Histology-informed liver diffusion MRI: biophysical model design and demonstration in cancer immunotherapy

Innovative diffusion Magnetic Resonance Imaging (dMRI) models enable in vivo mapping of biologically meaningful properties such as cell size, potential biomarkers in cancer. However, while cancers frequently spread to the liver, models tailored for liver applications and easy to deploy in the clinic are still sought. We tackle this unmet need by delivering a practical and clinically viable liver dMRI modelling framework. Through direct comparison of candidate dMRI approaches in mouse models and cancer patients' data, we select a model of intra-cellular diffusion fitted to highly diffusion-weighted images, as it provides the strongest radiological-histological correlates. We demonstrate the potential application of the proposed model in cancer immunotherapy, stratifying the risk of progression based on baseline tumour cell size/density from dMRI. This result, heretofore unreported and not achievable with standard dMRI indices (e.g., apparent diffusion coefficient), suggests that our approach may become a useful tool for precision imaging in oncology. ### Competing Interest Statement This study received funding from AstraZeneca. M.Vid. works for Siemens Healthineers. P.G.P.G works for GE HealthCare. K.B. worked as a researcher at the Vall d'Hebron Institute of Oncology (Barcelona), and is now an employee of AstraZeneca. AstraZeneca, Siemens and GE did not influence the acquisition and analysis of the data, the interpretation of the results, or the decision to submit the manuscript in its current form for a preprint or for consideration for publication in a journal. ### Funding Statement VHIO would like to acknowledge: the State Agency for Research (Agencia Estatal de Investigacion) for the financial support as a Center of Excellence Severo Ochoa (CEX2020-001024-S/AEI/10.13039/501100011033), the Cellex Foundation for providing research facilities and equipment and the CERCA Programme from the Generalitat de Catalunya for their support on this research. This research has been supported by PREdICT, sponsored by AstraZeneca. This study has been co-funded by the European Regional Development Fund/European Social Fund 'A way to make Europe' (to R.P.L.). R.P.L is supported by the "la Caixa" Foundation CaixaResearch Advanced Oncology Research Program, the Prostate Cancer Foundation (18YOUN19), a CRIS Foundation Talent Award (TALENT19-05), the FERO Foundation through the XVIII Fero Fellowship for Oncological Research, the Instituto de Salud Carlos III-Investigacion en Salud (PI18/01395 and PI21/01019), the Asociacion Espanola Contra el Cancer (AECC) (PRYCO211023SERR) and the Generitat de Catalunya Agency for Management of University and Research Grants of Catalonia (AGAUR) (2023PROD00178). This research has been funded by the CaixaResearch Advanced Oncology Research Program supported by "La Caixa" Foundation (to R.P.L.). The project that gave rise to these results received the support of a fellowship from "la Caixa" Foundation (ID 100010434). The fellowship code is "LCF/BQ/PR22/11920010" (funding F.G, A.V., and A.G) and "LCF/BQ/PI20/11760033" (funding I.C.S). I.C.S. also receives the support of the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 847648. This research has received support from the Beatriu de Pinos Postdoctoral Program from the Secretariat of Universities and Research of the Department of Business and Knowledge of the Government of Catalonia, and the support from the Marie Sklodowska-Curie COFUND program (BP3, contract number 801370; reference 2019 BP 00182) of the H2020 program (to K.B.). M.P. is supported by the UKRI Future Leaders Fellowship MR/T020296/2. A.G. is supported by a Severo Ochoa PhD fellowship (PRE2022-102586). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Clinical Research Ethics Committee (CEIm) of the Vall d'Hebron Hospital of Barcelona (Spain) gave ethical approval for this work (approval code: PR(AG)29/2020). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Raw MRI and histological images from the mouse livers will be released freely online through the Radiomics Group web site following publication in a peer-reviewed journal. Raw MRI and histological images of patients cannot be made freely available due to ethical restrictions at this stage. Python routines enabling the computation of the diffusion MRI metrics presented in this article will be released freely online after publication in a peer-reviewed journal (https://github.com/fragrussu/bodymritools).