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Furthermore, cluster analysis can aid in identifying multidimensional patterns in the diffusion MRI (dMRI) data that are not apparent when analyzing individual parameters in isolation. The aim of this study was to evaluate how well cluster analysis of VERDICT parameters can be used for intratumor tissue characterization compared to ADC in a mouse model of human small intestine neuroendocrine tumor (GOT1), and to validate the method by histological analysis. Mice implanted with GOT1 were irradiated and subsequently imaged using a dMRI protocol designed for estimation of VERDICT parameters and ADC values. Histological analysis using hematoxylin and eosin (H&amp;E), Masson's trichrome, and Ki67 staining identified three distinct tumor tissue types: necrotic, fibrotic, and viable tumor tissue. ROIs were drawn on regions of high and low ADC, which spatially matched with necrosis or fibrosis, and viable tumor tissue, respectively. Among the VERDICT parameters, the cell radius index (<jats:italic>R<\/jats:italic>) was most effective in distinguishing between necrotic and fibrotic tissue, whereas the intracellular fraction (<jats:italic>f<\/jats:italic><jats:sub>IC<\/jats:sub>) was the most effective in differentiating viable from non\u2010viable tissue. A Gaussian mixture model (GMM) of three clusters, representing each tumor tissue type, was fitted to <jats:italic>R<\/jats:italic> and <jats:italic>f<\/jats:italic><jats:sub>IC<\/jats:sub> of all tumor voxel data. VERDICT cluster maps corresponded well with the histology classification maps overall. Fibrotic tissue corresponded best with the cluster of low <jats:italic>f<\/jats:italic><jats:sub>IC<\/jats:sub> and low <jats:italic>R<\/jats:italic>, necrotic tissue with the cluster of low <jats:italic>f<\/jats:italic><jats:sub>IC<\/jats:sub> and high <jats:italic>R<\/jats:italic>, and viable tumor tissue with the cluster of high <jats:italic>f<\/jats:italic><jats:sub>IC<\/jats:sub> and intermediate <jats:italic>R<\/jats:italic>. In conclusion, GMM cluster analysis of VERDICT MRI data shows potential in differentiating necrotic, fibrotic, and viable tumor tissue in irradiated GOT1 tumors.<\/jats:p>","DOI":"10.1002\/nbm.70050","type":"journal-article","created":{"date-parts":[[2025,4,29]],"date-time":"2025-04-29T01:10:28Z","timestamp":1745889028000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Cluster Analysis of VERDICT MRI for Cancer Tissue Characterization in Neuroendocrine Tumors"],"prefix":"10.1002","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4891-5907","authenticated-orcid":false,"given":"Lukas","family":"Lundholm","sequence":"first","affiliation":[{"name":"Department of Medical Radiation Sciences Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg  Gothenburg 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