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        <jats:p>We adopted simulation\u2010informed modelling of the vascular dMRI signal. We synthesised signals from 1500 synthetic vascular networks, for a variety of protocols (flow\u2010compensated [FC], non\u2010compensated [NC], hybrid), featuring different  samplings and diffusion times. We estimated the number of independent, recoverable signal degrees of freedom in presence of noise (signal\u2010to\u2010noise ratio of 5), and ranked 12 microvascular metrics depending on the quality of their estimation. Lastly, we demonstrated the feasibility of estimating the top\u2010ranking metrics on 3T dMRI of a healthy volunteer and of a metastatic colorectal cancer (CRC) patient.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Both NC and FC synthetic vascular signals exhibited complex behaviour as, for example, non\u2010zero kurtosis and diffusion time dependence. Two independent degrees of freedom appeared recoverable from directionally\u2010averaged vascular signals (SNR of 5). Mean volumetric flow rate  and an\n                      <jats:italic>Apparent Network Branching<\/jats:italic>\n                      (ANB) index maximised correlations between ground truth and estimated values in silico. In the patient, both  and  detected re\u2010vascularisation after 3 months of targeted therapy against liver metastases, consistently with\n                      <jats:italic>Intra\u2010Voxel Incoherent Motion<\/jats:italic>\n                      (IVIM) metrics.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Simulation\u2010based modelling of the vascular dMRI signal suggests  and  as the most promising metrics for tissue microvasculature characterisation. Their estimation in vivo appears feasible to capture general trends, and demonstrates contrasts that are biologically plausible, encouraging their usage in future studies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mrm.70318","type":"journal-article","created":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T19:09:59Z","timestamp":1772996999000},"page":"387-402","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Simulation\u2010Informed Evaluation of Microvascular Parameter Mapping for Diffusion MR Imaging of Solid Tumours"],"prefix":"10.1002","volume":"96","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-9600-0436","authenticated-orcid":false,"given":"Anna Kira","family":"Voronova","sequence":"first","affiliation":[{"name":"Radiomics Group Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron Barcelona Hospital Campus  Barcelona Spain"},{"name":"Department of Biomedicine, Faculty of Medicine 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