cell Science 136, jcs260285. 10.1242/jcs.260285.

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  38. Louro, A.F., Paiva, M.A., Oliveira, M.R., Kasper, K.A., Alves, P.M., Gomes‐Alves, P., and Serra, M. (2022). Bioactivity and miRNome Profiling of Native Extracellular Vesicles in Human Induced Pluripotent Stem Cell‐Cardiomyocyte Differentiation. Advanced Science 9, 2104296. https://doi.org/10.1002/advs.202104296.

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