Academic Journal
Simulation-Informed Evaluation of Microvascular Parameter Mapping for Diffusion MR Imaging of Solid Tumours.
| Title: | Simulation-Informed Evaluation of Microvascular Parameter Mapping for Diffusion MR Imaging of Solid Tumours. |
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| Authors: | Voronova AK; Radiomics Group, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain.; Department of Biomedicine, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain., Prior O; Radiomics Group, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain., Grigoriou A; Radiomics Group, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain.; Department of Biomedicine, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain., Salvà F; Medical Oncology Service, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain., Elez E; Medical Oncology Service, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain., Atlagich LM; Radiomics Group, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain., Sala-Llonch R; Department of Biomedicine, Faculty of Medicine, Institut d'Investigacions Biomédiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain.; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Barcelona, Spain., Palombo M; Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK.; School of Computer Science and Informatics, Cardiff University, Cardiff, UK., Fieremans E; Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA., Novikov DS; Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA., Perez-Lopez R; Radiomics Group, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain., Grussu F; Radiomics Group, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain. |
| Source: | Magnetic resonance in medicine [Magn Reson Med] 2026 Jul; Vol. 96 (1), pp. 387-402. Date of Electronic Publication: 2026 Mar 07. |
| Publication Type: | Journal Article |
| Language: | English |
| Journal Info: | Publisher: Wiley Country of Publication: United States NLM ID: 8505245 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1522-2594 (Electronic) Linking ISSN: 07403194 NLM ISO Abbreviation: Magn Reson Med Subsets: MEDLINE |
| Imprint Name(s): | Publication: 1999- : New York, NY : Wiley Original Publication: San Diego : Academic Press |
| MeSH Terms: | Diffusion Magnetic Resonance Imaging*/methods , Microvessels*/diagnostic imaging , Colorectal Neoplasms*/diagnostic imaging , Image Processing, Computer-Assisted*/methods , Neoplasms*/diagnostic imaging, Image Interpretation, Computer-Assisted/methods ; Humans ; Computer Simulation ; Signal-To-Noise Ratio ; Algorithms |
| Abstract: | Purpose: We aim to inform the design of new diffusion MRI (dMRI) approaches for microvasculature quantification that enhance the biological specificity of imaging towards cancer. Methods: We adopted simulation-informed modelling of the vascular dMRI signal. We synthesised signals from 1500 synthetic vascular networks, for a variety of protocols (flow-compensated [FC], non-compensated [NC], hybrid), featuring different INLINEMATH samplings and diffusion times. We estimated the number of independent, recoverable signal degrees of freedom in presence of noise (signal-to-noise ratio of 5), and ranked 12 microvascular metrics depending on the quality of their estimation. Lastly, we demonstrated the feasibility of estimating the top-ranking metrics on 3T dMRI of a healthy volunteer and of a metastatic colorectal cancer (CRC) patient. Results: Both NC and FC synthetic vascular signals exhibited complex behaviour as, for example, non-zero kurtosis and diffusion time dependence. Two independent degrees of freedom appeared recoverable from directionally-averaged vascular signals (SNR of 5). Mean volumetric flow rate INLINEMATH and an Apparent Network Branching (ANB) index maximised correlations between ground truth and estimated values in silico. In the patient, both INLINEMATH and INLINEMATH detected re-vascularisation after 3 months of targeted therapy against liver metastases, consistently with Intra-Voxel Incoherent Motion (IVIM) metrics. Conclusions: Simulation-based modelling of the vascular dMRI signal suggests INLINEMATH and INLINEMATH 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. (© 2026 The Author(s). Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.) |
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| Grant Information: | 2023PROD00178 Agencia de Gestio d'Ajuts Universitaris i de Recerca; SGR-Cat2021 Agencia de Gestio d'Ajuts Universitaris i de Recerca; PRYCO211023SERR Fundacion Cientifica Asociacion Espanola Contra el Cancer; MR/T020296/2 UK Research and Innovation; TALENT19-05 CRIS Cancer Foundation; 18YOUN19 Prostate Cancer Foundation; FERO Foundation; PI18/01395 Instituto de Salud Carlos III; PI21/01019 Instituto de Salud Carlos III; CEX2020-001024-S/AEI/10.13039/501100011033 Agencia Estatal de Investigacion; PRE2022-102586 Agencia Estatal de Investigacion; CaixaResearch Advanced Oncology Research Program 'la Caixa' Foundation; LCF/BQ/PR22/11920010 'la Caixa' Foundation; 89/2017 Fundacion BBVA; Cellex Foundation; Fundació Institució dels Centres de Recerca de Catalunya (CERCA); European Regional Development Fund (European Commission, EU) |
| Contributed Indexing: | Keywords: cancer; diffusion MRI; microvasculature; modelling; simulations |
| Entry Date(s): | Date Created: 20260307 Date Completed: 20260710 Latest Revision: 20260710 |
| Update Code: | 20260711 |
| PubMed Central ID: | PMC13156458 |
| DOI: | 10.1002/mrm.70318 |
| PMID: | 41794653 |
| Database: | MEDLINE |
| ISSN: | 1522-2594 |
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| DOI: | 10.1002/mrm.70318 |