{
    "abstract": "Hyperspectral imaging (HSI) of murine tumor models grown in dorsal skinfold window chambers (DSWCs) offers invaluable insight into the tumor microenvironment. However, light loss in a glass coverslip is often overlooked, and particular tissue characteristics are improperly modeled, leading to errors in tissue properties extracted from hyperspectral images.\nWe highlight the significance of spectral renormalization in HSI of DSWC models and demonstrate the benefit of incorporating enhanced green fluorescent protein (EGFP) excitation and emission in the skin tissue model for tumors expressing genes to produce EGFP.\nWe employed an HSI system for intravital imaging of mice with 4T1 mammary carcinoma in a DSWC over 14 days. We performed spectral renormalization of hyperspectral images based on the measured reflectance spectra of glass coverslips and utilized an inverse adding-doubling (IAD) algorithm with a two-layer murine skin model, to extract tissue parameters, such as total hemoglobin concentration and tissue oxygenation ( \nHyperspectral image renormalization and the addition of EGFP fluorescence in the murine skin model reduced the mean absolute percentage errors (MAPEs) of fitted and measured spectra by up to 10% in tissue phantoms, 0.55% to 1.5% in the human forearm experiment and numerical simulations, and up to 0.7% in 4T1 tumors. Similarly, the MAPEs for tissue parameters extracted by IAD were reduced by up to 3% in human forearms and numerical simulations. For some parameters, statistically significant differences ( \nThe results contribute to improving intravital monitoring of DWSC models using HSI and pave the way for more accurate and precise quantitative imaging.",
    "authors": [
        {
            "affiliation": "University of Ljubljana, Faculty of Mathematics and Physics, Ljubljana, Slovenia.",
            "firstname": "Tadej",
            "initials": "T",
            "lastname": "Tomanic"
        },
        {
            "affiliation": "Institute of Oncology Ljubljana, Department of Experimental Oncology, Ljubljana, Slovenia.",
            "firstname": "Tim",
            "initials": "T",
            "lastname": "Bozic"
        },
        {
            "affiliation": "Institute of Oncology Ljubljana, Department of Experimental Oncology, Ljubljana, Slovenia.",
            "firstname": "Bostjan",
            "initials": "B",
            "lastname": "Markelc"
        },
        {
            "affiliation": "University of Ljubljana, Faculty of Mathematics and Physics, Ljubljana, Slovenia.\nJozef Stefan Institute, Ljubljana, Slovenia.",
            "firstname": "Jost",
            "initials": "J",
            "lastname": "Stergar"
        },
        {
            "affiliation": "Institute of Oncology Ljubljana, Department of Experimental Oncology, Ljubljana, Slovenia.\nUniversity of Ljubljana, Faculty of Health Sciences, Ljubljana, Slovenia.",
            "firstname": "Gregor",
            "initials": "G",
            "lastname": "Sersa"
        },
        {
            "affiliation": "University of Ljubljana, Faculty of Mathematics and Physics, Ljubljana, Slovenia.\nJozef Stefan Institute, Ljubljana, Slovenia.",
            "firstname": "Matija",
            "initials": "M",
            "lastname": "Milanic"
        }
    ],
    "conclusions": null,
    "copyrights": "\u00a9 2024 The Authors.",
    "doi": "10.1117/1.JBO.29.9.093504\n10.1016/j.cell.2011.02.013\n10.1158/2159-8290.CD-21-1059\n10.1038/nm.2537\n10.7860/JCDR/2015/12016.6135\n10.1186/s13046-020-01709-5\n10.1007/s00018-019-03351-7\n10.1002/mc.23360\n10.1111/j.1349-7006.2003.tb01395.x\n10.3389/fimmu.2021.811485\n10.1007/s10585-008-9234-7\n10.1142/S1793545811001319\n10.1088/0031-9155/58/11/R37\n10.1117/1.JBO.19.1.010901\n10.1007/s00464-023-09874-2\n10.1364/BOE.386338\n10.1117/1.2003369\n10.1117/1.3523363\n10.1364/OL.34.000289\n10.1117/1.3285584\n10.1117/12.905113\n10.1364/OL.38.000332\n10.1016/j.jconrel.2013.07.008\n10.1364/BOE.5.001965\n10.1364/OL.40.003292\n10.1142/S179354581250023X\n10.1016/j.bioelechem.2021.107795\n10.1038/nmeth.1455\n10.3390/s22166274\n10.1364/AO.58.009002\n10.1117/1.JBO.26.9.096003\n10.1364/AO.32.000559\n10.1364/BOE.443880\n10.1002/jbio.202200181\n10.1016/j.bbabio.2014.08.005\n10.1214/aoms/1177730491\n10.1038/nmeth.2019\n10.1016/j.jphotobiol.2016.03.047",
    "journal": "Journal of biomedical optics",
    "keywords": [
        "dorsal skinfold window chambers",
        "enhanced green fluorescent protein",
        "hyperspectral imaging",
        "renormalization",
        "tissue model",
        "tumors"
    ],
    "methods": null,
    "publication_date": "2024-07-23",
    "pubmed_id": "39040986\n21376230\n35022204\n22064426\n26266204\n32993787\n31690961\n34644811\n14662015\n34987525\n7692730\n19190882\n21994905\n23666068\n24441941\n36645484\n32637250\n16178638\n21198195\n19183634\n20210438\n23381428\n23871960\n24940553\n26176452\n28855967\n38236543\n33789177\n20453868\n36016033\n31873681\n34490762\n20802725\n35284194\n36054067\n25175349\n22743772\n27101274",
    "results": "Hyperspectral image renormalization and the addition of EGFP fluorescence in the murine skin model reduced the mean absolute percentage errors (MAPEs) of fitted and measured spectra by up to 10% in tissue phantoms, 0.55% to 1.5% in the human forearm experiment and numerical simulations, and up to 0.7% in 4T1 tumors. Similarly, the MAPEs for tissue parameters extracted by IAD were reduced by up to 3% in human forearms and numerical simulations. For some parameters, statistically significant differences ( ",
    "title": "Hyperspectral imaging of 4T1 mammary carcinomas grown in dorsal skinfold window chambers: spectral renormalization and fluorescence modeling.",
    "xml": "<Element 'PubmedArticle' at 0x788500cb2d90>"
}